importance of task analysis in education

How to Do a Task Analysis Like a Pro

Task analysis is one of the cornerstones of instructional design. But what is it, really? The name says a lot: you analyze a task, step by step, to document how that task is completed.

At first glance, this seems like a straightforward thing. But even the easiest tasks can be quite complex. Things you do every day might seem simple when you first think about them. But what happens when you eliminate internalized or assumed knowledge? 

Take sending an email. Easy, right? Maybe four or five steps? 

• Click the New Mail icon
• Enter a Recipient
• Enter a Subject
• Enter your email text 

But what about carbon copy or blind carbon copy recipients? What if you need to attach an invoice or picture? What app do you use to create the email in the first place (or are you sending from Gmail in your browser)? For that matter, from which device are you sending the email? 

Suddenly that “simple” task is a set of processes, organized by device, operating system, and application, with various subtasks along the way accounting for mailing list complexities and the purpose of your email. As I was writing this I came up with about a dozen different variations, all of which would need to be closely analyzed and broken down precisely. 

Even the most average task has a lot behind it.

This is why understanding how to do a task analysis is so important to becoming a successful instructional designer. When instructional designers create training, they’re teaching the learner how to accomplish something. Task analysis helps you focus on what they’re going to do and how they’ll do it (don’t worry so much about the why ; that comes later). 

The easiest way to illustrate the process is with an example. Let’s say you work at a midsize media company and your boss asks you to complete a task analysis on how the company’s social media manager does her job. They want this documented for training purposes for future hires. That means you’ll need to:

• Identify the task to analyze
• Break down the task into subtasks
• Identify steps in subtasks

Let’s take a closer look at each of these steps.

Step 1: Identify the Task to Analyze

Tasks are the duties carried out by someone on the job. The social media manager carries out a lot of duties, so you need to be able to break them down into broad activities (aka tasks!) and focus on them one at a time. Don’t worry about all the little things that make up the task; we’ll get to that in a second. Here we’re looking to paint with broad strokes.

One of the social media manager’s tasks is to add new content to social media sites every morning. Your tasks should describe what a person does on the job and must start with an action verb.

So, in this case, the first task to analyze is “Add new content to social media.”

Step 2: Break Down the Task into Subtasks

Once you identify the task, you need to identify the subtasks, the smaller processes that make up the larger task. Remember in the email example above where I mentioned attachments and carbon-copying recipients? That’s the kind of thing you capture here. These should also be brief and start with an action verb.

Continuing the social media manager example, you need to find out the subtasks of adding new content to social media. You can figure this out by talking to or observing the social media manager. Through this process, you discover that the subtasks for adding new content to social media are:

• Check the editorial calendar
• Add new content to Twitter

You’re making good progress! You can now move on to Step 3.

Step 3: Identify Steps in Subtasks

Now it’s time to get into the nitty-gritty. You’ve identified the task and broken it down into subtasks. The final step, then, is to identify and list the steps for each subtask. 

Do this by breaking down all of the subtasks into specific step-by-step, chronological actions. The key here is to use a “Goldilocks” approach to detail: not too much and not too little. Use just the right amount so learners can follow the instructions easily. Again, as with tasks and subtasks, your steps need to start with an action verb. 

So, putting everything together from steps 1 and 2 and then breaking the subtasks into steps, your final task analysis would look like this;

1. Adding new content to social media  

1.1 Check the editorial calendar

1.1.1 Navigate to the calendar webpage

1.1.2 Click today’s date

1.1.3 Click newest article title to open article

1.1.4 Click inside article URL bar

1.1.5 Copy URL for article to clipboard

1.1.6 Highlight title text of article

1.1.7 Copy the title text to clipboard

1.1.8 Close the calendar

1.2 Add new content to Twitter

1.2.1 Navigate to Twitter account

1.2.2 Log in to Twitter account

1.2.3 Click Tweet button

1.2.4 Paste article title from clipboard

1.2.5 Paste article URL from clipboard

1.2.6 Click Tweet button to publish

There are several ways to approach task analysis. It’s a fine art deciding how far down the rabbit hole you need to go with detail. Instructional designers can debate for hours whether saying “log in” is enough or if that needs to be broken down further into “enter user name,” “enter password,” and “click the login button.” Again, it all comes down to figuring out how much detail is just right for your audience.

Wrapping Up

That’s it! As you can see, while creating a task analysis boils down to “just” three steps, there are a lot of nuanced decisions to make along the way. Remember the Goldilocks Rule and always consider your audience and the seriousness of the subject matter when deciding just how nitpicky you need your task analysis to be. After all, there’s a marked difference between how much detail a learner needs when they’re learning how to perform brain surgery versus filling out their timecard.

Do you have any do’s and don’ts of your own for completing a successful task analysis? If you do, please leave a comment below. We love to hear your feedback!

Follow us on Twitter and come back to E-learning Heroes regularly for more helpful advice on everything related to e-learning.

Related Content

Top 3 types of e-learning analysis, 5 tips to improve your technical writing skills.

The One Thing You Need to Do to Organize Training Content: Task Analysis

20 comments.

• Christine Hounsham

• Akhila Vasan

• Jacinta Nelligan

• David Mayor

• Alexander Salas

• Nicole Legault

• Chris Purvis

• Jerrie Paniri

• Chris Janzen

Years ago, long before I ever even considered that I might possibly be an ID, my English professor assigned us a paper to write a set of directions for a task of our choosing that could be successfully executed by anyone who could read English. Coincidentally, like Jerrie, I chose making a peanut butter and jelly sandwich, but for my part because I was lazy and wanted to pick a task for which it would be very easy to write the steps. Two days later I had a paper that was just shy of three pages (it was an English class, and we had to write it in prose, not instructional format), and a much deeper understanding of how much unconscious knowledge and experience we rely on to perform what we consider to be the simplest of tasks. I've never forgotten the lesson I got from writing that paper, an... Expand

• Caroline Smith

• David Kolmer

• Djuana Lamb

• Brock Lenser

• John Maical

Task analysis is a systematic process used to understand a task or activity in detail. It involves breaking down a complex task into smaller, manageable steps to identify the specific skills and knowledge required. Here's a guide on how to perform a task analysis like a pro: 1. Define the Task: Clearly define the task you want to analyze. Be specific about the goals and objectives. 2. Identify the Users: Determine who will be performing the task. Consider their background, skills, and knowledge. 3. Break Down the Task: Divide the task into smaller, manageable steps. Start with the overall goal and then break it down into subtasks. 4. Sequence the Steps: Arrange the steps in a logical order. Consider dependencies between steps and how they contribute to the overall task. 5. Gathe... Expand

• Abigail ava

Task Analysis: The Foundation for Successfully Teaching Life Skills

A Well Written Task Analysis Will Help Students Gain Independence

• Applied Behavior Analysis
• Behavior Management
• Lesson Plans
• Math Strategies
• Reading & Writing
• Social Skills
• Inclusion Strategies
• Individual Education Plans
• Becoming A Teacher
• Assessments & Tests
• Elementary Education
• Secondary Education
• Homeschooling
• M.Ed., Special Education, West Chester University
• B.A., Elementary Education, University of Pittsburgh

A task analysis is a fundamental tool for teaching life skills.  It is how a specific life skill task will be introduced and taught. The choice of forward or backward chaining will depend on how the task analysis is written.

A good task analysis consists of a written list of the discrete steps required to complete a task, such as brushing teeth, mopping a floor, or setting a table. The task analysis is not meant to be given to the child but is used by the teacher and staff supporting the student in learning the task in question.

Customize Task Analysis for Student Needs

Students with strong language and cognitive skills will need fewer steps in a task analysis than a student with a more disabling condition. Students with good skills could respond to the step "Pull pants up," while a student without strong language skills may need that task broken down into steps: 1) Grasp pants on the sides at the student's knees with thumbs inside the waistband. 2) Pull the elastic out so that it will go over the student's hips. 3) Remove thumbs from waistband. 4) Adjust if necessary.

A task analysis is also helpful as well for writing an IEP goal. When stating how performance will be measured, you can write: When given a task analysis of 10 steps for sweeping the floor, Robert will complete 8 of 10 steps (80%) with two or fewer prompts per step.

A task analysis needs to be written in a way that many adults, not just teachers but parents, classroom aides , and even typical peers, can understand it. It need not be great literature, but it does need to be explicit and use terms that will easily be understood by multiple people.   

Example Task Analysis: Brushing Teeth

• Student removes toothbrush from toothbrush case
• Student turns on water and wets bristles.
• Student unscrews toothpaste and squeezes 3/4 inches of paste onto bristles.
• Student opens mouth and brushes up and down on upper teeth.
• Student rinses his teeth with water from a cup.
• Student opens mouth and brushes up and down on lower teeth.
• Student brushes the tongue vigorously with toothpaste.
• Student replaces toothpaste cap and places toothpaste and brush in toothbrush case.

Example Task Analysis: Putting on a Tee Shirt

• Student chooses a shirt from the drawer. Student checks to be sure the label is inside.
• Student lays the shirt on the bed with the front down. Students checks to see that the label is near the student.
• Student slips hands into the two sides of the shirt to the shoulders.
• Student pulls head through the collar.  
• Student slides right and then left arm through the armholes.  

Keep in mind that, prior to setting goals for the task to be completed, it is advisable to test this task analysis using the child, to see if he or she is physically able to perform each part of the task. Different students have different skills. 

• Chaining Forward and Chaining Backwards
• Ideas for Teaching Life Skills in and out of the Classroom
• Teaching Life Skills in the Classroom
• Hand Over Hand Prompting for Children With Disabilities
• A Dental Health Activity With Eggshells and Soda
• How to Successfully Teach English One-to-One
• Gradual Release of Responsibility Creates Independent Learners
• Chunking: Breaking Tasks into Manageable Parts
• Personal Hygiene in Space: How it Works
• Functional Skills: Skills to Help Special Education Students Gain Independence
• Writing a Lesson Plan: Independent Practice
• Benefits of Cooperative Learning
• IEP Goals for Progress Monitoring
• The 6 Most Important Theories of Teaching
• How to Teach Essay Writing
• Money Worksheets for Counting Change

The Radiant Spectrum

Task Analysis in Special Education: How to Deconstruct a Task

• September 15, 2022 April 11, 2024

As educators, we often go through the process of deconstructing a task by breaking down a complex skill into smaller steps so that students are able to learn the skill gradually, and easily. This process is known as Task Analysis and is especially crucial when teaching students with special needs.

We typically learn in two ways, explicitly and implicitly. Explicit learning is the intentional experience of acquiring a skill or knowledge, while implicit learning is the process of learning without conscious and deliberate awareness, such as learning how to talk and eat. Our students with special needs benefit more from explicit teaching and learning because they often face challenges acquiring skills implicitly due to the need for contextual understanding, communication skills, and so on. 

For explicit teaching and learning to be effective, it is important to have a thorough understanding of the skill through task analysis.

Task Analysis involves a series of thought processes:

1. Goal Selection: Know exactly what it is that you want to teach

Be clear and specific about the goal or the skill that you want to teach. Avoid having too many sub-goals. 

• Negative example: Play a complete song.
• Positive example: Press keys on the piano by following the alphabets shown on a flashcard or music score.

2. Identify any prerequisite skills, if any 

In our earlier example of teaching the sequence of piano keys, some of the prerequisite skills will include:

• Literacy skills of alphabets and/or colours
• Matching skills of alphabets and/or colours
• Visual referencing skills in top-down and/or left-right motion
• Motor skill of only using one finger to press the key, or to imitate an action

Prerequisite skills are important because these skills help to make the learning more feasible and increase the possibility of successfully performing the new skill. 

3. Write a list of all the steps needed to complete the skill you want to teach

A skill can be completed in a single step, or in a series of sequential steps. It is thus helpful that we list down all the steps needed to complete the skill we want to teach. With this, the Task Analysis becomes more detailed and effective. Let’s take the above goal and list down the steps needed. 

Goal: Press keys on the piano by following the alphabets shown on a flashcard or music score.

The keys steps needed to complete this task are:

• Look up at the flashed alphabet.
• Process and retain the information in the learner’s working memory.
• Look down at the piano keys.
• Find the corresponding key by scanning past non-target keys.
• Identify and stop at the target key.
• Aim and press with one finger. 

4. Identify which steps your child can do and which he/she cannot yet do

The next step will be to know the current skill level of your learner by identifying which steps the learner can do, and which the learner cannot. Assume the learner has the following challenges:

• Not consistent in visual referencing skill of looking up and down repeatedly.
• Unable to focus and scan more than 4 keys at one time.
• Often mistakes Letter G for C and vice versa. 

This means that this learner will have challenges in completing Steps 3, 4, and 5 in the above Task Analysis. 

5. Isolate any gap skills, if needed, and teach them first

The steps in which the learner cannot do or has challenges in are known as gap skills . After identifying the gap skills, take time to isolate the skills, teach them, and bridge them. This process takes time. For example, looking at the gap skills in the above example: 

• Visual Referencing Skill: 

This is an abstract skill that takes time to build. It is unlikely that the learner can learn and master this in a couple of weeks. Therefore, to bridge this, the teacher should intentionally provide opportunities for top-down visual referencing across activities and settings, such as taking a toy from a shelf above and keeping them back on top, or sorting activities whereby one item is on top, and one is at the bottom. 

• Working Memory Stamina

This is also another skill that takes time to build. Teaching it across settings and activities will be more effective and efficient. 

This is a skill that can be taught together with the target skill. Since the learner mistakes G for C and vice versa, and is unable to scan more than 4 keys at any one time, reduce the sequencing to CDEF or FGAB such that there is only either C or G in the target sequence. Once the learner is more confident, isolate C and G so that the learner learns to differentiate the two before the full sequence is introduced again. 

Once the gap skills are bridged, the likelihood of the learner performing the target skill will increase vastly.

6. Determine the strategy to be used when completing the target skill, with or without gap skills

At this stage, the learner might still have some gap skills to work on, but the teacher decides to move on to teaching the actual target skill. There are generally three strategies to use:

• Backward Chaining

As the name suggests, Backward Chaining involves the teacher helping the student complete all the steps in the front, leaving only the last step for the learner to do. This also means that the teacher focuses on the last step in the teaching process. The teacher then slowly moves to teach the step before the last until the learner is able to complete all the steps.

• Forward Chaining

This is the opposite of Backward Chaining. The teacher starts teaching from the first step and then moves on chronologically. 

• Total Chaining

This strategy involves the learner in all the steps and the teacher teaches all the steps to the learner with prompts. The learner is learning all the steps. 

It is common to have tried all three strategies before the teacher is able to decide which one works best, so do not be afraid to evaluate and change your mind halfway!

7. Develop a systematic teaching plan, implement, assess and evaluate the progress

After you decide on your teaching strategy, you can then plan and start the actual teaching. Do remember to assess and evaluate the learner’s progress regularly so as to make the learning effective!

Task Analysis may be a long and daunting process at the beginning. However, the more you do it, the better you get at it. In fact, we are practising the steps of Task Analysis as we write this article for you! Practice more and you will soon see how useful it is. 

Interested in more tips on teaching to children with special needs? You can read about the importance and features of a good classroom set-up here !

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Notify me of follow-up comments by email.

Notify me of new posts by email.

Tipping Mind

"Learning never exhausts the mind" Leonardo da Vinci

Why is task analysis important in teaching and learning?

1. Make a list of skill and knowledge (my previous article on Skill Hierarchy will be helpful) 2. Select the learning objective (learning objective will give you insight on the S/K) 3. Based on the S/K start to identify types of activity 4. Make a list of activity based on S/K 5. Organize the activity (in other words, “write a lesson plan”) 6. Based on the lesson plan draw a task analysis diagram

Image source: In Zahari Hamidon (2018). Online learning – Instructional strategy matters [Keynote Speaker] on 10 September 2018. Learning Resources Festival. International Medical University (IMU), Bukit Jalil Campus. 9-11 September 2018.

Through task analysis, you will be able to deliver the S/K effectively which will give impact to the learning outcomes.

Szidon, K., & Franzone, E. (2010). Task Analysis: Online Training Module. (Madison, WI: National Professional Development Center on Autism Spectrum Disorders, Waisman Center, University of Wisconsin). In Ohio Center for Autism and Low Incidence (OCALI), Autism Internet Modules , http://www.autisminternetmodules.org . Columbus, OH: OCALI.

Related posts:

Share this:.

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)
• Click to share on Pinterest (Opens in new window)
• Click to share on WhatsApp (Opens in new window)

2 thoughts on “ Why is task analysis important in teaching and learning? ”

• Pingback: Why is task analysis important in teaching and learning? – OPEN UNIVERSITY MALAYSIA
• Pingback: Instructional Strategy for Online Learning – Tipping Mind

Leave a Reply Cancel reply

Discover more from tipping mind.

Subscribe now to keep reading and get access to the full archive.

Type your email…

Continue reading

What is Task Analysis in Teaching?

• November 2022
• Task Boxes , Academics , Life Skills

What is Task Analysis?

Task analysis in teaching means the process of breaking down a skill into smaller, more manageable components . It's a great way to teach students in special education (especially with Autism Syndrome Disorder) a skill that may be too challenging to teach all at once.

When Should I Use Task Analysis in Special Education?

A lot of people tend to get mixed up between Discrete Trial Training (DTT) and task analysis. They can be similar but there are some major differences between DTT and task Analysis . (LINK the blog Kristina wrote that compares them) I typically like to use more of a task analysis for teaching certain life skills to my students that may be overwhelming. I use DTT as more of an Applied Behavior Analysis Approach.

Why is Task Analysis Important?

Using task analysis in teaching is important because it allows opportunities to teach our students a more challenging skill . The more challenging and functional skills that they can do, the more independent they can be! This is why using a task analysis approach in teaching is so important in special education!

What are Some Examples of Task Analysis?

A great example of a task analysis in teaching would be breaking down a life skill that some of our kids may find more difficult, such as brushing their teeth, washing hands or making a sandwich into smaller steps.

For example, when teaching students to brush their teeth , you teach them that it is an 11 step process:

• Get out toothbrush.
• Get out toothpaste.
• Open toothpaste lid.
• Squeeze a small amount of toothpaste on toothbrush.
• Brush your top teeth while counting in your head to 30.
• Brush your bottom teeth while counting in your head to 30.
• Spit out toothpaste into sink.
• Rinse toothbrush under running water.
• Rinse your mouth with a cup of water.
• Wipe your mouth with a towel.
• Put toothbrush and toothpaste away.

I would have these steps typed up on a sheet of paper for them to follow while in the bathroom (with visuals also). For some students, you may even want them to check off each step as they complete it to make sure that they don't miss anything. The more that they repeat this routine process, the more natural and less challenging the skill becomes for them. I hope this helps you better understand what a task analysis is.

CHECK OUT THESE LIFE SKILLS TASK BOXES FOR MORE IDEAS!

I am a High School, self-contained Autism teacher from Central New York, who is passionate about individualizing student learning. I am a mommy of three, lover of all things Disney, married to my best friend and addicted to chocolate!! I hope that you find great ideas and inspiration here, so welcome!!

REcent Posts

How to Prevent Over-prompting [Episode 29]

Functional Protesting-Why do we Teach this Skill [Episode 28]

Featured resources.

You Might Also Like...

Leave a Reply Cancel reply

Shipping Note:

Physical boxes will be shipped out on the first week of each month.  If you purchase on the 2nd, your first box will not arrive until the next month.  I.e. If you start your subscription January 15, your first box will arrive in February. All subscriptions will receive immediate access to digital files.  

Subscriptions are set to renew on the 1st of each month unless you opt for the annual plan.

Adapted Resources

Seasonal & holiday, life skills.

• Skip to Content
• Skip to Main Navigation
• Skip to Search

Indiana University Bloomington Indiana University Bloomington IU Bloomington

• Getting to IRCA
• What to Do If You Suspect Autism
• Learn the Signs. Act Early
• How and Where to Obtain a Diagnosis/Assessment
• After the Diagnosis: A Resource for Families Whose Child is Newly Diagnosed
• For Adolescents and Adults: After You Receive the Diagnosis of an Autism Spectrum Disorder
• Introducing Your Child to the Diagnosis of Autism
• Diagnostic Criteria for Autism Spectrum Disorder
• Diagnostic Criteria for Social (Pragmatic) Communication Disorder
• Indiana Autism Spectrum Disorder Needs Assessment
• Online Offerings
• Training and Coaching
• Individual Consultations
• School District Support
• Reporter E-Newsletter
• Applied Behavior Analysis
• Communication
• Educational Programming
• General Information
• Mental Health
• Self Help and Medical
• Social and Leisure
• Articles Written by Adria Nassim
• Articles by Temple Grandin
• Applied Behavior Analysis (ABA)
• Early Intervention
• Self-Help and Medical
• IRCA Short Clips
• Work Systems: Examples from TEACCH® Training
• Structured Tasks: Examples from TEACCH® Training
• Schedules: Examples from TEACCH® Training
• Holidays and Celebrations
• Health and Personal Care
• Behavior and Emotions
• After the Diagnosis
• Frustration
• Making Requests
• Trying New Foods
• Using Visual Supports
• Financial Resources
• Groups and Activities
• State Resources
• Materials Request
• COVID-19 Visuals and Social Narratives
• Foundations of Structured Teaching: A 3-day Hands-on Workshop
• Paraprofessional Training Modules
• Comprehensive Programming for Students Across the Autism Spectrum Training
• Family Support Webinars
• Workshops with Dr. Brenda Smith Myles
• Workshops with Dr. Kathleen Quill
• First Responder Training
• IRCA Briefs

Indiana Institute on Disability and Community

Indiana Resource Center for Autism

Applied behavior analysis: the role of task analysis and chaining.

By:   Dr. Cathy Pratt, BCBA-D, Director, Indiana Resource Center for Autism and Lisa Steward, MA, BCBA, Director, Indiana Behavior Analysis Academy

A task analysis is used to break complex tasks into a sequence of smaller steps or actions. For some individuals on the autism spectrum, even simple tasks can present complex challenges. Having an understanding of all the steps involved for a particular task can assist in identifying any steps that may need extra instruction and will help teach the task in a logical progression. A task analysis is developed using one of four methods. First, competent individuals who have demonstrated expertise can be observed and steps documented. A second method is to consult experts or professional organizations with this expertise in validating the steps of a required task. The third method involves those who are teaching the skill to perform the task themselves and document steps. This may lead to a greater understanding of all steps involved. The final approach is simply trial and error in which an initial task analysis is generated and then refined through field tests (Cooper, Heron, Howard, 2020).

As task analyses are developed, it is important to remember the skill level of the person, the age, communication and processing abilities, and prior experiences in performing the task. When considering these factors, task analyses may need to be individualized. For those on the autism spectrum, also remember their tendency toward literal interpretation of language. For example, students who have been told to put the peanut butter on the bread when making a peanut butter and jelly sandwich have literally just placed the entire jar on the bread. It is important that all steps are operationally defined. Below are two examples of task analyses.

Putting a Coat On

• Pick up the coat by the collar (the inside of the coat should be facing you)
• Place your right arm in the right sleeve hole
• Push your arm through until you can see your hand at the other end
• Reach behind with your left hand
• Place your arm in the left sleeve hole
• Move your arm through until you see your hand at the other end
• Pull the coat together in the front
• Zip the coat

Washing Hands  

• Turn on right faucet
• Turn on left faucet
• Place hands under water
• Dispense soap
• Rub palms to count of 5
• Rub back of left hand to count of 5
• Rub back of right hand to count of 5
• Turn off water
• Take paper towel
• Dry hands to count of 5
• Throw paper towel away

Skills taught using a task analysis (TA) include daily living skills such as brushing teeth, bathing, dressing, making a meal, and performing a variety of household chores. Task analysis can also be used in teaching students to perform tasks at school such as eating in the cafeteria, morning routines, completing and turning in assignments, and other tasks. Task analysis is also useful in desensitization programs such as tolerating haircuts, having teeth cleaned, and tolerating buzzers or loud environments. Remember that tasks we perceive as simple may be complex for those on the spectrum.

Again, the number of steps involved and the wording used will differ dependent on the individual. Determining the steps to a TA as well as the starting point for an individual often requires collecting baseline data, and/or examining the individual’s ability to complete any or all of the required steps. Assessing the individual’s level of mastery can occur in one of two ways. Single-opportunity data involves collecting information on each step correctly performed in the task analysis. Once a mistake is made, data collection stops and no further steps are examined. In multiple opportunity data collection, progress is documented on each step regardless of whether the performance was correct or not. This provides insight into those steps the student can perform and where additional training or support is needed. Remember that once implementation begins, the TA may need to be revised to address any additional needs.

Once a task analysis is developed, chaining procedures are used to teach the task. Forward chaining involves teaching the sequence beginning with the first step. Typically, the learner does not move onto the second step until the first step is mastered. In backward chaining, the sequence is taught beginning with the last step. And again, the previous step is not taught until the final step is learned. One final strategy is total task teaching. Using this strategy, the entire skill is taught and support is provided or accommodations made for steps that are problematic. Each of these strategies has benefits. In forward chaining, the individual learns the logical sequence of a task from beginning to end. In backward chaining, the individual immediately understands the benefit of performing the task. In total task training, the individual is able to learn the entire routine without interruptions. In addition, they are able to independently complete any steps that have been previously mastered.

Regardless of the strategy chosen, data has to be collected to document successful completion of the entire routine and progress on individual steps. How an individual progresses through the steps of the task analysis and what strategies are used have to be determined via data collection.

Cooper, J.O., Heron, T.E, and Heward, W.L. (2020). Applied behavior analysis (3rd Edition). Pearson Education, Inc.

Pratt, C. & Steward, L. (2020). Applied behavior analysis: The role of task analysis and chaining. https://www.iidc.indiana.edu/irca/articles/applied-behavior-analysis.html .

2810 E Discovery Parkway Bloomington IN 47408 812-855-6508 812-855-9630 (fax) Sitemap

Director: Rebecca S. Martínez, Ph.D., HSPP

Sign Up for Our Newsletter

The IRCA Reporter is filled with useful information for individuals, families and professionals.

About the Center

Special Educator Academy

Free resources, what you need to know about task analysis and why you should use it.

Sharing is caring!

Returning to the Effective Interventions in Applied Behavior Analysis series , I wanted to talk a little about the use of task analysis and why it’s important.  For more information on how we use task analyses, check out this post on using shaping and this one on using chaining .

Everyone in special education has probably heard about task analysis.  It’s a decidedly unexciting topic in some ways, but it so critical to systematic instruction that we have to address it.  In addition, there is a lot of misinformation flying around out there so hopefully this will address just what you need to know about them.  

We are told to use them frequently in the classroom to break skills down into smaller components.  So, we set up steps, like we do for some of our mini-schedules like the one below for washing hands .  Sometimes task analyses have visuals to support them and sometimes they are just written out for the staff.

What is a task analysis?

So if you aren’t familiar with the jargon, what does task analysis mean? The National Professional Development Center found task analysis to be an evidence-based practice, which interests me because I don’t think that behavioral task analysis is actually an intervention.  I see the task analysis process as part of other interventions.  A task analysis is simply a set of steps that need to be completed to reach a specific goals.  There are basically two different ways to break down a skill.  You can break it down by the steps in a sequence to complete the task.  The hand washing task analysis does that.  In this type of task analysis you have to complete one step to be ready for the next.  For instance, you have to turn on the water to get your hands wet.  This type of task analysis is typically used with chaining which will be the topic of our next post.

You can also have a task analysis that breaks skills down into smaller chunks, like increasing time.  A task analysis for remaining in a group might do that like the examples at the bottom of the picture above.   In this type of task analysis, each step replaces the one that comes before it.  So, when you sit for 5 minutes, that includes all the steps that come before.  This type of task analysis is usually used with shaping, which I will talk about in 2 weeks.

Why Do I Need a Task Analysis?

So if a task analysis is just breaking skills down into smaller skills, you probably do it all the time. Conducting a task analysis isn’t a very time-consuming process.

But, why is using a specific task analysis that is established for a student important?  Below are 3 reasons to answer that question.

1.  Consistency

In order to assure that everyone is teaching a skill in the same way, breaking it down into the same steps is critical.  I am willing to bet that if you ask parents, paraprofessionals or even your significant other how they brush their teeth, you will find some variation in the order of the steps.  Your significant other doesn’t put the cap back on the toothpaste.  You keep the water running while you brush your teeth while your paraprofessional turns it off to conserve water until she is ready to rinse.  My point is that we all have individual differences in the steps of completing simple, everyday tasks.  Now, imagine that you are a student who is having difficulty learning to brush his teeth.  If you show me one way and prompt me through the steps, and then the parapro shows me another way and prompts me through her steps, and my mom shows me a third way, I’m going to be pretty confused.  It’s the beginning of the year and we all need a laugh, so here’s a great video example of why it’s important.  Archie and Michael can’t even agree on how to put on shoes and socks.  Imagine if they both tried to teach one of our students to put theirs on (no, I would not recommend doing this)–how confused would that student be?

Take Away Point: Writing down a task analysis assures that everyone follows the same steps and teaches the student the same way.  Then your instruction is much less confusing and more efficient. 2. Tailor It To The Student

Students need task analyses that are tailored to their needs.  I love starting with standard ones, so I don’t have to reinvent the wheel, but then adjusting them to meet the needs of this student.  Here’s why the individualization is so important.  If your steps are too large for the student, he or she may not make it to the next step and will stall out.  For instance, if you are teaching Molly to stay in a group activity for 20 minutes and your task analysis jumps from 5 minutes (that she can currently stay) to 10 minutes, she might never be successful at jumping to 10 minutes and won’t progress.  She might do better if we went to 7 minutes next and then 9 minutes.  On the other hand, for Max, if we were teaching the same skill and we had him stay in the group for 5 minutes, then 7 minutes and then 9 minutes it might take a very long time when he could have made the jump straight to 10 minutes.  Each student is different and we have to figure out how to individualize their steps based on their past data.  Is it taking too long to master a step? Step it down to a smaller step.  Is he mastering steps really quickly?  Make the steps bigger.

3. It is the Basis for Systematic Instruction

Breaking skills down is a critical component of discrete trial programming as well as teaching life skills and other chaining and shaping applications.  Discrete trial programs are made up of smaller steps that lead to a larger goal.  Learn 1 letter, then 2, then 3?  That’s a shaping task analysis.  Our research shows us that it’s important to break skills down for students with autism in order to eliminate extraneous variables that might mess up their learning.  Teaching systematically is the key to success with any student and especially any student in special education.  It’s also key for some of our students to be able to show progress.  While it’s not exciting to say that a student has mastered 4 of the 8 steps of tying his shoes, it better than being able to say AGAIN that he can’t tie his shoes–assuming he had no steps mastered earlier in the year. It’s slow progress, but it’s progress.

So, how do you use task analyses in your classroom and why do you think they are important?  Are there questions you have about task analyses or teaching strategies that use them? Please share them in the comments and I will try to address them.  In the meantime, I’ll be back next Thursday to talk about ways to make your instruction using task analyses more efficient.

• Read more about: Curriculum & Instructional Activities , Effective Interventions in ABA

You might also like...

Summer Resources That Will Help You Survive the End of the Year

How to Effectively and Efficiently Teach Telling Time: Hands-On Learning in Action for Special Education

How To Provide Effective Whole Group Instruction in Special Education?

Valentines Day Activities for Special Education from Preschool to Life Skills-Free Download

Grab a free resource.

(and get free tips by email)

Training & Professional Development

• On-Site Training
• Virtual Training

Privacy Policy

Disclosures and copyright.

• Core Beliefs

Unlock Unlimited Access to Our FREE Resource Library!

Welcome to an exclusive collection designed just for you!

Our library is packed with carefully curated printable resources and videos tailored to make your journey as a special educator or homeschooling family smoother and more productive.

How to Conduct a Task Analysis (With Examples)

Apr 16, 2024

Creating a to-do list and using a daily task tracker can go a long way toward helping you and your team get things done. But identifying and delegating tasks is only one part of the process. Performing a task analysis can help you refine the purpose of your task, break your task down into subtasks, and improve productivity and efficiency.

Team leaders in nearly any industry can perform a task analysis as a way to optimize internal practices, improve the customer experience, or even to assist employees with autism spectrum disorder (ASD) . Let’s take a look at what a task analysis is, how to perform a task analysis, and some real-world task analysis examples.

What Is Task Analysis?

Task analysis is the process of identifying the purpose and components of a complex task and breaking it down into smaller steps. Rather than trying to teach a new skill or process all at once, the purpose of task analysis is to separate it into individual steps that can be followed in a logical sequence.

The principles of task analysis can be used in product design and industrial engineering. It provides a method to better understand the way a customer uses a product and to design more user-friendly workflows. Forward and backward chaining can even be applied to systems that use artificial intelligence (AI) to make data-driven decisions and solve problems.

You’ll often see principles of task analysis applied to special education settings, which can inform employers who have employees with disabilities. For example, applied behavior analysis (ABA) is a type of therapy that uses task analysis to teach complex skills to children with autism spectrum disorder or other developmental disabilities.

In ABA therapy, practitioners use techniques like forward chaining to break down a task into a sequence of discrete steps. A related approach, discrete trial training (DTT) , can be used for teaching students everything from motor skills to daily living skills.

Types of Task Analysis

When using task analysis to plan a project or develop a new product, you can choose from one of two forms: cognitive and hierarchical. A cognitive task analysis is useful for tasks that require critical thinking or decision-making, while a hierarchical task analysis can be used for processes with a consistent structure or workflow.

Here’s how these two types of task analysis differ.

Cognitive task analysis

Let’s say you’re developing a new piece of software and you want to better understand how your customers will interact with the user interface. Rather than tell them how to perform a task, you simply give them a goal and watch how they achieve it.

Since different users will complete the task in a different way, you can use this analysis to identify pain points or understand how a customer’s knowledge and mindset inform their approach to completing the task.

Hierarchical task analysis

A hierarchical task analysis is one in which the process is fixed. In other words, you give the user a set of specific steps and watch how they perform each step of the task. You may discover that some steps are unnecessary or don’t serve the overall goal.

A hierarchical task analysis can be used to determine how long it takes to perform the total task process, and which steps can be eliminated with task automation .

How to Perform a Task Analysis in 4 Steps

The steps to conducting a task analysis will vary depending on whether you’re analyzing an internal process, a UX workflow, or a social or academic skill. But you can use these five steps to break down nearly any type of task and perform a task analysis as part of team project management or your own self-management process .

1. Define your goal

Start by defining the overall goal or task process that you want to analyze. This could be as simple as “Create a new user account and buy a product” or as in-depth as “ Run a post-mortem meeting and send out meeting minutes to everyone who attended.” The more specific your goal, the more useful your task analysis will be.

2. Create a list of subtasks

Next, break your higher-level task down into manageable steps. The idea is to create a list of all the subtasks that go into performing the task, even those that you might take for granted. You never know which tasks are slowing the whole process down.

For example, if you’re testing a new app, the first step might be “Turn on your phone” and the last step might be “Turn off your phone.”

3. Make a flowchart or diagram

A process flow chart or workflow diagram can help you determine which type of analysis to perform. Is your workflow a linear process with a series of discrete tasks that need to be completed in a specific order? Consider performing a hierarchical task analysis to find steps that you can automate or eliminate.

Is it more of a “choose your own adventure” in which different users will complete the task in a different way? Conduct a cognitive task analysis to identify pain points and prerequisites based on how different categories of users complete the task.

4. Analyze the task

Now, you can run through the process and pay attention to the length, frequency, and difficulty of each subtask. Were there any steps that you missed or that took longer than expected to complete? If another user performed the task, did they have the skills and knowledge necessary to complete the entire process?

You can use this information to make changes to the product or process, create more accurate documentation, or improve your training or onboarding practices.

3 Task Analysis Examples

The principles of task analysis can be applied to a wide range of scenarios, so let’s take a look at a few examples of task analysis in the real world.

Task analysis in UX design

In UX design, a task analysis may take the form of a focus group or usability testing. If you’ve just designed a new app, you might want to see how easy it is for customers to download the app and sign up for a new account. The process might look like this:

• Go to the App Store
• Search for the app
• Download the app
• Open the app
• Select “Create account”
• Enter your email address
• Verify your email address
• Choose a username and password

Upon conducting a task analysis, you determine that Step 7, “Verify your email address,” actually consists of multiple subtasks, such as opening up an email app. You decide to move this step later in the process to avoid disrupting the workflow.

Task analysis in project management

As a project manager, it’s important to know how your team members are spending their time so you can improve productivity and team accountability . Let’s say you want to find ways to delegate tasks more efficiently by using task automation. You come up with a list of the steps you usually follow to delegate tasks:

• Document action items during team meetings
• Add action items to your task manager
• Create a description for each task
• Assign each task to a team member
• Attach a due date to each task
• Send out a reminder email

After performing a task analysis, you determine that you don’t actually have to do any of these steps manually. You can use an AI task manager like Anchor AI to identify and delegate action items, attach due dates, and send out reminders automatically.

Task analysis for learning disabilities

In employment settings, a task analysis can be used to help employees with learning disabilities who otherwise struggle to complete tasks. One study found that individuals with intellectual disabilities were able to complete office tasks like scanning, copying, and shredding when they were broken down into steps like:

• Pick up documents from folder
• Open the scanner cover
• Place documents face-down on the scanner
• Close the scanner cover
• Press “Scan”
• Remove documents
• Return documents to the folder

Employees with learning disabilities may benefit from similarly specific instructions for other daily tasks, such as using time management tools or a password manager.

Streamline Task Management With Anchor AI

Performing a task analysis is a way of breaking down complex tasks into smaller steps so you can better understand how they all fit together. It’s used in workplaces, learning environments, and other settings to standardize processes, streamline workflows, and even teach social skills. You can use a task analysis to optimize internal processes or customer-facing workflows and eliminate unnecessary tasks altogether.

Anchor AI makes it easy to identify tasks and break them down into manageable steps with Max, your AI project manager. Simply invite Anchor AI to your next team meeting and Max will identify action items and delegate tasks automatically. Or, Ask Max for deeper insights into how specific tasks align with your overall project goals.

Sign up today to try it out for yourself and streamline task and project management!

Ready to shed the busy work?

Let Max 10x your grind so you can focus on the gold.

No credit card required. Free forever.

See what's included.

Feel the power of a personal AI project manager.

Investor inquiries

[email protected]

PR inquiries

[email protected]

General inquiries

[email protected]

Copyright ©2023 Anchor AI. All rights reserved.

Privacy policy

Terms and conditions

Examining mathematics teachers’ creative actions in programming-based mathematical activities

• Original Paper
• Open access
• Published: 22 May 2024

Cite this article

You have full access to this open access article

• Huiyan Ye 1 ,
• Oi-Lam Ng   ORCID: orcid.org/0000-0003-3736-7845 1 &
• Allen Leung 1  

There has been a renewed interest in creativity as a twenty-first century skill in K-12 mathematics education. However, previous research has paid less attention to creative actions than to other learning outcomes, which are often product- instead of process-based, especially in a programming context. Thus, situated in the context of mathematical learning in a block-based programming environment, Scratch, this study seeks to investigate how in-service mathematics teachers develop mathematical concepts and programming skills to demonstrate their creative actions as a form of professional development. By conducting task-based interviews and thematic analysis, we found that testing and iterative practices of reusing and remixing are two important kinds of creative actions inspired by the programming environment, which give rise to new possibilities for doing mathematics in terms of generating new ways to engage in mathematical processes and to understand mathematics from a computational perspective. Our findings will inform teacher education and professional development programs addressing creativity in technology-enhanced mathematics classrooms, with particular attention to the role of mathematics, programming, and their interplay in inspiring teachers’ (and students’) creative actions and new possibilities for doing mathematics.

Avoid common mistakes on your manuscript.

1 Introduction

As a 21st-century skill, creativity has attracted increasing attention in mathematics education. Much of the early research on mathematical creativity examined the relationship between creativity and either mathematical ability (Kattou et al., 2013 ) or academic achievement (Mann, 2009 ), with a focus on gifted students (Leikin et al., 2009 ). Different definitions of creativity are emerging (Joklitschke et al., 2022 ), and research on creativity in mathematics education has expanded to address aspects such as students’ creativity in problem posing (Van Harpen & Sriraman, 2013 ), teachers’ perception of creativity (Bolden et al., 2010 ; Leikin et al., 2013 ; Lev-Zamir & Leikin, 2013 ), and creativity in teaching practices (Mhlolo, 2017 ). However, regarding creativity as a learning outcome in digital mathematical activities (Weng et al., 2022b ), few studies have examined the development of creativity with mathematical and computational thinking, specifically the emergence and merging of mathematical concepts and programming skills when individuals engage in creative programming tasks.

Although creativity in mathematics can be problem-oriented, as in being inventive in problem-solving situations, it is far more than that. For example, students’ creativity development in the context of mathematical problem-based digital making—a form of constructionist learning which emphasizes the creation of digital or tangible artifacts via programming during mathematical problem-solving (Ng & Cui, 2021 )—could be understood in terms of creative exploration, creative solution, or creative expression (Weng et al., 2022a , b ). While such characterizations offer new insights into different forms of creativity in mathematical activities, limited empirical evidence of them exists beyond snapshots of student work, and we lack understanding of the actions of creative exploration in constructing mathematical and programming concepts. As Leikin and Elgrably ( 2022 ) point out, the “relationship between creative process and creative products in mathematics has barely been explored systematically” (p. 36). Extending this argument, we suggest that studies linking creative actions (as processes) and creative artefacts (as products) in the context of programming-based mathematical activities are urgently required, given the recent rise of child-friendly programming language and emerging research on the integration of programming activities in mathematics education (see a review in Ye et al., 2023a ).

Moreover, more studies consider student creativity than teacher creativity: Only six of 49 empirical studies on creativity in mathematics education published between 2010 and 2021 investigated teachers’ creativity-related conceptions and competencies (Leikin & Sriraman, 2022 ). Among them, five investigated pre-service or in-service teachers’ conceptions of creativity (Bolden et al., 2010 ; Leikin et al., 2013 ; Lev-Zamir & Leikin, 2013 ), the development of creativity awareness (Shriki, 2010 ) and creativity-noticing professional knowledge (Hoth et al., 2017 ) through questionnaires, interviews and analysis of teachers’ engagement in mathematics activities or teaching practices. In addition, Zazkis ( 2017 ) explored lesson play tasks as a fruitful avenue for displaying and supporting teachers’ creativity. As the work of Kynigos and Diamantidis ( 2022 ) has evidenced that appropriate tools and discursive environments may offer space for actions with creative potential for students, we suggest teachers’ engagement in programming-based mathematical activities may also serve as significant professional development opportunities, giving rise to their new mathematical thinking and supporting their creativity-noticing. Furthermore, teachers’ situated knowledge, experiences, and practices play an important role in fostering students’ creativity (Lu & Kaiser, 2022 ; Pitta-Pantazi et al., 2018 ). Thus, this study aimed to illuminate the creative actions exhibited by school mathematics teachers during programming-based mathematical activities as part of their professional development. Specifically, we focused on the creative actions demonstrated by mathematics teachers in using the block-based programming tool, Scratch, to create geometric shapes, and we explored how their creative actions were mediated by their mathematical and programming concepts, as well as the programming tool used, which in turn provided new possibilities for doing mathematics. Therefore, this study seeks to address the following research questions (RQs):

What creative actions do mathematics teachers exhibit during programming-based mathematical activities?

How might creative actions serve as objects-to-think-with to engender new possibilities for mathematics teachers to do mathematics in a programming context?

2 Theoretical background

In this section, we first review the literature around creativity and introduce the framework of creative mathematical action (Riling, 2020 ). We then describe the theory of constructionism, which underpins the design of this study, and discuss our conceptualization of Scratch as an “object-to-think-with” during programming-based mathematical activities under the framework of creative mathematical action.

2.1 Creativity and creative mathematical action

Creativity, defined as the generation of novel and useful ideas or products (Amabile, 1996 ), has received widespread attention in K-12 education. Research about creativity in mathematics education often deals with the construct of “mathematical creativity”, though its notion in empirical studies is diverse. Joklitschke et al. ( 2022 ) conducted a systematic review and identified five predominant notions of creativity in mathematics education research. That is, creativity is defined as (1) flexibility, fluency, and/or other characteristics; (2) divergent thinking; (3) a sequence of stages; (4) creative mathematical reasoning; and (5) person-, product-, process-, and/or behavior-based notion. In addition, creativity can be also grouped into dimensions of creativity-as-talent, creativity-as-product, and creativity-as-process. Creativity-as-talent focuses on personal characteristics, such as the relationship between students’ creativity and mathematical abilities (Kattou et al., 2013 ), while creativity-as-product examines the novelty and usefulness of students’ artefacts as learning outcomes (Weng et al., 2022b ). As for creativity-as-process, attention is paid to personal creativity that occurs during the learning process, which relates to what Beghetto and Kaufman ( 2007 ) term mini-c creativity—“the novel and personally meaningful interpretation of experiences, actions, and events” (p.73). Other scholars also highlight the cognitive aspect of creativity-as-process, or the process of creative thinking (Schoevers et al., 2019 ) during learning activities.

Considering the interplay among person, product and process in mathematical creativity rather than addressing a particular level of creativity, Riling ( 2020 ) proposed the creative mathematical action framework (CMAF) which defines creative mathematical action as “one that transitions a given mathematical context into a new version of mathematics by creating ways of doing or thinking about mathematics that were previously not possible for a particular community of mathematicians” (p. 17). Noteworthy, the mathematician mentioned refers to any individual who engages in doing mathematics rather than only those who are mathematical experts. Specifically, the CMAF emphasizes four important components of action, context, new possibilities and community:

Mathematical context : creativity is not the sudden, random endeavor of individuals, but is inevitably influenced by the mathematical concepts and practices existing in the community.

New mathematical possibilities : the set of mathematical concepts and practices of any community is not pre-ordained; rather, it will vary according to the creative acts performed.

Mathematical community : how and what mathematicians (everyone in the community) create will depend on their identities, their relationship with one another and their relative engagement with privilege and oppression.

Creative action : since each action has its roots in one’s community, creative acts inside one community may or may not lead to new mathematical possibilities in another.

The CMAF highlights the interactions between the four components, and we thus also see the possibility of creative actions in programming-based mathematical activities. Concerning creativity, Kafai ( 2006 ) explains that constructionist learning is a form of creative experiment in which learners construct, examine, and revise connections between pre-existing and new knowledge gained from the real world. This idea has important implications for mathematics education, as it implies that learning is tangible and experimental. Furthermore, constructionist learning is highly relevant to doing mathematics by means of programming (Feurzeig et al., 2011 ; Kynigos et al., 2014 ; Papert, 1980 ). Thus, we see the potential to investigate mathematics teachers’ creative actions in a programming-based mathematical context as a form of professional development. We will detail the concept of constructionist learning and the relationship between creative mathematical actions in the next section.

2.2 Constructionism and “Object-to-think-with”

This research is underpinned by Seymour Papert’s constructionism (Papert & Harel, 1991 ) which was influenced by Jean Piaget’s constructivist learning theory. While both constructivism and constructionism are premised on students’ active construction of knowledge, constructionism highlights that the most productive learning happens when learners create a personal and shareable artefact. Therefore, the meaning of “construction” has two levels: learners create artefacts in the physical world (first-level construction) which serves as an “object-to-think-with” to facilitate them to build coherent and cognitive structures about the learning content (second-level construction), that is, “learning-by-making”. Thus, whereas constructivism suggests that learners move progressively from concrete objects to mental symbolic objects and can increasingly extract rules from empirical regularities, constructionism emphasizes knowledge construction in situ, in the sense that learners should be situated to become “one” with the environment instead of “looking at a distance” (Ackermann, 2001 ).

Papert ( 1980 ) identified his Logo programming as an “object-to-think-with,” namely a physical or digital or even mental object that becomes a cognitive artefact in which “there is an intersection of cultural presence, embedded knowledge, and the possibility for personal identification” (p. 11) during the thinking and learning process (e.g., a formula in a computer program can be seen as a digital object-to-think-with). As captured by Sinclair et al. ( 2013 ) making a square in Logo can be seen as a creative act or an example of “potential inventive moments in which the human-technology interaction gives rise to new ways of thinking and moving” (p. 242), which exemplifies Logo programming as engagement with intellectual tools and affording thinking about concepts and strategies that are grounded in intuitive knowledge (Noss & Hoyles, 2017 ). Thus, an object-to-think-with can serve as “a cognitive tool that thinkers can observe, manipulate, or probe, and in doing so test and explore complex phenomena or ideas with which they are unfamiliar” (Holbert & Wilensky, 2019 , p. 36).

While Papert’s Logo was, in the early 1990s, a high-tech and active computational expressive medium, the emergence of forthcoming digital technologies (e.g., block-based programming, geometrized programming, tangible programming; Ye et al., 2023a ) demands the need to reconceptualize constructionist learning with current programming tools. To this end, the work of Ng and colleagues (Ng & Cui, 2021 ; Ng et al., 2021 ) has provided insight into “digital making” as a form of constructionist learning afforded by block-based programming environments, where students actively engage in constructing digital artefacts in the form of programming solutions to mathematical problems. In these studies, it was shown that Scratch was instrumented as a creative environment in which mathematics can not only be read numerically but also heard and visually and dynamically represented.

From the perspective of creative mathematical actions, learners and their more-knowledgeable-others establish a community that occasions the creation of ideas and artefacts in the programming-based mathematical context. Within this shared community, learners will be expected to leverage pre-existing programming and mathematical knowledge to engage in creative activities in which programming artefacts serve as an object-to-think-with to yield new experiences of doing mathematics. Therefore, this study conceptualizes Scratch as an object-to-think-with that facilitates mathematical actions with creative potential, and we designed programming tasks to inspire new ways to think about geometry in the given constructionist learning context. From this, the overall objective of this study was to investigate what creative actions mathematics teachers exhibit while engaging in geometrical constructions in a programming context, and how these actions facilitated them to develop mathematical and computational concepts, thus experiencing new possibilities for doing mathematics as part of their professional development.

3 Methodology

This study is situated in a series of Scratch professional development workshops which aim to facilitate in-service mathematics teachers’ learning in a programming-based mathematical context. The following subsections detail the methods undertaken.

3.1 Participants and context

A 10-h, five-week professional development workshop series in Scratch programming was delivered online (one two-hour session per week) to six in-service secondary school mathematics teachers, recruited through the network of the first author (hereafter, “the researcher”) in Mainland China. Inclusion criteria of participants were: (1) having a range (1 to 5 years) of teaching experience; (2) having no prior experience of Scratch programming; and (3) showing a strong interest in programming-based mathematical activities as professional development. Four female and two male teachers, aged from 20 to 30, were divided into three pairs, and each pair attended the workshops separately to maintain an optimal researcher: participant ratio of 1:2 for in-depth analysis. Most of the sessions are completed by two participants working together throughout; but as the session chosen for this study aims to examine the creativity of each individual, the two participants first worked together to familiarize themselves with some basic functionality by solving a geometry task, and then worked independently with Scratch to create geometric figures. Only when the participants encountered difficulties would the researcher briefly pause their work and lead a discussion between the two participants.

3.2 Task design

We chose a task used during the third session as the focus of our investigation because it offered flexibility for participants to express and create their figures through tinkering with different aspects of rotational symmetry, namely, what figure to be rotated and how to rotate it. From a programming perspective, the task may prompt the use of loops when making a figure with congruent sides and congruent interior angles, and of subroutines (“My Block” in Scratch) when creating duplicates of a figure. During the session, we initially invited the teachers to draw some geometrical figures utilizing concepts such as angle of turn and interior angles of regular polygons. Then, they were given a sample figure made up of six identical pentagons differing by a 60-degree turn at one of the vertices of the pentagon (Fig.  1 ) and asked to work collaboratively to replicate it in Scratch. This was intended to familiarize the teachers with the drawing functions (“Pen up,” “Pen down,” “erase all”) and some transformation functions (“turn,” “move,” “rotate”). Following that, they were given 30 min to engage in the exploratory drawing task, working individually to create any figures that they wished according to their imagination.

Sample figure of rotational symmetry

3.3 Data collection and analysis

Given that “we may not, and probably cannot, account for students’ [or others’] mathematics using our own mathematical concepts and operations” (Steffe & Thompson, 2000 , p. 268), we collected data through task-based semi-structured interviews during participants’ geometry figure construction process. Task-based semi-structured interview is suitable for this qualitative and in-depth study, as we could interpret the participants’ task performance to look for evidence of creative actions from their discourse. To maximize discourse opportunities, we used open questions to prompt the participants to express their thought processes (e.g., What did you do? Why did you do this? How did you achieve this drawing? Is there anything else you would like to draw?) By asking a series of what, why and how questions, we aimed to interpret the participants’ thinking processes from a discursive approach while triangulating with their programming activities as captured by screen-recording. Since an important characteristic of the qualitative research methodology is the collection and analysis of data from multiple sources, we collected observation data and the programming artefacts during the task. In summary, the qualitative data emanated from several sources: video-recorded construction sessions which captured the participants’ interviews and computer screens on which they were working; the participants’ final programming codes and working notes; and the researcher’s field notes.

Under the framework of creative mathematical actions, our analysis of the teachers’ creative actions while engaging in their geometric creations was twofold in response to the two RQs posed. To answer RQ1, our data analysis focused on identifying the creative actions demonstrated by the participants during the task, particularly novelty as an attribute of creativity. As we see opportunities for our designed programming-based geometry task to be a medium for expression by extending and recreating the initial drawing in novel ways, we focus our attention on the creative process—“the sequence of thoughts and actions that leads to a novel, adaptive production” (Lubart, 2001 , p. 295)—rather than just the creative product. Thus, we attended to the actions taken with the programming tool (as context) upon which there emerged new ways to interpret teachers’ construction mathematically or computationally during the task from the perspective of CMAF. In terms of RQ2, we adopted thematic analysis to examine how creative actions provide new possibilities for doing mathematics by the teacher participants. Specifically, we look for evidence of how teachers both develop and integrate mathematical and programming concepts when they demonstrate creative actions during the construction.

We conducted thematic analysis coupled with deductive and inductive coding to analyze moments that participants demonstrated creative actions or (re-)shaped their mathematical and programming concepts in their ongoing geometric creation, and we undertook iterative comparisons to verify the findings obtained. In Phase 1, we conducted attribute coding, that is, to organize the data by their attributes (i.e., type of observation, type of data collection method, which participant). We then carried out topic coding, another deductive analysis, to sort the data into categories that are relevant to the respective research questions in Phase 2. From there, open coding was applied to identify emerging ideas in the data, which generated inductive codes: “changing values”, “remixing and reusing”, respectively under RQ 1, and “recognizing difference between counter- concepts”, “experiencing connections between family concepts”, “exploring particular concepts at multiple levels”, “algorithmic thinking”, “iterative thinking” under RQ 2 in Phase 3. Finally, based on the open codes, we developed themes that included two kinds of creative actions (i.e., testing and iterating practices) and two forms of new possibilities for doing mathematics (i.e., new ways to engage in mathematical processes and understand mathematics from a computational perspective). The thematic analysis is supported by the lens of CMAF, which informs the relations among the creative actions, tools, and new possibilities for doing mathematics.

In this section, we respond to the RQs by analyzing two participants’ creative mathematical actions during the geometric construction and detail the new possibilities of doing mathematics in the programming context. They were chosen because they were more expressive during the interview process, which allowed us to gain a clear understanding of their actions. Furthermore, although the other participants evidenced discussions and results similar to those evidenced by these two cases, the creation process of these two teachers encompassed the commonality and distinctiveness observed in this case study.

We characterized Teacher 1’s (T1) construction as encompassing three kinds of approach: initial intentional creation related to rotations of regular polygons; accidental or unplanned creation with rotations of non-regular polygons and purposeful new creation based on translation.

4.1.1 Intentional creation: rotations of regular polygons

In the given mathematical context to draw a sample figure, T1 first defined a My Block named “regular pentagon” and recalled the subroutine in the main program (Fig.  2 ) to draw several rotated pentagons. Then, T1 associated her drawing with another polygon by connecting the properties of hexagons with her programming codes. That is, she changed the number of sides from 5 to 6, and the angle of the rotation from 72 to 60 degrees in her original subroutine to draw the repeated hexagon six times. Figure  3 a shows her initial explorative drawing upon her enactment of the existing mathematics concepts and programming skills in the programming-based mathematical learning context.

Teacher 1’s programming codes for the sample figure

Some figures created by Teacher 1: ( a ) initial explorative drawing; ( b ) a trapezoidal rotation figure; ( c ) a non-enclosed figure; ( d ) an enclosed trapezoid; ( e ) a figure formed by the rotation of a triangle. Note. The red arrows indicate the final position and direction of the pen

4.1.2 Unplanned creation: rotations of non-enclosed polygons

Subsequently, the action of T1 to change the values of different parameters triggered some unplanned creative works that just opened new possibilities for doing mathematics. At first, T1 offered to draw a new figure with a triangle as the base figure (Episode 1, [25:16]), to be rotated six times. However, when she changed the number of sides of the figure from six to three, she neglected to change the turn angle, thus inadvertently drawing three sides of a regular hexagon. Finding that the drawing resembled a trapezoidal rotation shape (Fig.  3 b), T1 realized that the [turn clockwise 60°] block in the subroutine had made a different interior angle from that anticipated. Here, her mathematical knowledge of interior angles of regular polygons in the programming context of turning the Pen supported her new experience of drawing geometric figures while debugging the program. The following episode illustrates this new experience of doing mathematics brought by T1’s creative actions.

Episode 1. Teacher 1 questioned why she had created a trapezoid instead of a triangle.

• T1 represents Teacher 1, R represents researcher

As shown above, T1 identified that she had created a non-enclosed figure upon the loop executed three times, each creating a line and performing a 60-degree rotation of the Pen direction (Fig.  3 c). Furthermore, when the next subroutine was called in the main program, the Pen would be initialized to move back to (0,0) each time it was in a “Pen down” position, hence forming a line connecting the current position and (0,0), resulting in an enclosed trapezoid (Fig.  3 d). With her programming knowledge, she modelled the codes with the properties of triangles and reflected that it was incorrect to make the Pen turn by 60 degrees (instead, the turn should be by 120°). Upon her change of codes at [28:04], the final figure which was made up of six triangles and with a rotational symmetry of degree six was formed (Fig.  3 e).

Thus far, we see that T1’s creation is caused by changing two parameters, namely the number of line segments to be formed and the turn angle between each line, which would determine the shape of the base figure. Interestingly, by figuring out a bug in the program, T1 realized that even if she had made three segments, the base shape would not necessarily be a triangle if coupled with an incorrect turn angle, which would produce a non-enclosed figure [29:25]. Such a new experience of drawing provided opportunities for T1 to recognize the relationship between regular and non-regular, enclosed and non-enclosed figures which was illustrated in Episode 2.

Episode 2. Teacher 1’s exploration of base shapes evidencing her creative actions.

As depicted above, T1 has identified the underlying processes in the generation of regular and non-regular polygons which implicated new possibilities for doing mathematics upon the creative actions. Specifically, when drawing an interior angle (α o ) of an n -sided regular polygon in Scratch, one needs to turn the Pen by its exterior angle (180- α o ) because of the way Scratch interprets an angle by the turning of a Pen, as opposed to the angle formed by turning an array at a vertex. In other words, to create a regular octagon, one would need to make eight turns, each equaling the exterior angle of that regular octagon (i.e., 360/ n  = 360/8 = 45°; see [35:23]). Meanwhile, as in the case of making a trapezoid by forming three segments in the subroutine, T1 also generalized that when making n line segments and n turns that do not total 360°, the shape formed would be non-enclosed. Therefore, a non-regular polygon with n  +  1 sides would be created due to the Pen moving back to (0,0) as programmed. Upon this discovery, T1 used the subroutine to create n -sided regular polygons and ( n  + 1)-sided non-regular polygonal base shapes, as well as tested different parameters in the main program that served to control the angle and number of rotations of the base shapes, thus producing the series of novel figures shown in Table  1 .

In summary, the creation of non-regular and regular shapes in Table  1 featured T1’s creative actions as afforded by the programming environment—she randomly changed the parameters inherited in the program (number of loops and exterior angle of the figure in the subroutine; the degrees and number of rotations in the main program) and explored how they generated different kinds of polygons with and without rotational symmetry. This indicates that T1 could flexibly create novel and esthetic graphics by integrating her mathematical concepts about regular polygons and rotational symmetry with her programming knowledge about loops and subroutines, which she developed from testing the value of different parameters in the program as a kind of creative mathematical action. The mathematical and programming concepts (emerged in the programming process) and artefacts (geometrical shapes created) developed contributed to T1’s creative actions uniquely within a programming-based mathematical context.

4.1.3 Purposeful new creation: translation of regular polygons

After experiencing new construction to explore the relationship between non-regular polygons and regular polygons, T1 proposed to produce some novel shapes by translating the base figure rather than rotating it at a point. As translating a figure was a different transformation from rotating it, she faced various challenges throughout the creation process and had to integrate her existing mathematical concepts of transformation and programming skills (a new block [change x by XX ] which would translate the x -coordinate of the Pen) to achieve her creation. Initially, T1 placed the [change x by 10] block in the subroutine loop (Fig.  4 a), resulting in a shape that did not match her imagining (Fig.  4 b and c).

a Teacher 1’s initial subroutine for figure translation; b a shape created by the subroutine of (a); c the overall shape created when executing the codes as shown in (a)

By reflecting on the difference between the translation process (in the mathematical sense) and the code sequence (in the programming sense), T1 found a bug in that the Pen position was changed after each side was drawn rather than after each figure was drawn, which relates to the computational concept of “sequence”. She then repositioned the block [change x by 10] (related to translation) in the main program loop (Fig.  5 a) but had not expected that the program would cause the graphic to be rotated while simultaneously being translated to the right (Fig.  5 b, i-ii), which provided opportunities for T1 to experience the connection of translations and rotations. Referred to the properties of translations and rotations, T1 successfully debugged the code by removing the [turn clockwise XX degrees] block (related to rotation) from the loop and produced her imagined figure (Fig.  5 b, iii), which indicates that the computational concept of sequence is important to achieve a mathematical process. This episode also evidenced the role of the unexpected programming artefact as an object-to-think-with in inquiring about geometrical properties and reflecting on the program as T1 integrated a combination of mathematical and programming knowledge to facilitate her creative actions.

a Teacher 1 repositioned the block [change x by 10] in the main program loop; b some shapes created during the reflecting process

Unlike T1’s parameterless subroutine, Teacher 2’s (T2) figure construction began with a parameterized subroutine, which led to a series of progressive constructions related to the same mathematical concept: rotational symmetry of single figure, rotational symmetry of composite figures, and rotational symmetry of figures with rotational symmetry.

4.2.1 Rotational symmetry of single figure

In the pre-construction stage, by connecting the existing mathematical concepts of rotational symmetry and programming skills (loop and subroutines etc.) to investigate the method of creating regular pentagons with rotations, T2 designed a My Block (subroutine) with one parameter (“side_length,” Fig.  6 a) which could take on different values of side lengths to change the overall size of the base shape. When the researcher proposed drawing another polygon (e.g. a regular hexagon) as the base figure, T2 soon added a second parameter, “exterior_angle,” in her My Block (Fig.  6 b). Episode 3 illustrates T2’s sharing of her thinking with Teacher 3 (T3), which also depicts how she imagined her existing approach to solving the problem.

a A My Block with one parameter; b A My Block with two parameters; c a non-enclosed “hexagon” with one side missing

Episode 3. Teacher 2’s sharing with Teacher 3 on her imagined approach.

As can be seen from the episode above, T2 stated that her subroutine with two parameters, “side_length” and “exterior_angle,” was sufficient to draw different regular polygons as long as the parameters were changed [36:03]. Therefore, she quickly changed the parameter in the subroutine—exterior angle—from 72 degrees of the regular pentagon (Fig.  6 b) to 60 degrees of the regular hexagon. However, the code only produced a non-enclosed “hexagon” with one side missing (Fig.  6 c). This was because the subroutine did not contain a loop that would control repeatedly drawing n sides of a n -sided regular polygon, but instead included five [move XX steps] blocks to fix the number of sides to five (Fig.  6 b).

T3 then proposed to simplify the program by using a loop to avoid reusing multiple [move XX steps, turn clockwise YY degrees] blocks, where the number of loops, n , corresponded to the number of sides (and angles) in a regular n -sided polygon. By observing T3 used a repeat block and created a My Block with three parameters (“side_length,” “exterior_angle,” “number_of_sides,” Fig.  7 a), T2 then successfully debugged her subroutine differently, that is, T2 did not set a third parameter in the subroutine but made the second parameter “number_ of_sides” instead of “exterior_angle” (Fig.  7 b), suggesting that she optimized the My Block with only two parameters to the same effect. We infer that T2 had integrated her programming and mathematical thinking by relating the two parameters in a multiplicative relationship: The second parameter (“exterior_angle”, x ) could be deduced from the third parameter (“number_of_sides”, n ) in the sense that x  = 360/ n . Thus, the My Block only requires two parameters to control its shape (“number_of_sides”) and size (“side_length”) respectively.

a Teacher 3’s My Block with three parameters; b Teacher 2’s My Block with two parameters

T2’s debugging of the subroutine that could change the shape and size of regular polygons prepared for her subsequent creations in significant ways. Like T1, she first constructed some regular polygonal base shapes by changing the different parameters (Method 1). This creation process was much simpler and more accurate than T1’s parameterless subroutine which had occasioned unplanned drawings, since T2 only needed to input the values of “side_length” and “number_of_sides,” upon which the size of the exterior angle and number of loops could be computed automatically without any data mismatch resulting in non-regular polygonal shapes. Thus, the process of developing a subroutine with key parameters aligned with geometrical properties generated new ways for T2 to do mathematics from a computational perspective.

4.2.2 Rotational symmetry of multiple figures

After a few attempts at changing the number of sides and loops to form the rotational symmetry of a single polygon (Method 1), T2 tried a second round of creation built on Method 1. That is, she innovated to create a new base shape by using “a combination of pentagon and hexagon”. Converting to the programming context, T2 replicated her My Block (subroutine) named “polygon” to create two regular polygons with different parameters. In programming terms, she was remixing her polygon creation by calling the subroutine twice (3-sided, 30 steps; 6-sided, 50 steps) within the main program (Fig.  8 a). She then kept trying different values of the two parameters in each subroutine and the number of rotations in the main program to create different composite base shapes consisting of multiple polygons varying in shape and size for her rotational symmetrical figure (see Table  2 ). She also added a third subroutine to the main program (Fig.  8 b) to perform rotation of a base shape composed of three different-sized and shaped regular polygons (Table  2 , Figure c-d). Thus far, T2’s creative actions were demonstrated in remixing and reusing subroutines several times by connecting properties of polygons to generate shapes that were personally meaningful. Importantly, she did so by integrating her geometrical knowledge about the parameters of regular polygons (size and shape) and programming concepts of subroutines , which provided a new way to achieve the drawings with rotational symmetry.

Teacher 2 remixed her polygon creation by calling the My Block ( a ) twice; ( b ) three times

4.2.3 Rotational symmetry of figures with rotational symmetry

Thus far, T2’s creations have extended from a base shape made of a single polygon to composite shapes made of several polygons by reusing multiple My Blocks . Having inquired into the mathematical concept of composite figures and the codes used in Method 1, T2 derived a third method of creation—using Method 1 to create a rotational symmetrical figure formed by rotating an equilateral triangle three times as the new composite figure (Fig.  9 a), then rotating the base figure again to form the symmetrical figure (Fig.  9 b). We analyze her actions in detail below.

a A base shape created by using Method 1; b the final symmetrical figure

Before finalizing the figure shown in Fig.  9 b, T2 experienced challenges while inquiring how she could rotate her composite base figure. To do so, she decomposed the problem and tried the [go to random position] block to check if the composite base figure would appear in random positions. Initially, T2 was confused as to how to rotate the base shapes while changing their positions, as she placed the [go to random position] block after the first loop in the main program (to draw the first composite figure) (Fig.  10 a). Thus, even though the loops were able to draw multiple composite shapes, the position could only be changed once because the position-changing block was not placed inside the loop. Upon reflecting on the relationship between codes and artefacts, she realized the problem and placed the [move to random position] block after creating each composite figure, successfully drawing several composite shapes in random positions (Fig.  10 b). Here, the programming artefact as an object-to-think-with related to the programming concept of sequence supported her reflection. Having figured out this process, T2 then replaced the [move to random position] block with [move XX steps] and [turn right YY degrees] by referring to mathematical concepts of rotational symmetry. Through several times of debugging, T2 eventually succeeded in drawing a rotational symmetric figure of a composite base shape that was formed by rotating an equilateral triangle three times (Fig.  9 b). Overall, this case supported the view that T2 regarded an artefact as an object-to-think-with by drawing upon mathematical properties (rotational symmetry) and programming concepts (sequences, loops) in her iterative creative action, which not only contributes to her understanding of rotational symmetry at multiple levels but also facilitated T2’s experience of the rotational process from a computational perspective.

a Initial codes that only changed the position of composite shape once; b several composite shapes were drawn in random positions

5 Discussion

Prior studies have noted the importance of regarding programming as an object-to-think-with to learn mathematics (Papert, 1980 ), which is also an expressive medium for exploring personal ideas supported by existing mathematical concepts (Kynigos, 1995 ; Lewis, 2017 ). Linking mathematical creativity and programming as constructionist learning, we set out to investigate the characteristics of creative mathematical actions exhibited by mathematics teachers during programming-based mathematical activities. In the following, we will discuss the findings that responded to the two RQs (Table  3 ) and some further implications.

5.1 Two kinds of creative actions in a programming-based mathematical context

We have described and analyzed the creative process of the two cases in detail in the results section, from which we noted that the teachers went through different creation processes. In the first case, T1 produced a series of unstructured, independent creations related to different mathematical concepts, whereas in the second case, T2 showed a progressive, structured creation rooted in the same concept of rotational symmetry. Despite the difference in the creative process between the two cases, the results indicate two kinds of creative mathematical actions inspired by the programming-based mathematical context.

5.1.1 Unstructured creative action by testing: Changing the value of different parameters (variables)

The testing practices demonstrated by the teacher participants were seen as one kind of important creative action. As shown in Table  1 , T1 tested various combinations of parameters by changing their values in the subroutine (“side_number” and “turn_angle”) and main program (“turn_angle” and “rotation_times”) to explore different rotational symmetry or asymmetrical shapes that were made of regular or non-regular polygons. Although these may seem like random actions of trial and error, the practice of changing the value of several parameters in the programming-based mathematical activity did provide a rich opportunity for creative actions. That is, the programmer could proceed to a new round of reflection-based exploration and creation relying on the programming artefacts by trial and error as an object-to-think-with, which engendered new possibilities for doing mathematics in their community. These random testing practices to create new geometrical figures, despite producing unstructured results, were indeed an important source of new experience for doing mathematics.

5.1.2 Structured creative action by iterating: reusing and remixing codes

Another significant creative action shown in this study was the iterative practice of reusing and remixing codes as exhibited by T2. In the case of T2, we notice a gradual and sustained development from her initial figure (adopting Method 1) to the final figure (adopting Method 3) through an iterative creative process. That is, T2 created three levels of rotational symmetry, starting from the single polygon as the base figure to multiple polygons by reusing several subroutines, and finally derived a rotational symmetric figure with the base figure also having rotational symmetry. This was achieved by remixing codes related to drawing rotational symmetric figures. Hence, T2 was advancing her knowledge about rotational symmetry and loops in her creative actions, finally generating a nested loop which performed one level of rotation inside another. Simultaneously, she was working with each level of the base figure as an object-to-think-with in an increasingly sophisticated manner. Thus, we regard such iterative practices of reusing and remixing codes as a kind of structured creative action underlying the programming-based mathematical context.

5.2 New possibilities for doing mathematics engendered by creative actions

In this study, we were also interested in what and how new mathematics possibilities may be engendered by creative actions for mathematics teachers in a programming context. From the results of the study, we suggest that new realizations and interpretations of mathematics may be engendered by creative actions. First, we evidence T1’s new realization of mathematics through her unstructured creative actions. As argued by previous studies (Cui & Ng, 2021 ), given there exists a mismatch between mathematical and programming languages, new realizations may emerge when participants need to transform mathematical processes into a programming language (Ye et al., 2023b ). Likewise, while exploring the series of non-regular polygons and regular polygons, T1’s unexpected creation led her to a new interpretation of making n -sided regular polygons and non-regular polygons with n  + 1 sides using a combination of n line segments and n angle turns as part of her creative actions, which generated a new opportunity for T1 to experience geometric figures different from a paper-and-pencil context. From this and together with T2’s iterative creation of rotational symmetry, we infer that programming artefacts generated by testing and iterating creative actions served as an object-to-think-with, yielding three different opportunities for teacher participants to make sense of mathematics in a new context: (a) recognizing the difference between counter-concepts (e.g., non-regular and regular polygons; symmetry and asymmetry); (b) experiencing connections between family concepts (e.g., transformation concepts of translations and rotations); and (c) exploring particular concepts at multiple levels (e.g., rotation symmetry). These findings may help us to better understand the kinds of new mathematical experiences elicited by creative actions in the programming-based mathematical context.

Secondly, the results suggest that the practices of algorithmic thinking and iterative thinking , which are highly relevant to computational thinking (Wing, 2006 ), could facilitate new interpretations of mathematics from a computational perspective (Ye et al., 2023a ). Taking the case of T1, she manipulated her code sequences and used nested loops to repeatedly (re-)interpret her geometric transformations. From the perspective of computational thinking, sequences determine the order of events, while loops control the number of times an event occurs, and nested loops imply that a certain cyclic process is repeated. Hence, T1’s algorithmic thinking was interacting with her interpretations of mathematics in a mutual and complementary way.

Regarding iterative thinking, in the case of T2, we notice two different ways of reusing codes, namely repetition and iteration. As illustrated in Method 2 (Sect. 4.2.2), T2 realized her idea of rotating a composite figure as the base shape by repeatedly calling a subroutine to draw multiple regular polygons of different shapes and sizes within the rotation loop. That is, the composite figure was generated by reusing the same subroutines several times but with different parameters. Furthermore, in Method 3, although T2 did not directly call a subroutine with the function to draw a figure of rotational symmetry, she remixed codes related to rotational symmetry that was used in Method 1 to form the base shape and then nested the codes in another level of rotation, demonstrating that her concept of rotational symmetry evolved from an iterative perspective. Taken together, these findings suggest that creative action in a programming environment is supportive of new realizations and interpretations of mathematics from a computational perspective.

5.3 An adapted framework for investigating creative actions in a programming-based mathematical context

Overall, by adopting the framework of creative mathematical action (Riling, 2020 ), this study provides qualitative evidence of the creative actions taking place in a programming-based mathematical context, which has significant implications for understanding creativity in K-12 mathematics education. The teachers’ creative actions highlight the potential affordances of Scratch as a creative learning environment (Weng et al., 2022b ) and an object-to-think-with that facilitates participants’ mathematics learning and programming practices. Not only does Scratch’s block-based programming environment support a dynamic visualization of the geometry drawing process; but its open-ended, free-form coding provides opportunities for flexible understanding and application of participants’ geometry concepts and programming skills. Unlike traditional curriculum where geometry knowledge is applied to solving a specific type of geometry problem, the free creation of geometric shapes in Scratch can inspire connections between various geometry concepts. Thus, concerning the context of programming-based mathematical activities, we propose an adapted framework (Fig.  11 ) which would be helpful for future research in identifying creative mathematical actions in domain-specific ways by drawing close connections with concepts from mathematics and computer science. Specifically, we emphasize the creative actions in the programming context, and thus extend the given mathematical context to a programming-based mathematical context which includes the programming tool as a constructionist learning environment. Furthermore, we highlight the role of the programming artefact as an “object-to-think-with” to inspire creative actions that bring new possibilities for doing mathematics in a cyclical way.

Framework adapted from the CMAF (Riling, 2020 ) for programming-based mathematical learning context

Nevertheless, it is important to realize that creativity should be seen as a dynamic process of interaction between participant, task and situation (Tromp & Sternberg, 2022 ), which are important components of a mathematical community. Thus, rather than seeing creativity as an end in itself, we should see it as a means to other ends (Beghetto & Kaufman, 2014 ).

6 Conclusion

In conclusion, this study provided evidence that testing and iterative practices of reusing and remixing are two kinds of creative actions afforded by the programming environment, which offered new possibilities for doing mathematics in the sense of generating new ways to engage in mathematical processes and to understand mathematics from a computational perspective. The findings of this study contribute to our understanding of creative mathematical actions and new possibilities in mathematics inspired by a programming-based mathematical context, particularly the role of mathematics and programming concepts and their interplay, in developing teachers’ creative mathematical actions. The results also support the idea that Scratch can be a creative learning environment and an object-to-think-with to facilitate mathematics teachers’ experience of doing mathematics, which informs future research on task design to support teacher professional development. Furthermore, our adapted framework for creative actions in the context of programming-based mathematical activities is worthy of future research and can be practical for supporting teachers in identifying students’ mathematical creativity from the perspective of creative actions during classroom teaching. However, as our design of the study only focuses on one sample task related to rotational symmetry in Scratch, these findings may be somewhat limited by the task design and participants’ programming experience. Thus, future work is needed to shed light on different creative mathematical actions in different programming contexts with various tasks.

Amabile, T. M. (1996). Creativity and innovation in organizations (Vol. 5). Harvard Business School.

Google Scholar  

Ackermann, E. (2001). Piaget’s constructivism, papert’s constructionism: What’s the difference. Future of Learning Group Publication , 5 (3), 438. Retrieved October 15, 2023, from  http://www.sylviastipich.com/wp-content/uploads/2015/04/Coursera-Piaget-_-Papert.pdf

Beghetto, R. A., & Kaufman, J. C. (2007). Toward a broader conception of creativity: A case for “mini-c” creativity. Psychology of Aesthetics, Creativity, and the Arts, 1 (2), 73. https://doi.org/10.1037/1931-3896.1.2.73

Article   Google Scholar  

Beghetto, R. A., & Kaufman, J. C. (2014). Classroom contexts for creativity. High Ability Studies, 25 (1), 53–69. https://doi.org/10.1080/13598139.2014.905247

Bolden, D. S., Harries, T. V., & Newton, D. P. (2010). Pre-service primary teachers’ conceptions of creativity in mathematics. Educational Studies in Mathematics, 73 , 143–157. https://doi.org/10.1007/s10649-009-9207-z

Cui, Z., & Ng, O. (2021). The interplay between mathematical and computational thinking in primary school students’ mathematical problem-solving within a programming environment. Journal of Educational Computing Research, 59 (5), 988–1012. https://doi.org/10.1177/0735633120979930

Feurzeig, W., Papert, S. A., & Lawler, B. (2011). Programming-languages as a conceptual framework for teaching mathematics. Interactive Learning Environments, 19 (5), 487–501. https://doi.org/10.1080/10494820903520040

Holbert, N., & Wilensky, U. (2019). Designing educational video games to be objects-to-think-with. Journal of the Learning Sciences, 28 (1), 32–72. https://doi.org/10.1080/10508406.2018.1487302

Hoth, J., Kaiser, G., Busse, A., Doehrmann, M., Koenig, J., & Blömeke, S. (2017). Professional competences of teachers for fostering creativity and supporting high-achieving students. ZDM-Mathematics Education, 49 (1), 107–120. https://doi.org/10.1007/s11858-016-0817-5

Joklitschke, J., Rott, B., & Schindler, M. (2022). Notions of creativity in mathematics education research: A systematic literature review. International Journal of Science and Mathematics Education, 20 (6), 1161–1181. https://doi.org/10.1007/s10763-021-10192-z

Kafai, Y. B. (2006). Constructionism. In K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 35–46). Cambridge University Press.

Kattou, M., Kontoyianni, K., Pitta-Pantazi, D., & Christou, C. (2013). Connecting mathematical creativity to mathematical ability. ZDM – Mathematics Education, 45 (2), 167–181. https://doi.org/10.1007/s11858-012-0467-1

Kynigos, C. (1995). Programming as a means of expressing and exploring Ideas: Three case studies situated in a directive educational system. In A. A. diSessa, C. Hoyles, R. Noss, & L. D. Edwards (Eds.), Computers and Exploratory Learning (pp. 399–419). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-57799-4_22

Kynigos, C., & Diamantidis, D. (2022). Creativity in engineering mathematical models through programming. ZDM–Mathematics Education, 54 , 149–162. https://doi.org/10.1007/s11858-021-01314-6

Kynigos, C., Moustaki, F., Smyrnaiou, R., & Xenos, M. (2014, August). Half-baked microworlds as expressive media for fostering creative mathematical thinking. In  Constructionism and creativity: Proceedings of the 3rd International Constructionism Conference 2014  (pp. 19–23). OCG (Österreichische Computer Gesellschaft).

Leikin, R., Berman, A., & Koichu, B. (2009). Creativity in mathematics and the education of gifted students . Brill.

Book   Google Scholar  

Leikin, R., & Elgrably, H. (2022). Strategy creativity and outcome creativity when solving open tasks: Focusing on problem posing through investigations. ZDM – Mathematics Education, 54 (1), 35–49. https://doi.org/10.1007/s11858-021-01319-1

Leikin, R., & Sriraman, B. (2022). Empirical research on creativity in mathematics (education): From the wastelands of psychology to the current state of the art. ZDM – Mathematics Education, 54 (1), 1–17. https://doi.org/10.1007/s11858-022-01340-y

Leikin, R., Subotnik, R., Pitta-Pantazi, D., Singer, F. M., & Pelczer, I. (2013). Teachers’ views on creativity in mathematics education: An international survey. ZDM – Mathematics Education, 45 (2), 309–324. https://doi.org/10.1007/s11858-012-0472-4

Lev-Zamir, H., & Leikin, R. (2013). Saying versus doing: Teachers’ conceptions of creativity in elementary mathematics teaching. ZDM – Mathematics Education, 45 (2), 295–308. https://doi.org/10.1007/s11858-012-0464-4

Lewis, C. M. (2017). Good (and bad) reasons to teach all students computer science. In S. B. Fee, A. M. Holland-Minkley, & T. E. Lombardi (Eds.), New directions for computing education (pp. 15–34). Springer. https://doi.org/10.1007/978-3-319-54226-3_2

Lu, X., & Kaiser, G. (2022). Can mathematical modelling work as a creativity-demanding activity? An empirical study in China. ZDM – Mathematics Education, 54 (1), 67–81. https://doi.org/10.1007/s11858-021-01316-4

Lubart, T. I. (2001). Models of the creative process: Past, present and future. Creativity Research Journal, 13 (3–4), 295–308. https://doi.org/10.1207/s15326934crj1334_07

Mann, E. L. (2009). The search for mathematical creativity: Identifying creative potential in middle school students. Creativity Research Journal, 21 (4), 338–348. https://doi.org/10.1080/10400410903297402

Mhlolo, M. K. (2017). Regular classroom teachers’ recognition and support of the creative potential of mildly gifted mathematics learners. ZDM – Mathematics Education, 49 (1), 81–94. https://doi.org/10.1007/s11858-016-0824-6

Ng, O., & Cui, Z. (2021). Examining primary students’ mathematical problem-solving in a programming context: Towards computationally enhanced mathematics education. ZDM – Mathematics Education, 53 (4), 847–860. https://doi.org/10.1007/s11858-020-01200-7

Ng, O., Liu, M., & Cui, Z. (2021). Students’ in-moment challenges and developing maker perspectives during problem-based digital making. Journal of Research on Technology in Education , 1–15. https://doi.org/10.1080/15391523.2021.1967817

Noss, R., & Hoyles, C. (2017). Constructionism and microworlds. In Duval, E., Sharples, M., Sutherland, R. (Eds.) Technology Enhanced Learning (pp. 29–35). Springer. https://doi.org/10.1007/978-3-319-02600-8_3

Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas . Basic Books Inc.

Papert, S., & Harel, I. (1991). Situating constructionism. In S. Papert & I. Harel (Eds.), Constructionism (pp. 1–11). Ablex Publishing.

Pitta-Pantazi, D., Kattou, M., & Christou, C. (2018). Mathematical creativity: Product, person, process and press. In F. M. Singer (Ed.), Mathematical creativity and mathematical giftedness: Enhancing creative capacities in mathematically promising students (pp. 27–53). Springer. https://doi.org/10.1007/978-3-319-73156-8_2

Riling, M. (2020). Recognizing mathematics students as creative: Mathematical creativity as community-based and possibility-expanding. Journal of Humanistic Mathematics, 10 (2), 6–39. https://doi.org/10.5642/jhummath.202002.04

Schoevers, E. M., Leseman, P. P. M., Slot, E. M., Bakker, A., Keijzer, R., & Kroesbergen, E. H. (2019). Promoting pupils’ creative thinking in primary school mathematics: A case study. Thinking Skills and Creativity, 31 , 323–334. https://doi.org/10.1016/j.tsc.2019.02.003

Shriki, A. (2010). Working like real mathematicians: Developing prospective teachers’ awareness of mathematical creativity through generating new concepts. Educational Studies in Mathematics, 73 (2), 159–179. https://doi.org/10.1007/s10649-009-9212-2

Sinclair, N., de Freitas, E., & Ferrara, F. (2013). Virtual encounters: The murky and furtive world of mathematical inventiveness. ZDM – Mathematics Education, 45 , 239–252. https://doi.org/10.1007/s11858-012-0465-3

Steffe, L. P., & Thompson, P. W. (2000). Teaching experiment methodology: Underlying principles and essential elements. In R. Lesh & A. E. Kelly (Eds.), Research design in mathematics and science education (pp. 267–307). Erlbaum.

Tromp, C., & Sternberg, R. J. (2022). Dynamic creativity: A Person × Task × Situation interaction framework. The Journal of Creative Behavior, 56 (4), 553–565. https://doi.org/10.1002/jocb.551

Van Harpen, X. Y., & Sriraman, B. (2013). Creativity and mathematical problem posing: An analysis of high school students’ mathematical problem posing in China and the USA. Educational Studies in Mathematics, 82 (2), 201–221. https://doi.org/10.1007/s10649-012-9419-5

Weng, X., Cui, Z., Ng, O., Jong, M. S. Y., & Chiu, T. K. F. (2022a). Characterizing students’ 4C skills development during problem-based digital making. Journal of Science Education and Technology, 31 (3), 372–385. https://doi.org/10.1007/s10956-022-09961-4

Weng, X., Ng, O., Cui, Z., & Leung, S. (2022b). Creativity development with problem-based digital making and block-based programming for Science, Technology, Engineering, Arts, and Mathematics Learning in middle school contexts. Journal of Educational Computing Research , 07356331221115661. https://doi.org/10.1177/07356331221115661

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49 (3), 33–35.

Ye, H., Liang, B., Ng, O.-L., & Chai, C. S. (2023a). Integration of computational thinking in K-12 mathematics education: A systematic review on CT-based mathematics instruction and student learning. International Journal of STEM Education, 10 (1), 3. https://doi.org/10.1186/s40594-023-00396-w

Ye, H., Ng, O., & Cui, Z. (2023b). Conceptualizing flexibility in programming-based mathematical problem-solving. Journal of Educational Computing Research . https://doi.org/10.1177/07356331231209773

Zazkis, R. (2017). Lesson play tasks as a creative venture for teachers and teacher educators. ZDM – Mathematics Education, 49 (1), 95–105. https://doi.org/10.1007/s11858-016-0808-6

Download references

Acknowledgements

This study was fully supported by the Research Grants Council, General Research Fund (Ref. No. 14603720).

Author information

Authors and affiliations.

The Chinese University of Hong Kong, Shatin, Hong Kong SAR

Huiyan Ye, Oi-Lam Ng & Allen Leung

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Oi-Lam Ng .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Ye, H., Ng, OL. & Leung, A. Examining mathematics teachers’ creative actions in programming-based mathematical activities. ZDM Mathematics Education (2024). https://doi.org/10.1007/s11858-024-01579-7

Download citation

Accepted : 17 April 2024

Published : 22 May 2024

DOI : https://doi.org/10.1007/s11858-024-01579-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Creative action
• Mathematics learning
• Programming
• Constructionist learning
• Find a journal
• Publish with us
• Track your research

• Skip to main content
• Keyboard shortcuts for audio player

Your Health

• Treatments & Tests
• Health Inc.
• Public Health

Why writing by hand beats typing for thinking and learning

Jonathan Lambert

If you're like many digitally savvy Americans, it has likely been a while since you've spent much time writing by hand.

The laborious process of tracing out our thoughts, letter by letter, on the page is becoming a relic of the past in our screen-dominated world, where text messages and thumb-typed grocery lists have replaced handwritten letters and sticky notes. Electronic keyboards offer obvious efficiency benefits that have undoubtedly boosted our productivity — imagine having to write all your emails longhand.

To keep up, many schools are introducing computers as early as preschool, meaning some kids may learn the basics of typing before writing by hand.

But giving up this slower, more tactile way of expressing ourselves may come at a significant cost, according to a growing body of research that's uncovering the surprising cognitive benefits of taking pen to paper, or even stylus to iPad — for both children and adults.

Is this some kind of joke? A school facing shortages starts teaching standup comedy

In kids, studies show that tracing out ABCs, as opposed to typing them, leads to better and longer-lasting recognition and understanding of letters. Writing by hand also improves memory and recall of words, laying down the foundations of literacy and learning. In adults, taking notes by hand during a lecture, instead of typing, can lead to better conceptual understanding of material.

"There's actually some very important things going on during the embodied experience of writing by hand," says Ramesh Balasubramaniam , a neuroscientist at the University of California, Merced. "It has important cognitive benefits."

While those benefits have long been recognized by some (for instance, many authors, including Jennifer Egan and Neil Gaiman , draft their stories by hand to stoke creativity), scientists have only recently started investigating why writing by hand has these effects.

A slew of recent brain imaging research suggests handwriting's power stems from the relative complexity of the process and how it forces different brain systems to work together to reproduce the shapes of letters in our heads onto the page.

Your brain on handwriting

Both handwriting and typing involve moving our hands and fingers to create words on a page. But handwriting, it turns out, requires a lot more fine-tuned coordination between the motor and visual systems. This seems to more deeply engage the brain in ways that support learning.

Shots - Health News

Feeling artsy here's how making art helps your brain.

"Handwriting is probably among the most complex motor skills that the brain is capable of," says Marieke Longcamp , a cognitive neuroscientist at Aix-Marseille Université.

Gripping a pen nimbly enough to write is a complicated task, as it requires your brain to continuously monitor the pressure that each finger exerts on the pen. Then, your motor system has to delicately modify that pressure to re-create each letter of the words in your head on the page.

"Your fingers have to each do something different to produce a recognizable letter," says Sophia Vinci-Booher , an educational neuroscientist at Vanderbilt University. Adding to the complexity, your visual system must continuously process that letter as it's formed. With each stroke, your brain compares the unfolding script with mental models of the letters and words, making adjustments to fingers in real time to create the letters' shapes, says Vinci-Booher.

That's not true for typing.

To type "tap" your fingers don't have to trace out the form of the letters — they just make three relatively simple and uniform movements. In comparison, it takes a lot more brainpower, as well as cross-talk between brain areas, to write than type.

Recent brain imaging studies bolster this idea. A study published in January found that when students write by hand, brain areas involved in motor and visual information processing " sync up " with areas crucial to memory formation, firing at frequencies associated with learning.

"We don't see that [synchronized activity] in typewriting at all," says Audrey van der Meer , a psychologist and study co-author at the Norwegian University of Science and Technology. She suggests that writing by hand is a neurobiologically richer process and that this richness may confer some cognitive benefits.

Other experts agree. "There seems to be something fundamental about engaging your body to produce these shapes," says Robert Wiley , a cognitive psychologist at the University of North Carolina, Greensboro. "It lets you make associations between your body and what you're seeing and hearing," he says, which might give the mind more footholds for accessing a given concept or idea.

Those extra footholds are especially important for learning in kids, but they may give adults a leg up too. Wiley and others worry that ditching handwriting for typing could have serious consequences for how we all learn and think.

What might be lost as handwriting wanes

The clearest consequence of screens and keyboards replacing pen and paper might be on kids' ability to learn the building blocks of literacy — letters.

"Letter recognition in early childhood is actually one of the best predictors of later reading and math attainment," says Vinci-Booher. Her work suggests the process of learning to write letters by hand is crucial for learning to read them.

"When kids write letters, they're just messy," she says. As kids practice writing "A," each iteration is different, and that variability helps solidify their conceptual understanding of the letter.

Research suggests kids learn to recognize letters better when seeing variable handwritten examples, compared with uniform typed examples.

This helps develop areas of the brain used during reading in older children and adults, Vinci-Booher found.

"This could be one of the ways that early experiences actually translate to long-term life outcomes," she says. "These visually demanding, fine motor actions bake in neural communication patterns that are really important for learning later on."

Ditching handwriting instruction could mean that those skills don't get developed as well, which could impair kids' ability to learn down the road.

"If young children are not receiving any handwriting training, which is very good brain stimulation, then their brains simply won't reach their full potential," says van der Meer. "It's scary to think of the potential consequences."

Many states are trying to avoid these risks by mandating cursive instruction. This year, California started requiring elementary school students to learn cursive , and similar bills are moving through state legislatures in several states, including Indiana, Kentucky, South Carolina and Wisconsin. (So far, evidence suggests that it's the writing by hand that matters, not whether it's print or cursive.)

Slowing down and processing information

For adults, one of the main benefits of writing by hand is that it simply forces us to slow down.

During a meeting or lecture, it's possible to type what you're hearing verbatim. But often, "you're not actually processing that information — you're just typing in the blind," says van der Meer. "If you take notes by hand, you can't write everything down," she says.

The relative slowness of the medium forces you to process the information, writing key words or phrases and using drawing or arrows to work through ideas, she says. "You make the information your own," she says, which helps it stick in the brain.

Such connections and integration are still possible when typing, but they need to be made more intentionally. And sometimes, efficiency wins out. "When you're writing a long essay, it's obviously much more practical to use a keyboard," says van der Meer.

Still, given our long history of using our hands to mark meaning in the world, some scientists worry about the more diffuse consequences of offloading our thinking to computers.

"We're foisting a lot of our knowledge, extending our cognition, to other devices, so it's only natural that we've started using these other agents to do our writing for us," says Balasubramaniam.

It's possible that this might free up our minds to do other kinds of hard thinking, he says. Or we might be sacrificing a fundamental process that's crucial for the kinds of immersive cognitive experiences that enable us to learn and think at our full potential.

Balasubramaniam stresses, however, that we don't have to ditch digital tools to harness the power of handwriting. So far, research suggests that scribbling with a stylus on a screen activates the same brain pathways as etching ink on paper. It's the movement that counts, he says, not its final form.

Jonathan Lambert is a Washington, D.C.-based freelance journalist who covers science, health and policy.

• handwriting

• Open access
• Published: 17 May 2024

Self-regulated learning of anatomy during the COVID-19 lockdown period in a low-income setting

• Tapiwa Chapupu 1 , 3 ,
• Anesuishe B Gatsi 3 ,
• Fidelis Chibhabha 4 &
• Prince L. M. Zilundu 1 , 2  

BMC Medical Education volume  24 , Article number:  548 ( 2024 ) Cite this article

208 Accesses

Metrics details

In March 2020, universities in Zimbabwe temporarily closed and switched to remote learning to contain the spread of SARS Cov2 infections. The sudden change to distance learning gave autonomy to students to direct their own learning. To understand how the students at the University of Zimbabwe and Midlands State University adapted to emergency remote learning, focus group discussions and a self-administered questionnaire survey based on the self-regulated learning inventory were conducted to capture cognitive, motivational, and emotional aspects of anatomy learning during the COVID-19 pandemic. Thematic analysis was used to identify patterns among these students’ lived experiences. Two coders analyzed the data independently and discussed the codes to reach a consensus. The results showed that students at the two medical schools cognitively and meta-cognitively planned, executed and evaluated self-regulated strategies in different ways that suited their environments during the COVID-19 lockdown. Several factors, such as demographic location, home setting/situation, socioeconomic background and expertise in using online platforms, affected the students’ self-directed learning. Students generally adapted well to the constraints brought about by the lockdown on their anatomy learning in order to learn effectively. This study was able to highlight important self-regulated learning strategies that were implemented during COVID-19 by anatomy learners, especially those in low-income settings, and these strategies equip teachers and learners alike in preparation for similar future situations that may result in forced remote learning of anatomy.

Peer Review reports

Introduction

In March 2020, universities in Zimbabwe temporarily closed and switched to emergency remote teaching following a government lockdown directive meant to curtail the spread of SARS-CoV-2 infections. The lifting of the COVID-19-induced lockdowns proved premature, resulting in a three-time opening and closure of universities between March 2020 and September 2021 as the country battled three waves of infections [ 1 ]. This situation, which was also reported in other parts of the world, forced university teachers and students alike to adapt to a new mode of teaching and learning that had never been tested before [ 2 ]. The closure of medical schools meant that cadaver dissection was foregone, potentially depriving students of teamwork, a visuospatial picture of the organization of the human body, experience of the texture of human tissues, understanding of pathological as well as anatomical variations, and inculcation of humanistic values [ 3 ]. Remote anatomy teaching was conducted virtually [ 4 ], thereby placing the burden of mastering content-heavy anatomy courses on preclinical medical students who were at home.

Compared to traditional face-to-face learning, emergency remote teaching offers flexible scheduling, ease of distributing information, opportunities to individualize learning processes, and the potential to enhance self-regulated learning skills [ 5 ]. However, preclinical medical students still face challenges associated with transitioning from high school to higher education, such as managing study time effectively and becoming self-regulated learners who can cope with the exponential growth of knowledge in medical education [ 6 ]. The sudden transition to remote online learning pushed students to direct their own learning, but the greater flexibility afforded by emergency remote teaching places high demands on them to quickly adapt and self-regulate their learning. The COVID-19 pandemic-induced distance education is different from regular online anatomy education in that it was abrupt, unplanned and often a case of learning on the job for teachers and new to students for a hands-on subject such as cadaver dissection-based anatomy [ 7 ]. In a study from Botswana by Mogodi and colleagues [ 8 ] noted that while there was high smart phone penetration, internet access and affordability was a challenge for both teachers and learners. Therefore, it is important to understand how medical students adapted to this emergency remote learning [ 9 ]. This understanding could inform future instructional modalities, such as blended, hybrid, or remedial medical education/learning.

Due to recent pushes toward student-centered learning in higher education [ 10 ], pre-pandemic university students already enjoyed a considerable amount of autonomy in covering course content and ensuring skills acquisition. As a result, they are expected to plan, monitor, and control their own learning process during self-study and thus engage in self-regulated learning [ 11 ]. Under self-regulated learning, students use cognitive, metacognitive, and resource-management strategies to meet curriculum goals [ 12 ]. Cognitive and metacognitive strategies encompass skills used to process information and monitor and control one’s mastery of subject content [ 13 ]. Resource-management strategies include regulating effort, attention, motivation, and time use [ 14 ]. Because remote learning is typically less structured, it places the burden of learning on students to autonomously regulate and organize their learning processes [ 15 ].

Self-regulated learning (SRL) is a cyclical process wherein students plan for a task, monitor their performance, and then reflect on the outcome [ 11 ]. SRL includes cognitive skills, which are the ability to critically plan and execute strategies of studying; metacognitive skills, which are the ability to know how to implement formulated strategies; behavioral skills; motivational skills, which are self-efficacy; and emotional/affective aspects of learning [ 12 ]. The theory is an extraordinary umbrella under which a considerable number of variables that influence active learning (volition, cognitive strategies and self-efficacy) are studied within a much more comprehensive and holistic approach [ 14 ]. For that reason, SRL has become one of the most important areas of research within educational psychology [ 12 ]. Self-regulated learning strategies are actions directed at acquiring information or skills that involve agency, purpose (goals), and instrumentality of self-perceptions by a learner [ 16 ]. Zimmerman [ 17 ] pioneered this theory and suggested that the self-regulated learning process has three stages:

Forethought, learners prepare work before the performance of their studies.

Volitional control, which is also called “performance control”, occurs in the learning process. It involves the learner’s attention and willpower.

Self-reflection occurs in the final stage when learners review their performance toward final goals. At the same time, focusing on their learning strategies during the process is also efficient for their final outcomes.

Under the SRL theory, students are active participants who proactively use forethought, performance and self-reflection on their learning tasks, thus generating important experiences [ 12 ]. They included goal-setting, environmental structuring, self-consequences (self-rewarding and self-punishment), and self-evaluating. Several other categories were included on the basis of closely allied theoretical formulations, namely, the strategies of organizing and transforming [ 18 ] seeking and selecting information [ 19 ], and rehearsal and mnemonic strategies [ 20 ]. Also included were the strategies of seeking social assistance and reviewing previously compiled records such as class notes and notes on text material, which showed that self-regulated strategies are not anti-social mechanisms of study [ 19 ]. The issue of interactive learning between tutors and students and peer-to-peer discussions is one of the factors of the theory of seeking social assistance.

The ability of an individual to use the self-regulation skills is more crucial in distance learning than in traditional classroom settings due to reduced or absent supervision and guidance [ 21 ]. Understanding how students generally use the SRL strategies is important as previous studies have investigated how performance is associated with several aspects of it in medical leaning [ 22 ]. The importance of SRL in Anatomy education is justified because due to several studies it has shown that academic success is mostly influenced by the students’ ability to control their learning independent of the instructor`s support [ 23 ]. The aspects include self-efficacy, motivation, metacognitive monitoring and strategy use [ 24 ].

A research on first year medical students studying gross anatomy showed that their use of cognitive, resource management and metacognitive strategies was positively associated with higher marks [ 25 ]. A study underscored the need for the student to regularly monitor their study as it was shown that successful students undertaking online courses generally use SRL strategies [ 26 ]. Prior research has explored self-directed learning in anatomy among students in various environments pre-pandemic finding it important. A study in Zimbabwean medical schools found prevalent self-regulated learning traits [ 27 ]. Anatomy study, requiring intensive memorization, often involves rehearsal techniques. In self-regulated learning’s performance phase, students need effective memorization strategies [ 28 ]. Many students at the University of Cape Town research reported a heavy reliance on mnemonics and sticky notes for anatomy learning, with mnemonics and sticky notes being perceived as key to effective study [ 29 , 30 ]. However, mnemonics’ limited generalizability and English-centric nature disadvantage non-English speakers [ 31 ]. Some nursing educators critiqued mnemonics as a ‘lazy’ method, and their use in patient care is viewed as potentially undermining a humanistic approach by oversimplifying symptoms [ 32 , 33 ].

During the COVID-19 lockdown, anatomy at the University of Zimbabwe and Midlands State University was taught in three parts, gross anatomy, histology and embryology, for a year (allied health students) or two years (medical and dental students). The topics covered in gross anatomy regional format were upper limb, lower limb, thorax, abdomen, pelvis, perineum, neuroanatomy, head and neck. The histology and embryology would correspond to those regions in gross anatomy. In gross anatomy, the students were required to know the structure, relations, vascular supply, innervation and clinical correlates. After each region, an exam was written that contributed to the course’s continuous assessment mark. The courses were described previously by Zilundu [ 27 ]. The current study participants are post high school university entrants. This is a major transition whereby “college students need to be more independent and self-organized in their learning behavior than in high school”. Research among low income setting students, like the present sample, noted a significant moderating effect of social adjustment on academic adjustment and transition experiences [ 34 ]. Therefore, self-regulated learning (SRL) skills became even more essential when switching to distance learning during the COVID-19 pandemic to allow students to direct their own learning [ 35 ].

Preclinical medical students are post-high school students in Zimbabwe [ 27 ]. As younger adults, they need guidance and motivation to find their footing in self-regulated learning and subsequent lifelong learning. Motivation and the use of self-regulated learning strategies have been positively correlated with superior academic performance [ 36 ]. However, stress and maladaptive behaviors such as low self-control, low self-discipline, and disorganization, which are possible in remote learning settings, are usually associated with poor outcomes [ 37 ]. Therefore, self-regulated learning (SRL) skills became essential when switching to distance learning during the COVID-19 pandemic [ 38 ].

The transition to remote learning during the COVID-19 pandemic created a critical research gap in how it affects self-regulated learning among preclinical medical students, especially in under-resourced settings like Zimbabwe. This shift was particularly impactful in anatomy education, which moved from hands-on dissection to virtual learning, potentially impairing essential skill and knowledge development. These challenges could be compounded by the difficulty of transitioning from high school to university education, that necessitates advanced SRL skills. This study seeks to address the urgent need to understand the effect of remote learning on SRL strategies crucial for the success of medical students. By exploring their challenges and adaptations, the research aims to guide the creation of educational interventions and models that enhance learning and support the academic and mental well-being of future healthcare professionals in similar environments. Therefore, this study was designed to use a phenomenological approach to highlight the lived experiences, self-regulation during anatomy study, and the potential impact of the COVID-19 outbreak on the education of preclinical medical students in a low income setting.

Materials and methods

Study design.

This study used an interpretative phenomenological analysis (IPA) approach to explore the lived experiences of medical students learning anatomy during lockdown. IPA is a qualitative research method that seeks to understand the meaning and significance of people’s experiences through in depth, reflective inquiry [ 39 ]. According to Sparkes and Smith [ 40 ], human lived experience can be understood by examining the meanings that people ascribe to it. Since medical students in this study shared a common experience of learning anatomy during lockdown, focus group discussions were used as a data collection method. Focus group discussion, a research method involving a small participant group, centers around a specific topic to gather data. This approach is characterized by the interactions between the moderator and participants, and among the group members themselves whose aim is to provide researchers with insights into the participants’ views on the discussed subject [ 41 ].

Flowers, [ 42 ] argued that focus groups can enhance personal accounts by capitalizing on peer-to-peer interactions and rapport. This is particularly relevant in a homogeneous sample such as that of the present medical students, who share experiences and are emotionally invested in the same topic of exploring learning anatomy during the lockdown. Focus group data can also promote experiential insight and reflection that may not be achieved in an interview, thereby enriching the topic under study. Additionally, the researchers have prior experience using this approach in the design, conduct, and analysis of medical education studies [ 27 ]. The interpretive nature of IPA was particularly well suited for this study, as it builds on the researchers’ experience with this approach and its intersection with the self-regulated learning approach to medical education.

Study setting

University of Zimbabwe and Midlands State University. The two Universities, at the time, were part of three medical schools in the country and enrolled students from all the residential areas in Zimbabwe as they cater for all 10 provinces in the country.

Study participants

A total of 86 students comprising first- and second-year medical students registered at the University of Zimbabwe (UZ) and Midlands State University (MSU) who attended a compulsory anatomy course during the multiple COVID-19 lockdowns between March 2020 and September 2021 voluntarily participated in this study.

Recruitment of participants

Messages introducing the study (participant information sheet), a consent form and an invitation to participate were sent to all first- and second-year medical students enrolled at UZ and MSU via their WhatsApp groups opened for purposes of online learning. In the message was a link to Google forms that directed them to a data-gathering tool as well as flexible scheduling of online focus group discussion slots. Students who were willing to participate were asked to self-identify, return signed informed consent sheets and fill in the Google Forms slots of the scheduled times that they would be available to take part in a focus group discussion of approximately 5 to 7 students each.

Data collection instruments

Focus group discussions were conducted following the guidelines contained in the Self-Regulated Learning Interview Schedule [ 43 ]. The Self-Regulated Learning Interview Schedule has 15 items covering self-evaluation, organization, transformation, goal-setting and planning, seeking information, keeping records and monitoring, environmental structuring, self-consequating, rehearsing and memorizing, seeking peer, teacher, or adult assistance, as well as reviewing tests, notes, and texts. Study participants described and reflected on how they used any of these during their anatomy learning when under lockdown.

Data collection

The focus group discussions comprising 5 to 7 participants were conducted by TC and PLMZ over the Zoom video conferencing platform. They were conducted serially until a point of saturation was reached, that is, after the 6th session. Saturation in focus group discussions refers to the point at which no new information or themes are observed in the data, indicating that enough data has been collected to understand the research topic [ 28 ]. They normally lasted one to one and a half hours each. The audios of the focus group discussions were recorded and stored securely. Data was collected from June to August 2021.

Data analysis

The audio recordings of the focus group discussions were transcribed verbatim by TC, FC and ABG. The transcripts were subjected to an interpretative phenomenological analysis (IPA) using the approach described by Pietkiewicz and Smith [ 44 ]. First, the authors immersed themselves in the data by reading and rereading the transcripts. During this process, they made notes on the transcripts, highlighting distinctive phrases and emotional responses, as described by [ 44 ]. Next, the notes and transcripts were reviewed to identify initial emergent themes. These emergent themes were then scrutinized to identify relationships between them, leading to the generation of analytical theme clusters. Finally, the theme clusters were compared back to the original transcripts to ensure that they were representative of the data. Disagreements were discussed and reanalyzed until the final analysis was agreed upon in this iterative process.

The qualitative data were systematically analyzed using the converging coding process. All qualitative data were coded using a priori coding using the 15 strategies outlined in by Zimmerman and Pons [ 43 ]. Responses captured from the participants using Zoom recorder were grouped into four main self-regulated learning themes: cognition, metacognitive self-regulation, effort regulation and resource management. The data were analyzed qualitatively with notes written down initially from the student responses to the 15 questions in the interview guide.

Each strategy was analyzed to determine how it was affected by the COVID-19-induced lockdown. Students in different geographical locations were assessed on how they were positively and negatively affected by the lockdown. The locations were classified from low-density suburbs to rural areas, and the distribution in each class was noted. Adaptation to the home-based learning of anatomy was investigated by examining how each student faced every challenge to achieve their self-set goals. Associations between responses and demographics were analyzed to observe the common use of specific strategies within groups.

Ethics approval and consent to participate

The University of Zimbabwe (UZ) and Midlands State University (MSU) departments of anatomy and the Joint Research Ethics Committee (JREC/329/2021) approved this study. Informed consent was obtained from all students participating in this study prior to their involvement in this research.

A total of 13 focus group discussions were conducted with 86 participants (male = 36, female = 50). The age of the students ranged from 19 to 22 (20 ± 1.2) years. The distribution of residency was 8 for rural areas, 37 for low density, 20 for medium density and 21 for high density. Table  1 below shows the distribution of study participants by sex, residence area, learning institution and academic year.

Cognitive regulation

Organizing and transforming.

Most students who participated in the focus group discussions reported self-initiated rearrangement of instructional materials to improve learning. These students said that they recapped the objectives of each class and then grouped related information for easy understanding during lockdown learning. For example, one student mentioned that: “I normally just prefer listing down related information as well as tabulating differences so that my studying is neater” (#20, M, 22). Another student agreed: “I can list down structures found at every significant vertebral level” (#5, F, 21).

The majority of the students also compressed information into short notes. However, a minority struggled to organize learned information due to their fears of capturing incorrect information in the process and inadequate time to do so. A student in this group that struggled to organize learned information noted: “I do not usually organize my study because at the end of the day I am supposed to know everything, and with the vast of information and little time we have it is difficult” (#79, M, 22).

The use of an atlas alongside reading anatomy textbooks was noted by some students, as they claimed that it fills the gap that the dissection room was supposed to fill. Atlases helped visualize the information as well as used to annotate lecture content. A female student quipped that: “My atlas textbook is almost like my dissection cadaver at home” (#11, F, 22). Another reported that she uses the atlas reduce lecture content by “annotating lecturer notes on the pictures in the atlas” (#30, F, 22). A greater fraction of students from both universities reported that organizing their anatomy study and content while studying the subject at home was rewarding.

Rehearsing and memorizing

In their study of anatomy during the COVID-19 lockdown while at their respective homes, the students gave statements indicating self-initiated efforts to memorize material by overt or covert practice indicating that they employed a great deal of memorization and rehearsing. Almost all the students reported using this strategy frequently and in several ways. The majority of the students used commonly known mnemonics, while others preferred homemade mnemonics derived from common words in their home environment, such as the names of pets (#12, M, 20), siblings (#41, F, 20) and friends (#16, F, 21) For example, a commonly used strategy was captured by one student who noted the following: “I find mnemonics being the fast and easy way to bring back information, especially in an exam setting, because large sets of information are generally compressed to common words or statements” (#7, F, 21).

A minority of the students were not using mnemonics as they claimed to be “extra work” but used other techniques instead, such as “reproducing concepts through discussions with classmates” (#62, M, 22), “homemade notes” (#50, F, 19) and “self-initiated rehearsal sessions” (#33, F,23). One such student captured this as follows: “I might end up having a mini textbook for mnemonics, so it is better that I understand the concept only” (#02, M, 20).

Instead of mnemonics and self-study, a larger fraction of students who participated in the focus group discussions resorted to doing “mock presentations of the anatomy content” (#09, M, 22) that they would have learned to each other via the WhatsApp platform despite the challenges of electricity and internet access. The remainder reported not doing so because of “internet access problems and prohibitive costs” (#76, F, 21), especially those who were residing in remote and high-density areas during the lockdown period. These students, however, utilized their family members by conducting mock lecturing sessions just to help them recall the anatomy they would have learned or been reading from textbooks. For instance, one student quipped: “I teach my mom or sister, even though they don’t understand it, but it helps me remember.” (#22, F, 20) .

The majority of the students also used paper as well as soft copy “flashcards” (#70, M, 21) that have “questions, short statements, and reminders that they would stick on several places in their homes”. The students reported that they found it challenging to memorize structures and relations without dissection, so they used atlases such as Gray’s Atlas of Anatomy and Netter’s Essential Histology for both gross anatomy and histology, respectively. In addition, they said it was easier to recall a photographic image than written statements. Some students preferred using their artistic abilities to draw anatomical structures as part of their memorizing.

Meta-cognitive regulation

Self-evaluation.

Self-evaluation during the lockdown was necessary for the anatomy students to keep themselves in check to effectively monitor their study habits. The whole sample of students who participated in the focus group discussions showed self-initiated evaluation of the quality and progress of their work in different ways. The majority revised anatomy using multiple choice questions (MCQs) obtained from several internet anatomy sites. They also set their own questions before and after the study to check their progress. Many students echoed the following sentiment of one student: “I find MCQs being the most useful tool to evaluate my study because they indicate areas of weakness to me” (#44, M, 23).

The students also “wrote notes from memory and compared them with the anatomy textbook” (#47, M, 21) to show them how much information they obtained from their study. Some students also utilized their peers using online platforms such as WhatsApp during the discussions to see how much they were lacking in comparison to other students. The following statement by one student received concurrence from the majority of the group members during discussions: “My discussion group helps me see where I am, relative to others, and then I know the amount of effort that I need to put in later on” (#45, F, 20). However, some students reported facing challenges in carrying out such as a “lack of a reliable internet connection” (#54, M, 22) as well as “failing to synchronize the lockdown-era learning schedule” (#38, F, 21) and peers’ free time with “household chores” (#65, F, 21). For instance, one said: “It is hard to constantly have discussions at a fixed (time) because anyone can get caught up with anything at any time” (#19, F, 20).

Some students reported resorting to “spaced repetition and retrieval” (#80, M, 21) in which they repeated anatomical information over spaced intervals to remember and judge how much they remember.

Goal setting and planning

The majority of the students reported that they were able to set goals and plans for sequencing, timing, and completing activities related to learning anatomy during the lockdown. However, a minority of students reported having “less time to fulfil the set goals” (#64, M, 20). They reported that the home environment, especially in high-density areas, did not have space for effective study undisturbed, while others, especially females, noted that “household chores” (#77, F, 21) assigned to them at home made it hard to set goals, plan and follow them. They were demotivated to continue with meticulous goal setting such that they ended up stopping carrying out study plans over time. Both male and female students reported similar patterns of goal setting and work planning.

Some students chose to balance their attention on all courses instead of just anatomy during the lockdown period. However, they largely admitted that anatomy is challenging, leading to the subject receiving more attention than others, as captured below:

“I plan to spend 60% of my week’s study time reading anatomy because it is tough and then divide the rest into other courses” (#37, M. 22).

“I draft timetables because they prevent the overlapping of Anatomy study into sessions for other courses” (#03, M, 20).

Female students highlighted experiencing more disruptions to their set goals due to disproportionate participation in household chore compared to their male counterparts. For example:

“It’s hard to plan and set goals knowing that there are high chances of not being able to achieve them with all disturbances at home” (#84, F, 19).

“It is hard to follow timetables when at home… being a woman at home you get to perform most of the duties such as cleaning, cooking, laundry and taking care of younger children, something male members of the family do not do, I guess it’s the culture” (#57, F, 21).

Overall, studying from home during the COVID-19-induced lockdown was generally viewed as challenging, with female students being affected more due to the patriarchal home environment as well as the skewed nature of the distribution of numerous “household duties falling on women” (#26, F, 20).

Keeping/reviewing records and monitoring anatomy learning during lockdown

Most of the students reported keeping records of the anatomy information they learned in many different forms for future use. However, a few focus group discussants did not keep records due to the challenges of revisiting citing the “heavy workload and limited time” (#14, M, 22) during the lockdown. The majority of such students were male.

The widely used record-keeping method was “note-taking during online lectures” (#13, M, 20) and when studying. Many students felt that this method helps them to boost their focus, as explained below: “I wrote some notes to keep myself motivated during studying, and I wrote down everything I got wrong in an exam to work on them as objectives.”

Other records were kept in form of “short notes” (#66, F, 20), “flashcards” (#18, F, 20), audio and even videos. Modifying the notes was done in successive study sessions as the students added more information. A small fraction of anatomy learners found it challenging to keep records, as they never had enough time to revisit them due to ever-increasing workloads and other competing needs in the home environment. One such student quipped: “It’s hard to write notes that you know you will never read them again in such pressure-filled times .” (#10, M, 21).

Reviewing handwritten notes, textbooks, and MCQs were widely used by the majority of the students. Many students reported that reviewing past MCQs was an effective tool in evaluating their level of learning and understanding as well as exam preparation and was mostly used by second-year anatomy students as shown below.

“I revise MCQs with my (handwritten) notes and also revisit the anatomy textbooks” (#07, F, 22).

“In the first year, I relied more on the textbook to prepare for anatomy examinations, but now I do MCQs then discuss with peers.” (#30, F, 22).

On the other hand, a minority reported that using MCQs just before exams increased panic and anxiety as exemplified by: “I cannot use MCQs just before an anatomy exam because I may panic by seeing several questions whose answers I do not know” (#41, F, 20).

Most students did not review textbooks before exams due to their large volumes of information in a short period, hence the use of notes, audio, YouTube videos and flashcards, but could do so in preparation for a discussion group with classmates.

Effort regulation

Environmental structuring.

Effort regulation refers to the student’s ability to continue performing a task even when faced with inherent difficulties [ 44 ]. The majority of students who participated in the focus group discussions portrayed how they managed their anatomy studies on their own in different environments during the lockdown. Some students residing in high-density suburbs and rural areas had “trouble finding a conducive study environment” (#71, M, 20), with most of them resorting to studying at night when most family members are asleep, as captured by some below:

“I need to check what my environment is like before I sit to study” (#61, F, 19).“It is hard to find a quiet place unless, during night time, that is why I study during the night” (#25, M, 22).

On the other hand, a few students who stayed in low-density suburbs that provided a quiet, clean and isolated environment during lockdown could not care much about the state of the surroundings for studying anatomy, as one noted below:

“I am not much affected by my environment at home” (#54, M, 22).

However, studying at new places was found to be “motivating” (#85, F, 21); hence, some students rotated around their homes trying to find suitable places to study anatomy during the lockdown. The use of music during the study was noted by some students as an effective tool to support effort regulation, while some students opted for “total silence for maximum concentration” (#23, F, 20).

Self-consequences

Statements indicating self-initiated imagination of rewards or punishment for success or failure to achieve self-set goals were noted in approximately half of the focus group discussions participants. Many students reported rewarding themselves more than punishment, as they felt that there was no need to punish themselves if the “workload was already heavy” (#73, M, 19). Those who rewarded themselves did so by temporarily stopping reading for a while to gain motivation, spending time with the family, watching television, surfing the internet and visiting social media. For example:

“I feel like my end goal is to pass exams so better I motivate myself by constant rewards than punishments” (#33, F, 23).

A few students punished themselves by depriving themselves of social media, friends, and family time until a specific task was completed. Other students never used any of the two strategies, as they said that passing is the reward and studying hard is the price for it.

“I am punished and rewarded by my result on the exam results noticeboard, so I don’t do it myself” (#49, F, 21).

Resource management

Seeking social assistance (elder, teacher and tutor, peers).

All students who participated in the focus group discussions reported seeking educational assistance from either an elder/mentor in medical school, a lecturer, a tutor, or peers. Most students mentioned being uncomfortable seeking assistance from their lecturers but could frequently approach their tutors (BSc intercalated anatomy students) instead:

“I find it hard to text my lecturer so I usually pass my question to the tutors” (#65, F, 21).

The use of mentors/elders, especially those who are streams ahead, was noted, as students preferred someone who once studied anatomy and understands for emotional support:

“Parents and friends were necessary for emotional support, as students needed constant mental support during the pandemic.” (#01, F, 22).

The majority of students showed that the assistance that comes from a peer was very helpful. This was noted as many students raised the issue of discussion groups being the best learning platform at all times, especially toward Anatomy exams”.

“… my discussion group is almost my everything from academic to emotional support because we are in the same boat and we face everything together.” (#40, M, 22).

Team work was a very useful tool in anatomy studies during the pandemic season, as the students stayed connected in their work and discussions through social media.

Seeking information

The ability to search for information from several online sources was important in studying anatomy during the lockdown, where the student had to hunt for the source of information to keep up with the subject content and everyone else. The majority of students looked for information mostly online through Google searches, retrieving uploaded videos, and classmates.

“I go online to check textbooks, notes and videos to try and understand more about what I know already” (#58, M, 21).

Some students preferred to search for other texts online just to remain motivated on the subject. Social media platforms such as WhatsApp were used more commonly to ask for books, notes, videos, recordings and extra sources of anatomical information from colleagues. A few students preferred sticking to the recommended anatomy textbooks to minimize confusion between texts as well as because of the limited time.

“I already have no time to finish up all the anatomy books. So, why do l have to fish for other books?” (#72, F, 20).

However, a considerable number of students reported facing “poor internet connectivity” in some areas of Zimbabwe, as almost all the accessible sources for anatomy during remote learning were available online. This was captured by representative students, one lived in a rural setting and another in a medium density suburb:

“in my rural environment, the network boosters are far apart and mobile internet connectivity was very poor and often offline whenever there was no ZESA ( electricity )” (#63, M, 20).

“I lived in the city but with frequent power outages and expensive broadband internet activity, sometimes the only time I could access mobile internet to study would very late in the night” (#29, F, 22).

The study aimed at exploring how anatomy learners in a low-income country employed self-regulated learning skills during the Covid-19 lockdown induced distance learning. The ten focus group discussions that were conducted involving 86 students showed that anatomy learners at UZ and MSU demonstrated use of self-directed learning skills during the COVID-19 remote learning period. They showed mostly relatively similar use of cognitive, meta-cognitive and effort regulation despite their differences in gender, socioeconomic background or academic year.

The present study revealed that learning anatomy during lockdown was very challenging due to the absence of physical interactive learning, poor internet connectivity, disturbances at home and the absence of cadaver dissection and histology practicals. As a result, the students resorted to directing their learning as an adaptative strategy to pandemic-induced online remote learning. The study has shown that the majority of students were able to reorganize and transform as well as employ rehearsal and memorizing techniques despite the several challenges faced during home learning. The majority of the students actively utilized different cognitive and metacognitive skills in self-regulating learning anatomy during the lockdown. However, a minority reported some challenges partially due to COVID-19-induced home learning warranting a look back so that similar problems could be approached by anatomy teachers in the future.

The present study’s findings are concordant with previous studies that have shown that students can also initiate task transformation for effective learning [ 25 ]. During the home-based learning of anatomy, students from both universities (UZ and MSU) found ways to tackle the vast anatomical information by rearranging, transforming and selecting the required information. This was done by the use of homemade mnemonics, drawings, tables and paraphrased notes. However, experts in cognitive and educational psychology have questioned the utility of some of these learning techniques, such as the use of mnemonics, for the majority of students [ 30 ]. Therefore, while current students reported using and drawing some benefit from the said techniques, further research is needed to identify which techniques have generalizable effects.

In the present study, most students relied on memorizing and rehearsing to effectively understand anatomy content during the lockdown. Due to the absence of physical peer-to-peer interaction, students tended to mock-teach close family members to try and memorize anatomy content. They also asked family members to test them on specific anatomy concepts and content. The students also utilized atlases, mnemonics, sticky notes and repeated reading. This way of learning portrays the skills of self-regulated learning [ 14 ].

Some students who participated in the present study reported using mnemonics created in native Zimbabwean languages which proved to be useful in their understanding of anatomy basing on their testimonies. Mnemonics are useful only for memorization and are not tools for higher-order learning skills such as analysis, understanding or application [ 45 ]. They only encourage shallow learning rather than developing an in-depth understanding of concepts in learning [ 32 ]. It is important for teachers to be aware of the mnemonics their students are using, as these can be valuable tools for learning. However, it is also important to check these mnemonics for mistakes, as students may not be creating them accurately. Teachers can help students create accurate mnemonics by providing them with examples of mnemonics that work well and by teaching them how to create their own mnemonics. They can also help students check their mnemonics for mistakes by asking them to explain how the mnemonic works or by having them quiz each other on the information that the mnemonic is supposed to help them remember.

One of the key aspects of memorizing anatomy concepts is visualization, which was aided by the use of cadavers during campus learning time. However, at home, the students utilized online 3D anatomy software and atlases that worked efficiently to boost learning and appreciation of spatial relationships between anatomical structures in lieu of actual dissection and teamwork.

In the present study, it was observed that students were able to control their thoughts and actions, hence showing meta-cognitive skills use in anatomy learning. With reduced constant supervision, the skill was employed differently among anatomy learners in both universities during COVID-19-induced home learning. The majority of the students were able to self-evaluate, set goals, plan their work, and keep, monitor and review the information records in several different ways. Studies have examined the use of metacognition in the learning of anatomy before [ 46 ] and after the COVID-19 lockdown [ 47 ]. In Zimbabwe, students were finding challenges in meta-cognitively monitoring their anatomy learning due to several factors, such as the nonfixed learning schedules during the pandemic or disruptions caused by doing household chores. However, students were planning their study for a shorter period (within a few days) and monitored their notes regularly to keep the information easy to recall. They also worked with other students to evaluate each other using online platforms such as WhatsApp.

Self-evaluation skills are necessary at every stage of self-regulated learning, especially for anatomy learners who have to cover a large amount of information in a short period. The students used multiple-choice questions, online discussions and homemade review questions to evaluate their own learning. These results indicated that anatomy learners at UZ and MSU were able to evaluate themselves at home during the self-reflection phase of self-regulated learning amid challenges imposed by the COVID-19 pandemic [ 16 ]. The use of self-evaluation by anatomy students before the lockdown [ 48 ] and during the COVID-19 pandemic lockdown has been noted as an important tool that provides room for improvement [ 49 ]. The results from the current study on self-evaluation reports are in agreement with those of previous studies that evaluated its use among medical students and particularly anatomy learners in India [ 47 ] and in the USA [ 47 ]. Zimbabwean anatomy learners at UZ and MSU developed self-evaluation strategies to compensate for the reduced in-person discussions, quiz sessions and practice tests. Family members were utilized to evaluate the learner by employing randomly set questions and presentations as a way to use a multisensory learning strategy.

Due to the different environments in which students lived, a wide range of evaluation strategies were employed. The students who lived in remote areas did not have reliable internet connections to engage in online academic activities like their peers. Hence, such students are more prone to depression, less motivation [ 50 ], and even poor academic performance than expected [ 51 ]. However, while many studies in resource-limited settings listed similar challenges with the internet, overall anatomy learning has largely been reported as comparable to pre-pandemic levels [ 52 ]. Future studies must find connections between different student circumstances and academic performance as well as posit solutions that would be relevant in crisis and normal education times.

Self-initiated study plans and goals are crucial in the learning of anatomy, which is a content-heavy subject [ 25 ]. Most students from both institutions in the present study planned and set goals for their daily and weekly studies. However, a minority showed weakness in this skill, mainly due to disturbances at home. For instance, participating in household chores, attending to visitors and other unplanned events disrupted plans and goal attainment during the lockdown period. This reflects the use of goal- and plan-setting strategies by anatomy students in Zimbabwean medical schools, which is an element of the forethought phase of self-regulated learning [ 53 ]. Previous studies have shown results similar to those of this current study on the employment of self-initiated goals and plans. A study conducted in the USA [ 54 ] before and during the COVID-19 lockdown showed that anatomy students planned and set goals. Anatomy learners in Zimbabwe planned and set goals to make it easier to study anatomy. This skill is an important lifelong tool in different aspects of life, of keynote in the medical field [ 55 ]. However, a minority have also faced challenges due to the instability of home environments, which slowed down the student’s work rate. Most Zimbabwean female students reported more difficulties due to frequent house chores and related disturbances. Student residency [ 52 ] and gender [ 56 ] have previously been shown to affect learning differently. Several studies have reported that many students generally face challenges in learning anatomy at home and eventually become worried and stressed over their study progress [ 57 ]. Therefore, it is crucial for anatomy educators to be aware of the breadth of students’ challenges so that they can offer support.

Students at UZ and MSU kept records of past online lectures, tutorials, personal study sessions and discussions in the form of short notes, audio, videos and pictures for future use, hence proving a meta-cognitive skill in anatomy learning that reflected their metacognitive skills in the performance phase [ 58 ]. Previous studies have shown results similar to those obtained in the current study. A study that was performed in Spain showed that anatomy students kept track of what they had learned for future reference as self-regulators [ 59 ]. Note writing, as a way of keeping simplified and compressed information, also motivated students during their studying and online lecture sessions. Some students were not able to revise their notes due to the vast information they had to take in every daytime as well as accumulated over time. Students who stayed in remote areas of Zimbabwe depended more on their self-kept records to frequently visit and revise because they could not participate more frequently in online classes, which proved to be useful.

In the performance phase of self-regulated learning, effort regulation is an essential skill during home-based anatomy learning [ 60 ]. Self-control was assessed in students during focus group discussions, and students generally showed abilities to govern their environments and actions by self-reward and punishment in different ways, which is effort regulation. Challenges in sustaining effort were widely reported, but some students could still adapt during the lockdown, as was described previously in a similar study [ 49 ].

Environmental structuring is an important aspect of student learning during the COVID-19-induced phase of online learning at home [ 61 ]. The environment affects the productivity of students’ learning, as noted previously [ 62 ]. Some students structured their environment to be suitable for effective study before time. Students from different residential areas managed their environments differently. For instance, students who resided in high-density residential areas and semi-urban and rural areas were greatly affected by the lockdown, even though they came up with ways to manage even in such places. Other studies have reported similar results to those of the current study, showing that students could also manage their study environment during the pandemic lockdown [ 62 ]. Self-isolation from other family members was used to reduce disturbances and boost their focus during the anatomy study. Most students tended to utilize the night time more than they normally did before the lockdown. This change in study time was to escape the busy and noisy daytime at home. Music was also used to close out the noise at home, and some students gained concentration through it [ 63 ]. Concentration and motivation to study are affected by the environment; hence, anatomy students in Zimbabwe regulate their environment to achieve personal study goals.

Self-reward and punishment are required for the learner to control their actions and increase motivation [ 64 ]. The current study reviewed how first- and second-year anatomy learners at UZ and MSU controlled themselves when studying anatomy during the COVID-19-induced lockdown. The majority rewarded themselves mainly with food, social media and sleep. Upon achieving a specific study goal, students tend to reward and punish themselves accordingly, hence showing an element of self-control [ 65 ]. This is in line with reports from other studies concerning the balance between self-reward and punishment [ 66 ]. Students had minimum supervision at home over their studies compared to the time they were on campus; hence, some controlled their actions by reward and punishment mechanisms to boost motivation and self-discipline, respectively [ 67 ]. Anatomy learning is difficult for most students [ 68 ]; hence, punishment after not reaching a specific self-set goal seemed to add pain to pain. Most students commonly rewarded themselves with more time on social media because it is the most commonly used form of leisure and entertainment and a way of connecting with other peers in several places. Students also rewarded themselves with sleep because it is an aspect of their lives that is commonly deprived due to long late-night studies. This was important in refreshing their minds and boosting motivation as well as confidence, which led to a healthy mental state.

The transition from campus to a home-based learning environment required the students to search for anatomy information from many sources. Most students studying anatomy in Zimbabwe sought information on the internet from online libraries. This finding showed that students were self-regulators by seeking information during the performance phase of the regulation process [ 69 ]. Studies in the USA have also examined the utilization of learning resources by medical students, which reflects results from the current study [ 69 ]. Most physical libraries closed in line with COVID-19 pandemic regulations, which is why students resorted to online libraries and information platforms. The main challenges faced by most students who resided in remote areas were limited internet data access and connectivity as well as resources to fund such pursuits [ 70 ]. A minority of the students could not search for extra sources of information beyond what was provided by the lecturer because of the limited information and to reduce confusion in their studies.

As part of self-directed resource utilization, seeking social assistance is an important strategy in the learning of anatomy. The results from the present study at two medical schools showed that students sought social assistance and that females reached out more for help than males, as previously reported by a study on university students at the University of Edinburgh [ 71 ]. Most students in the present study sought help with anatomy from peers, elders and teachers, which is in line with previous observations [ 65 ]. Harmon and colleagues recently demonstrated that anatomy students can utilize available resources to enhance their learning and academic performance [ 69 ]. However, most challenges were faced by students who could not obtain good internet connectivity, as they could not seek help from their friends, tutors and lecturers. Students at UZ and MSU preferred peer-to-peer interactions, which were also more common and comfortable than student-to-lecturer interactions. Family members played a crucial part in providing emotional and psychological support to the student during the home learning period; hence, the role of the family is significant, as noted in other studies [ 72 ]. Therefore, awareness of students’ help-seeking behaviors and student counseling during the lockdown was essential and could be incorporated into future student support systems.

Study limitations

The current study has some limitations. The study may not have captured a good picture of the student’s self-regulated learning behaviors due to the unequal numbers between students at UZ and MSU. Further studies must consider larger samples of medical students across many subjects in crises and normal times. The online questionnaire may have largely been responded to by those who had an internet connection at the time of data collection; hence, the majority of students in remote areas could not have fully participated. The online focus group discussions that were conducted using Zoom meetings were only attended by those who could also afford and access an internet connection. Future studies must provide equal opportunities for the full participation of all in the target population.

From this present phenomenological study, it has been noted that students were generally self-regulators despite the challenges they met during the COVID-19-induced home-based learning period. There was no specific difference in how the students from both universities directed their anatomy learning during lockdown. The effect of student location during lockdown had a significant effect on how students regulated learning, with grave challenges affecting students coming from low-income homes and remote areas. This study sheds light on the dynamic interplay between individual agency and external challenges faced by preclinical medical students in a low-income setting during the COVID-19 pandemic. The findings underscore the necessity of adaptable, supportive educational frameworks that can accommodate the diverse needs of students, especially in times of crisis. The resilience, adaptability, and collaborative spirit demonstrated by the students offer valuable insights for future educational planning and the development of more inclusive and flexible learning environments.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due guarantees given to audio data confidentiality but quantitative data are available from the corresponding author on reasonable request.

Murewanhema G, Burukai TV, Chiwaka L, Maunganidze F, Munodawafa D, Pote W et al. The effect of increased mobility on SARS-CoV-2 transmission: a descriptive study of the trends of COVID-19 in Zimbabwe between December 2020 and January 2021. Pan Afr Med J. 2021;39(1).

Brown A, Kassam A, Paget M, Blades K, Mercia M, Kachra R. Exploring the global impact of the COVID-19 pandemic on medical education: an international cross-sectional study of medical learners. Can Med Educ J. 2021;12(3):28–43.

Google Scholar  

Souza AD, Kotian SR, Pandey AK, Rao P, Kalthur SG. Cadaver as a first teacher: a module to learn the ethics and values of cadaveric dissection. J Taibah Univ Med Sci. 2020;15(2):94–101.

Iwanaga J, Loukas M, Dumont AS, Tubbs RS. A review of anatomy education during and after the COVID-19 pandemic: revisiting traditional and modern methods to achieve future innovation. Clin Anat. 2021;34(1):108–14.

Article   Google Scholar  

Dost S, Hossain A, Shehab M, Abdelwahed A, Al-Nusair L. Perceptions of medical students towards online teaching during the COVID-19 pandemic: a national cross-sectional survey of 2721 UK medical students. BMJ Open. 2020;10(11):e042378.

Barbosa J, Silva Á, Ferreira MA, Severo M. Transition from secondary school to medical school: the role of self-study and self-regulated learning skills in freshman burnout. Acta Med Port. 2016;29(12):803–8.

Zhang J, Zilundu PLM, Fu R, Zheng X, Zhou L, Guo G. Medical students’ perceptions and performance in an online regional anatomy course during the Covid-19 pandemic. Anat Sci Educ. 2022;15(5):928–42.

Mogodi M, Griffiths D, Molwantwa M, Kebaetse M, Tarpley M, Prozesky D. Justice as fairness in preparing for emergency remote teaching: a case from Botswana. Afr J Health Prof Educ. 2022;14(1):8–12.

Biwer F, Wiradhany W, Oude Egbrink M, Hospers H, Wasenitz S, Jansen W, et al. Changes and adaptations: how university students self-regulate their online learning during the COVID-19 pandemic. Front Psychol. 2021;12:642593.

Santos J, Figueiredo AS, Vieira M. Innovative pedagogical practices in higher education: an integrative literature review. Nurse Educ Today. 2019;72:12–7.

Zimmerman BJ. Self-regulated learning. 2001.

Panadero E. A review of self-regulated learning: six models and four directions for research. Front Psychol. 2017;8:422.

Zimmerman BJ. Self-regulation involves more than metacognition: a social cognitive perspective. Educ Psychol. 1995;30(4):217–21.

Cleary TJ, Callan GL. Assessing self-regulated learning using microanalytic methods. Handbook of self-regulation of learning and performance. Routledge; 2017. pp. 338–51.

Mahlangu VP. The good, the bad, and the ugly of distance learning in higher education. Trends E-Learn. 2018;10:17–29.

Schunk DH. Self-Evaluation and Self-Regulated Learning. 1996.

Zimmerman BJ. Becoming a self-regulated learner: which are the key subprocesses? Contemp Educ Psychol. 1986;11(4):307–13.

Corno L, Mandinach EB. The role of cognitive engagement in classroom learning and motivation. Educ Psychol. 1983;18(2):88–108.

Ysseldyke JE, Pianta B, Christenson S, Wang J, Algozzine B. An analysis of prereferral interventions. Psychol Sch. 1983;20(2):184–90.

McCombs BL. Processes and skills underlying continuing intrinsic motivation to learn: toward a definition of motivational skills training interventions. Educ Psychol. 1984;19(4):199–218.

Bol L, Garner JK. Challenges in supporting self-regulation in distance education environments. J Comput High Educ. 2011;23:104–23.

Pintrich PR. The role of goal orientation in self-regulated learning. Handbook of self-regulation. Elsevier; 2000. pp. 451–502.

Kingsbury T. Exploring the Potential for a First Year Experience Online with Learning Styles. 2015.

Pandey P, Zimitat C. Medical students’ learning of anatomy: memorisation, understanding and visualisation. Med Educ. 2007;41(1):7–14.

Pizzimenti MA, Axelson RD. Assessing student engagement and self-regulated learning in a medical gross anatomy course. Anat Sci Educ. 2015;8(2):104–10.

Yukselturk E, Bulut S. Predictors for student success in an online course. J Educ Technol Soc. 2007;10(2):71–83.

Zilundu PL, Chibhabha F, Yu G, Fu R, Zhou L. Pre-clinical medical students’ use of motivational and cognitive study strategies during anatomy learning: a three‐year cross‐sectional survey. Anat Sci Educ. 2022;15(3):522–34.

Guy R, Byrne B, Dobos M. Optional anatomy and physiology e-learning resources: student access, learning approaches, and academic outcomes. Adv Physiol Educ. 2018.

Cazan AM, Indreica SE. Need for cognition and approaches to learning among university students. Procedia-Soc Behav Sci. 2014;127:134–8.

Dunlosky J, Rawson KA, Marsh EJ, Nathan MJ, Willingham DT. Improving students’ learning with effective learning techniques: promising directions from cognitive and educational psychology. Psychol Sci Public Interest. 2013;14(1):4–58.

Wilhelmsson N, Dahlgren LO, Hult H, Scheja M, Lonka K, Josephson A. The anatomy of learning anatomy. Adv Health Sci Educ. 2010;15:153–65.

Ferrel MN, Ryan JJ. The impact of COVID-19 on medical education. Cureus. 2020;12(3).

Smith CF, Border S. The twelve cranial nerves of Christmas: mnemonics, rhyme, and anatomy–seeing the lighter side. Anat Sci Educ. 2019;12(6):673–7.

Owusu-Agyeman Y, Mugume T. Academic adjustment of first year students and their transition experiences: the moderating effect of social adjustment. Tert Educ Manag. 2023;1–21.

Alsoufi A, Alsuyihili A, Msherghi A, Elhadi A, Atiyah H, Ashini A, et al. Impact of the COVID-19 pandemic on medical education: medical students’ knowledge, attitudes, and practices regarding electronic learning. PLoS ONE. 2020;15(11):e0242905.

Tomas N, Poroto A. The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: a cross-sectional survey. Heliyon. 2023;9(11).

Gandomkar R, Mirzazadeh A, Jalili M, Yazdani K, Fata L, Sandars J. Self-regulated learning processes of medical students during an academic learning task. Med Educ. 2016;50(10):1065–74.

Pelikan ER, Lüftenegger M, Holzer J, Korlat S, Spiel C, Schober B. Learning during COVID-19: the role of self-regulated learning, motivation, and procrastination for perceived competence. Z Für Erzieh. 2021;24(2):393–418.

Biggerstaff D, Thompson AR. Interpretative phenomenological analysis (IPA): a qualitative methodology of choice in healthcare research. Qual Res Psychol. 2008;5(3):214–24.

Sparkes AC, Smith B. Judging the quality of qualitative inquiry: Criteriology and relativism in action. Psychol Sport Exerc. 2009;10(5):491–7.

Wong LP. Focus group discussion: a tool for health and medical research. Singap Med J. 2008;49(3):256–60.

McParland JL, Flowers P. Nine lessons and recommendations from the conduct of focus group research in chronic pain samples. Br J Health Psychol. 2012;17(3):492–504.

Zimmerman BJ, Pons MM. Development of a structured interview for assessing student use of self-regulated learning strategies. Am Educ Res J. 1986;23(4):614–28.

Pietkiewicz I, Smith JA. A practical guide to using interpretative phenomenological analysis in qualitative research psychology. Psychol J. 2014;20(1):7–14.

Chung E, Subramaniam G, Dass LC. Online learning readiness among university students in Malaysia amidst COVID-19. Asian J Univ Educ. 2020;16(2):45–58.

Wenger E. A social theory of learning. Contemp Theor Learn. 2009;209–18.

Dobson JL, Linderholm T. Self-testing promotes superior retention of anatomy and physiology information. Adv Health Sci Educ. 2015;20:149–61.

Travill A. The anatomical basis of clinical practice: an anatomy learning programme. Med Educ. 1977;11(6):377–9.

Singal A, Bansal A, Chaudhary P, Singh H, Patra A. Anatomy education of medical and dental students during COVID-19 pandemic: a reality check. Surg Radiol Anat. 2021;43:515–21.

Egalite AJ. How family background influences student achievement. Educ Next. 2016;16(2):70–8.

Azin N, Ali N, Arezoo E, Alireza A, Mohammad Hossein K. Comparison of E-learning and traditional classroom instruction of dental public health for dental students of Shahid Beheshti dental school during 2010–2011. 2012.

Simões CA, Ribeiro MA Jr, Portilho AS, Favaro M, Santin S, Ferrada P, et al. Evaluation of a training model for cervical trauma using cadavers. Am Surg. 2019;85(1):21–3.

Eilam B, Aharon I. Students’ planning in the process of self-regulated learning. Contemp Educ Psychol. 2003;28(3):304–34.

Terrell M. Anatomy of learning: instructional design principles for the anatomical sciences. Anat Rec Part B New Anat off Publ Am Assoc Anat. 2006;289(6):252–60.

Turan S, Konan A. Self-regulated learning strategies used in surgical clerkship and the relationship with clinical achievement. J Surg Educ. 2012;69(2):218–25.

Pajares F. Gender and perceived self-efficacy in self-regulated learning. Theory Pract. 2002;41(2):116–25.

Cuschieri S, Calleja Agius J. Spotlight on the shift to remote anatomical teaching during Covid-19 pandemic: perspectives and experiences from the University of Malta. Anat Sci Educ. 2020;13(6):671–9.

Ablard KE, Lipschultz RE. Self-regulated learning in high-achieving students: relations to advanced reasoning, achievement goals, and gender. J Educ Psychol. 1998;90(1):94.

Bransen D, Govaerts MJ, Sluijsmans DM, Driessen EW. Beyond the self: the role of co-regulation in medical students’ self‐regulated learning. Med Educ. 2020;54(3):234–41.

Fisher D, Solomons D, Makhathini KB. Face-to-face versus online-based lectures: a COVID-19 induced study on assessments. In Frontiers; 2022. p. 1045311.

Roslan NS, Halim AS. Enablers and barriers to online learning among medical students during COVID-19 pandemic: an explanatory mixed-method study. Sustainability. 2021;13(11):6086.

Mahdy MA, Sayed RK. Evaluation of the online learning of veterinary anatomy education during the Covid-19 pandemic lockdown in Egypt: students’ perceptions. Anat Sci Educ. 2022;15(1):67–82.

de Moya Martínez M, del Syroyid Syroyid V. Music as a Tool for promoting environmental awareness. Experiences of Undergraduate Education students on the production of video tales in the COVID-19 pandemic. Educ Sci. 2021;11(10):582.

Lapan RT, Kardash CM, Turner S. Empowering students to become self-regulated learners. Prof Sch Couns. 2002;5(4):257.

Karabenick SA, Urdan TC. Transitions across schools and cultures. Emerald Group Publishing Limited; 2012.

ten Cate OTJ, Kusurkar RA, Williams GC. How self-determination theory can assist our understanding of the teaching and learning processes in medical education. AMEE Guide 59 Med Teach. 2011;33(12):961–73.

Huang R, Ritzhaupt AD, Sommer M, Zhu J, Stephen A, Valle N, et al. The impact of gamification in educational settings on student learning outcomes: a meta-analysis. Educ Technol Res Dev. 2020;68:1875–901.

Saverino D. Teaching anatomy at the time of COVID-19. Clin Anat N Y Ny. 2020;34(8):1128–1128.

Harmon DJ, Attardi SM, Barremkala M, Bentley DC, Brown KM, Dennis JF, et al. An analysis of anatomy education before and during Covid-19: May–August 2020. Anat Sci Educ. 2021;14(2):132–47.

Polly D, McGee JR, Wang C, Lambert RG, Pugalee DK, Johnson S. The association between teachers’ beliefs, enacted practices, and student learning in mathematics. Math Educ. 2013;22(2):11–30.

Astin AW, Banta TW, Cross KP, El-Khawas E, Ewell PT, Hutchings P et al. Nine principles of good practice for assessing student learning. Am Assoc High Educ. 2003.

Hodges TS, Kerch C, Fowler M. Teacher Education in the Time of COVID-19: creating Digital Networks as University-School-Family partnerships. Middle Grades Rev. 2020;6(2):n2.

Download references

Acknowledgements

The authors wish to thank all the students who participated in this study. We would also like to extend our sincere gratitude to the UZ and MSU Anatomy departments for allowing us to give us permission to collect data from anatomy students. learners and creating a favorable environment for research. We are grateful to Ms. Phillipa, who accommodated us well in Gweru during data collection at MSU.

This research and manuscript was not funded by any external sources or organizations.

Author information

Authors and affiliations.

Department of Basic Dental and Medical Sciences, College of Dentistry, Ajman University, Ajman, United Arab Emirates

Tapiwa Chapupu & Prince L. M. Zilundu

Center of Medical and Bio-allied Health Sciences Research, Ajman, United Arab Emirates

Prince L. M. Zilundu

Anatomy Unit, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe

Tapiwa Chapupu & Anesuishe B Gatsi

Department of Anatomy, Faculty of Medicine and Health Sciences, Midlands State University, Gweru, Zimbabwe

Fidelis Chibhabha

You can also search for this author in PubMed   Google Scholar

Contributions

PLMZ and FC conceived and planned the study. ABG and TC carried out the survey. PLMZ, FC, TC and ABG planned and carried out the focus group discussions. All authors contributed to the interpretation of the results. ABG took the lead in writing the manuscript. All authors provided critical feedback and helped shape the research, analysis and manuscript.

Corresponding author

Correspondence to Prince L. M. Zilundu .

Ethics declarations

Consent for publication.

Consent for publication was obtained from all individuals whose data or information is included in this study.

Competing interests

We declare that there was no conflict of interest to disclose in relation to this study.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Chapupu, T., Gatsi, A.B., Chibhabha, F. et al. Self-regulated learning of anatomy during the COVID-19 lockdown period in a low-income setting. BMC Med Educ 24 , 548 (2024). https://doi.org/10.1186/s12909-024-05329-x

Download citation

Received : 08 September 2023

Accepted : 20 March 2024

Published : 17 May 2024

DOI : https://doi.org/10.1186/s12909-024-05329-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Self-regulated learning
• Remote learning
• Low income setting

BMC Medical Education

ISSN: 1472-6920

• Submission enquiries: [email protected]
• General enquiries: [email protected]

Trending News

Related Practices & Jurisdictions

• Health Law & Managed Care
• Antitrust & Trade Regulation
• Corporate & Business Organizations
• Administrative & Regulatory
• All Federal

The U.S. Department of Justice (“DOJ”) recently  announced  the creation of the Health Care Monopolies and Collusion Task Force (the “HCMC Task Force”) aimed at resolving antitrust issues in the health care industry. Specifically, the HCMC Task Force will focus on investigating issues related to the quality of patient care, consolidations between health care entities, labor and employment, and access and misuse of data. It will further promote DOJ’s public policy relating to the need for and benefits of preserving competition in health care. The HCMC Task Force’s mandate is broad and extends to scrutiny, not only of direct health care service providers, but also of companies that work with health care data and health care technology.

The HCMC Task Force will bring together health care experts, accountants, investigators, civil and criminal prosecutors, economists, data scientists, and policy advisors from across DOJ’s Antitrust Division to identify and address antitrust issues in health care markets. In the announcement, the Deputy Director of Civil Enforcement for DOJ’s Antitrust Division, Katrina Rouse, stated: “The task force will identify and root out monopolies and collusive practices that increase costs, decrease quality and create single points of failure in the health care industry.” The Secretary of the U.S. Department of Health and Human Services (“HHS”), Xavier Becerra, agreed, reminding the public that “[c]ompetition helps ensure patients have access to high-quality, lower cost care, and that health care workers receive higher pay and work under better conditions … and saves taxpayers money.”

The formation of the HCMC Task Force comes on the heels of the  launch of HealthyCompetition.gov , an  online public portal  to report antitrust violations to DOJ, HHS, and the Federal Trade Commission (“FTC”). This public portal allows businesses and individuals to alert DOJ and the FTC about such anticompetitive behaviors, including, for example, alleged instances of illegal roll-ups, price-gouging, and collusion amongst competitors. Information received by DOJ and FTC may then provide a basis for investigation. 

Additionally, this past March, DOJ, HHS, and the FTC launched a  cross-government inquiry  into the observed increasing control by private equity of the health care industry. The agencies have been collectively examining the effect of private equity’s involvement on patient outcomes, prices, employee benefits and wages, and innovation in health care. FTC Chair Lina Khan stated that, “[t]hrough this inquiry the FTC will continue scrutinizing private equity roll-ups, strip-and-flip tactics, and other financial plays that can enrich executives but leave the American public worse off.” The agencies issued a  Request for Information  seeking comments on transactions between health systems, insurers, facilities, and private equity funds. The comment period, which closed on May 6, resulted in more than 1,600  public comments . Proskauer has the knowledge, experience, and expertise to help health care stakeholders understand and navigate the implications of the law and the enforcement priorities of regulators in this era of increased scrutiny.

Current Legal Analysis

More from proskauer rose llp, upcoming legal education events.

Sign Up for e-NewsBulletins