research about computer literacy

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A systematic review on digital literacy

Hasan tinmaz.

1 AI & Big Data Department, Endicott College of International Studies, Woosong University, Daejeon, South Korea

Yoo-Taek Lee

2 Endicott College of International Studies, Woosong University, Daejeon, South Korea

Mina Fanea-Ivanovici

3 Department of Economics and Economic Policies, Bucharest University of Economic Studies, Bucharest, Romania

Hasnan Baber

4 Abu Dhabi School of Management, Abu Dhabi, United Arab Emirates

Associated Data

The authors present the articles used for the study in “ Appendix A ”.

The purpose of this study is to discover the main themes and categories of the research studies regarding digital literacy. To serve this purpose, the databases of WoS/Clarivate Analytics, Proquest Central, Emerald Management Journals, Jstor Business College Collections and Scopus/Elsevier were searched with four keyword-combinations and final forty-three articles were included in the dataset. The researchers applied a systematic literature review method to the dataset. The preliminary findings demonstrated that there is a growing prevalence of digital literacy articles starting from the year 2013. The dominant research methodology of the reviewed articles is qualitative. The four major themes revealed from the qualitative content analysis are: digital literacy, digital competencies, digital skills and digital thinking. Under each theme, the categories and their frequencies are analysed. Recommendations for further research and for real life implementations are generated.

Introduction

The extant literature on digital literacy, skills and competencies is rich in definitions and classifications, but there is still no consensus on the larger themes and subsumed themes categories. (Heitin, 2016 ). To exemplify, existing inventories of Internet skills suffer from ‘incompleteness and over-simplification, conceptual ambiguity’ (van Deursen et al., 2015 ), and Internet skills are only a part of digital skills. While there is already a plethora of research in this field, this research paper hereby aims to provide a general framework of digital areas and themes that can best describe digital (cap)abilities in the novel context of Industry 4.0 and the accelerated pandemic-triggered digitalisation. The areas and themes can represent the starting point for drafting a contemporary digital literacy framework.

Sousa and Rocha ( 2019 ) explained that there is a stake of digital skills for disruptive digital business, and they connect it to the latest developments, such as the Internet of Things (IoT), cloud technology, big data, artificial intelligence, and robotics. The topic is even more important given the large disparities in digital literacy across regions (Tinmaz et al., 2022 ). More precisely, digital inequalities encompass skills, along with access, usage and self-perceptions. These inequalities need to be addressed, as they are credited with a ‘potential to shape life chances in multiple ways’ (Robinson et al., 2015 ), e.g., academic performance, labour market competitiveness, health, civic and political participation. Steps have been successfully taken to address physical access gaps, but skills gaps are still looming (Van Deursen & Van Dijk, 2010a ). Moreover, digital inequalities have grown larger due to the COVID-19 pandemic, and they influenced the very state of health of the most vulnerable categories of population or their employability in a time when digital skills are required (Baber et al., 2022 ; Beaunoyer, Dupéré & Guitton, 2020 ).

The systematic review the researchers propose is a useful updated instrument of classification and inventory for digital literacy. Considering the latest developments in the economy and in line with current digitalisation needs, digitally literate population may assist policymakers in various fields, e.g., education, administration, healthcare system, and managers of companies and other concerned organisations that need to stay competitive and to employ competitive workforce. Therefore, it is indispensably vital to comprehend the big picture of digital literacy related research.

Literature review

Since the advent of Digital Literacy, scholars have been concerned with identifying and classifying the various (cap)abilities related to its operation. Using the most cited academic papers in this stream of research, several classifications of digital-related literacies, competencies, and skills emerged.

Digital literacies

Digital literacy, which is one of the challenges of integration of technology in academic courses (Blau, Shamir-Inbal & Avdiel, 2020 ), has been defined in the current literature as the competencies and skills required for navigating a fragmented and complex information ecosystem (Eshet, 2004 ). A ‘Digital Literacy Framework’ was designed by Eshet-Alkalai ( 2012 ), comprising six categories: (a) photo-visual thinking (understanding and using visual information); (b) real-time thinking (simultaneously processing a variety of stimuli); (c) information thinking (evaluating and combining information from multiple digital sources); (d) branching thinking (navigating in non-linear hyper-media environments); (e) reproduction thinking (creating outcomes using technological tools by designing new content or remixing existing digital content); (f) social-emotional thinking (understanding and applying cyberspace rules). According to Heitin ( 2016 ), digital literacy groups the following clusters: (a) finding and consuming digital content; (b) creating digital content; (c) communicating or sharing digital content. Hence, the literature describes the digital literacy in many ways by associating a set of various technical and non-technical elements.

Digital competencies

The Digital Competence Framework for Citizens (DigComp 2.1.), the most recent framework proposed by the European Union, which is currently under review and undergoing an updating process, contains five competency areas: (a) information and data literacy, (b) communication and collaboration, (c) digital content creation, (d) safety, and (e) problem solving (Carretero, Vuorikari & Punie, 2017 ). Digital competency had previously been described in a technical fashion by Ferrari ( 2012 ) as a set comprising information skills, communication skills, content creation skills, safety skills, and problem-solving skills, which later outlined the areas of competence in DigComp 2.1, too.

Digital skills

Ng ( 2012 ) pointed out the following three categories of digital skills: (a) technological (using technological tools); (b) cognitive (thinking critically when managing information); (c) social (communicating and socialising). A set of Internet skill was suggested by Van Deursen and Van Dijk ( 2009 , 2010b ), which contains: (a) operational skills (basic skills in using internet technology), (b) formal Internet skills (navigation and orientation skills); (c) information Internet skills (fulfilling information needs), and (d) strategic Internet skills (using the internet to reach goals). In 2014, the same authors added communication and content creation skills to the initial framework (van Dijk & van Deursen). Similarly, Helsper and Eynon ( 2013 ) put forward a set of four digital skills: technical, social, critical, and creative skills. Furthermore, van Deursen et al. ( 2015 ) built a set of items and factors to measure Internet skills: operational, information navigation, social, creative, mobile. More recent literature (vaan Laar et al., 2017 ) divides digital skills into seven core categories: technical, information management, communication, collaboration, creativity, critical thinking, and problem solving.

It is worth mentioning that the various methodologies used to classify digital literacy are overlapping or non-exhaustive, which confirms the conceptual ambiguity mentioned by van Deursen et al. ( 2015 ).

Digital thinking

Thinking skills (along with digital skills) have been acknowledged to be a significant element of digital literacy in the educational process context (Ferrari, 2012 ). In fact, critical thinking, creativity, and innovation are at the very core of DigComp. Information and Communication Technology as a support for thinking is a learning objective in any school curriculum. In the same vein, analytical thinking and interdisciplinary thinking, which help solve problems, are yet other concerns of educators in the Industry 4.0 (Ozkan-Ozen & Kazancoglu, 2021 ).

However, we have recently witnessed a shift of focus from learning how to use information and communication technologies to using it while staying safe in the cyber-environment and being aware of alternative facts. Digital thinking would encompass identifying fake news, misinformation, and echo chambers (Sulzer, 2018 ). Not least important, concern about cybersecurity has grown especially in times of political, social or economic turmoil, such as the elections or the Covid-19 crisis (Sulzer, 2018 ; Puig, Blanco-Anaya & Perez-Maceira, 2021 ).

Ultimately, this systematic review paper focuses on the following major research questions as follows:

• Research question 1: What is the yearly distribution of digital literacy related papers?
• Research question 2: What are the research methods for digital literacy related papers?
• Research question 3: What are the main themes in digital literacy related papers?
• Research question 4: What are the concentrated categories (under revealed main themes) in digital literacy related papers?

This study employed the systematic review method where the authors scrutinized the existing literature around the major research question of digital literacy. As Uman ( 2011 ) pointed, in systematic literature review, the findings of the earlier research are examined for the identification of consistent and repetitive themes. The systematic review method differs from literature review with its well managed and highly organized qualitative scrutiny processes where researchers tend to cover less materials from fewer number of databases to write their literature review (Kowalczyk & Truluck, 2013 ; Robinson & Lowe, 2015 ).

Data collection

To address major research objectives, the following five important databases are selected due to their digital literacy focused research dominance: 1. WoS/Clarivate Analytics, 2. Proquest Central; 3. Emerald Management Journals; 4. Jstor Business College Collections; 5. Scopus/Elsevier.

The search was made in the second half of June 2021, in abstract and key words written in English language. We only kept research articles and book chapters (herein referred to as papers). Our purpose was to identify a set of digital literacy areas, or an inventory of such areas and topics. To serve that purpose, systematic review was utilized with the following synonym key words for the search: ‘digital literacy’, ‘digital skills’, ‘digital competence’ and ‘digital fluency’, to find the mainstream literature dealing with the topic. These key words were unfolded as a result of the consultation with the subject matter experts (two board members from Korean Digital Literacy Association and two professors from technology studies department). Below are the four key word combinations used in the search: “Digital literacy AND systematic review”, “Digital skills AND systematic review”, “Digital competence AND systematic review”, and “Digital fluency AND systematic review”.

A sequential systematic search was made in the five databases mentioned above. Thus, from one database to another, duplicate papers were manually excluded in a cascade manner to extract only unique results and to make the research smoother to conduct. At this stage, we kept 47 papers. Further exclusion criteria were applied. Thus, only full-text items written in English were selected, and in doing so, three papers were excluded (no full text available), and one other paper was excluded because it was not written in English, but in Spanish. Therefore, we investigated a total number of 43 papers, as shown in Table ​ Table1. 1 . “ Appendix A ” shows the list of these papers with full references.

Number of papers identified sequentially after applying all inclusion and exclusion criteria

Data analysis

The 43 papers selected after the application of the inclusion and exclusion criteria, respectively, were reviewed the materials independently by two researchers who were from two different countries. The researchers identified all topics pertaining to digital literacy, as they appeared in the papers. Next, a third researcher independently analysed these findings by excluded duplicates A qualitative content analysis was manually performed by calculating the frequency of major themes in all papers, where the raw data was compared and contrasted (Fraenkel et al., 2012 ). All three reviewers independently list the words and how the context in which they appeared and then the three reviewers collectively decided for how it should be categorized. Lastly, it is vital to remind that literature review of this article was written after the identification of the themes appeared as a result of our qualitative analyses. Therefore, the authors decided to shape the literature review structure based on the themes.

As an answer to the first research question (the yearly distribution of digital literacy related papers), Fig.  1 demonstrates the yearly distribution of digital literacy related papers. It is seen that there is an increasing trend about the digital literacy papers.

Yearly distribution of digital literacy related papers

Research question number two (The research methods for digital literacy related papers) concentrates on what research methods are employed for these digital literacy related papers. As Fig.  2 shows, most of the papers were using the qualitative method. Not stated refers to book chapters.

Research methods used in the reviewed articles

When forty-three articles were analysed for the main themes as in research question number three (The main themes in digital literacy related papers), the overall findings were categorized around four major themes: (i) literacies, (ii) competencies, (iii) skills, and (iv) thinking. Under every major theme, the categories were listed and explained as in research question number four (The concentrated categories (under revealed main themes) in digital literacy related papers).

The authors utilized an overt categorization for the depiction of these major themes. For example, when the ‘creativity’ was labelled as a skill, the authors also categorized it under the ‘skills’ theme. Similarly, when ‘creativity’ was mentioned as a competency, the authors listed it under the ‘competencies’ theme. Therefore, it is possible to recognize the same finding under different major themes.

Major theme 1: literacies

Digital literacy being the major concern of this paper was observed to be blatantly mentioned in five papers out forty-three. One of these articles described digital literacy as the human proficiencies to live, learn and work in the current digital society. In addition to these five articles, two additional papers used the same term as ‘critical digital literacy’ by describing it as a person’s or a society’s accessibility and assessment level interaction with digital technologies to utilize and/or create information. Table ​ Table2 2 summarizes the major categories under ‘Literacies’ major theme.

Categories (more than one occurrence) under 'literacies' major theme

Computer literacy, media literacy and cultural literacy were the second most common literacy (n = 5). One of the article branches computer literacy as tool (detailing with software and hardware uses) and resource (focusing on information processing capacity of a computer) literacies. Cultural literacy was emphasized as a vital element for functioning in an intercultural team on a digital project.

Disciplinary literacy (n = 4) was referring to utilizing different computer programs (n = 2) or technical gadgets (n = 2) with a specific emphasis on required cognitive, affective and psychomotor skills to be able to work in any digital context (n = 3), serving for the using (n = 2), creating and applying (n = 2) digital literacy in real life.

Data literacy, technology literacy and multiliteracy were the third frequent categories (n = 3). The ‘multiliteracy’ was referring to the innate nature of digital technologies, which have been infused into many aspects of human lives.

Last but not least, Internet literacy, mobile literacy, web literacy, new literacy, personal literacy and research literacy were discussed in forty-three article findings. Web literacy was focusing on being able to connect with people on the web (n = 2), discover the web content (especially the navigation on a hyper-textual platform), and learn web related skills through practical web experiences. Personal literacy was highlighting digital identity management. Research literacy was not only concentrating on conducting scientific research ability but also finding available scholarship online.

Twenty-four other categories are unfolded from the results sections of forty-three articles. Table ​ Table3 3 presents the list of these other literacies where the authors sorted the categories in an ascending alphabetical order without any other sorting criterion. Primarily, search, tagging, filtering and attention literacies were mainly underlining their roles in information processing. Furthermore, social-structural literacy was indicated as the recognition of the social circumstances and generation of information. Another information-related literacy was pointed as publishing literacy, which is the ability to disseminate information via different digital channels.

Other mentioned categories (n = 1)

While above listed personal literacy was referring to digital identity management, network literacy was explained as someone’s social networking ability to manage the digital relationship with other people. Additionally, participatory literacy was defined as the necessary abilities to join an online team working on online content production.

Emerging technology literacy was stipulated as an essential ability to recognize and appreciate the most recent and innovative technologies in along with smart choices related to these technologies. Additionally, the critical literacy was added as an ability to make smart judgements on the cost benefit analysis of these recent technologies.

Last of all, basic, intermediate, and advanced digital assessment literacies were specified for educational institutions that are planning to integrate various digital tools to conduct instructional assessments in their bodies.

Major theme 2: competencies

The second major theme was revealed as competencies. The authors directly categorized the findings that are specified with the word of competency. Table ​ Table4 4 summarizes the entire category set for the competencies major theme.

Categories under 'competencies' major theme

The most common category was the ‘digital competence’ (n = 14) where one of the articles points to that category as ‘generic digital competence’ referring to someone’s creativity for multimedia development (video editing was emphasized). Under this broad category, the following sub-categories were associated:

• Problem solving (n = 10)
• Safety (n = 7)
• Information processing (n = 5)
• Content creation (n = 5)
• Communication (n = 2)
• Digital rights (n = 1)
• Digital emotional intelligence (n = 1)
• Digital teamwork (n = 1)
• Big data utilization (n = 1)
• Artificial Intelligence utilization (n = 1)
• Virtual leadership (n = 1)
• Self-disruption (in along with the pace of digitalization) (n = 1)

Like ‘digital competency’, five additional articles especially coined the term as ‘digital competence as a life skill’. Deeper analysis demonstrated the following points: social competences (n = 4), communication in mother tongue (n = 3) and foreign language (n = 2), entrepreneurship (n = 3), civic competence (n = 2), fundamental science (n = 1), technology (n = 1) and mathematics (n = 1) competences, learning to learn (n = 1) and self-initiative (n = 1).

Moreover, competencies were linked to workplace digital competencies in three articles and highlighted as significant for employability (n = 3) and ‘economic engagement’ (n = 3). Digital competencies were also detailed for leisure (n = 2) and communication (n = 2). Furthermore, two articles pointed digital competencies as an inter-cultural competency and one as a cross-cultural competency. Lastly, the ‘digital nativity’ (n = 1) was clarified as someone’s innate competency of being able to feel contented and satisfied with digital technologies.

Major theme 3: skills

The third major observed theme was ‘skills’, which was dominantly gathered around information literacy skills (n = 19) and information and communication technologies skills (n = 18). Table ​ Table5 5 demonstrates the categories with more than one occurrence.

Categories under 'skills' major theme

Table ​ Table6 6 summarizes the sub-categories of the two most frequent categories of ‘skills’ major theme. The information literacy skills noticeably concentrate on the steps of information processing; evaluation (n = 6), utilization (n = 4), finding (n = 3), locating (n = 2) information. Moreover, the importance of trial/error process, being a lifelong learner, feeling a need for information and so forth were evidently listed under this sub-category. On the other hand, ICT skills were grouped around cognitive and affective domains. For instance, while technical skills in general and use of social media, coding, multimedia, chat or emailing in specific were reported in cognitive domain, attitude, intention, and belief towards ICT were mentioned as the elements of affective domain.

Sub-categories under ‘information literacy’ and ‘ICT’ skills

Communication skills (n = 9) were multi-dimensional for different societies, cultures, and globalized contexts, requiring linguistic skills. Collaboration skills (n = 9) are also recurrently cited with an explicit emphasis for virtual platforms.

‘Ethics for digital environment’ encapsulated ethical use of information (n = 4) and different technologies (n = 2), knowing digital laws (n = 2) and responsibilities (n = 2) in along with digital rights and obligations (n = 1), having digital awareness (n = 1), following digital etiquettes (n = 1), treating other people with respect (n = 1) including no cyber-bullying (n = 1) and no stealing or damaging other people (n = 1).

‘Digital fluency’ involved digital access (n = 2) by using different software and hardware (n = 2) in online platforms (n = 1) or communication tools (n = 1) or within programming environments (n = 1). Digital fluency also underlined following recent technological advancements (n = 1) and knowledge (n = 1) including digital health and wellness (n = 1) dimension.

‘Social intelligence’ related to understanding digital culture (n = 1), the concept of digital exclusion (n = 1) and digital divide (n = 3). ‘Research skills’ were detailed with searching academic information (n = 3) on databases such as Web of Science and Scopus (n = 2) and their citation, summarization, and quotation (n = 2).

‘Digital teaching’ was described as a skill (n = 2) in Table ​ Table4 4 whereas it was also labelled as a competence (n = 1) as shown in Table ​ Table3. 3 . Similarly, while learning to learn (n = 1) was coined under competencies in Table ​ Table3, 3 , digital learning (n = 2, Table ​ Table4) 4 ) and life-long learning (n = 1, Table ​ Table5) 5 ) were stated as learning related skills. Moreover, learning was used with the following three terms: learning readiness (n = 1), self-paced learning (n = 1) and learning flexibility (n = 1).

Table ​ Table7 7 shows other categories listed below the ‘skills’ major theme. The list covers not only the software such as GIS, text mining, mapping, or bibliometric analysis programs but also the conceptual skills such as the fourth industrial revolution and information management.

Categories (one-time occurrence) under 'skills' major theme

Major theme 4: thinking

The last identified major theme was the different types of ‘thinking’. As Table ​ Table8 8 shows, ‘critical thinking’ was the most frequent thinking category (n = 4). Except computational thinking, the other categories were not detailed.

Categories under ‘thinking’ major theme

Computational thinking (n = 3) was associated with the general logic of how a computer works and sub-categorized into the following steps; construction of the problem (n = 3), abstraction (n = 1), disintegration of the problem (n = 2), data collection, (n = 2), data analysis (n = 2), algorithmic design (n = 2), parallelization & iteration (n = 1), automation (n = 1), generalization (n = 1), and evaluation (n = 2).

A transversal analysis of digital literacy categories reveals the following fields of digital literacy application:

• Technological advancement (IT, ICT, Industry 4.0, IoT, text mining, GIS, bibliometric analysis, mapping data, technology, AI, big data)
• Networking (Internet, web, connectivity, network, safety)
• Information (media, news, communication)
• Creative-cultural industries (culture, publishing, film, TV, leisure, content creation)
• Academia (research, documentation, library)
• Citizenship (participation, society, social intelligence, awareness, politics, rights, legal use, ethics)
• Education (life skills, problem solving, teaching, learning, education, lifelong learning)
• Professional life (work, teamwork, collaboration, economy, commerce, leadership, decision making)
• Personal level (critical thinking, evaluation, analytical thinking, innovative thinking)

This systematic review on digital literacy concentrated on forty-three articles from the databases of WoS/Clarivate Analytics, Proquest Central, Emerald Management Journals, Jstor Business College Collections and Scopus/Elsevier. The initial results revealed that there is an increasing trend on digital literacy focused academic papers. Research work in digital literacy is critical in a context of disruptive digital business, and more recently, the pandemic-triggered accelerated digitalisation (Beaunoyer, Dupéré & Guitton, 2020 ; Sousa & Rocha 2019 ). Moreover, most of these papers were employing qualitative research methods. The raw data of these articles were analysed qualitatively using systematic literature review to reveal major themes and categories. Four major themes that appeared are: digital literacy, digital competencies, digital skills and thinking.

Whereas the mainstream literature describes digital literacy as a set of photo-visual, real-time, information, branching, reproduction and social-emotional thinking (Eshet-Alkalai, 2012 ) or as a set of precise specific operations, i.e., finding, consuming, creating, communicating and sharing digital content (Heitin, 2016 ), this study reveals that digital literacy revolves around and is in connection with the concepts of computer literacy, media literacy, cultural literacy or disciplinary literacy. In other words, the present systematic review indicates that digital literacy is far broader than specific tasks, englobing the entire sphere of computer operation and media use in a cultural context.

The digital competence yardstick, DigComp (Carretero, Vuorikari & Punie, 2017 ) suggests that the main digital competencies cover information and data literacy, communication and collaboration, digital content creation, safety, and problem solving. Similarly, the findings of this research place digital competencies in relation to problem solving, safety, information processing, content creation and communication. Therefore, the findings of the systematic literature review are, to a large extent, in line with the existing framework used in the European Union.

The investigation of the main keywords associated with digital skills has revealed that information literacy, ICT, communication, collaboration, digital content creation, research and decision-making skill are the most representative. In a structured way, the existing literature groups these skills in technological, cognitive, and social (Ng, 2012 ) or, more extensively, into operational, formal, information Internet, strategic, communication and content creation (van Dijk & van Deursen, 2014 ). In time, the literature has become richer in frameworks, and prolific authors have improved their results. As such, more recent research (vaan Laar et al., 2017 ) use the following categories: technical, information management, communication, collaboration, creativity, critical thinking, and problem solving.

Whereas digital thinking was observed to be mostly related with critical thinking and computational thinking, DigComp connects it with critical thinking, creativity, and innovation, on the one hand, and researchers highlight fake news, misinformation, cybersecurity, and echo chambers as exponents of digital thinking, on the other hand (Sulzer, 2018 ; Puig, Blanco-Anaya & Perez-Maceira, 2021 ).

This systematic review research study looks ahead to offer an initial step and guideline for the development of a more contemporary digital literacy framework including digital literacy major themes and factors. The researchers provide the following recommendations for both researchers and practitioners.

Recommendations for prospective research

By considering the major qualitative research trend, it seems apparent that more quantitative research-oriented studies are needed. Although it requires more effort and time, mixed method studies will help understand digital literacy holistically.

As digital literacy is an umbrella term for many different technologies, specific case studies need be designed, such as digital literacy for artificial intelligence or digital literacy for drones’ usage.

Digital literacy affects different areas of human lives, such as education, business, health, governance, and so forth. Therefore, different case studies could be carried out for each of these unique dimensions of our lives. For instance, it is worth investigating the role of digital literacy on lifelong learning in particular, and on education in general, as well as the digital upskilling effects on the labour market flexibility.

Further experimental studies on digital literacy are necessary to realize how certain variables (for instance, age, gender, socioeconomic status, cognitive abilities, etc.) affect this concept overtly or covertly. Moreover, the digital divide issue needs to be analysed through the lens of its main determinants.

New bibliometric analysis method can be implemented on digital literacy documents to reveal more information on how these works are related or centred on what major topic. This visual approach will assist to realize the big picture within the digital literacy framework.

Recommendations for practitioners

The digital literacy stakeholders, policymakers in education and managers in private organizations, need to be aware that there are many dimensions and variables regarding the implementation of digital literacy. In that case, stakeholders must comprehend their beneficiaries or the participants more deeply to increase the effect of digital literacy related activities. For example, critical thinking and problem-solving skills and abilities are mentioned to affect digital literacy. Hence, stakeholders have to initially understand whether the participants have enough entry level critical thinking and problem solving.

Development of digital literacy for different groups of people requires more energy, since each group might require a different set of skills, abilities, or competencies. Hence, different subject matter experts, such as technologists, instructional designers, content experts, should join the team.

It is indispensably vital to develop different digital frameworks for different technologies (basic or advanced) or different contexts (different levels of schooling or various industries).

These frameworks should be updated regularly as digital fields are evolving rapidly. Every year, committees should gather around to understand new technological trends and decide whether they should address the changes into their frameworks.

Understanding digital literacy in a thorough manner can enable decision makers to correctly implement and apply policies addressing the digital divide that is reflected onto various aspects of life, e.g., health, employment, education, especially in turbulent times such as the COVID-19 pandemic is.

Lastly, it is also essential to state the study limitations. This study is limited to the analysis of a certain number of papers, obtained from using the selected keywords and databases. Therefore, an extension can be made by adding other keywords and searching other databases.

See Table ​ Management9 9 .

List of papers (n = 43) included in the qualitative analysis—ordered alphabetically by title

Author contributions

The authors worked together on the manuscript equally. All authors have read and approved the final manuscript.

This research is funded by Woosong University Academic Research in 2022.

Availability of data and materials

Declarations.

The authors declare that they have no competing interests.

Publisher's Note

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

Contributor Information

Hasan Tinmaz, Email: rk.ca.ttocidne@zamnith .

Yoo-Taek Lee, Email: rk.ca.usw@eelty .

Mina Fanea-Ivanovici, Email: [email protected] .

Hasnan Baber, Email: [email protected] .

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• Research article
• Open access
• Published: 19 June 2006

Computer literacy and attitudes towards e-learning among first year medical students

• Thomas Michael Link 1 &
• Richard Marz 1  

BMC Medical Education volume  6 , Article number:  34 ( 2006 ) Cite this article

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At the Medical University of Vienna, most information for students is available only online. In 2005, an e-learning project was initiated and there are plans to introduce a learning management system. In this study, we estimate the level of students' computer skills, the number of students having difficulty with e-learning, and the number of students opposed to e-learning.

The study was conducted in an introductory course on computer-based and web-based training (CBT/WBT). Students were asked to fill out a questionnaire online that covered a wide range of relevant attitudes and experiences.

While the great majority of students possess sufficient computer skills and acknowledge the advantages of interactive and multimedia-enhanced learning material, a small percentage lacks basic computer skills and/or is very skeptical about e-learning. There is also a consistently significant albeit weak gender difference in available computer infrastructure and Internet access. As for student attitudes toward e-learning, we found that age, computer use, and previous exposure to computers are more important than gender. A sizable number of students, 12% of the total, make little or no use of existing e-learning offerings.

Many students would benefit from a basic introduction to computers and to the relevant computer-based resources of the university. Given to the wide range of computer skills among students, a single computer course for all students would not be useful nor would it be accepted. Special measures should be taken to prevent students who lack computer skills from being disadvantaged or from developing computer-hostile attitudes.

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Computer literacy has been a subject of educational research ever since personal computers were introduced to the classroom, either as teaching aids or as tools for self-study. In the 1980s, research on computer literacy focused on the question whether medical students were ready for the foreseeable omnipresence of computers in the future doctors' professional environments [ 1 – 4 ], i.e., whether they possessed the necessary computer skills [ 2 , 5 – 9 ]. The vision of a knowledge-based society saw future economic wealth dependent on people's abilities to deal with the growing information load and to adapt to an ever-changing working environment [ 10 – 13 ]. It was assumed that computers would become ubiquitous tools for managing medical knowledge [ 14 ]. In some medical schools, a privately owned computer was made a requirement for medical students [ 15 , 16 ].

E-Learning, in particular the use of learning management systems (LMSs), introduced a new aspect. Researchers [ 17 ] suggested that some students may lack the necessary skills to use web-based learning platforms effectively and are therefore handicapped. This issue is often discussed in the context of gender differences. The main concern is that female students are at a disadvantage due to different patterns of computer usage, e.g. a less dominant style of discussion in web-based communication [ 18 , 19 ]. These gender differences can be observed in students' computer-related behaviors but also in their attitudes towards computer-based and web-based training (CBT/WBT). In a Danish study, Dørup [ 9 ] reported that among first-year students, 46% of the men were in favor of replacing "traditional teaching with use of computers if possible" while only 22% women agreed with this statement.

In 2004, 80% of Austria's 20–29 year olds had Internet access and 75% of university and high school students used a computer daily [ 20 ]. We can thus assume that, in general, students entering university have good basic computer skills. Studies nevertheless demonstrate that there is a considerable difference in computer use according to students' disciplines. Middendorff [ 21 ] reports that German medical students spend an average of 8 hours per week at the computer (including private activities). This is the lowest value of all disciplines, what makes it difficult to draw conclusions about medical students' computer use from general surveys. Often the degree of "informational fluency" remains at a basic level and students tend to over-estimate their computer skills [ 22 ].

This study examines the level of computer literacy and patterns of computer usage of first-year medical students at the Medical University of Vienna. It was conducted in an introductory course for first-year students on CBT/WBT. The goal of the study was to determine the need for such introductory courses and to provide information that could be used to improve them. A secondary aim was to identify difficulties that may be encountered in implementing a university-wide LMS due to students' lack of computer literacy or low acceptance of e-learning. While multimedia learning programs have been praised for their educational superiority, actual use of these programs has sometimes failed to meet our expectations.

Since autumn 2003, we have required students to take an introductory course on CBT/WBT as a single 90-minute class session. This course is held for first-year students (about 1500 students took it in 2004 and 2005) and second-year students (about 600 students from 2003 to 2005) [ 23 ]. The course serves two main purposes:

To ensure a certain level of computer and information literacy, including online communication skills.

To acquaint students with computer and web-based learning materials.

In 2003 and 2004, students had to review web-based learning programs (e.g. [ 24 ]) and post their statements in a dedicated online forum. In the course for first-year students we used a student-developed platform [ 25 ]. In the course for second-year students, we used Manila [ 26 ] in 2003 and TikiWiki [ 27 ] in 2004 as a collaboration tool. In 2005, we switched to tools that were partly self-developed and less demanding with respect to the server load.

This paper reports on data from an online survey for the 2004 course for first-year students. Participation in the survey was voluntary and anonymous (though students were asked to give their student ID if they wanted to). The tutors were not able to determine who has or has not filled out the questionnaire. Using class time for students to fill out the questionnaire nevertheless ensured a high response rate of 79%.

A total of 1232 questionnaires were completed, 1160 of which remained in the data set after applying some filtering rules in order to eliminate records of uncertain origin. The gender breakdown of respondents was 61% female and 39% male. This corresponds exactly to the gender breakdown of the 1560 students entering the study module (61% female and 39% male). We thus conclude that our sample was representative of the 2004 cohort. Missing values due to non-responses are not included in tables or figures. Differences between the reported counts and the sample size (n = 1160) are thus due to missing responses.

Questionnaire

The questionnaire [ 28 ] (see Additional file 1 ) was designed to collect the following information:

Overall evaluation of the course

Attitudes towards e-learning as well as previous experiences and expectations about the use of CBT/WBT

Computer and Internet usage

Extent of students' private computer infrastructure

Basic demographic data.

In the following, we will focus on students' computer usage and private computer infrastructure as well as their attitudes toward e-learning.

Attitudes towards e-learning (understood as an umbrella concept for learning methods supported by information- and communication technologies (ICT) in general) were determined by the students' agreement or disagreement with several statements about the importance of ICT in medical education. These statements contained items like "Web-based learning programs are able to replace lectures" or "In medical teaching, there is no need for the use of Web-based programs." The students rated their agreement or disagreement on a bi-polar eight-point Likert scale. For the purpose of comparability with Dørup [ 9 ], we recoded their answers into dichotomous variables. As computer use and attitudes towards e-learning were measured on an ordinal scale, we accordingly used Spearman rho to describe the statistical relationship of these variables with other items. For other metric variables Pearson r was used.

Computer infrastructure

Almost all students (94%) have access to a privately owned PC they can use for their studies, which is either owned by the students themselves (74%) or shared with family members or roommates (20%). Only 5% rely primarily on public computer facilities (Table 1 ).

Student-owned PCs are on average 2.3 years old; 92% are newer than 5 years, 87% newer than 4 years. This corresponds to the life span of computers in companies or public administration offices. Only 3.2% of the students have a computer older than 6 years. Male students' PCs (mean ± SD: 2 ± 1.42 years) are newer than those owned by women (2.5 ± 2.05 years). The 95% confidence interval for the difference is 0.33..0.79 years.

Internet access

The great majority of students also have access to the Internet, though the quality of connectivity varies widely; 60% have access via ADSL, cable TV, or LAN (which, however, usually signifies the use of public facilities at the university or elsewhere); 37% have access using a telephone connection (modem or ISDN) (Table 2 ). The type of Internet access differs according to gender (Cramer V = 0.28, p = 0.001). Male students tend to have faster Internet access while older technologies (e.g. modem) are more common among women. The proportion of modem users is twice as high among women (33%) than among men (15%).

Computer use

Types of computer use.

Students are familiar with e-mail and the use of the Internet for information research; 94% of the students communicate via e-mail and 97% use the Internet for information research at least several times per month. While the use of word processors is very common (82% use such a program several times a month), students are less familiar with other program types (Table 3 ).

Very few medical students have experience in Web design or the creation of HTML documents (5% at least weekly) and thus make no use of the Internet for publishing or more sophisticated collaboration purposes. The frequencies of using communication technologies other than e-mail, e.g., chats (21%), forums and bulletin boards (13%), are also low.

One noteworthy detail is the proportion of students who use computers for organizing appointments, to do lists, or making notes: 28% use such a personal organizer software several times per week, which may point to the use of personal digital assistants (PDA) or smart cell phones.

Except for the categories "Word Processor" and "E-mail," male students use the computer significantly more often than women. The strength of this statistical relationship is weak. Spearman rho is highest for the categories "Web-design" (r s = 0.25, p = 0.001), "Games" (r s = 0.23, p = 0.001), "Forums" (r s = 0.21, p = 0.001), and "Spreadsheets" (r s = 0.20, p = 0.001).

Age when using a computer for the first time

Half of all students (50%) used a computer for the first time by the age of 11 (mean 11.2 ± 3.77 SD). By the time they entered university, i.e., before the age of 18, fully 96% of all students had begun to use computers. The average age when students began using computers for the first time is slightly lower for men (10.7 ± 3.40 years) than women (11.5 ± 3.96 years). The 95% confidence interval for this difference is 0.33..1.24 years.

Prior experiences and expectations

Half of the students (49%) report using a computer or Web-based learning program at least once per month. In order to determine how many students have little or no experience with e-learning, we consolidated answers to questions about four different kinds of e-learning programs (information retrieval, downloading scripts, LMS, and CBT/WBT) into one index. Because of the high response rates for "downloading learning material," we defined inexperienced users as those who answered "less often" or "never" to questions about at least three of these kinds of programs. Following this typology, 12% of the students are inexperienced, having used at most one kind of e-learning program at least once per term (Table 4 ).

The majority of students (66%) have already used a computer or Web-based dictionary like the Pschyrembel medical dictionary, which is one of the standard references used by Vienna medical students. Half of them (50%) have used an online image repository at least once and 42% have used some kind of online quiz to test their knowledge (Table 5 ). Other kinds of learning programs, such as those associated with a constructivist approach, are less well known among first-year Vienna students. The results given in Tables 4 and 5 relating to students' use of LMS are inconsistent. This inconsistency arises most likely from the students' lack of understanding of what a LMS is since very few lecturers use this kind of software to support their courses.

About 10% of the students have never used any of the above-mentioned kinds of e-learning programs and 4.4% do not regard any of them as helpful. Those who regard only two or fewer as helpful tend to prefer learning programs that have no "built-in" educational theory, such as encyclopedias (38%), image collections (23%), and quizzes (23%). The number of different kinds of programs that students have experience with and that they consider helpful correlates with Pearson r = 0.32 (p = 0.001) – the more kinds of programs they know, the more kinds they consider useful.

A majority of the students agree (median = 2, interquartile range = 3) that CBT/WBT should be offered as a supplement to lectures and seminars (Figure 1 ). On the other hand, most students disagree with the statement that e-learning should replace these traditional forms of teaching (median = 7, IQR = 4).

Students' agreement or disagreement with statements on the usefulness of e-learning . The x-axis represents the values of an 8-point bi-polar rating scale: 1 = strong agreement, 8 = strong disagreement. The boxes show the quartiles (25% of the distribution) and the median (50% cut).

Men (median = 6) tend to be slightly more in favor of replacing traditional lectures with CBT/WBT than women (median = 7). The strength of this effect is negligible (r s = 0.06, p = 0.041). After recoding to a dichotomous scale (1..4 = pro, 5..8 = contra), 28% of male and 25% of female students can be considered favoring the replacement of traditional teaching methods with e-learning. The gender difference is slightly bigger for the item "Computer or Web-based training should play a more important role" but still hardly noteworthy (r s = 0.16, p = 0.001). In general, the following variables have bigger effects on e-learning-related attitudes than gender per se:

Lack of experience with CBT/WBT

Productive computer and Internet use (e.g. spreadsheets, organizer, word processor, graphics, e-mail, Web design, and information research).

We consolidated statements 2 to 4 in Figure 1 into one index (Cronbach alpha = 0.65; inclusion of the items 1 and 5 leads to a slight decrease in reliability). In a regression model (Table 6 ) that includes the above 3 variables and gender (R 2 adj = 0.15, p = 0.001, SEE = 1.54), gender is not statistically significant (p = 0.41). When the stepwise regression method is used, gender is excluded from the final model.

Computer infrastructure and internet access

A sizable number of students still have Internet access only via dial-up connections using a modem. This mode of Internet access is slow and impedes the use of synchronous communication tools that require one to stay online for a long period of time. Even if the majority of students do have broadband access to the Internet, mandatory e-learning solutions cannot rely on synchronous online communication tools like chats and on extensive video material, e.g. recordings from lectures. Instead, preference should be given to asynchronous online communication tools and textual information along with videos. Asynchronous communication tools also have the advantage that teachers and students do not have to be online at the same time.

Computer use patterns

Only a small number of students have experience with Internet publishing and asynchronous communication tools like BBS or forums. Thus, most of our students are rather passive Internet users and miss out on numerous possibilities of virtual communities and Web-based publishing. The lack of experience with synchronous and asynchronous online communication, with the exception of e-mail, may cause problems when using the collaboration tools included in an LMS [ 29 ].

Attitudes towards e-learning

Most students agree that e-learning could serve as a supplement for lectures and seminars. However, about as many students disagree with the statement that e-learning could replace traditional ways of teaching. In the Danish context, Dørup [ 9 ] reported a slightly greater proportion of first-year medical students in favor of replacing traditional lectures with e-learning (47% men, 22% women). These higher levels of agreement could be explained by the different response scales used but also by the fact that Danish people in general are reported [ 30 ] to be more "digital literate" than Austrians – although this difference cannot be claimed for persons under 24 years of age [ 30 ].

The intensity of computer use and previous experience with CBT/WBT have the greatest effect on students' attitudes towards e-learning. The explanation for this could be a general discomfort with the technology that makes students who lack experience with ICT express themselves cautiously about its use in education [ 31 ]. It could also be explained by the relative novelty of e-learning and students' difficulties in integrating CBT/WBT into their way of learning [ 32 ].

Most students seem to acknowledge the range of possibilities of new media to enhance their learning experience although they consider CBT/WBT a supplement to rather than a replacement of other learning materials. However, there is also a group of students who are strictly opposed to CBT/WBT (4.4% of the first-year students do not value any of the kinds of programs mentioned above). More disturbing, 24% strongly agree (values 1 and 2 on an 8-point rating scale) with the statement that the Medical University of Vienna could do well without CBT/WBT. When introducing an online LMS or Web-based learning program, special care should be taken not to lose these students because of the choice of a certain learning technology.

In December 2005, we also held a few focus groups with teachers and students on a similar subject. In the course of these discussions it became clear how some characteristics of the new curriculum, especially the emphasis on the MCQ-based year-end examinations, impeded the use of CBT/WBT. In these discussions the students had doubts about the usability and efficiency of e-learning (with regard to costs, handling of ICT, but also learning efficiency) while they still acknowledged the possibilities of ICT support with respect to visualization, simulation, self-quizzing, and fast information retrieval from several sources such as encyclopedias or Web pages.

Gender differences

We were able to identify gender differences for all computer-related variables. In sum, men make more frequent use of computers and have access to better computer infrastructure and faster Internet connections. While this difference is quite consistent over several variables, the strength of the statistical relationship is weak and, with respect to students' attitudes towards e-learning, overshadowed by other variables (e.g. previous exposure to CBT/WBT) that are more important for predicting students' attitudes.

With respect to the implementation of an LMS, the most important difference between men and women is the relatively high number of women still using a slow dial-up connection to the Internet, which could impede the use of synchronous communication tools or multimedia-rich Web applications. Well planned use of e-learning and supportive measures should help to neutralize this difference. Although women have less experience with forums, Gunn [ 19 ] showed that these differences in online communication behavior do not necessarily result in worse examination outcomes.

E-Learning must be appropriate to students' level of computer expertise in order not to become a source of frustration. Courses to develop students' computer skills can improve this situation by influencing students' attitudes and capabilities. Our conclusions with respect to such introductory courses are twofold. Students certainly need some kind of formal introduction to the new ICT for learning purposes. But due to the wide range of previous experience and computer skills, there is no one-size-fits-all course design available. Such a course should either be split into several tracks according to students' different levels of computer literacy [ 33 ], or it should be held only for students with little or no computer experience.

There is, however, the danger that precisely those students who need this course the most will hesitate to attend it voluntarily. It is difficult to say how these students could be persuaded to take such a course despite their skepticism towards ICT and e-learning. One strategy would be to emphasize the practical value for solving everyday problems and obtaining useful information. Once they have learned how computers help them solve recurring problems, they will perhaps develop more computer-friendly attitudes. Another solution could be to make the course compulsory but to make the impact negligible for students with good ICT knowledge. This could be achieved with a Web-based entry test. Students who pass the test would be exempted from having to take the course.

When introducing a campus-wide LMS, one has to take into consideration that some students lack the necessary computer skills or infrastructure to participate effectively in online courses, and that others are strictly opposed to e-learning. Introducing a campus-wide e-learning solution thus poses not only technical and organizational challenges but also calls for a promotional strategy. In the future, we can expect more students to think of computers as standard tools for learning as schools make more use ICT in their classrooms. For example, an "avant-garde" of Vienna medical students already created an online forum [ 34 – 36 ] for informally exchanging information about courses as well as students authored learning materials.

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Acknowledgements

We thank Thomas Benesch for statistical advice. We would also like to thank Jens Dørup, William Fulton, and Sean Marz for critically reading the manuscript and their helpful suggestions.

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Authors' contributions

RM and TML planned and organized courses [ 23 ] to promote computer literacy among medical students.

TML was responsible for designing the study, implementing the online questionnaire, analyzing the data, writing the first draft, and proofreading the final draft.

RM was responsible for designing the course content, recruiting and training the tutors and supervising all aspects of the course. He revised the article extensively.

Both authors read and approved the final version.

Thomas Michael Link and Richard Marz contributed equally to this work.

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Link, T.M., Marz, R. Computer literacy and attitudes towards e-learning among first year medical students. BMC Med Educ 6 , 34 (2006). https://doi.org/10.1186/1472-6920-6-34

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Received : 02 March 2006

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Published : 19 June 2006

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• Moerth-Teo J Bobek V Horvat T (2021) The Effects of Consumers’ Buying Behavior on the E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria Naše gospodarstvo/Our economy 10.2478/ngoe-2021-0021 67 :4 (56-73) Online publication date: 30-Dec-2021 https://doi.org/10.2478/ngoe-2021-0021
• Song D Chen M Fan S (2021) The Study of Privacy Protection of Scientific Data Sharing Based on Data Life Cycle Journal of Physics: Conference Series 10.1088/1742-6596/1952/4/042142 1952 :4 (042142) Online publication date: 1-Jun-2021 https://doi.org/10.1088/1742-6596/1952/4/042142
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A systematic review on digital literacy

• Hasan Tinmaz   ORCID: orcid.org/0000-0003-4310-0848 1 ,
• Yoo-Taek Lee   ORCID: orcid.org/0000-0002-1913-9059 2 ,
• Mina Fanea-Ivanovici   ORCID: orcid.org/0000-0003-2921-2990 3 &
• Hasnan Baber   ORCID: orcid.org/0000-0002-8951-3501 4  

Smart Learning Environments volume  9 , Article number:  21 ( 2022 ) Cite this article

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The purpose of this study is to discover the main themes and categories of the research studies regarding digital literacy. To serve this purpose, the databases of WoS/Clarivate Analytics, Proquest Central, Emerald Management Journals, Jstor Business College Collections and Scopus/Elsevier were searched with four keyword-combinations and final forty-three articles were included in the dataset. The researchers applied a systematic literature review method to the dataset. The preliminary findings demonstrated that there is a growing prevalence of digital literacy articles starting from the year 2013. The dominant research methodology of the reviewed articles is qualitative. The four major themes revealed from the qualitative content analysis are: digital literacy, digital competencies, digital skills and digital thinking. Under each theme, the categories and their frequencies are analysed. Recommendations for further research and for real life implementations are generated.

Introduction

The extant literature on digital literacy, skills and competencies is rich in definitions and classifications, but there is still no consensus on the larger themes and subsumed themes categories. (Heitin, 2016 ). To exemplify, existing inventories of Internet skills suffer from ‘incompleteness and over-simplification, conceptual ambiguity’ (van Deursen et al., 2015 ), and Internet skills are only a part of digital skills. While there is already a plethora of research in this field, this research paper hereby aims to provide a general framework of digital areas and themes that can best describe digital (cap)abilities in the novel context of Industry 4.0 and the accelerated pandemic-triggered digitalisation. The areas and themes can represent the starting point for drafting a contemporary digital literacy framework.

Sousa and Rocha ( 2019 ) explained that there is a stake of digital skills for disruptive digital business, and they connect it to the latest developments, such as the Internet of Things (IoT), cloud technology, big data, artificial intelligence, and robotics. The topic is even more important given the large disparities in digital literacy across regions (Tinmaz et al., 2022 ). More precisely, digital inequalities encompass skills, along with access, usage and self-perceptions. These inequalities need to be addressed, as they are credited with a ‘potential to shape life chances in multiple ways’ (Robinson et al., 2015 ), e.g., academic performance, labour market competitiveness, health, civic and political participation. Steps have been successfully taken to address physical access gaps, but skills gaps are still looming (Van Deursen & Van Dijk, 2010a ). Moreover, digital inequalities have grown larger due to the COVID-19 pandemic, and they influenced the very state of health of the most vulnerable categories of population or their employability in a time when digital skills are required (Baber et al., 2022 ; Beaunoyer, Dupéré & Guitton, 2020 ).

The systematic review the researchers propose is a useful updated instrument of classification and inventory for digital literacy. Considering the latest developments in the economy and in line with current digitalisation needs, digitally literate population may assist policymakers in various fields, e.g., education, administration, healthcare system, and managers of companies and other concerned organisations that need to stay competitive and to employ competitive workforce. Therefore, it is indispensably vital to comprehend the big picture of digital literacy related research.

Literature review

Since the advent of Digital Literacy, scholars have been concerned with identifying and classifying the various (cap)abilities related to its operation. Using the most cited academic papers in this stream of research, several classifications of digital-related literacies, competencies, and skills emerged.

Digital literacies

Digital literacy, which is one of the challenges of integration of technology in academic courses (Blau, Shamir-Inbal & Avdiel, 2020 ), has been defined in the current literature as the competencies and skills required for navigating a fragmented and complex information ecosystem (Eshet, 2004 ). A ‘Digital Literacy Framework’ was designed by Eshet-Alkalai ( 2012 ), comprising six categories: (a) photo-visual thinking (understanding and using visual information); (b) real-time thinking (simultaneously processing a variety of stimuli); (c) information thinking (evaluating and combining information from multiple digital sources); (d) branching thinking (navigating in non-linear hyper-media environments); (e) reproduction thinking (creating outcomes using technological tools by designing new content or remixing existing digital content); (f) social-emotional thinking (understanding and applying cyberspace rules). According to Heitin ( 2016 ), digital literacy groups the following clusters: (a) finding and consuming digital content; (b) creating digital content; (c) communicating or sharing digital content. Hence, the literature describes the digital literacy in many ways by associating a set of various technical and non-technical elements.

• Digital competencies

The Digital Competence Framework for Citizens (DigComp 2.1.), the most recent framework proposed by the European Union, which is currently under review and undergoing an updating process, contains five competency areas: (a) information and data literacy, (b) communication and collaboration, (c) digital content creation, (d) safety, and (e) problem solving (Carretero, Vuorikari & Punie, 2017 ). Digital competency had previously been described in a technical fashion by Ferrari ( 2012 ) as a set comprising information skills, communication skills, content creation skills, safety skills, and problem-solving skills, which later outlined the areas of competence in DigComp 2.1, too.

• Digital skills

Ng ( 2012 ) pointed out the following three categories of digital skills: (a) technological (using technological tools); (b) cognitive (thinking critically when managing information); (c) social (communicating and socialising). A set of Internet skill was suggested by Van Deursen and Van Dijk ( 2009 , 2010b ), which contains: (a) operational skills (basic skills in using internet technology), (b) formal Internet skills (navigation and orientation skills); (c) information Internet skills (fulfilling information needs), and (d) strategic Internet skills (using the internet to reach goals). In 2014, the same authors added communication and content creation skills to the initial framework (van Dijk & van Deursen). Similarly, Helsper and Eynon ( 2013 ) put forward a set of four digital skills: technical, social, critical, and creative skills. Furthermore, van Deursen et al. ( 2015 ) built a set of items and factors to measure Internet skills: operational, information navigation, social, creative, mobile. More recent literature (vaan Laar et al., 2017 ) divides digital skills into seven core categories: technical, information management, communication, collaboration, creativity, critical thinking, and problem solving.

It is worth mentioning that the various methodologies used to classify digital literacy are overlapping or non-exhaustive, which confirms the conceptual ambiguity mentioned by van Deursen et al. ( 2015 ).

• Digital thinking

Thinking skills (along with digital skills) have been acknowledged to be a significant element of digital literacy in the educational process context (Ferrari, 2012 ). In fact, critical thinking, creativity, and innovation are at the very core of DigComp. Information and Communication Technology as a support for thinking is a learning objective in any school curriculum. In the same vein, analytical thinking and interdisciplinary thinking, which help solve problems, are yet other concerns of educators in the Industry 4.0 (Ozkan-Ozen & Kazancoglu, 2021 ).

However, we have recently witnessed a shift of focus from learning how to use information and communication technologies to using it while staying safe in the cyber-environment and being aware of alternative facts. Digital thinking would encompass identifying fake news, misinformation, and echo chambers (Sulzer, 2018 ). Not least important, concern about cybersecurity has grown especially in times of political, social or economic turmoil, such as the elections or the Covid-19 crisis (Sulzer, 2018 ; Puig, Blanco-Anaya & Perez-Maceira, 2021 ).

Ultimately, this systematic review paper focuses on the following major research questions as follows:

Research question 1: What is the yearly distribution of digital literacy related papers?

Research question 2: What are the research methods for digital literacy related papers?

Research question 3: What are the main themes in digital literacy related papers?

Research question 4: What are the concentrated categories (under revealed main themes) in digital literacy related papers?

This study employed the systematic review method where the authors scrutinized the existing literature around the major research question of digital literacy. As Uman ( 2011 ) pointed, in systematic literature review, the findings of the earlier research are examined for the identification of consistent and repetitive themes. The systematic review method differs from literature review with its well managed and highly organized qualitative scrutiny processes where researchers tend to cover less materials from fewer number of databases to write their literature review (Kowalczyk & Truluck, 2013 ; Robinson & Lowe, 2015 ).

Data collection

To address major research objectives, the following five important databases are selected due to their digital literacy focused research dominance: 1. WoS/Clarivate Analytics, 2. Proquest Central; 3. Emerald Management Journals; 4. Jstor Business College Collections; 5. Scopus/Elsevier.

The search was made in the second half of June 2021, in abstract and key words written in English language. We only kept research articles and book chapters (herein referred to as papers). Our purpose was to identify a set of digital literacy areas, or an inventory of such areas and topics. To serve that purpose, systematic review was utilized with the following synonym key words for the search: ‘digital literacy’, ‘digital skills’, ‘digital competence’ and ‘digital fluency’, to find the mainstream literature dealing with the topic. These key words were unfolded as a result of the consultation with the subject matter experts (two board members from Korean Digital Literacy Association and two professors from technology studies department). Below are the four key word combinations used in the search: “Digital literacy AND systematic review”, “Digital skills AND systematic review”, “Digital competence AND systematic review”, and “Digital fluency AND systematic review”.

A sequential systematic search was made in the five databases mentioned above. Thus, from one database to another, duplicate papers were manually excluded in a cascade manner to extract only unique results and to make the research smoother to conduct. At this stage, we kept 47 papers. Further exclusion criteria were applied. Thus, only full-text items written in English were selected, and in doing so, three papers were excluded (no full text available), and one other paper was excluded because it was not written in English, but in Spanish. Therefore, we investigated a total number of 43 papers, as shown in Table 1 . “ Appendix A ” shows the list of these papers with full references.

Data analysis

The 43 papers selected after the application of the inclusion and exclusion criteria, respectively, were reviewed the materials independently by two researchers who were from two different countries. The researchers identified all topics pertaining to digital literacy, as they appeared in the papers. Next, a third researcher independently analysed these findings by excluded duplicates A qualitative content analysis was manually performed by calculating the frequency of major themes in all papers, where the raw data was compared and contrasted (Fraenkel et al., 2012 ). All three reviewers independently list the words and how the context in which they appeared and then the three reviewers collectively decided for how it should be categorized. Lastly, it is vital to remind that literature review of this article was written after the identification of the themes appeared as a result of our qualitative analyses. Therefore, the authors decided to shape the literature review structure based on the themes.

As an answer to the first research question (the yearly distribution of digital literacy related papers), Fig.  1 demonstrates the yearly distribution of digital literacy related papers. It is seen that there is an increasing trend about the digital literacy papers.

Yearly distribution of digital literacy related papers

Research question number two (The research methods for digital literacy related papers) concentrates on what research methods are employed for these digital literacy related papers. As Fig.  2 shows, most of the papers were using the qualitative method. Not stated refers to book chapters.

Research methods used in the reviewed articles

When forty-three articles were analysed for the main themes as in research question number three (The main themes in digital literacy related papers), the overall findings were categorized around four major themes: (i) literacies, (ii) competencies, (iii) skills, and (iv) thinking. Under every major theme, the categories were listed and explained as in research question number four (The concentrated categories (under revealed main themes) in digital literacy related papers).

The authors utilized an overt categorization for the depiction of these major themes. For example, when the ‘creativity’ was labelled as a skill, the authors also categorized it under the ‘skills’ theme. Similarly, when ‘creativity’ was mentioned as a competency, the authors listed it under the ‘competencies’ theme. Therefore, it is possible to recognize the same finding under different major themes.

Major theme 1: literacies

Digital literacy being the major concern of this paper was observed to be blatantly mentioned in five papers out forty-three. One of these articles described digital literacy as the human proficiencies to live, learn and work in the current digital society. In addition to these five articles, two additional papers used the same term as ‘critical digital literacy’ by describing it as a person’s or a society’s accessibility and assessment level interaction with digital technologies to utilize and/or create information. Table 2 summarizes the major categories under ‘Literacies’ major theme.

Computer literacy, media literacy and cultural literacy were the second most common literacy (n = 5). One of the article branches computer literacy as tool (detailing with software and hardware uses) and resource (focusing on information processing capacity of a computer) literacies. Cultural literacy was emphasized as a vital element for functioning in an intercultural team on a digital project.

Disciplinary literacy (n = 4) was referring to utilizing different computer programs (n = 2) or technical gadgets (n = 2) with a specific emphasis on required cognitive, affective and psychomotor skills to be able to work in any digital context (n = 3), serving for the using (n = 2), creating and applying (n = 2) digital literacy in real life.

Data literacy, technology literacy and multiliteracy were the third frequent categories (n = 3). The ‘multiliteracy’ was referring to the innate nature of digital technologies, which have been infused into many aspects of human lives.

Last but not least, Internet literacy, mobile literacy, web literacy, new literacy, personal literacy and research literacy were discussed in forty-three article findings. Web literacy was focusing on being able to connect with people on the web (n = 2), discover the web content (especially the navigation on a hyper-textual platform), and learn web related skills through practical web experiences. Personal literacy was highlighting digital identity management. Research literacy was not only concentrating on conducting scientific research ability but also finding available scholarship online.

Twenty-four other categories are unfolded from the results sections of forty-three articles. Table 3 presents the list of these other literacies where the authors sorted the categories in an ascending alphabetical order without any other sorting criterion. Primarily, search, tagging, filtering and attention literacies were mainly underlining their roles in information processing. Furthermore, social-structural literacy was indicated as the recognition of the social circumstances and generation of information. Another information-related literacy was pointed as publishing literacy, which is the ability to disseminate information via different digital channels.

While above listed personal literacy was referring to digital identity management, network literacy was explained as someone’s social networking ability to manage the digital relationship with other people. Additionally, participatory literacy was defined as the necessary abilities to join an online team working on online content production.

Emerging technology literacy was stipulated as an essential ability to recognize and appreciate the most recent and innovative technologies in along with smart choices related to these technologies. Additionally, the critical literacy was added as an ability to make smart judgements on the cost benefit analysis of these recent technologies.

Last of all, basic, intermediate, and advanced digital assessment literacies were specified for educational institutions that are planning to integrate various digital tools to conduct instructional assessments in their bodies.

Major theme 2: competencies

The second major theme was revealed as competencies. The authors directly categorized the findings that are specified with the word of competency. Table 4 summarizes the entire category set for the competencies major theme.

The most common category was the ‘digital competence’ (n = 14) where one of the articles points to that category as ‘generic digital competence’ referring to someone’s creativity for multimedia development (video editing was emphasized). Under this broad category, the following sub-categories were associated:

Problem solving (n = 10)

Safety (n = 7)

Information processing (n = 5)

Content creation (n = 5)

Communication (n = 2)

Digital rights (n = 1)

Digital emotional intelligence (n = 1)

Digital teamwork (n = 1)

Big data utilization (n = 1)

Artificial Intelligence utilization (n = 1)

Virtual leadership (n = 1)

Self-disruption (in along with the pace of digitalization) (n = 1)

Like ‘digital competency’, five additional articles especially coined the term as ‘digital competence as a life skill’. Deeper analysis demonstrated the following points: social competences (n = 4), communication in mother tongue (n = 3) and foreign language (n = 2), entrepreneurship (n = 3), civic competence (n = 2), fundamental science (n = 1), technology (n = 1) and mathematics (n = 1) competences, learning to learn (n = 1) and self-initiative (n = 1).

Moreover, competencies were linked to workplace digital competencies in three articles and highlighted as significant for employability (n = 3) and ‘economic engagement’ (n = 3). Digital competencies were also detailed for leisure (n = 2) and communication (n = 2). Furthermore, two articles pointed digital competencies as an inter-cultural competency and one as a cross-cultural competency. Lastly, the ‘digital nativity’ (n = 1) was clarified as someone’s innate competency of being able to feel contented and satisfied with digital technologies.

Major theme 3: skills

The third major observed theme was ‘skills’, which was dominantly gathered around information literacy skills (n = 19) and information and communication technologies skills (n = 18). Table 5 demonstrates the categories with more than one occurrence.

Table 6 summarizes the sub-categories of the two most frequent categories of ‘skills’ major theme. The information literacy skills noticeably concentrate on the steps of information processing; evaluation (n = 6), utilization (n = 4), finding (n = 3), locating (n = 2) information. Moreover, the importance of trial/error process, being a lifelong learner, feeling a need for information and so forth were evidently listed under this sub-category. On the other hand, ICT skills were grouped around cognitive and affective domains. For instance, while technical skills in general and use of social media, coding, multimedia, chat or emailing in specific were reported in cognitive domain, attitude, intention, and belief towards ICT were mentioned as the elements of affective domain.

Communication skills (n = 9) were multi-dimensional for different societies, cultures, and globalized contexts, requiring linguistic skills. Collaboration skills (n = 9) are also recurrently cited with an explicit emphasis for virtual platforms.

‘Ethics for digital environment’ encapsulated ethical use of information (n = 4) and different technologies (n = 2), knowing digital laws (n = 2) and responsibilities (n = 2) in along with digital rights and obligations (n = 1), having digital awareness (n = 1), following digital etiquettes (n = 1), treating other people with respect (n = 1) including no cyber-bullying (n = 1) and no stealing or damaging other people (n = 1).

‘Digital fluency’ involved digital access (n = 2) by using different software and hardware (n = 2) in online platforms (n = 1) or communication tools (n = 1) or within programming environments (n = 1). Digital fluency also underlined following recent technological advancements (n = 1) and knowledge (n = 1) including digital health and wellness (n = 1) dimension.

‘Social intelligence’ related to understanding digital culture (n = 1), the concept of digital exclusion (n = 1) and digital divide (n = 3). ‘Research skills’ were detailed with searching academic information (n = 3) on databases such as Web of Science and Scopus (n = 2) and their citation, summarization, and quotation (n = 2).

‘Digital teaching’ was described as a skill (n = 2) in Table 4 whereas it was also labelled as a competence (n = 1) as shown in Table 3 . Similarly, while learning to learn (n = 1) was coined under competencies in Table 3 , digital learning (n = 2, Table 4 ) and life-long learning (n = 1, Table 5 ) were stated as learning related skills. Moreover, learning was used with the following three terms: learning readiness (n = 1), self-paced learning (n = 1) and learning flexibility (n = 1).

Table 7 shows other categories listed below the ‘skills’ major theme. The list covers not only the software such as GIS, text mining, mapping, or bibliometric analysis programs but also the conceptual skills such as the fourth industrial revolution and information management.

Major theme 4: thinking

The last identified major theme was the different types of ‘thinking’. As Table 8 shows, ‘critical thinking’ was the most frequent thinking category (n = 4). Except computational thinking, the other categories were not detailed.

Computational thinking (n = 3) was associated with the general logic of how a computer works and sub-categorized into the following steps; construction of the problem (n = 3), abstraction (n = 1), disintegration of the problem (n = 2), data collection, (n = 2), data analysis (n = 2), algorithmic design (n = 2), parallelization & iteration (n = 1), automation (n = 1), generalization (n = 1), and evaluation (n = 2).

A transversal analysis of digital literacy categories reveals the following fields of digital literacy application:

Technological advancement (IT, ICT, Industry 4.0, IoT, text mining, GIS, bibliometric analysis, mapping data, technology, AI, big data)

Networking (Internet, web, connectivity, network, safety)

Information (media, news, communication)

Creative-cultural industries (culture, publishing, film, TV, leisure, content creation)

Academia (research, documentation, library)

Citizenship (participation, society, social intelligence, awareness, politics, rights, legal use, ethics)

Education (life skills, problem solving, teaching, learning, education, lifelong learning)

Professional life (work, teamwork, collaboration, economy, commerce, leadership, decision making)

Personal level (critical thinking, evaluation, analytical thinking, innovative thinking)

This systematic review on digital literacy concentrated on forty-three articles from the databases of WoS/Clarivate Analytics, Proquest Central, Emerald Management Journals, Jstor Business College Collections and Scopus/Elsevier. The initial results revealed that there is an increasing trend on digital literacy focused academic papers. Research work in digital literacy is critical in a context of disruptive digital business, and more recently, the pandemic-triggered accelerated digitalisation (Beaunoyer, Dupéré & Guitton, 2020 ; Sousa & Rocha 2019 ). Moreover, most of these papers were employing qualitative research methods. The raw data of these articles were analysed qualitatively using systematic literature review to reveal major themes and categories. Four major themes that appeared are: digital literacy, digital competencies, digital skills and thinking.

Whereas the mainstream literature describes digital literacy as a set of photo-visual, real-time, information, branching, reproduction and social-emotional thinking (Eshet-Alkalai, 2012 ) or as a set of precise specific operations, i.e., finding, consuming, creating, communicating and sharing digital content (Heitin, 2016 ), this study reveals that digital literacy revolves around and is in connection with the concepts of computer literacy, media literacy, cultural literacy or disciplinary literacy. In other words, the present systematic review indicates that digital literacy is far broader than specific tasks, englobing the entire sphere of computer operation and media use in a cultural context.

The digital competence yardstick, DigComp (Carretero, Vuorikari & Punie, 2017 ) suggests that the main digital competencies cover information and data literacy, communication and collaboration, digital content creation, safety, and problem solving. Similarly, the findings of this research place digital competencies in relation to problem solving, safety, information processing, content creation and communication. Therefore, the findings of the systematic literature review are, to a large extent, in line with the existing framework used in the European Union.

The investigation of the main keywords associated with digital skills has revealed that information literacy, ICT, communication, collaboration, digital content creation, research and decision-making skill are the most representative. In a structured way, the existing literature groups these skills in technological, cognitive, and social (Ng, 2012 ) or, more extensively, into operational, formal, information Internet, strategic, communication and content creation (van Dijk & van Deursen, 2014 ). In time, the literature has become richer in frameworks, and prolific authors have improved their results. As such, more recent research (vaan Laar et al., 2017 ) use the following categories: technical, information management, communication, collaboration, creativity, critical thinking, and problem solving.

Whereas digital thinking was observed to be mostly related with critical thinking and computational thinking, DigComp connects it with critical thinking, creativity, and innovation, on the one hand, and researchers highlight fake news, misinformation, cybersecurity, and echo chambers as exponents of digital thinking, on the other hand (Sulzer, 2018 ; Puig, Blanco-Anaya & Perez-Maceira, 2021 ).

This systematic review research study looks ahead to offer an initial step and guideline for the development of a more contemporary digital literacy framework including digital literacy major themes and factors. The researchers provide the following recommendations for both researchers and practitioners.

Recommendations for prospective research

By considering the major qualitative research trend, it seems apparent that more quantitative research-oriented studies are needed. Although it requires more effort and time, mixed method studies will help understand digital literacy holistically.

As digital literacy is an umbrella term for many different technologies, specific case studies need be designed, such as digital literacy for artificial intelligence or digital literacy for drones’ usage.

Digital literacy affects different areas of human lives, such as education, business, health, governance, and so forth. Therefore, different case studies could be carried out for each of these unique dimensions of our lives. For instance, it is worth investigating the role of digital literacy on lifelong learning in particular, and on education in general, as well as the digital upskilling effects on the labour market flexibility.

Further experimental studies on digital literacy are necessary to realize how certain variables (for instance, age, gender, socioeconomic status, cognitive abilities, etc.) affect this concept overtly or covertly. Moreover, the digital divide issue needs to be analysed through the lens of its main determinants.

New bibliometric analysis method can be implemented on digital literacy documents to reveal more information on how these works are related or centred on what major topic. This visual approach will assist to realize the big picture within the digital literacy framework.

Recommendations for practitioners

The digital literacy stakeholders, policymakers in education and managers in private organizations, need to be aware that there are many dimensions and variables regarding the implementation of digital literacy. In that case, stakeholders must comprehend their beneficiaries or the participants more deeply to increase the effect of digital literacy related activities. For example, critical thinking and problem-solving skills and abilities are mentioned to affect digital literacy. Hence, stakeholders have to initially understand whether the participants have enough entry level critical thinking and problem solving.

Development of digital literacy for different groups of people requires more energy, since each group might require a different set of skills, abilities, or competencies. Hence, different subject matter experts, such as technologists, instructional designers, content experts, should join the team.

It is indispensably vital to develop different digital frameworks for different technologies (basic or advanced) or different contexts (different levels of schooling or various industries).

These frameworks should be updated regularly as digital fields are evolving rapidly. Every year, committees should gather around to understand new technological trends and decide whether they should address the changes into their frameworks.

Understanding digital literacy in a thorough manner can enable decision makers to correctly implement and apply policies addressing the digital divide that is reflected onto various aspects of life, e.g., health, employment, education, especially in turbulent times such as the COVID-19 pandemic is.

Lastly, it is also essential to state the study limitations. This study is limited to the analysis of a certain number of papers, obtained from using the selected keywords and databases. Therefore, an extension can be made by adding other keywords and searching other databases.

Availability of data and materials

The authors present the articles used for the study in “ Appendix A ”.

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Americans fall along a spectrum of preparedness when it comes to using tech tools to pursue learning online, and many are not eager or ready to take the plunge

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• 1. The meaning of digital readiness
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• 3. Greater digital readiness translates to higher level of use of technology in learning
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For many years concerns about “digital divides” centered primarily on whether people had access to digital technologies. Now, those worried about these issues also focus on the degree to which people succeed or struggle when they use technology to try to navigate their environments, solve problems, and make decisions. A recent Pew Research Center report showed that adoption of technology for adult learning in both personal and job-related activities varies by people’s socio-economic status, their race and ethnicity, and their level of access to home broadband and smartphones. Another report showed that some users are unable to make the internet and mobile devices function adequately for key activities such as looking for jobs .

In this report, we use newly released Pew Research Center survey findings to address a related issue: digital readiness. The new analysis explores the attitudes and behaviors that underpin people’s preparedness and comfort in using digital tools for learning as we measured it in a survey about people’s activities for personal learning .

Specifically, we assess American adults according to five main factors: their confidence in using computers, their facility with getting new technology to work, their use of digital tools for learning, their ability to determine the trustworthiness of online information, and their familiarity with contemporary “education tech” terms. It is important to note that the findings here just cover people’s learning activities in digital spaces and do not address the full range of important things that people can do online or their “readiness” to perform them.

To better understand the way in which different groups of Americans line up when it comes to digital readiness, researchers used a statistical technique called cluster analysis that places people into groups based on similarities in their answers to key questions.

The analysis shows there are several distinct groups of Americans who fall along a spectrum of digital readiness from relatively more prepared to relatively hesitant. Those who tend to be hesitant about embracing technology in learning are below average on the measures of readiness, such as needing help with new electronic gadgets or having difficulty determining whether online information is trustworthy. Those whose profiles indicate a higher level of preparedness for using tech in learning are collectively above average on measures of digital readiness.

Relatively Hesitant – 52% of adults in three distinct groups. This overall cohort is made up of three different clusters of people who are less likely to use digital tools in their learning. This has to do, in part, with the fact that these groups have generally lower levels of involvement with personal learning activities. It is also tied to their professed lower level of digital skills and trust in the online environment.

• A group of 14% of adults make up The Unprepared . This group has both low levels of digital skills and limited trust in online information. The Unprepared rank at the bottom of those who use the internet to pursue learning, and they are the least digitally ready of all the groups.
• We call one small group Traditional Learners, and they make up of 5% of Americans. They are active learners, but use traditional means to pursue their interests. They are less likely to fully engage with digital tools, because they have concerns about the trustworthiness of online information.
• A larger group, The Reluctant, make up 33% of all adults. They have higher levels of digital skills than The Unprepared, but very low levels of awareness of new “education tech” concepts and relatively lower levels of performing personal learning activities of any kind. This is correlated with their general lack of use of the internet in learning.

Relatively more prepared – 48% of adults in two distinct groups. This cohort is made up of two groups who are above average in their likeliness to use online tools for learning.

• A group we call Cautious Clickers comprises 31% of adults. They have tech resources at their disposal, trust and confidence in using the internet, and the educational underpinnings to put digital resources to use for their learning pursuits. But they have not waded into e-learning to the extent the Digitally Ready have and are not as likely to have used the internet for some or all of their learning.
• Finally, there are the Digitally Ready . They make up 17% of adults, and they are active learners and confident in their ability to use digital tools to pursue learning. They are aware of the latest “ed tech” tools and are, relative to others, more likely to use them in the course of their personal learning. The Digitally Ready, in other words, have high demand for learning and use a range of tools to pursue it – including, to an extent significantly greater than the rest of the population, digital outlets such as online courses or extensive online research.

There are several important qualifying notes to sound about this analysis. First, the research focuses on a particular activity – online learning. The findings are not necessarily projectable to people’s capacity (or lack of capacity) to perform health-related web searches, use mobile apps for civic activities, or use smartphones to apply for a job.

Second, while there are numerical descriptions of the groups, there is some fluidity in the boundaries of the groups. Unlike many other statistical techniques, cluster analysis does not require a single “correct” result. Instead, researchers run numerous versions of it (e.g., asking it to produce different numbers of clusters) and judge each result by how analytically practical and substantively meaningful it is. Fortunately, nearly every version produced had a great deal in common with the others, giving us confidence that the pattern of divisions were genuine and that the comparative shares of those who were relatively ready and not ready each constituted about half of Americans.

Third, it is important to note that the findings represent a snapshot of where adults are today in a fairly nascent stage of e-learning in society. The groupings reported here may well change in the coming years as people’s understanding of e-tools grows and as the creators of technology related to e-learning evolve it and attempt to make it more user friendly.

Even allowing for those caveats, the findings add additional context to insights about those who pursue personal learning activities. Although factors such as educational attainment or age might influence whether people use digital tools in learning, other things such as people’s digital skills and their trust in online information may also loom large. These “readiness” factors, separate and apart from demographic ones, are the focus in this report.

The results are also significant in light of Americans’ expressed interest in learning and personal growth. Most Americans said in the Center survey that they like to look for opportunities to grow as people: 58% said this applies to them “very well” and another 31% said it applies to them “somewhat well.” Additionally, as they age, many Americans say they hope to stay active and engaged with the world .

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Analysis of the impact of digital literacy on life satisfaction (2019–2022) for older adults in South Korea: a national community-based panel study

• Hocheol Lee 1  

Scientific Reports volume  14 , Article number:  20399 ( 2024 ) Cite this article

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This study analyzed the effects of digital literacy on life satisfaction in older adults aged 65 years and above in modern day Korea. It utilized raw data from the 2019–2022 Report on the Digital Divide, an annual survey conducted by the Korean Ministry of Science and Information and Communications Technology. A total of 4,216 participants were assessed from 2019–2022. Correlation between digital literacy and life satisfaction was analyzed using Pearson correlation analysis and polynomial linear regression analysis. Life satisfaction was significantly positively correlated with digital access, digital competency, and digital utilization in all the years. In 2019, participants’ life satisfaction score rose significantly by 0.15 with every one-point increase in digital competency. It further rose by 0.035 in 2020, 0.030 in 2021, and 0.116 in 2022. Digital literacy was consistently positively correlated with life satisfaction in each year from 2019–2022. Of the three main elements, digital competency had the strongest impact and digital information, income, and education level also significantly impacted life satisfaction. While digital competency improved steadily from 2019 to 2022, it remains below 50% for Korea’s older adult population. Further efforts are required to improve digital competency and subsequent life satisfaction among Korea’s older adult population.

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Introduction.

Given tremendous global advances in healthcare, the world’s older adult population (≥ 65 years) is projected to double from 727 million (9.3%) in 2020 to 1.5 billion (16.0%) by 2050 1 . In response to population aging, the World Health Organization (WHO) announced the "Decade of Healthy Ageing: Plan of Action," which emphasizes the importance of narrowing the digital divide to facilitate the increased use of digital technology among older adults. This is viewed as key to promote healthy aging 2 . The WHO has also highlighted the need to plan and implement health policies that promote successful aging using digital technology, and to develop suitable health policies adapted to aging in the digital era 3 . Ensuring that older adults have access to new digital technologies and diverse sources of information is beneficial to promoting successful aging. However, globally some older adults face challenges in utilizing digital technology due to their low levels of digital literacy 4 , 5 , 6 .

Literacy is defined as the understanding and skills in reading, writing, and arithmetic, collectively known as the 'three Rs'. Building on this foundation, an individual’s literacy is crucial for effective participation in social communications and decision-making processes, making it an essential competence for social engagement 7 . In the digital era, digital literacy is increasingly emphasized. Digital literacy is defined the ability to effectively use digital technologies based on upon the traditional competencies known as the 'three Rs'—reading, writing, and arithmetic. Specifically, digital literacy is also defined the capacity to search, evaluate, utilize, share, and create content through digital technologies using the internet and smartphone. Digital literacy enables social communication and activities through the use of digital tools such as smartphones, social media platforms, and other digital devices 8 . Digital literacy is essential for correctly managing the vast amounts of information available in the digital age and facilitating social activities.South Korea is projected to become the world’s first super-aged society 9 with older adults accounting for more than 20% of the population by 2025. This will create societal issues, including a reduction in the economically active population and an increased burden on primary care, additional strain on national health insurance funds, greater social isolation, and heightened demands for social caregiving 10 . The Korean government officially launched its digital government strategy in 2021 with a vision to progressively digitalize society. Various informatization policies were announced to address population aging, with a focus on reducing the digital divide affecting older adults.

As digital technologies continue to advance, demand for digital technology and digital literacy has increased. Previous studies have reported that digital literacy is associated with a range of health determinants 11 , especially with social satisfaction. As access to various social activities and information has become digitalized, individuals with lower digital literacy engage in less social activities, which leads to reduced life satisfaction 12 . Moreover, the outbreak of COVID-19 in 2019 accelerated the process of informatization globally, with most aspects of social communications, health information, and administrative services having transitioned to digital systems. The digitalization of social services has further widened the digital divide, decreasing access to information, and increasing social loneliness, thereby diminishing life satisfaction 13 . Particularly in South Korea, which is among the OECD countries experiencing rapid digital transformation, the digital gap among the elderly is increasing annually 14 . This digital gap impacts life satisfaction and it is further related to successful aging. Therefore, the capability of the elderly to utilize digital technologies is becoming an essential societal requirement in the digital era 15 .

Among older adults, life satisfaction increases in parallel with digital information level. People with higher digital literacy have access to more diverse information with the ability to engage in social communications offering significant psychological benefits 16 . High digital literacy also helps to alleviate social loneliness among older adults with diminished physical functioning, thus potentially boosting their overall life satisfaction 17 , 18 . Therefore, in contemporary Korean society, having high digital literacy is expected to enhance life satisfaction among older adults.

This study aimed to investigate the effects of digital literacy on life satisfaction among older adults in Korea’s increasingly digitalized and aging society. Therefore, this study analyzed the association between digital literacy and life satisfaction, with specific reference to the older adult population.

Study design

This community-based panel study examined the correlation between digital literacy and life satisfaction among the older adult population in Korea and identified associated factors.

Data collection

Raw data on older adults aged 65 years and above from the 2019–2022 Report on the Digital Divide, an annual survey conducted by the Korean Ministry of Science and Information and Communications Technology (MSIT), were used for this study. Data were collected through a structured questionnaire interview format from September to December across each of the four years covered by the report. A representative sample was obtained via proportional stratified probability sampling in terms of region, sex, age, and estimates of standard error for the parameters of each stratum. The questionnaire was administered by trained surveyors from a professional survey company, and the data was de-identified for analysis according to the Personal Information Protection Act. Data from a total of 4,216 participants—1,089 in 2019, 1,150 in 2020, 807 in 2021, and 1,170 in 2022—were included in the final analysis.

Instruments

To measure digital literacy, participants’ level of “digital access,” “digital competency,” and “digital utilization” were assessed. Participants’ demographics and “satisfaction with daily life” were also included in the analysis. The questionnaire was developed by a panel of experts covering several fields of study at the MSIT and National Information Society Agency including IT, healthcare, and digital technology. The questionnaire possessed significant internal reliability as evidenced by a Cronbach’s α of 0.966.

• Digital access

Digital access was assessed using four items: desktop computer ownership, laptop ownership, smartphone ownership, and internet access at home (1 for yes, 0 for no).

• Digital competency

Digital competency was assessed using 14 items across two domains: personal computer (PC) competency and mobile device competency. PC competency was measured through items pertaining to software installation, connecting to the internet, connecting to a web browser, connecting an external drive, sending files, dealing with malicious codes, and creating documents. Mobile device competency was assessed using items pertaining to manipulating settings, using wireless internet, sending files, sending pictures, installing apps, dealing with malicious codes in smartphones, and creating documents. Each item was rated on a four-point Likert scale ranging from 1 “Strongly disagree” to 4 “Strongly agree.” The scores were converted to a 100-point scale score.

• Digital utilization

Digital utilization was assessed using 50 items covering wired and mobile internet utilization, diversity of digital services utilized, and advanced internet utilization. Wired and mobile internet utilization was assessed in terms of frequency, and the diversity of digital services utilized including the internet for information searches, e-mail, messengers, social media, education, internet searches, blogs, online communities, booking transportation, financial services, administrative services, cloud services, and making appointments. Advanced internet utilization was assessed in terms of producing and sharing information, networking, social involvement, and economic activities. Each item was rated on a four-point Likert scale from 1 “Do not use at all” to 4 “Use frequently.” The scores were converted to a 100-point scale score.

Satisfaction with daily life

Satisfaction with daily life was defined as the participants’ level of satisfaction with recreational and cultural activities, financial status, social activities, interpersonal relationships, family relationships, work, physical and mental health, and political activities using a four-point Likert scale. The scores were converted to a 100-point scale score.

Participant demographics

Participant demographics included sex (male, female), age (≥ 65 years), education level (no education, elementary school, middle school, college or higher), disability (yes, no), household size (1, ≥ 2), and income (quintiles). The actual questionnaire (Korean) is attached in Appendix 1 (Table 1 ).

To analyze the effects of digital literacy on life satisfaction in older adults aged ≥ 65, the collected data (2019–2022) were analyzed using SPSS 25.0 software as follows: First, the correlation between digital literacy and life satisfaction was analyzed using Pearson correlation coefficients. Digital literacy was categorized into digital access, digital competency, and digital utilization.

Second, the results were analyzed using stepwise polynomial linear regression. The dependent variable was set to life satisfaction, and the independent variables were set to participant demographics, digital access, digital competency, and digital utilization. The fit of the regression model was assessed based on the F value derived from an analysis of variance. The percentage of variance of the dependent variable explained by the independent variable was determined using the R-squared (R 2 ) value.

Ethical considerations

This study was conducted in accordance with the Declaration of Helsinki and under the review and approval of the Institutional Research Ethics Committee of the Yonsei University Institutional Review Board, Wonju city, South Korea (No. 1041849-202,109-SB-146–01). All procedures were conducted following the relevant institutional guidelines and regulations. Informed consent was obtained from all participants or their legal guardians prior to their involvement in the study.

A total of 4,216 participants—1,089 in 2019, 1,150 in 2020, 807 in 2021, and 1,170 in 2022—were included in the analysis (Table 2 ). There were more female than male participants in each of these years: 59.9% in 2019, 56.9% in 2020, 50.8% in 2021, and 52.8% in 2022. The most common age groups were 70–74 years in 2019 (37.9%) and 65–69 years in 2020 (33.0%), 2021 (42.6%), and 2022 (41.6%). The most common education level was elementary school or lower (36.37%) in 2019 and high school in 2020 (58.5%), 2021 (39.2%), and 2022 (37.4%).

The mean digital access score was 27.4 in 2019, 24.4 in 2020, 44.4 in 2021, and 57.2 in 2022, showing an increasing trend over the years. The mean digital competency score was 37.6 in 2019, 39.9 in 2020, 46.1 in 2021, and 42.1 in 2022. The mean digital utilization score was 33.2 in 2019, 33.6 in 2020, 36.8 in 2021, and 62.3 in 2022.

Correlation between digital literacy and life satisfaction

The correlation between digital literacy and life satisfaction was analyzed using Pearson correlation analysis (Table 3 ). Digital literacy was divided into digital access, competency, and utilization, and the correlation of each of these aspects with life satisfaction were analyzed. In 2019, life satisfaction was found to be significantly positively correlated (weak) with digital access (γ = 0.265**), digital competency (γ = 0.316**), and digital utilization (γ = 0.205**).

In 2020, life satisfaction was significantly positively correlated (weak) with digital access (γ = 0.260**), digital competency (γ = 0.360**), and digital utilization (γ = 0.258**).

In 2021, life satisfaction was significantly positively correlated (weak) with digital access (γ = 0.171**), digital competency (γ = 0.311**), and digital utilization (γ = 0.341**).

In 2022, life satisfaction was significantly positively correlated (weak) with digital access (γ = 0.150**), digital competency (γ = 0.307**), and digital utilization (γ = 0.242**).

Regression analysis

Polynomial linear regression analysis was performed to examine the effects of digital literacy on life satisfaction (Table 4 ). The polynomial linear regression model had a good fit in 2019 (F = 4.055, p  < 0.001), 2020 (F = 6.585, p  < 0.001), 2021 (F = 22.178, p  < 0.001), and 2022 (F = 8.054, p  < 0.001).

In 2019, the life satisfaction score was significantly higher, by 3.343, among participants with an income of 2–2.99 million KRW as compared to participants with an income of ≤ 1 million KRW ( β  = 3.343, p  = 0.047). The life satisfaction score rose significantly by 0.033 with every one-point increase in the digital access score ( β  = 0.033, p  = 0.031). Furthermore, the life satisfaction score also rose significantly by 0.15 with every one-point increase in digital competency ( β  = 0.150, p  < 0.001).

In 2020, the life satisfaction score was significantly lower, by 1.203, among participants aged 80 years and over as compared to those aged 65–69 years (β = -1.203, p  = 0.029). Furthermore, life satisfaction rose significantly by 0.035 with every one-point increase in digital competency ( β  = 0.035, p  = 0.006).

In 2021, the life satisfaction score was significantly higher, by 1.786, among participants aged 70–74 years as compared to those aged 65–69 years ( β  = 1.786, p  = 0.013), and significantly higher again, by 3.946, among those aged 80 years and over as compared to those aged 65–69 years ( β  = 3.946, p  = 0.013). In terms of income (ref < 1 million KRW), life satisfaction was significantly higher, by 5.242, among participants with an income of 1–1.99 million KRW ( β  = 5.242, p  < 0.001), 7.518 among those with an income of 2–2.99 million KRW ( β  = 7.518, p  < 0.001), 8.046 among those with an income of 3–3.99 million KRW ( β  = 8.046, p  < 0.001), and 9.376 among those with an income of 4 million KRW ( β  = 9.376, p  < 0.001). Life satisfaction rose significantly by 0.143 with every one-point increase in digital access ( β  = 0.143, p  < 0.001). Life satisfaction rose significantly by 0.030 with every one-point increase in digital competency ( β  = 0.030, p  < 0.001), and by 0.136 with every one-point increase in digital utilization ( β  = 0.42, p  < 0.001).

In 2022, the life satisfaction score was significantly higher, by 4.637, among those aged 80 years and over as compared to those aged 65–69 years ( β  = 4.637, p  = 0.033). With reference to individuals with elementary school education or lower, the life satisfaction score was significantly higher, by 2.550, among those with a middle school level education ( β  = 2.550, p  = 0.023), 3.559 among those with high school education ( β  = 3.559, p  = 0.002), and 8.893 among those with college education ( β  = 8.893, p  < 0.001). Furthermore, life satisfaction significantly rose by 0.116 with every one-point increase in digital competency ( β  = 0.116, p  < 0.001).

South Korea is projected to become the world’s first super-aged society by 2025. In this context, the digital literacy of older adults is an increasingly relevant societal issue. Several studies have shown that digital literacy is associated with a number of key quality life indicators, including health issues, social isolation, social activities, and communication, and thus has a significant impact on overall life satisfaction 19 . Accordingly, this study investigated the effects of digital literacy on life satisfaction among older adults in Korea. The key findings are discussed below.

First, digital literacy was positively correlated with life satisfaction throughout the period 2019 to 2021. Successful aging and life satisfaction are particularly relevant in an aging society. In modern Korean society, many social activities and services have been digitalized, and digital access, competency, and utilization are essential for engaging in and utilizing these activities/services. In other words, older adults can access a range of social services if they possess a higher digital literacy, which ultimately increases their overall life satisfaction. Previous studies have reported that digital literacy is an important predictor of healthy aging in older adults aged 65 years and over in Korea and has a positive impact on depressive mood, quality of life, and cognitive functioning 19 , 20 , 21 . Moreover, digital literacy is also likely to determine older adults’ degree of daily communication, such as smartphone usage to keep in touch with family 22 , 23 . Digital literacy among the elderly can be utilized not only for communication with family but also among seniors themselves. A notable example is South Korea's senior-senior caregiving program. In this program, younger seniors care for older seniors. If interactions between the elderly are conducted both face-to-face and via digital devices, a sustainable caregiving program can be achieved. Moreover, if the caregiving program can continue remotely, it is expected to significantly reduce social isolation 24

Second, among the various aspects of digital literacy analyzed in this study, digital competency had the greatest impact on life satisfaction by a significant degree. The Korean government launched a digital government platform in 2022 and is transitioning various governmental services to it. Welfare and financial aid services have already been entirely digitalized, from the commencement of the application process through to disbursement. Such digitalization increases the barriers to government services for older adults who are not familiar with digital devices. A previous study reported that poor access to government policies and services and failure to receive the desired service induces social deprivation and is likely to result in poor life satisfaction 25 . To enhance the ability to use digital platforms effectively, it is necessary to boost public awareness through social campaigns. The Korean government has identified population groups with information vulnerability and provides digital education and easy-access smartphone education to enhance digital competency and reduce the digital divide 26 . The South Korean government, through local governments, has established regional digital education centers to provide digital education to the elderly. In particular, senior welfare centers serve as these digital education hubs, and seniors who have received digital competency training experience an improvement in their quality of life. However, seniors who have limited physical access to these digital hubs face an increasing digital divide, which in turn lowers their quality of life. Therefore, policies that improve accessibility to digital education centers need to be developed and implemented in the future 27 . Given these initiatives, information competency among older adults has continuously improved in South Korea since 2019. However, the number of older adults who are digitally literate remains below 50%, indicating the clear need for further digital competency education initiatives.

Third, digital literacy was identified as a key predictor of life satisfaction in 2021. In 2020, senior centers and cultural facilities were closed in Korea due to the restrictions implemented during the COVID-19 pandemic, with most social activities transitioned to virtual platforms. In 2020, the Korea Institute for Health and Social Affairs conducted a questionnaire survey of 1,500 older adults regarding the impact of COVID-19 on their lives. The results showed that more than 80% of the participants refrained from meeting family or friends, attending social gatherings or religious meetings, using public facilities, or engaging in recreational activities, while more than 30% refrained from hospital visits. Furthermore, 96.1% of older adult participants stated that they had increased or experienced no change in their smartphone usage. 28 . During the COVID-19 pandemic, the Korean government disseminated information about COVID-19, health risks, and epidemiology data to the public via smartphones. Consequently, older adults, considered a vulnerable population in terms of information access, are speculated to have experienced a decreased quality of life given the limited access to information and closures of public facilities. The digital literacy gap among the elderly is growing. In this situation, we need to provide programs tailored to the level and intended use of digital literacy for the elderly. Since digital information has a vast range and variety, it is important to develop customized programs and deliver them to the right people. Particularly for the elderly, the adoption of digital platforms for telemedicine consultations and the receipt of prescriptions via mail delivery are increasingly prevalent globally. This widespread implementation of digital healthcare services underscores the essential role of digital literacy among older adults. Such literacy significantly influences their ability to leverage these technologies, which in turn markedly affects their overall life satisfaction 29 .Fourth, in 2021 and 2022, income had a significant effect on life satisfaction. The disruption created by the COVID-19 pandemic led to an economic recession, with older adults particularly vulnerable 30 . Financial difficulties, in turn, affected daily living, subsequently leading to a deterioration in older adults’ overall life satisfaction 31 .

Fifth, in contrast to other years, education level had a significant impact on life satisfaction in 2022. With the declaration of the COVID-19 pandemic, the Korean government digitalized various government-provided services and many public and private agencies provided digital education for older adults, the effectiveness of which was higher in older adults with higher levels of education 20 . Enhancing these individuals’ level of digital access boosted their life satisfaction.

This study has several limitations. First, the data used for analysis was obtained from annual community-based panel surveys conducted from 2019 to 2022. However, as the panel surveys did not remain the same each year, it was difficult to analyze individual-level trends. 32 . Second, this study was based on secondary data with a nationally representative sample, therefore sampling error was a risk.

Conclusions

As South Korea acknowledges the prospect of becoming a super-aged society in the digital era, the digital competency of the country’s older adults is an urgent societal issue. This is evident by the Korean government’s decision to launch a digital government platform in 2021 and to provide digitalized policies, services, and financial support. While this transition has made digital literacy an essential consideration for older adults in everyday life, the digital divide is steadily widening.

The effect of digital literacy on life satisfaction of older adults was assessed during a four-year period from 2019–2022. The findings indicate that life satisfaction increased in parallel with individuals’ digital literacy. This suggests that the government must provide better digital education for older adults. Although digital education is currently provided at public senior welfare facilities, policies that obligate public facilities to screen for and cater to the education of medically vulnerable populations should also be devised.

Second, older adults’ digital competency improved steadily from 2019 to 2022, but remains below 50%. This low competency score, despite the increases in digital device penetration, internet technology, and governmental policy support, highlights the need for a more novel approach. For instance, the senior-senior care program implemented in Korea has had a tremendous impact on promoting emotional growth and successful socialization among older adults. Thus, it may prove beneficial to link older adults who have a competent level of digital literacy with others who do not(called digital senior-senior care services).

Data availability

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Acknowledgements

This research was supported by Regional Innovation Strategy through the National Research Foundation of Korea funded by the Ministry of Education (2022RIS-005), and by the National Research Foundation of Korea grant funded by the Korea government (No. 2021R1C1C2005464).

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Lee, H. Analysis of the impact of digital literacy on life satisfaction (2019–2022) for older adults in South Korea: a national community-based panel study. Sci Rep 14 , 20399 (2024). https://doi.org/10.1038/s41598-024-71397-0

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Digital literacy, technological literacy, and internet literacy as predictors of attitude toward applying computer-supported education

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Even though there is an abundance of research on computer supported education (CSE), digital literacy (DL), technological literacy (TL), and internet literacy (IL), the correlation between them and their effect on each other have not been analyzed in the literature. However, no study has been conducted on the correlation between and effect of CSE, DL, TL, and IL and which additionally explains their relationship to each other. This study aims to analyze the effect levels among the latent variables of DL, TL, and IL, and the attitude toward applying CSE and these latent variables’ ratios to each other. For this purpose, eight hypotheses were developed after reviewing the literature. A relational descriptive model is used to detect the presence and extent of covariance. The participants of this study were 510 prospective teachers. Exploratory and confirmatory factor analysis of the scales were performed. The hypotheses of the research were tested with the structural equation model. As a result, it was revealed that DL, TL, and IL together significantly affect and explain the attitude towards CSE. Different suggestions have been developed based on the results of the research.

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1 Introduction

With the rapid acceleration of the technological developments in the world and the advent of the COVID-19 pandemic, the needs, learning perspectives, learning styles, and habits of today’s learners have changed and reshaped. Educators started to search for alternative methods to meet new learning needs in the technology age, and developing technologies have started to be used predominantly in learning environments including higher education (Darling-Hammond & Hyler, 2020 ; García-Peñalvo et al., 2021 ; Hadar et al., 2020 ). Research reveal that using technology-based teaching tools affect teachers’ successful teaching performances (Hatlevik & Hatlevik, 2018 ; Howard et al., 2020 ). Therefore, examining the factors explaining teachers’ technology integration in classrooms took considerable attention in the literature (Scherer et al., 2019 ), and provided a deeper understanding of the new roles, skills, and attitudes in the learning environments (Fraillon et al., 2014 ).

Using these new technologies in learning environments necessitates acquiring twenty-first Century skills including information, media, and information, communications, and technology (ICT) literacies (World Economic Forum, 2016 ). Since learning through the use of new technologies generally takes place in online environments (Kukulska-Hulme & Traxler, 2007 ), computer-supported education (CSE), which necessitates digital skills and new literacies, has started to be used more and more. As a result, new learners of the technology age need to improve new literacy skills such as digital, technological, and Internet literacy skills to keep up with the new requirements of CSE. Hence, it is thought that the relationship between digital literacy (DL), technological literacy (TL), Internet literacy (IL), and attitude toward applying CSE should be dwelt upon.

The purpose of this study was to analyze the effect of DL, TL, and IL level on attitude toward CSE, their explaining ratio, and their statistical significance. This study’s biggest difference from similar studies in the literature is that there is no study conducted on the link between them, the effect of DL, TL, and IL, the attitude toward CSE, and their explaining ratio to each other. For this reason, it is essential to determine which variables affect prospective teachers’ attitudes toward CSE and to what extent changes in these attitudes are explained under which variables, and to present a strong model.

2 Theoretical frameworks

Research have shown that developing technologies have started to be used predominantly in education. In recent studies on the teachers, prospective teachers, and CSE, a positive and significant relationship between academic success and the use of computers is reported (Akdeniz et al., 2017 ; Åžakar et al., 2016 ; Backer et al., 2022 ; Berkant, 2016 ). Since using CSE necessitates acquiring and improving new literacies, the most significant aspects that affect the attitudes toward CSE and new literacy skills will be explained in this section.

2.1 Computer-supported education

Computers and related new technologies have become one of the most important means of education, efficient learning, and teaching in the technology age. In the literature, there are several terms related to the usage of computers in learning. Some of them are Computer Assisted Learning, Computer-Based Instruction, Computer-Aided Learning, and Computer Aided Instruction, which are also used instead of CSE (Schittek et al., 2001 ). In CSE, a computer is used as a helpful tool for educators to enrich learning and teaching activities and improve their quality. In this study, CSE has been handled as an inclusive term for the above-mentioned ones.

The computer can be used for multiple purposes in the classroom including helping students in their learning process. Since CSE is using a computer to facilitate learning (Sharma, 2017 ), improve the learning and teaching process (Arslan, 2006 ), and combine learning principles with computer technologies (Uşun, 2000 ; Amiel, 2006 ), it uses different practices, simulations, and approaches to deliver knowledge and does assessments. Aktürk et al. ( 2008 ) defined CSE as the whole of the activities designed in the computer environment, directed by the teacher, and where the computer plays the role of a rich environment and platform in the learning-teaching process and the activities in which the learners interact. There is plenty of research underlying CSE’s several advantages and its positive effect on learners in cognitive, affective, and psychomotor learning domains and skills (Asrifan et al., 2020 ; Bariham, 2019 ; Berkant, 2016 ; Haseski & İlic, 2020 ; Kan & Yel, 2019 ; Konstantinidou & Scherer, 2022 ; Lieberman & Linn, 1991 ; Lodhi et al., 2019 ; Munoz-Carril et al., 2021 ; Raji, 2019 ; Schacter & Fagnano, 1999 ).

Attitude is defined as the tendency of a person to show positive or negative behavior towards any event, thing, or person (Turgut & Baykul, 2013 ), and it is an element that directly affects the learning process. Attitudes of teachers and prospective teachers towards CSE are one of the most important factors for success in the CSE practice (Chen & Chen, 2012 ; Kutluca & Ekici, 2010 ; Ozdamli & Tavukcu, 2016 ; Yilmaz & Yilmaz, 2022 ). Moreover, it is reported that attitudes are also one of the essential determinants of CSE efficiency (Chen et al., 2018 ; Liaw et al., 2008 ).

2.2 Digital literacy

Literacy refers to a skill that can be improved (Kurudayıoğlu & Tüzel, 2010 ). Therefore, in general terms, literacy is a concept related to the person’s perception and understanding of the life she/he lives and the objects and events in this life, and ascribing meaning to all relationships in her/his social life (Aşıcı, 2009 ). The broad meaning of the concept of literacy is closely related to the contexts in which this concept is articulated. The concept of literacy has been articulated with many concepts such as information, media, communication, science, environment, finance, health, language, culture, civil, visuality, and electronics, and it has taken its place in the literature (Karagülle et al., 2019 ). In addition to these, the articulation of the literacy concept to the digital concept has caused the usage of the “digital literacy” concept; the articulation of it to the technology has caused the usage of the “technology literacy” concept, and the articulation of it to the internet concept has caused the usage of “internet literacy” concept. All these concepts have started to take their place in both the literature and the practice.

Even though the notion of DL is not new, it started to be mentioned in the literature with the work of Gilster ( 1997 ). There are several definitions of DL in the literature. Buckingham ( 2015 ), states that DL is much more than a functional issue, such as learning to use a computer and keyboard or searching online. In other words, DL refers to various competencies related to the skillful use of computers and information technology, not just a functional use of computers. In a more global context, DL is defined as the ability to evaluate information from various sources, assess its trustworthiness and usefulness, and solve tasks by locating information (OECD, 2015 ).

Another perspective underlines the usage and contribution of DL in different areas of life, and the definitions underline this feature of DL. For instance, Huerta and Sandoval-Almazán ( 2007 ), define DL as an ability to assist people in their engagement with social and cultural activities through using several media. In a general sense, a person with DL can search and understand information, and express, share, and understand opinions or thoughts freely (Kwon & Hyun, 2014 as cited in Noh, 2017 ). Fraillon et al. ( 2013 ) had a broader definition of DL. According to their definition, it is an ability to investigate, create, and communicate via using computers to participate effectively in all areas of life including home, school, workplace, and society.

Eshet-Alkalai ( 2004 ) reports that DL consists of five literacies (Photo-visual, reproduction, branching, information, and socio-emotional) that are related to each other. These skills include, respectively, reading or comprehending the graphic and other multimedia information; combining different pieces of information; navigating the range of information; analyzing and evaluating the variety of information; and social sharing of information, adhering to online norms for collaboration and communication on the Internet (Eshet-Alkalai, 2012 ). Consequently, there is a common acknowledgment that DL is an essential competence for learners who are facing the challenging demands (the technological, informational, cognitive, and socio-emotional) of the digital age (List et al., 2020 ).

2.3 Technological literacy

TL is knowing what can be done with the technology, how to use the technology proficiently, and deciding on the type of the technology and the appropriate time/date for usage (Davies, 2011 ). In a pragmatist approach, TL may be defined as the capability to adopt, adapt, invent, and assess technology to affect own life, community, and environment positively (Hansen, 2003 ). In particular, it is using, managing, and evaluating technology for specific objectives (Becker et al., 2010 ; Georgina & Olson, 2008 ). In a broader sense, technologically literate person must attain a certain amount of fundamental knowledge about technology and some basic technical capabilities, such as identifying and fixing simple problems in the technological devices, employing an approach to solve problems, thinking critically about technological matters, and behave in accordance. (Gamire & Pearson, 2006 ).

Based on the relevant literature, Bauer and Ahooei ( 2018 ) defined TL as the capability to use relevant technology for effective and responsible communication, find solutions for issues, reach accurate information, and create information for a better learning process by using problem-solving and critical thinking. In this study, Bauer and Ahooei’s ( 2018 ) TL definition is grounded on.

2.4 Internet literacy

Similar to other literacies mentioned above, there are various definitions of IL in the literature. According to the definition of the Association of Colleges and Research Libraries (2010 as cited in Leung & Lee, 2012 ), IL is the ability to use computers, software applications, databases, and other technologies for an academic, work-related, or personal purpose. In a broader sense, IL is defined as the ability to assess, analyze, evaluate, and create online content (Lee & Chae, 2012 ; Livingstone, 2004 ). Besides, Vijayalakshmi et al. ( 2020 ) stated that IL includes effectively navigating and interacting on the Internet, such as downloading a file or accessing a video. As a result, IL is not only having the operational knowledge and essential skills to use a device, but also having information processing skills, such as interpreting, analyzing, and evaluating information in online messages (Kim & Yang, 2015 ).

An Internet literate individual should notice illegal and harmful content on the Internet, properly communicate on the Internet, protect own privacy, and take security measures (Fuji & Yoshida, 2015 ). Based on the relevant literature, IL can refer to the capability to access, understand, critique, and create information and communication content on the internet (Bauer & Ahooei, 2018 ; Livingstone, 2008 ). In this study, Bauer and Ahooei’s ( 2018 ) IL definition is based on.

2.5 Research hypotheses

There is a vast amount of literature on the predictors of CSE such as teacher self-efficacy, academic self-efficacy, computer self-efficacy, attitudes to technology, and computer self-efficacy and anxiety (Yeşilyurt et al., 2016 ; Celik & Yesilyurt, 2013 ). Besides the literature on the predictors of CSE, other studies on CSE reveal that there is a relationship between CSE, DL, TL, and IL (Aslan & Zhu, 2017 ; Berkant, 2016 ; Calaguas & Consunji, 2022 ; Falloon, 2020 ; Ferdousi, 2019 ; Kara, 2020 ; Lai, 2017 ; Tour et al., 2021 ). DL, TL, and IL are also stated as the determinants, influencers, and predictors of CSE and attitudes towards CSE (Estes, 2019 ; Guillen, 2014 ; Schumacher & Morahan-Martin, 2001 ). There is an abundance of research on CSE, DL, TL, and IL. These research are generally based on only one of them and focus on the need for teachers and prospective teachers to acquire these competencies and their level. However, as it is known from the current scientific and research perspective, an independent variable is affected by more than one dependent variable at the same time. In addition to this, with the use of high-level analysis in the social sciences, the effect level of more independent variables and explaining ratios can be detected. As it is explained in the theoretical framework of this study, CSE indpendent variable affects DL, TL, and IL dependent variables. In this study, DL, TL, and IL level of effect on the attitude toward applying CSE both separately and together, their explaining ratio and their statistical significance are dwelt upon. This situation also reveals this study’s biggest difference from similar studies in the literature. On the other hand, no study has been conducted on the link between and effect of DL, TL, and IL on the attitude toward applying CSE and their explaining ratio to each other. For this reason, it is important to detect which variables affect prospective teachers’ attitudes toward applying CSE and to what extent changes in these attitudes are explained under which variables and it is also important to put forward a concrete model in this subject.

To provide quality education with CSE, teachers should have basic skills in information literacy, computer literacy, and especially DL (Konstantinidou & Scherer, 2022 ). DL, with a dynamic and comprehensive structure, is a more comprehensive concept and regarded as an umbrella or roof (Bayrakçı, 2020 ; Güneş & Bahçıvan, 2018 ). It is underlined that a teacher’s DL skill means more than helping students with digital technology usage (Zhao et al., 2018 ). According to Martin and Grudziecki ( 2006 ), DL includes various types of literacies such as digital, media, information, and visual literacies. Similarly, it is argued that the concept of DL consists of technology, computer, information, media, communication, and visual literacy (Chetty et al., 2017 ; Covello & Lei, 2010 ). DL, IT literacy, computer literacy, and media literacy are used interchangeably, and the usage of different concepts reflects rapidly changing technology and the popularity of technology-related literacies. Since DL comprises not only basic ICT skills but also more advanced skills regarding the creative and critical use of digital tools, it is now defined as all engagements with digital technologies mediating most of the social interactions. According to Sefton-Green et al. ( 2009 ), DL includes a computer, technology, media, Internet, and it mediates most of our social interactions in varying degrees. This points out that DL can be considered as an influencing variable.

It is seen as essential for teachers to have a comprehensive understanding of technology to support teaching and learning (Compton & Compton, 2013 ; Forret et al., 2013 ). Similarly, TL and technology self-efficacy are determined as the most significant elements of the UNESCO’s ( 2018 ) ICT qualification framework for teachers. The results of studies conducted in different countries on technology and technology education reveal that the perception, opinion, and literacy levels of teachers and prospective teachers are essential for CSE (Hasse, 2017 ; Lee et al., 2020 ).

Besides TL, IL is one of the essential skills and deals with an individual’s competency, fluency, and knowledge in online environments. Therefore, IL is expected to affect the experience of the Internet and computer usage (Lee & Chae, 2012 ; Litt, 2013 ). In a study conducted by Miao et al. ( 2020 ), it is revealed the role of academic competence as a mediator between IL and academic achievement. Therefore, it is expected that IL will affect the attitude towards CSE.

Attitudes and self-efficacy perceptions of teachers and prospective teachers are the most important factors in achieving success in CSE practice. Analyzing the attitudes of prospective teachers towards CSE, their self-efficacy perceptions, and other variables that affect CSE is essential to improve the quality of higher education (Kutluca & Ekici, 2010 ). Therefore, there are numerous studies in which complex or various structural equation models are presented between various variables and CSE (Celik & Yesilyurt, 2013 ; Henseler et al., 2016 ; Hernández-Sellés et al., 2019 , 2020 ; Molinillo et al., 2018 ; Yeşilyurt et al., 2016 ). Moreover, theoretical and empirical evidence about close relationships among DL, TL, IL, and CSE were presented in recent findings.

The aim of this study is to test the relationship among the latent variables of TL, DL, IL, and attitude toward CSE, their effect on each other, and the levels of explanation. To reach this aim, the following eight research hypotheses, supported both theoretically and by the results of the related research, were tested:

H1. DL positively and significantly affects TL.

H2. DL significantly explains TL.

H3. DL positively and significantly affects attitude toward applying CSE.

H4. DL positively and significantly affects IL.

H5. DL significantly explains IL.

H6. TL positively and significantly affects attitude toward applying CSE.

H7. IL positively and significantly affects attitude toward applying CSE.

H8. DL, TL, and IL together explain attitude toward applying CSE.

One of the most important features of SEM is to develop hypotheses suitable for the general purpose of the research by taking the theoretical basis into account, and to test these hypotheses through a model. Therefore, the fact that the modification indexes of the model created and tested based on the theoretical information are at good fit or acceptable fit values embody the validity, reliability and practicality of the theoretical knowledge. The hypotheses and the path diagram to test the hypotheses in Fig. 1 were developed by the authors of this study.

Path diagram related to study hypothesis

3.1 Research model

A relational descriptive model is used for determining the change or the degree of the change between two or among more than two variables (Karasar, 2012 ), and detecting the presence and extent of covariance. Therefore, it was used in this study, and analyses were conducted using structural equation modeling. The eight hypotheses were tested, and the effect of prospective teachers’ attitudes toward using CSE, DL, TL, and IL on each other and their relationship with each other were analyzed in this study.

3.2 Participants

The participants of this study were 510 prospective teachers studying at the education faculty of a state university in Turkey in the fall semester of the 2021–2022 academic year. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used during the data analyses process. For this reason, the analysis method was decisive in determining the number of participants. There are different criteria for determining the size of the study group in the literature. Considering the sample size, Preacher and MacCallum ( 2002 ) stated that the minimum sample size should be between 100 and 250, or the number of items must be multiplied by at least three to determine the number of participants. Similarly, Bayram ( 2010 ) points out that the study group should be more than 200. According to Schumacker and Lomax ( 2010 ), 250–500 participants were used in many studies, and this number was sufficient for conducting SEM. In this context, it can be said that the number of participants in this study is sufficient.

3.3 Data analysis

After the data entry to the software package, the participants’ demographic characteristics were analyzed and exploratory factor analyses of scales were completed. The validity and reliability of the scales were statistically appropriate. It is sated that if the study group of the research and the study group in which the scales were developed were different, reliability and validity of the scales may need to be re-examined (Ercan & Kan, 2004 ). The fact that the Kaiser-Meyer-Olkin (KMO) result is greater than .60 and the Bartlett test is significant indicates that the data set is suitable for factor analysis. According to Büyüköztürk ( 2007 ), calculations for the internal consistency coefficient of the whole scale and sub-dimensions can be done by using the Cronbach Alpha (α), which is one of the reliability estimation methods. Moreover, if the Cronbach Alpha (α) value is .60 and above, the scale is considered reliable, and if it is above .80, the scale is considered highly reliable (Kayış, 2006 ). Besides, for acceptable reliability coefficients, it can be said that a scale with a value above .70 is reliable (Field, 2017 ; Kline, 1999 ). In addition, the structure revealed by exploratory factor analysis (EFA) was also examined by CFA.

In EFA and CFA, especially in social sciences, the boundary value of factor loads can be lowered to 0.30 when the number of items in a scale is limited. Furthermore, although the content validity is affected by a factor load below 0.30, researchers can conduct the analyses without taking the related item from the scale (Osborne, 2014 ). As recommended by Arbuckle ( 2009 ), researchers used software package, for the CFA of scales and SEM to examine the relationships. CFA, generally applied after EFA, brings out more exact statistical outcomes (Kline, 2015 ). Besides, researchers generated an SEM, which is a highly preferred model since it is better for the philosophy of discovery and confirmation in experimental or survey research (Bagozzi & Yi, 2012 ). The above-mentioned advantages are the reasons for using CFA and SEM. In the evaluation of the model goodness of fit, the following were used: The root mean square error of approximation (RMSEA), the standardized root mean square residual (SRMR), the goodness of fit index (GFI), the comparative fit index (CFI), the adjusted goodness of fit index (AGFI), the normed fit index (NFI), the chi-square/degrees of freedom (X 2 /sd = CMIN/DF), and the level of significance (p) fit indexes. According to Tabachnick and Fidell ( 2013 ), these fit indexes should be taken into account for CFA and SEM. The following indicate good fit indexes: RMSEA value between 0 and 0.08; SRMR value between 0 and 0.10; AGFI value between 0.85 and 1.00; X 2 /sd (CMIN/DF) value between 0 and 3, p value between 0.01 and 0.05, and the values of GFI, CFI and NFI between 0.90 and 1.00 (Barrett, 2007 ; Byrne, 2001 ; Hu & Bentler, 1999 ; Kline, 2015 ; Raju et al., 2002 ; Reisinger & Mavondo, 2006 ; Schermelleh-Engel et al., 2003 ). Besides, normality tests for CFA and SEM were based on a critical ratio below 10, since a problem may come up in the kurtosis value of distribution when the ratio is more than 10 (Kline, 2015 ; Mardia, 1974 ).

3.4 Data collection instruments

3.4.1 digital literacy scale.

The “DL Scale” consisting of six factors and 28 items and developed by Bayrakçı ( 2020 ) was used to determine the DL levels of prospective teachers. According to the Cronbach Alpha internal consistency analysis of the scale, the ethics and responsibility factor was α = .842, general knowledge, and functional skills factor was α = .875, daily use factor was α = .782, professional production factor was α = .719, confidentiality and security factor was α = .820, social factor was α = .86. Internal consistency analysis for the overall scale was α = .911. The DL Scale included five-point Likert-type items and the items were evaluated with “strongly agree” (5), “agree” (4), “undecided” (3), “disagree” (2), and “strongly disagree” (1) options. The items in this scale are exemplified as follows: Ethics and responsibility factor; “I am aware of the ethical and legal responsibilities of cyberbullying (insulting, profanity, hate speech, etc.) and abuse in online environments (DL4).” General knowledge and functional skills factor; “I know what are licensed software, demo software, pirated software, malware and crack (DL8).” Daily usage factor; “I can use cloud computing technologies (Google Drive, iCloud, Dropbox etc.) effectively in daily life (DL15).” Professional production factor; “I can develop software/application based on digital technologies (DL20).” Privacy and security factor; “I know how to restrict applications’ access to my personal information (location, contacts, camera, etc.) (DL22).” Social factor; “With the help of digital technologies, I can change various images (photo, sound recording and video, etc.) and produce new content (DL28).” In addition, the CFA of the scale was also performed and the fit indexes were found to be within acceptable limits. All items in the scale had the same structure and positive meaning.

After the analysis of the data, it was determined that the KMO value of the scale was .936. The results obtained from the KMO and Bartlett Sphericity tests (χ2 = 6979.701, df = 406, p = .000) indicated that the data were suitable for factor analysis. The factor loads of the items varied between .693 and .362. The Cronbach Alpha values of the internal consistency coefficient of the scale were as follows: Ethics and responsibility factor α = .866, general knowledge and functional skills factor α = .860, daily use factor α = .810, professional production factor α = .760, privacy and security factor α = .765, social factor α = .769, and α = .922 for the overall scale. This six-factor scale explained 61.716% of the total variance. The structure obtained as a result of EFA was tested with CFA. To obtain the appropriate (fit) values of the scale in terms of fit indexes, the modification indexes (M.I.) were taken into account. In line with the modification indexes and suggestions, four items were removed from the scale and six error covariances were created (e1-e2, e6-e7, e8-e9, e14-e17, e23-e25, and e27-e29). The CFA results of the scale are given in Fig.  2 . When the modification indexes (p, X2/sd, GFI, CFI, NFI, AGFI, RMSEA, SRMR) given under the heading of data analysis were taken into account, the CFA fit indexes of the scale had “good fit” and “acceptable fit” values.

Diagram for confirmatory factor analysis of the DL scale

3.4.2 Technological literacy scale

The TL Scale, which consists of five factors and thirty-three items, was developed by Yiğit ( 2011 ). The Cronbach Alpha values of the internal consistency coefficient of the scale were as follows: Technological life-oriented skills factor α = .78, nature of technology factor α = .73, designed world factor α = .96, design factor α = .63, technology and society factor α = .66, and α = .86 for the overall scale. Three-point Likert-type items were included in the Technology Literacy Scale with “yes” (3), “undecided” (2), and “no” (1) options. The items in this scale are exemplified as follows: Skills for technological life factor; “Before using a technological product, I examine its positive and negative aspects” (TL4).” The nature of technology factor; “Technology has a great role in human interaction with society (TL18).” The designed world factor; “In solving problems, people process information with the help of technology (TL19).” Design factor; “Technological designs must be functional (TL29).” Technology and society factor; “Identification of the problem is an important element of the design process (TL30).”

In the data obtained in this study, first of all, four negative items were converted to positive. After the analysis, it was determined that the KMO value of the scale was .874. The results obtained from the KMO and Bartlett Sphericity tests (χ2 = 4592.593, df = 496, p = .000) indicated that the data were suitable for factor analysis. The factor loads varied between .707 and .378. The Cronbach Alpha values of the internal consistency coefficient of the scale were as follows: Technological life-oriented skills factor α = .812, nature of technology factor α = .721, designed world factor α = .725, design factor α = .705, technology, society factor α = .711, and α = .872 for the overall scale. This five-factor scale explained 46.623% of the total variance. The structure obtained as a result of EFA was tested with CFA. To obtain the appropriate (fit) values of the scale in terms of fit indexes, the modification indexes (M.I.) were taken into account. In line with the modification indexes and suggestions, eight items were removed from the scale and three error covariances were created (e1-e9, e12-e17, and e21-e22). The CFA results of the scale are given in Fig.  3 . When the modification indexes (p, X2/sd, GFI, CFI, NFI, AGFI, RMSEA, SRMR) given under the heading of data analysis were taken into account, the CFA fit indexes of the scale had “good fit” and “acceptable fit” values.

Diagram for CFA of the TL scale

3.4.3 Internet literacy scale

“IL Self-Efficacy Scale for Pre-service Teachers” consisting of four factors and 16 items and developed by Yasan Ak ( 2020 ) was used to measure pre-service teachers’ IL. The Cronbach Alpha values of the internal consistency coefficient of the scale were as follows: Reliability factor α = .91, creation factor α = .82, technical information factor α = .85, and information factor α = .72. The scale was a seven-point Likert-type with “I have a lot of confidence in myself” (7), (6), (5), (4), (3), (2), (1) “I don’t trust myself at all.” options. The items in this scale are exemplified as follows: Creation factor; “I can create blogs (IL9).” Obtaining information factor; “I can use academic reference programs (e.g. Mendeley, Evernote, etc.) (IL15).” Safety factor; “I can distinguish whether information on the web is trustworthy (IL3).” Technical knowledge factor; “I can solve other Internet access problems (IL6).” In addition, CFA of the scale was also performed and it was revealed that the fit indexes were within acceptable limits.

All items of the scale were positive and had the same structure. After the analysis, it was determined that the KMO value of the scale was .948. The results obtained from the KMO and Bartlett Sphericity tests (χ2 = 5175.273, df = 120, p = .000) indicated that the data were suitable for factor analysis. The factor loads varied between .768 and .446. The Cronbach Alpha values of the internal consistency coefficient of the scale were as follows: The creation factor was calculated as α = .875, information acquisition factor α = .779, safety factor α = .896, technical knowledge factor α = .838, and α = .940 for the overall scale. This four-factor scale explained 72.053% of the total variance. The structure obtained as a result of EFA was tested with CFA. To obtain the appropriate (fit) values of the scale in terms of fit indexes, the modification indexes (M.I.) were taken into account. In line with the modification indexes and suggestions, one item was removed from the scale and four error covariances were created (e1-e3, e4-e5, e7-e8, and 10-e11). The CFA results of the scale are given in Fig.  4 . When the modification indexes (p, X2/sd, GFI, CFI, NFI, AGFI, RMSEA, SRMR) given under the heading of data analysis are taken into account, the CFA fit indexes of the scale had “good fit” and “acceptable fit” values.

Diagram for CFA of the IL scale

3.4.4 The attitude scale toward applying computer supported education

To measure the attitudes of prospective teachers towards CSE, the “Attitude Scale Towards CSE” developed by Arslan ( 2006 ) and consisting of a single factor and 20 items was used. The reliability coefficient was calculated as .93. There were five-point Likert-type items with “strongly agree” (5), “agree” (4), “undecided” (3), “disagree” (2), and “strongly disagree” options. The items in this scale are exemplified as follows: I think computer is an effective teaching tool (ACSE18); I try to use computers in my lessons (ACSE20); students learn better in lessons where computers are used (ACSE8).

In the data obtained in this study, first of all, ten negative items were converted to positive. After the analysis, it was determined that the KMO value of the scale was .939. The results obtained from the KMO and Bartlett Sphericity tests (χ2 = 5191.561, df = 190, p = .000) indicated that the data were suitable for factor analysis. The factor loads varied between .642 and .449. The internal consistency coefficient of the scale, Cronbach Alpha, was found to be .939. This single-factor scale explained 46.704% of the total variance. The structure obtained as a result of EFA was tested with CFA. To obtain the appropriate (fit) values of the scale in terms of fit indexes, the modification indexes (M.I.) were taken into account. In line with the modification indexes and suggestions, four items were removed from the scale and three error covariances were created (e2-e4, e5-e13, and e10-e16). The CFA results of the scale are given in Fig.  5 . When the modification indexes (p, X2/sd, GFI, CFI, NFI, AGFI, RMSEA, SRMR) given under the heading of data analysis were taken into account, the CFA fit indexes of the scale had “good fit” and “acceptable fit” values.

Confirmatory factor analysis diagram of the attitude scale toward CSE

As a result of this study, a model presenting the effect level of the latent variables of DL, TL, IL, and CSE on each other and their explaining ratios on each other was proposed. SEM as shown in Fig.  6 was built for this study.

Structural equation modeling and analysis results of hypothesis

The fit index was as follows: Chi squared = 6621.737; df = 3128; p = .000; χ2/sd (CMIN/DF) = 2.117; GFI = .912; CFI = .967; NFI = .902; AGFI = .864; RMSEA = .047 and SRMR = .088. These results illustrate an acceptable and desired level of the model fit index.

There were six latent variables and 25 observed variables in the DL scale. Whereas DL1 and DL25 had the lowest effect coefficient, DL4 and DL21 had the highest effect coefficient hierarchically. Besides, the effect coefficients were between 0.89 and 0.46.

There were five latent variables and 25 observed variables in the TL scale. Whereas TL22, TL6, and TL26 had the lowest effect coefficient, TL30 and TL8 had the highest effect coefficient hierarchically. Besides, the effect coefficients were between 0.97 and 0.58.

There were four latent variables and 15 observed variables in the IL scale. Whereas IL2 and IL7 had the lowest effect coefficient, IL10 and IL3 had the highest effect coefficient hierarchically. Besides, the effect coefficients were between 0.98 and 0.78.

There were 16 observed variables in the attitude scale toward applying CSE. Whereas ACSE6 and ACSE9 had the lowest effect coefficient, ACSE18 and ACSE20 had the highest effect coefficient among the observed variables. Besides, the effect coefficients were between 0.78 and 0.55.

Considering the hypotheses, the following results were obtained. As shown in Fig. 6 , it was confirmed that DL positively and significantly affected TL at a level of 0.45. The accuracy of the hypothesis that appeared in H1 (DL positively and significantly affects TL) was confirmed by this result. Furthermore, DL significantly explained TL at a ratio of 34%. To put it another way, it can be said that the change in TL was dependent on DL at a rate of 34%. The hypothesis in H2 (DL significantly explains TL) was confirmed by this result.

Regarding the third hypothesis, it was confirmed that DL positively and significantly affected attitude toward applying CSE at a level of 0.21. The accuracy of the hypothesis stated in H3 (DL positively and significantly affects attitude toward applying CSE) was confirmed by this result. Nevertheless, as shown in Fig. 6 , it was confirmed that DL affected IL at the highest level and the attitude toward applying CSE at the lowest level.

The study results also confirmed that DL affected IL positively and significantly at a level of 0.89. Therefore, the accuracy of the hypothesis stated in H4 (DL positively and significantly affects IL) was confirmed by this result. Moreover, it was confirmed that DL explained IL at a ratio of 79%. To put it another way, the change in IL arouse from DL at a ratio of 79%. The hypothesis in H5 (DL significantly explains IL) was confirmed by this result.

According to the results, it was confirmed that TL affected the attitude toward applying CSE positively and significantly at a level of 0.26. The accuracy of the hypothesis that appeared in H6 (TL positively and significantly affects attitude toward applying CSE) was confirmed by this result. As a result, it was confirmed that IL positively and significantly affected the attitude toward applying CSE at a level of 0.23. The accuracy of the hypothesis stated in H7 (IL positively and significantly affects attitude toward applying CSE) was confirmed by this result.

Considering the last research hypothesis, it was confirmed that DL, TL, and IL together significantly explained the attitude toward applying CSE at a ratio of 39%. Therefore, H8 (DL, TL, and IL together explain attitude toward applying CSE) was confirmed.

5 Discussion

In this study, the effect level of the latent variables of DL, TL, IL, and the attitude toward CSE on each other and their explaining ratios on each other were tested. Hence, eight hypotheses were developed in the framework of the research theory. In this section, the results of this study and other research results in the literature were discussed.

Considering the first hypothesis, it is found that the DL of prospective teachers positively and significantly affected TL. Moreover, considering the second hypothesis, it was confirmed that the DL of prospective teachers significantly explained TL. Prospective teachers need to have DL skills to use technology efficiently and functionally (List et al., 2020 ). In the literature, it is emphasized that there was a significant relationship between students’ perceptions and beliefs about DL and their attitudes towards technology (García-Martín & García-Sanchez, 2017 ; Hatlevik et al., 2018 ; Lee et al., 2019 ). Similarly, teachers’ DL had been regarded as an important element of ICT-supported education (Zhao et al., 2018 ). As a result of a study conducted by García-Martín and García-Sanchez ( 2017 ), prospective teachers’ perceptions of the use of web 2.0 tools were positive and their DL skills had an impact on this situation. Moreover, the results of H1 and H2 overlaped with other research results. Accordingly, some studies revealed a positive relationship between DL and TL (Falloon, 2020 ; Potyrała & Tomczyk, 2021 ; Yondler & Blau, 2021 ).

Regarding the third hypothesis, it was confirmed that the DL of prospective teachers positively and significantly affected attitude toward applying CSE. There are similar findings in the literature. For instance, in a study by Ferdousi ( 2019 ), it was stated that computer use self-efficacy significantly affected learners’ intention to use digital technology in their learning. In another study, it was found that prospective teachers’ tool literacy and metacognitive self-regulating capabilities had predictive effects on their attitudes towards structuring personal learning environments with Web 2.0 tools (Lim & Newby, 2021 ). There were also other studies showing a positive relationship between DL and CSE (Tour et al., 2021 ; van Rensburg & Son, 2010 ).

Considering the fourth hypothesis, the result confirmed that prospective teachers’ DL positively and significantly affected IL. Moreover, regarding the fifth hypothesis, it was confirmed that prospective teachers’ DL significantly explained IL. According to Ilomäki et al. ( 2011 ), DL is using the computer to access information and transfer data, communicate with the help of the Internet, work in teams and use communication technologies effectively in daily work. The results of this study for H4 and H5 were consistent with other research results in the literature. Among the results of the studies, it was emphasized that there was a relationship between DL and IL (Bauer & Ahooei, 2018 ; Gui & Argentin, 2011 ; Koltay, 2011 ; Reddy et al., 2021 ; The Royal Society, 2012 ).

Regarding the sixth hypothesis , it was confirmed that prospective teachers’ TL positively and significantly affected attitude toward applying CSE. In a study conducted by Santoso and Lestari ( 2019 ), it was revealed that TL significantly affected teaching competencies, and the teaching competencies were significantly influenced by TL and technology integration. In addition, according to the study by Hohlfeld et al. ( 2013 ), there was a relationship between TL and CSE. These results overlaped with the result of H6. Moreover, concerning the seventh hypothesis, it was confirmed that prospective teachers’ IL positively significantly affected attitude toward applying CSE. Similarly, in a study conducted by Calaguas and Consunji ( 2022 ), a positive and significant effect of the Internet and information-seeking self-efficacy on computer-assisted online learning self-efficacy was revealed. Moreover, in another study conducted by Wegmann et al. ( 2015 ), it was found that IL was a variable that affected and predicted the use of social networking sites accessed via computer. Accordingly, there are studies in the literature that shows a positive and significant relationship between IL and academic performance (Leung & Lee, 2012 ; McCoy, 2010 ; Miao et al., 2020 ). In addition to these, some studies reveal a positive relationship between IL and CSE (Lee & Chae, 2012 ; Lee et al., 2015 ; Schumacher & Morahan-Martin, 2001 ; Vernanda et al., 2018 ). As a result, the literature supported the result obtained from the H7 hypothesis.

Considering the eighth hypothesis, it is confirmed that prospective teachers’ DL, TL, and IL together significantly explained attitude toward applying CSE. Similarly, some studies reveal positive prospective teachers’ attitudes towards CSE (Aslan & Zhu, 2017 ; Kara, 2020 ; Önder et al., 2011 ). Moreover, among the results of meta-analysis studies on CSE in the literature, it is statistically more effective than traditional education (Anıl et al., 2018 ; Cheung & Slavin, 2012 ; Dinçer, 2015 ; Jong & Van Joolingen, 1998 ; Kumar & Mahajan, 2013 ; Porebska & Wantuch, 2015 ; Rutten et al., 2012 ; Seo & Bryant, 2009 ; Trey & Khan, 2008 ; Wayangkau & Loupatty, 2017 ). Therefore, some research results supported the result of H8. Accordingly, Çam and Kiyici ( 2017 ) reported that prospective teachers’ use of technological devices inside or outside the classroom may be useful for DL levels. Furthermore, in a study conducted by Link and Marz ( 2006 ), it was revealed that the majority of the students who had computer skills and knowledge had positive attitudes towards e-learning. Similarly, Khalifeh et al. ( 2020 ) reported that higher education students who were using personal computers, laptops, or tablets had a higher level of online learning ability and they were ready for CSE. There are other studies in the literature that have reported similar findings (Ellington et al., 2011 ; Ferdousi, 2019 ; Fister & McCarthy, 2008 ; Horton et al., 2011 ; Ozdamli & Tavukcu, 2016 ; Önder & Sılay, 2016 ).

In terms of quality and functional education, teachers and prospective teachers need to have DL, TL, and IL, but it is not enough on its own. They also need to be compatible with each other and with CSE. It is stated that types of literacies such as ‘information literacy’ (Zurkowski, 1974 ), ‘computer literacy’ (Tsai, 2002 ), ‘media literacy’ (Christ & Potter, 1998 ), and recently, ‘multi-modal literacy’ (Heydon, 2007 ) do not have an effect on learning alone, and that relevant literacy skills can be beneficial by properly integrating with CSE (Liao, 2007 ). For this reason, the result of the eighth hypothesis (DL, TL, and IL of pre-service teachers significantly explained their attitude towards CSE) showed that these four variables supported, explained, and were compatible with each other statistically.

6 Conclusion

The theoretical information in the literature and the results of the research on the subject show that teachers’ and prospective teachers’ level of DL, TL, and IL predict their attitudes towards CSE. In other words, the theoretical knowledge and study results indicate that pre-service teachers’ DL, TL, and IL levels significantly affect and explain their attitudes towards their CSE. However, no study could be found in the literature on the extent to which DL, TL, and IL levels both separately and together affect or explain teachers’ or prospective teachers’ attitudes towards CSE. Therefore, the aim of this study is to test the relationship among the latent variables of TL, DL, IL, and attitude toward CSE, their effect on each other, and the levels of explanation.

As a result, it was revealed that DL, TL, and IL together significantly affected and explained the attitude towards CSE. In other words, it has been determined that DL, TL, and IL are important predictors of attitude towards CSE. Moreover, DL, TL, and IL exogeneous (external-independent) variables were found to significantly affect and explain, that is, predict the CSE endogeneous (intrinsic-dependent) variable. According to this result, prospective teachers’ DL level should be determined and developed at first to have a positive and high level of attitude towards CSE. Determining the level of DL will affect prospective teachers’ attitudes towards CSE, as well as their TL and IL positively and significantly. The results showed that the TL of prospective teachers also contributed to their attitude towards CSE. For this reason, prospective teachers’ high attitudes towards CSE, and therefore their implementation of CSE, were closely related to a sufficient level of TL. In addition to these, it has been determined that IL is also effective in the attitude of prospective teachers towards CSE. Therefore, a sufficient IL level of prospective teachers will contribute to their high positive attitude towards CSE, thus contributing to their CSE. In short, the DL, TL, and IL levels of prospective teachers are essential in terms of their attitude towards CSE. In line with the results obtained in accordance with the general purpose of the research, it can be concluded that in order for prospective teachers to develop a positive attitude towards CSE and to conduct CSE, they should first acquire DL, TL, and IL skills. Therefore, the contents of the courses and program outputs in the pre-service education should ensure the achievements of these literacy types and increase the attitude towards CSE in a positive way.

7 Limitations

In addition to the contributions of the study, there are also some limitations that should be mentioned. Apart from DL, TL, and IL, other literacy types also affect attitude toward applying CSE. It is recommended that researchers conduct research on other variables that affect the attitude towards CSE, especially other types of literacy. Secondly, in this study, prospective teachers’ DL, TL, and IL levels were determined according to their opinions through scales. In future research, DL, TL, IL, and applying CSE levels of prospective teachers can also be determined by empirical studies based on practice and observation. Thirdly, this study was conducted on prospective teachers. Future research can be done on teachers. In addition, studies that aim to determine the place of DL, TL, IL, and CSE variables in pre-service education course contents and program outputs can be conducted. Despite its limitations, this study contributes to the literature in terms of revealing the effect level and explanation ratio of DL, TL, and IL variables on attitude toward applying CSE and testing the accuracy of the hypotheses based on the theoretical basis.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Yeşilyurt, E., Vezne, R. Digital literacy, technological literacy, and internet literacy as predictors of attitude toward applying computer-supported education. Educ Inf Technol 28 , 9885–9911 (2023). https://doi.org/10.1007/s10639-022-11311-1

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Received : 14 May 2022

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DOI : https://doi.org/10.1007/s10639-022-11311-1

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