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As the English language grows and spreads to more parts of the world, the field of English as a Second Language (ESL) is expanding as well. Students studying ESL education can consider several different topics and angles that would serve as good subjects for a research paper.
Schools abroad promote immersion as they best way to teach a child to become fluent in English. This may involve employing an English-only rule in the classroom, sending the children to overnight English-only camps or sending them to study English in an English-speaking country. A comparison of these methods to more traditional teaching methods would make a strong topic for a research paper.
The increase of ESL teachers and classes in other countries has had varying levels of impact on their way of life, cost of living, and in some cases, their native language. Choose three to five countries, preferably from different continents, and write a research paper comparing the ways in which ESL has affected their culture over the last decade.
Educators interested in entering the field of ESL have the option of teaching or studying in the United States or abroad. The experience of teaching ESL varies greatly from country to country. Write a research paper comparing the salary, hours, case studies and living aspects of ESL teachers from three to five different locations. Or, write a persuasive essay comparing the details of teaching or studying ESL in the United States to teaching or studying ESL overseas.
ESL teachers can earn a variety of degrees and certificates. Some earn degrees in English, linguistic studies or education, while others pursue their Teachers of English to Speakers of Other Languages (TESOL) or Certificate in Teaching English to Speakers of Other Languages (CELTA) certificates, as reflected on the TESOL and CELTA websites. Write a research paper comparing and contrasting these different programs and certificates, including costs, materials and international perceptions.
A variety of courses aim at teaching English only for a specific purpose, rather than aiming for fluency as a whole. Some professional adults, for example, enroll in Business English courses, which focus on learning appropriate phrases for interviews, emails and meetings. Several different angles would be appropriate for a research paper in this area. One option is to write about the effectiveness of these programs by researching how many students that chose this route were hired for a job as a result (using the Business English as an example). Another is to compare the benefits of a narrowly focused ESL program to a broad ESL program that promotes total fluency.
Kara Page has been a freelance writer and editor since 2007. She maintains several blogs on travel, music, food and more. She is also a contributing writer for Suite101 and has articles published on eHow and Answerbag. Page holds a Bachelor of Music Education degree from the University of North Texas.
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The number of English Language Learners (ELLs) has been growing worldwide. ELLs are at risk for reading disabilities due to dual difficulties with linguistic and cultural factors. This raises the need for finding practical and efficient reading interventions for ELLs to improve their literacy development and English reading skills. The purpose of this study is to examine the evidence-based reading interventions for English Language Learners to identify the components that create the most effective and efficient interventions. This article reviewed literature published between January 2008 and March 2018 that examined the effectiveness of reading interventions for ELLs. We analyzed the effect sizes of reading intervention programs for ELLs and explored the variables that affect reading interventions using a multilevel meta-analysis. We examined moderator variables such as student-related variables (grades, exceptionality, SES), measurement-related variables (standardization, reliability), intervention-related variables (contents of interventions, intervention types), and implementation-related variables (instructor, group size). The results showed medium effect sizes for interventions targeting basic reading skills for ELLs. Medium-size group interventions and strategy-embedded interventions were more important for ELLs who were at risk for reading disabilities. These findings suggested that we should consider the reading problems of ELLs and apply the Tier 2 approach for ELLs with reading problems.
English language learners, Evidenced-based intervention, Meta-analysis, Reading.
There is a growing body of literature that recognizes the importance of quality education for learners who study in a language other than their native language ( Estrella et al., 2018 ; Ludwig et al., 2019 ). As cultural, racial, ethnic, and linguistic diversification takes place globally, the number of students studying a second language different from their native language is also increasing worldwide. In the United States, nearly 5 million learners who are not native speakers of English are currently attending public schools, and this figure has increased significantly over the past decade ( NCES, 2016 ). As the number of children whose native language is not English increased, the need for educational support also increased. Furthermore, the implementation of NCLB policy emphasizes the need for quality education for all students included in all schools. Accordingly, NCLB has emerged as a critical policy for learners to study in their second language. In other words, there is an urgent need to ensure that non-native English speakers receive appropriate education due to NCLB, which has not only increased the demand for education but also led to the practice of enhanced education for learners whose English is not their native language.
ELLs (English language learners) refer to the education provided for learners whose native language is not English in English-speaking countries ( National Center for Education Statistics, 2021 ). The education provided to these ELLs is called ESL (English as a second language), ESOL (English to speakers of other languages), EFL (English as a foreign language), and so on. Each term is adopted differently depending on the policy, purpose, and status of operation of the state and/or school district. While a variety of terms have been suggested, this paper uses the term ‘ELLs’ to refer to learners who are not native speakers of English and uses the terms ‘the English education program’ and the ‘ELL program’ to refer to the English education program provided to ELLs.
To ensure quality education, students identified as ELLs can participate in supportive programs to improve their English skills. These ELL programs can be broadly divided into two methods: “pull-out” and “push-in” ( Honigsfeld, 2009 ). In the pull-out program, students are taken to a specific space other than the classroom at regular class time and are separately taught English. In the push-in program, the ELL teacher joins the mainstream ELLs’ classroom and assists them during class time. Through these educational supports, ELLs are required to achieve not only English language improvements addressed in Title III of NCLB but also language art achievements appropriate to their grade level addressed in Title I of NCLB. ELLs are expected to achieve the same level of academic achievement as students of the same grade level, as well as comparable language skills.
A considerable amount of literature has been published on the achievement and learning status of ELLs ( Ludwig, 2017 ; Soland and Sandilos, 2020 ). These studies revealed that despite the intensive, high-quality education support for ELLs, they encounter difficulties learning and academic achievement. The National Reading Achievement Test (NAEP) results show that the achievement gap between non-ELLs and ELLs is steadily expanding in the areas of both mathematics and reading ( Polat et al., 2016 ). Ultimately, ELLs are reported to have the highest risk of dropping out of school ( Sheng et al., 2011 ). These difficulties are not limited to early school age. Fry (2007) reported that the results from a national standardized test of 8th-grade students found that ELLs performed lower than white students in both reading and math. Callahan and Shifrer (2016) analyzed data from a nationally representative educational longitudinal study in 2002 and found that, despite taking into account language, socio-demographic and academic factors, ELLs still have a large gap in high school academic achievement. Additionally, research has suggested that ELLs are less likely to participate in higher education institutions compared to non-ELL counterparts ( Cook, 2015 ; Kanno and Cromley, 2015 ).
Factors found to influence the difficulties of ELLs in learning have been explored in several studies ( Dussling, 2018 ; Thompson and von Gillern, 2020 ; Yousefi and Bria, 2018 ). There are two main reasons for these difficulties. First, ELLs face many challenges in learning a new language by following the academic content required in the school year ( American Youth Policy Forum, 2009 ). Moreover, language is an area that is influenced by sociocultural factors, and learning academic contents such as English language art and math are also influenced by sociocultural elements and different cultural backgrounds, which affects the achievement of ELLs in school ( Chen et al., 2012 ; Orosco, 2010 ). Second, it is reported that the heterogeneity of ELLs makes it challenging to formulate instructional strategies and provide adequate education for them. Due to the heterogeneous traits in the linguistic and cultural aspects of the ELL group, there are limitations in specifying and guiding traits. Therefore, properly reflecting their characteristics is difficult.
The difficulties for ELLs in academic achievement raise the necessity for searching practical and efficient reading interventions for ELLs to improve English language and academic achievement, including ELLs' English language art achievement. These needs and demands led to the conduct of various studies that analyze the difficulties of ELLs. Over the past decade, these studies have provided important information on education for ELLs. The main themes of the studies are difficulties in academic achievement and interventions for ELLs, including reading ( Kirnan et al., 2018 ; Liu and Wang, 2015 ; Roth, 2015 ; Shamir et al., 2018 ; Tam and Heng, 2016 ), writing ( Daugherty, 2015 ; Hong, 2018 ; Lin, 2015 ; nullP ) or both reading and math ( Dearing et al., 2016 ; Shamir et al., 2016 ). The influences of teachers on children's guidance ( Kim, 2017 ; Daniel and Pray, 2017 ; Téllez and Manthey, 2015 ; Wasseell, Hawrylak, Scantlebuty, 2017 ) and the influences of family members ( Johnson and Johnson, 2016 ; Walker, Research on 2017 ) are also examined.
Reading is known to function as an important predictor of success not only in English language art itself but also in overall school life ( Guo et al., 2015 ). This is because reading is conducted throughout the school years, as most of the activities students perform in school are related to reading. Furthermore, reading is considered one of the major fundamental skills in modern society because it has a strong relationship with academic and vocational success beyond school-based learning ( Lesnick et al., 2010 ). In particular, for ELLs, language is one of the innate barriers; thereafter, reading is one of the most common and prominent difficulties in that it is not done in their native language ( Rawian and Mokhtar, 2017 ; Snyder et al., 2017 ). In this respect, several studies have investigated reading for ELLs. These studies explore effective interventions and strategies ( Kirnan et al., 2018 ; Mendoza, 2016 ; Meredith, 2017 ; Reid and Heck, 2017 ) and suggest reading development models or predictors for reading success ( Boyer, 2017 ; Liu and Wang, 2015 ; Rubin, 2016 ). For these individual studies to provide appropriate guidance to field practitioners and desirable suggestions for future research, aggregation of the overall related studies, not only of the individual study, and research reflections based on them are required. Specifically, meta-analysis can be an appropriate research method. Through meta-analysis, we can derive conclusions from previous studies and review them comprehensively. Furthermore, meta-analysis can ultimately contribute to policymakers and decision-makers making appropriate decisions for rational strategies and policymaking.
Although extensive research has been carried out on the difficulties of ELLs and how to support them, a sufficiently comprehensive meta-analysis of these studies has not been carried out. Some studies have focused on specific interventions, such as morphological interventions ( Goodwin and Ahn, 2013 ), peer-mediated learning ( Cole, 2014 ), and video game-based instruction ( Thompson and von Gillern ). Ludwig, Guo, and Georgiou (2019) demonstrated the effectiveness of reading interventions for ELLs. However, they divided reading-related variables into “reading accuracy”, “reading fluency”, and “reading comprehension” and examined the effectiveness of the reading-related attributes in each of the variables. Therefore, the study has limitations for exploring the various aspects of reading and their effectiveness for reading interventions.
Individual studies have their characteristics and significance. However, for individual studies to be more widely adopted in the field and to be a powerful source for future research, it is necessary to analyze these individual studies more comprehensively. Meta-analysis reviews past studies related to the topic by 'integrating' previous studies, analyzes and evaluates them through 'critical analysis', provides implications to the field, and gives rise to intellectual stimulation to future studies by ‘identifying issues’ ( Cooper et al., 2019 ). Through this, meta-analysis can be a useful tool for diagnosing the past where relevant research has been conducted, taking appropriate treatment for the present, and providing intellectual stimulation for future studies.
Therefore, the purposes of this study are to examine evidence-based reading interventions for ELLs presented in the literature to analyze their effects and to identify the actual and specific components for creating the most effective and efficient intervention for ELLs. The findings of this study make a major contribution to research on ELLs by demonstrating the implications for the field and future study.
A meta-analysis of peer-reviewed articles on ELL reading interventions published between January 2008 and March 2018 was conducted. According to the general steps of a meta-analysis, data related to reading interventions for English language learners were collected as follows. First, educational and psychological publication databases, such as Google Scholar ( https://scholar.google.co.kr ), ERIC ( https://eric.ed.gov/ ), ELSEVIER ( http://www.elsevier.com ), and Springer ( https://www.springer.com/gp ) were used to find the articles to be analyzed using the search terms “ELLs,” ESL,” “Reading,” “Second language education,” “Effectiveness,” and “Intervention” separately and in combination with each other. We reviewed the results of the web-based search for articles and included all relevant articles on the preliminary list. We selected the final list of the articles to be analyzed by applying inclusion and exclusion criteria to the preliminary list of articles. Studies were included in the final list based on three primary criteria. First, each study should evaluate the effectiveness of a school-based reading intervention using an experimental or quasi-experimental group design. In this process, single case, qualitative, and/or descriptive studies for ELLs were excluded from the analysis. Second, we included all types of reading-related interventions (i.e., phonological awareness, word recognition, reading fluency, vocabulary, and reading comprehension). Third, each study needed to report data in a statistical format to calculate an effect size. Fourth, we only included studies whose subjects were in grades K-12. The preliminary list had 75 articles, but since some of these studies did not meet the inclusion criteria, we excluded them from the final list for analysis. In total, this meta-analysis included 28 studies with 234 effect sizes (see Figure 1 ).
Prisma flow diagram.
2.2.1. coding procedure.
To identify the relevant components of the evidence-based reading interventions for ELLs, we developed an extensive coding document. Our interest was in synthesizing the effect sizes and finding the variables that affect the effectiveness of reading interventions for ELLs. The code sheet was made based on a code sheet used in Vaughn et al. (2003) and Wanzek et al. (2010) . All studies were coded for the following: (a) study characteristics, including general information about the study, (b) student-related variables, (c) intervention-related variables, (d) implementation-related variables, (e) measurement-related variables, and (f) quantitative data for the calculation of effect sizes.
Within the study characteristics category, we coded the researchers’ names, publication year, and title from each study to identify the general information about each study. For the student-related variables, mean age, grade level(s), number of participants, number of males, number of females, sampling method, exceptionality type (reading ability level), identification criteria in case of learning disabilities, race/ethnicity, and SES were coded. We divided grade level(s) into lower elementary (K-2), upper elementary (3–5), and secondary (6–12). When students with learning disabilities participated in the study, we coded the identification criteria reported in the study. For race/ethnicity, we coded white, Hispanic, black, Asian, and others. Within intervention-related variables, we coded for the title of the intervention, the key instructional components of the intervention, the type of intervention, and the reading components of the intervention. The reading components coded were phonemic awareness, phonics, fluency, vocabulary, reading comprehension, listening comprehension, and others. If an intervention contained multiple reading components, all reading components included in the intervention were coded. Fourth, within implementation-related variables, we coded group size, duration of the intervention (weeks), the total number of sessions, frequency of sessions per week, length of each session (minutes), personnel who provided the intervention (i.e., teacher, researchers, other), and the setting. Fifth, in measurement-related variables, we coded the title of the measurement, reliability coefficient, validity coefficient, type of measurement, type of reliability, and type of validity. We also coded quantitative data such as the pre- and posttest means, the pre- and posttest standard deviations, and the number of participants in the pre- and posttests for both the treatment and control groups. These coding variables are defined in Table 1 . The research background and sample information are in Appendix 1 .
Coding variables.
Study Component | Code | Details |
---|---|---|
General Information | Title | |
Names of researchers | ||
Publication year | ||
Participant | Mean age | |
Age and Grade levels | Preschool, Lower elementary (K-2), Upper elementary (3–5), Secondary (6–12) | |
Number of participants | Total number of participants, Number of girls, Number of boys | |
Exceptionality | General, Learning difficulties, Learning disabilities, Others | |
Race/Ethnicity | European-American, Hispanic, African-American, Asian/Pacific Islander, Others | |
SES | Lower, Middle, Upper | |
Intervention | Title of intervention | |
Key instructional components | ||
Type of reading intervention | Strategy instruction, Peer tutoring, Computer-based learning, and Others | |
Reading components | Phonemic awareness, Phonics, Fluency, Vocabulary, Reading comprehension, Listening comprehension and Others | |
Implementation | Group size | Small group (1 or more and 5 or less), Middle group (6 or more and 15 or less), and Large group or class size (16 or more) |
Duration of intervention (weeks) | ||
Total number of sessions | ||
Frequency per week | ||
Length of each session (minutes) | ||
Instructor | Teachers, Graduate students, Researchers, Others | |
Setting | Classroom, Resource room, Afternoon school, and Others | |
Measurement | Title of measurement methods | |
Type of measurement | Standardized measurement and Researcher-developed measurement | |
Reliability coefficient | Reported and Unreported | |
Validity coefficient | Reported and Unreported | |
Type of reliability | Test-retest reliability, Cronbach α, and Others | |
Type of validity | Criterion validity, Construct validity, Content validity and Others |
The included articles were coded according to the coding procedure described above. Two researchers coded each study separately and reached 91% agreement. Afterward, the researchers reviewed and discussed the differences to resolve the initial disagreements.
First, we calculated 234 effect sizes from the interventions included in the 28 studies. The average effect size was calculated using Cohen's d formula. In addition, we conducted a two-level meta-analysis through multilevel hierarchical linear modeling (HLM) using the HLM 6.0 interactive mode statistical program to analyze the computed effect sizes and find the predictors that affect the effect sizes of reading interventions. HLM is appropriate to quantitatively obtain both overall summary statistics and quantification of the variability in the effectiveness of interventions across studies as a means for accessing the generalizability of findings. Moreover, HLM easily incorporates the overall mean effect size using the unconditional model, and HLM is useful to explain variability in the effectiveness of interventions between studies in the conditional model. The aim of the current study is to provide a broad overview of interventions for ELLs. To achieve this aim, we conducted an unconditional model for overall mean effect size and conducted a conditional model to identify factors that have an impact on the strength of effect sizes. In regard to variables related to the effectiveness of interventions, we conducted a conditional model with student-related, measurement-related, intervention-related, and implementation-related variables. In the case of quantitative meta-analyses, it is assumed that observations are independent of one another ( How and de Leeuw, 2003 ). However, this assumption is usually not applied in social studies if observations are clustered within larger groups ( Bowman, 2003 ) because each effect size within a study might not be homogeneous ( Beretvas and Pastor, 2003 ). Thus, a two-level multilevel meta-analysis using a mixed-effect model was employed because multiple effect sizes are provided within a single education study. To calculate effect size (ES) estimates using Cohen's d, we use the following equation [1]:
The pooled standard deviation, SD pooled , is defined as
In HLM, the unconditional model can be implemented to identify the overall effect size across all estimates and to test for homogeneity. If an assumption of homogeneity is rejected by an insignificant chi-square coefficient in the unconditional model, this means that there are differences within and/or between studies. This assumption must go to the next step to find moderators that influence effect sizes. This step is called a level two model or a conditional model. A conditional model is conducted to investigate the extent of the influence of the included variables.
The level one model (unconditional model) was expressed as [3], and the level two model (the conditional model was expressed as [4].
In equation (3) , δ j represents the mean effect size value for study j, and e j is the within-study error term assumed to be theoretically normally distributed with a mean of 0 and a variance of V j . In the level two model equation [4], γ 0 represents the overall mean effect size for the population, and u j represents the sampling variability between studies presumed to be normally distributed with a mean of 0 and a variance τ .
Regarding publication bias, we looked at the funnel plot with the 'funnel()' command of the metafor R package ( Viechtbauer, 2010 ), and to verify this more statistically, we used the dmetar R package ( Harrer et al., 2019 ). Egger's regression test ( Egger et al., 1997 ) was conducted using the 'eggers.test()' command to review publication bias. Egger's regression analysis showed that there was a significant publication error (t = 3.977, 95% CI [0.89–2.54], p < .001). To correct this, a trim-and-fill technique ( Duval and Tweedie, 2000 ) was used. As a result, the total effect size corrected for publication bias was also calculated. The funnel plot is shown in [ Figure 2 ].
Funnel plot.
We analyzed 28 studies to identify influential variables that count for reading interventions for ELLs. Before performing the multilevel meta-analysis, the effect size of 28 studies was analyzed by traditional meta-analysis. The forest plots for the individual effect sizes of 28 studies are shown in Appendix 2. We present our findings with our research questions as an organizational framework. First, we showed an unconditional model for finding the overall mean effect size. Then, we described the variables that influenced the effect size of reading interventions for ELLs using a conditional model.
An unconditional model of the meta-analysis was tested first. In the analysis, restricted maximum likelihood estimation was used. This analysis was conducted to confirm the overall mean effect size and to examine the variability among all samples. The results are shown in Table 2 .
Results of the unconditional model analysis.
Fixed Effect | |||||
---|---|---|---|---|---|
Coefficient | Ratio( ) | 95% CI | |||
Lower | Upper | ||||
Intercept | 0.653 | 0.063 | 10.173∗∗(233) | 0.530 | 0.776 |
Random Effect | |||||
Variance Component | Chi | ||||
Intercept | 0.589 | 0.767 | 1245.90∗∗∗ |
∗∗∗ p < 0.001, df: degree of freedom.
The intercept coefficient in the fixed model is the overall mean effect size from 234 effect sizes. This means that the effect of reading intervention for English language learners is medium based on Cohen's d. Cohen's d is generally interpreted as small d = 0.2, medium d = 0.5 and large d = 0.8. The variance component indicates the variability among samples. The estimate was 0.589 and remained significant (χ 2 = 1245.90, p < . 001). This statistical significance means that moderator analysis with dominant predictors in a model is required to explore the source of variability.
Moderator analysis using the conditional model was expected to identify factors that have an impact on the strength of effect sizes. In this study, the moderator analysis was administered by nine critical variable categories: students’ grade, exceptionality, SES, reading area, standardized test, test reliability, intervention type, instructor, and group size. Variables in each category were coded by dummy coding. Dummy coding was used to identify the difference in dependent variables between the categories of independent variables. For example, we used four dummy variables to capture the five dimensions. The parameter estimates capture the differences in effect sizes between the groups that are coded 1 and a reference group that is coded 0. From a mathematical perspective, it does not matter which categorical variable is used as the referenced group ( Frey, 2018 ). We labeled one variable in each category as a reference group to make the interpretation of the results easier. We used an asterisk mark to denote the reference group for each category; if a word has an asterisk next to it, this indicates that it is the reference group for that category.
The results of the conditional meta-analysis for students' grade variables are presented in Table 3 . In Table 3 , the significant coefficients mean that mean effect sizes are significantly larger for studies in reference conditions. For student grades, upper elementary students showed significantly larger mean effect sizes than secondary students (2.720, p = 0.000), but preschool students showed significantly lower mean effect sizes than secondary students (-0.103, p = 0.019). The Q statistic was significant for students’ grades ( Q = 27.20, p < 0.001) (see Table 4 ).
Results of the moderator analysis for student grade.
Fixed Effect | K | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Secondary∗ | 20 | 0.482 | 0.066 | 7.261 | 230 | 0.000 | 27.70 |
Preschool | 110 | -0.103 | 0.043 | -2.370 | 230 | 0.019 | |
Lower Elementary | 87 | 0.068 | 0.084 | 0.810 | 230 | 0.419 | |
Upper Elementary | 17 | 2.720 | 0.169 | 16.076 | 230 | 0.000 |
df: degree of freedom.
Results of the moderator analysis for exceptionality.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Low achievement∗ | 6 | 0.707 | 0.198 | 3.581 | 232 | 0.001 | 0.0278 |
General | 228 | -0.080 | 0.208 | -0.385 | 232 | 0.700 |
For the student-related variables, students with low achievement showed significantly larger mean effect sizes scores than general students (0.707, p = 0.001). However, there was no significant difference between students with low achievement and general students. The Q statistic was significant for students’ exceptionality ( Q = 0.0278, p < 0.001).
Table 5 shows that low and low-middle SES was not significantly different from students with no information about SES (0.055, p = 0.666). Moreover, students with middle and upper SES did not have significantly smaller effect sizes than students with nonresponse (-0.379, p = 0.444). The Q statistic was significant for students’ SES ( Q = 68.50, p < 0.001).
Results of the moderator analysis for SES.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Nonresponse∗ | 88 | 0.613 | 0.092 | 6.656 | 231 | 0.000 | 68.50 |
Low-Middle | 124 | 0.055 | 0.127 | 0.432 | 231 | 0.666 | |
Middle-Upper | 22 | -0.379 | 0.494 | -0.767 | 231 | 0.444 |
Table 6 shows the results of the moderator analysis for measurement types. The coefficient for the standardized measurement-related variable was not significant. The Q statistic was significant for the standardization of measurement tools ( Q = 5.28, p < 0.001).
Results of the moderator analysis for standardization of measurement tools.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Researcher developed∗ | 61 | 0.721 | 0.107 | 6.727 | 232 | 0.000 | 5.28 |
Standardized | 173 | -0.129 | 0.131 | -0.983 | 232 | 0.327 |
Table 7 shows the results of the moderator analysis for the reliability of the measurement tools. The coefficient for the measurement reliability-related variable was significant (0.409, p = 0.003), which means that the effect sizes of measurements that reported reliability (ES = 0.770) were significantly larger than the effect sizes of measurements that had information about reliability (ES = 0.361). The Q statistic was significant for the reliability of the measurement tools ( Q = 5.82, p < 0.001) (see Table 8 ).
Results of the moderator analysis for reliability.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Nonresponse about reliability∗ | 81 | 0.361 | 0.108 | 3.338 | 232 | 0.001 | 5.82 |
Reliability | 153 | 0.409 | 0.132 | 3.093 | 232 | 0.003 |
Results of the moderator analysis for content of the intervention.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Other area∗ | 21 | 0.096 | 0.150 | 0.642 | 228 | 0.521 | 24.005 |
Phonological awareness | 58 | 0.528 | 0.209 | 2.521 | 228 | 0.013 | |
Reading fluency | 13 | 1.150 | 0.324 | 3.549 | 228 | 0.001 | |
Vocabulary | 93 | 0.442 | 0.179 | 2.464 | 228 | 0.000 | |
Reading comprehension | 32 | 0.971 | 0.209 | 4.651 | 228 | 0.000 | |
Listening Comprehension | 17 | 0.834 | 0.257 | 3.244 | 228 | 0.002 |
The content of the intervention was divided into phonological awareness, reading fluency, vocabulary, reading comprehension, listening comprehension, and other areas. Studies measured other areas that functioned as a reference group. For the measurement area, all reading areas were significantly larger than other areas. Reading fluency (1.150, p = 0.001), reading comprehension (0.971, p = 0.000) and listening comprehension (0.834, p = 0.002) were significantly larger than those in the other areas. However, phonological awareness and vocabulary were significantly larger than other areas but lower than reading fluency, reading comprehension, and listening comprehension (0.528, p = 0.013; 0.442, p = 0.000). The Q statistic was significant for the content of the intervention ( Q = 24.005, p < 0.001).
For intervention types, strategy instruction, peer tutoring, and computer-based learning were compared to other methods, which were fixed as a reference group. Table 9 shows that strategy instruction was significantly larger than other methods in mean effect sizes (0.523, p = 0.001). However, studies that applied peer tutoring and computer-based learning showed lower than other methods, but these differences were not statistically significant (-0.113, p = 0.736; -0114, p = 0.743). The Q statistic was significant for intervention types ( Q = 73.343, p < 0.001).
Results of the moderator analysis for intervention types.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Other method∗ | 34 | 0.269 | 0.135 | 1.986 | 230 | 0.048 | 73.343 |
Strategy instruction | 154 | 0.523 | 0.154 | 3.405 | 230 | 0.001 | |
Peer tutoring | 18 | -0.113 | 0.337 | -0.337 | 230 | 0.736 | |
Computer based learning | 28 | -0.114 | 0.348 | -0.328 | 230 | 0.743 |
For instructor-related variables, other instructor-delivered instructions were assigned as a reference group. Table 10 shows that the teacher and researcher groups showed significantly larger than the other instructors. Moreover, the teacher group showed larger than the researcher group (0.909, p = 0.000). The Q statistic was significant for instructor-related variables ( Q = 14.024, p < 0.001).
Results of the moderator analysis for instructor.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Other instructor∗ | 6 | -0.197 | 0.225 | -0.873 | 230 | 0.384 | 14.024 |
Teacher | 182 | 0.909 | 0.237 | 3.837 | 230 | 0.000 | |
Graduate students | 4 | 0.691 | 0.469 | 1.476 | 230 | 0.141 | |
Researcher | 42 | 0.894 | 0.273 | 3.273 | 230 | 0.002 |
For group size, mixed groups were fixed as a reference group. Group size variables were divided into a small group (1 or more and 5 or less), a middle group (6 or more and 15 or less), and a large group or class size (16 or more). Table 11 shows that the middle group (6 or more and 15 or less) and the small group (1 or more and 5 or less) were significantly larger than the mixed group (0.881, p = 0.000; 0.451, p = 0.006). However, the difference between the large group and the mixed group was not significant (0.120, p = 0.434). The Q statistic was significant for group size variables ( Q = 17.756, p < 0.001).
Results of the moderator analysis for group size.
Fixed Effect | k | Coefficient (d) | Standard Error | Ratio | -value | ||
---|---|---|---|---|---|---|---|
Mixed group∗ | 62 | 0.391 | 0.111 | 3.528 | 230 | 0.001 | 17.756 |
Small group | 61 | 0.451 | 0.160 | 2.824 | 230 | 0.006 | |
Middle group | 18 | 0.881 | 0.231 | 3.808 | 230 | 0.000 | |
Large group | 93 | 0.120 | 0.153 | 0.783 | 230 | 0.434 |
The purpose of this meta-analysis was to explore the effects of reading interventions for ELLs and to identify research-based characteristics of effective reading interventions for enhancing their reading ability. To achieve this goal, this study tried to determine the answers to two research questions. What is the estimated mean effect size of reading interventions for ELLs in K-12? To what extent do student-, intervention-, implementation-, and measurement-related variables have effects on improving the reading ability of ELLs in K-12? Therefore, our study was limited to recent K-12 intervention studies published between January 2008 and March 2018 that included phonological awareness, fluency, vocabulary, reading comprehension, and listening comprehension as intervention components and outcome measures. A total of 28 studies were identified and analyzed. To inquiry the two main research questions, a two-level meta-analysis was employed in this study. For the first research question, the unconditional model of HLM was conducted to investigate the mean effect size of reading interventions for ELLs. The conditional model of HLM was conducted to determine which variables have significant effects on reading interventions for ELLs. Below, we briefly summarized the results of this study and described the significant factors that seem to influence intervention effectiveness. These findings could provide a better understanding of ELLs and support implications for the development of reading interventions for ELLs.
The first primary finding from this meta-analysis is that ELLs can improve their reading ability when provided appropriate reading interventions. Our findings indicated that the overall mean effect size of reading interventions of ELLs yielded an effect size of 0.653, which indicates a medium level of effect. From this result, we can conclude that the appropriate reading interventions generally have impacts on reading outcomes for ELLs in K-12. This is consistent with prior syntheses reporting positive effects of reading interventions for ELLs ( Vaughn et al., 2006 ; Abraham, 2008 ).
Effect size information is important to understand the real effects of the intervention. Therefore, this finding indicated that supplementary reading interventions for ELLs will be developed and implemented. This finding also showed that states are required to develop a set of high-quality reading interventions for ELLs. Language interventions for ELLs have become one of the most important issues in the U.S. Increasing numbers of children in U.S. schools have come from homes in which English is not the primary language spoken. NCES (2016) showed that 4.9 million students, or 9.6% of public school students, were identified as ELLs, which was higher than the 3.8 million students, or 8.1%, identified in 2000 ( NCES, 2016 ). While many students of immigrant families succeed in their academic areas, too many do not. Some ELLs lag far behind native English speakers in the school because of the strong effect of language factors on the instruction or assessment. Although English is not their native language, ELLs should learn educational content in English. This leads to huge inequity in public schools. Thus, improving the English language and literacy skills of ELLs is a major concern for educational policymakers. This finding can support practitioners’ efforts and investments in developing appropriate language interventions for ELLs.
The second primary finding of this meta-analysis relates to four variable categories: student-, intervention-, implementation-, and measurement-related variables. Effective instruction cannot be designed by considering one factor. The quality of instruction is the product of many factors, including class size, the type of instructions, and other resources. This finding showed which factors affected the effectiveness of reading interventions. Specifically, we found that the variables that proved to have significant effects on reading outcomes of ELLs were as follows: upper elementary students, reliable measurement tools, reading and listening comprehension-related interventions, strategy instruction, and the middle group consisting of 6 or more and 15 or less. Teachers and practitioners in the field may choose to adopt these findings into their practices. ELL teachers may design their instruction as strategy-embedded instruction in middle-sized groups.
We found that grades accounted for significant variability in an intervention's effectiveness. Specifically, we found that reading interventions were substantially more effective when used with upper elementary students than secondary students. This means that the magnitude of an intervention's effectiveness changed depending on when ELLs received reading interventions. Specifically, the larger effect sizes on upper elementary students than secondary schools showed the importance of early interventions to improve ELLs' language abilities. Students who experience early reading difficulty often continue to experience failure in later grades. ELLs, or students whose primary language is other than English and are learning English as a second language, often experience particular challenges in developing reading skills in the early grades. According to Kieffer (2010) , substantial proportions of ELLs and native English speakers showed reading difficulties that emerged in the upper elementary and middle school grades even though they succeeded in learning to read in the primary grades.
Regarding students’ English proficiency and academic achievement, there was no statistically significant difference between students with low achievement and general students. Given the heterogeneity of the English language learner population, interventions that may be effective for one group of English language learners may not be effective with others ( August and Shanahan, 2006 ). This result is similar to the results achieved by Lovett et al. (2008) . Lovett et al. (2008) showed that there were no differences between ELLs and their peers who spoke English as a first language in reading intervention outcomes or growth intervention. This finding suggests that systematic and explicit reading interventions are effective for readers regardless of their primary language.
For students' socioeconomic status (SES), there was no significant difference between the low-middle group and the nonresponse group. However, we cannot find that students' SES is critical for implementing reading interventions. Low SES is known to increase the risk of reading difficulties because of the limited access to a variety of resources that support reading development and academic achievement ( Kieffer, 2010 ). Many ELLs attend schools with high percentages of students living in poverty ( Vaughn et al., 2009 ). These schools are less likely to have adequate funds and resources and to provide appropriate support for academic achievement ( Donovan and Cross, 2002 ). Snow, Burns and Griffin (1998) highlighted multiple and complex factors that contribute to poor reading outcomes in school, including a lack of qualified teachers and students who come from poverty. Although this study cannot determine the relationship between the effectiveness of reading interventions and the SES of students, more studies are needed. In addition, these results related to students’ characteristics showed that practitioners and teachers can consider for whom to implement some interventions. Researchers should provide a greater specification of the student samples because this information will be particularly critical for English language learners.
Although many of the studies measured a variety of outcomes across all areas of reading, interventions that focused on improving reading comprehension and listening comprehension obtained better effects than other reading outcomes. This result is similar to those discussed in previous findings ( Wanzek and Roberts, 2012 ; Carrier, 2003 ).
With regard to effective intervention types, the findings indicated that strategy instruction was statistically significant for improving the reading skills of ELLs. However, computer-based interventions, which are frequently used for reading instruction for ELLs in recent years, showed lower effect sizes than mixed interventions. Strategy instructions are known as one of the effective reading interventions for ELLs ( Proctor et al., 2007 ; Begeny et al., 2012 ; Olson and Land, 2007 ; Vaughn et al., 2006 ). These strategies included activating background knowledge, clarifying vocabulary meaning, and expressing visuals and gestures for understanding after reading. Some studies have shown that computer-based interventions are effective for ELLs ( White and Gillard, 2011 ; Macaruso and Rodman, 2011 ), but this study does not. Therefore, there is little agreement in the research literature on how to effectively teach reading to ELLs ( Gersten and Baker, 2000 ). Continued research efforts must specify how best to provide intervention for ELLs.
With respect to the implementation of the intervention, teachers and researchers as instructors would produce stronger effects than other instructors. In this study, multiple studies showed that various instructors taught ELLs, including teachers, graduate students, and researchers. The professional development of instructors is more important than that of those who taught ELLs. This finding is consistent with Richards-Tutor et al. (2016) . They also did not find differences between researcher-delivered interventions and school personnel-delivered interventions. Continuing professional development should build on the preservice education of teachers, strengthen teaching skills, increase teacher knowledge of the reading process, and facilitate the integration of newer research on reading into the teaching practices of classroom teachers ( Snow et al., 1998 ). Overall, professional development is the key factor in strengthening the reading skills of ELLs.
This study showed that medium-sized groups of 6 or more and 15 or less had larger effect sizes than the mixed groups. In addition, the medium-sized group showed a larger effect size than the small group of 5 or less. This finding showed that a multi-tiered reading system should be needed in the general classroom. This finding is linked to the fact that the reaction to intervention (RTI) approach is more effective for ELLs. Linan-Thompson et al. (2007) pointed out that RTI offers a promising alternative for reducing the disproportionate representation of culturally and linguistically diverse students in special education by identifying students at risk early and providing preventive instruction to accelerate progress. Regarding interventions for ELLs who are struggling with or at risk for reading difficulties, Ross and Begeny (2011) compared the effectiveness between small group interventions and implementing the intervention in a 1/1 context for ELLs. They showed that nearly all students benefitted from the 1/1 intervention, and some students benefitted from the small group intervention. This finding is commensurate with a previous study investigating the comparative differences between group sizes and suggests research-based support for the introduction of the RTI approach.
However, most implementation-related variables, including duration of intervention, the total number of sessions, frequency per week, length of each session, settings, and instructor, did not have any significant effect on the reading ability of ELLs. That is, ELLs are able to achieve their reading improvement regardless of the duration of intervention, where they received the reading intervention, and who taught them. This finding is similar to those discussed by Snyder et al. (2017) . They also synthesized the related interventions for ELLs and showed that the length of intervention did not seem to be directly associated with overall effect sizes for reading outcomes. This finding is also the same as recent research on intervention duration with native English speakers ( Wanzek et al., 2013 ). Wanzek and colleagues examined the relationship between student outcomes and hours of intervention in their meta-analysis. The findings showed no significant differences in student outcomes based on the number of intervention hours. Elbaum et al. (2000) stated that the intensity of the interventions is most important for effectiveness. Our results somewhat support these researchers’ opinions, but we cannot be certain that a brief intervention would have the same overall effect on reading outcomes as a year-long intervention. Thus, we should consider the intervention intensity, such as student attendance at the sessions, with the duration of the intervention.
The most effective and efficient education refers to education that is made up in the right ways, that includes proper content, and that is delivered on time so that the students can benefit the most. To implement this, research to identify a particular framework based on the synthesis of research results through meta-analysis, such as this study, must be conducted. Furthermore, the implications based on the results must be deeply considered. In this respect, important implications for the practice and research of practitioners, researchers, and policymakers on enhancing reading competence for ELLs of this study are as follows.
First, reading interventions for ELLs are expected to be the most efficient when conducted on a medium-sized group of 6–15 students. This indicates that implementing reading interventions for ELLs requires a specially designed group-scale configuration rather than simply a class-wide or one-to-one configuration. Second, the implementation of reading interventions for ELLs is most effective when conducted for older elementary school students. This is in contrast to Morgan and Sideridis (2006) , who demonstrated the characteristics of students with learning disabilities using multilevel meta-analysis and showed that age groups were irrelevant in the effect size of reading interventions for students with learning disabilities. Therefore, it can be seen that the ELLs group, unlike the learning disability group, the students of which have reading difficulty due to their disabilities, is in the normal development process but has reading difficulty due to linguistic differences. Accordingly, it can be seen that the senior year of elementary school, in which a student has been exposed to the academic environment for a sufficiently long time and language is sufficiently developed, is the appropriate time for learning English for ELLs. Third, effective reading interventions for ELLs should be performed with a strategy-embedded instruction program. This is based on the fact that strategic instructions are effective for vocabulary or concepts in unfamiliar languages ( Carlo et al., 2005 ; Chaaya and Ghosn, 2010 ).
The above implications require the implementation of Tier 2 interventions for reading interventions for ELLs in practice. In Tier 2 interventions, students can participate in more intensive learning through specially designed interventions based on their personal needs ( Ortiz et al., 2011 ). In other words, in policymaking and administrative decision-making, intensive education programs for ELLs who have been exposed to the academic environment for a certain period but still have reading difficulties, including having achievements that fall short of the expected level, are needed.
Considering further applications, these findings could guide practitioners and policymakers to develop effective evidence-based reading programs or policies. The significant variables in this study can be considered to develop new programs for ELLs.
Author contribution statement.
All authors listed have significantly contributed to the development and the writing of this article.
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A3A2A02103411).
Declaration of interests statement.
The authors declare no conflict of interest.
No additional information is available for this paper.
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This paper presents a study on the impact of ChatGPT as a formative feedback tool on the writing skills of undergraduate ESL students. Since artificial intelligence-driven automated writing evaluation tools positively impact students’ writing, ChatGPT, a generative artificial intelligence-propelled tool, can be expected to have a more substantial positive impact. However, very little empirical evidence regarding the impact of ChatGPT on writing is available. The current mixed methods intervention study tried to address this gap. Data were collected from tertiary level ESL students through three tests and as many focus group discussions. The findings indicate a significant positive impact of ChatGPT on students' academic writing skills, and students’ perceptions of the impact were also overwhelmingly positive. The study strengthens and advances theories of feedback as a dialogic tool and ChatGPT as a reliable writing tool, and has practical implications. With proper student training, ChatGPT can be a good feedback tool in large-size writing classes. Future researchers can investigate the impact of ChatGPT on various specific genres and micro aspects of writing.
Formative feedback positively impacts students’ writing (Anderson & Ayaawan, 2023 ; Butterfuss et al., 2022 Huisman et al., 2019 ). Usually associated with formative assessment strategies such as self-and peer assessment, formative feedback can be directed to address students’ needs for explanation (Bozorgian & Yazdani, 2021 ; Zhang et al., 2023 ) concerning various aspects of writing such as content, organization, grammar, vocabulary, and style. Since formative feedback is a continuous process, it offers real-time support to students as they write (Zhu et al., 2020 ). However, it is time-consuming and challenging to implement in a large classroom (Golzar et al., 2022 ). Such crowded classrooms are parts of everyday realities in many educational institutions in most developing and underdeveloped countries across the Global South. Addressing students’ individual feedback needs in such classrooms is a significant challenge. Computer-mediated feedback has evolved as a potential solution to this problem in writing classrooms (Taskiran & Goksel, 2022 ; Yamashita, 2021 ), especially in institutions of higher education in countries where students have access to portable computing devices and the Internet (Mahapatra, 2021 ). Globally, artificial intelligence (AI)-driven automated feedback is fast becoming a norm (Rad et al., 2023 ). Based on a large language model, ChatGPT, a relatively new addition to the repertoire of AI tools, can provide meaningful writing samples (Barrot, 2023 ), adjust the difficulty level of texts matching leaners’ proficiency level (Bonner et al., 2023 ), offer advice regarding various structural aspects of a text and translate it (Imran & Almusharraf, 2023 ), and facilitate guided writing (Kohnke et al., 2023 ). These affordances can aid self-reliance and fulfill instant feedback needs of students. It can provide human-like expert assistance to students in idea generation, organization, maintaining accuracy and choosing appropriate vocabulary (Tai et al., 2023 ). However, currently, little empirical evidence is available on the impact of ChatGPT on students' writing skills (Su et al., 2023 ). Though there are discussions on its utility as a feedback tool (Bonner et al., 2023 ), few empirical studies make such claims. Thus, the present study looked into the impact of ChatGPT as a feedback tool on the academic writing skills of undergraduate English as a second language (ESL) students in a relatively crowded classroom at a university. To achieve the aim, the study employed a mixed methods intervention design with ChatGPT (as a feedback tool) as the independent variable and writing skills as the dependent variable. It was hypothesized that the employment of ChatGPT as a feedback tool would significantly impact students’ writing skills. Considering that the study was set in relatively crowded classes, the findings can be generalized to similar ESL/English as a foreign language (EFL) settings. Additionally, the attempt to use ChatGPT as a feedback tool can be of significant pedagogic value and lead to further explorations globally.
The utility and positive impact of formative feedback in the writing classroom are well-established (Olsen & Huns, 2023 ). When operationalized in the form of self-and peer assessment (SA and PA), formative feedback leads to reflection, self-regulation, self-monitoring, and revision on the parts of students (Lam, 2018 ). SA and PA can be used to augment learning in large-size writing classrooms often encountered in developing and under-developed countries in the Global South (Fathi & Khodabakhsh, 2019 ; Mathur & Mahapatra, 2022 ). However, research on feedback in large writing classes is limited (Rodrigues et al., 2022 ). It has been reported that smarter techniques must replace traditional ways to offer personalized dialogic feedback to students (Kohnke et al., 2023 ). With the proliferation of AI-driven tools such as Grammarly, QuillBot, Copy.ai, WordTune, ChatGPT, and others, it has become easier for students to obtain feedback on their writing (Marzuki et al., 2023 ; Zhao, 2022 ). They have advanced automated writing evaluation (AWE) and feedback in writing (Gayed et al., 2022 ). While the literature on Grammarly as a feedback tool in the writing classroom is well-established (Fitriana & Nurazani, 2022 ; Koltovskaia, 2020 ; Thi & Nikolov, 2022 ) and its positive impact on writing has been investigated empirically (Chang et al., 2021 ), the use of AI chatbots like ChatGPT for leveraging feedback in writing classes is a relatively new area and requires further investigation (Barrot, 2023 ). Since ChatGPT is a large generative language model, its potential to help students with writing is immense. It is more student-friendly and can provide more need-based assistance than other AWE tools, as suggested by Guo et al. ( 2022 ) and Rudolph et al. ( 2023 ). It can support student writing by providing appropriate directions related to content and organization as they write (Allagui, 2023 ). Since it can automatically train itself and learn from previous conversations (Chan & Hu, 2023 ), students can receive tailored feedback suitable for individual needs.
Like earlier AI chatbots, ChatGPT can be used for generating ideas and brainstorming (Lingard, 2023 ). Recently, it has been accepted that ChatGPT can make writing easier and faster (Stokel-Walker, 2022 ). This potential, when exploited by teachers, can be converted into a dependable feedback tool. Wang and Guo ( 2023 ) discuss ChatGPT supporting students with learning grammar and vocabulary. As pointed out by Rudolph et al. ( 2023 ), irrespective of students’ ability to use language accurately to ask questions, ChatGPT can provide feedback and information. In another study by Dai et al. ( 2023 ), students received corrective feedback from ChatGPT. Mizumoto and Eguchi ( 2023 ) also highlight similar findings when they tried ChatGPT as an AWE tool. In a study conducted in Saudi Arabia, Ali et al. ( 2023 ) discuss the positive impact of its use on learners’ motivation. It could be due to its ability to provide reliable explanations (Kohnke et al., 2023 ) without the student having to go through the anxiety of asking the query in a classroom (Su et al., 2023 ). Since coming into existence in the last part of 2022 (OpenAI, 2022 ), ChatGPT has gained immense popularity among language educators. It has been reported as capable of producing high-quality texts (Gao et al., 2022 ), offering feedback on text organization, language use and recommending corrections (Ohio University, 2023 ), logically organizing content, adding appropriate supporting details and conclusion (Fitria, 2023 ). While Yan ( 2023 ) has reported benefits to students’ writing skills through its use, he has also warned that its use can threaten academic honesty and ethicality in writing.
Theoretically, the utilization of ChatGPT for leveraging formative feedback can be placed within a framework comprising two theories. The first one is the theory of feedback as a dialogic process advocated by Winstone and Carless ( 2020 ). According to them, when feedback involves interactions, it leads to students clarifying their expectations, obtaining desired information and guidance, and making progress in learning. ChatGPT facilitates dialogue by responding to the user’s queries regarding various aspects of writing. It offers suggestions when sought and functions as a support-on-demand tool. Additionally, it admits mistakes and rectifies itself thereby making dialogue meaningful. The second one is Barrot’s ( 2023 ) theory of ChatGPT as a reliable writing tool that can provide immediate, need-based, and tailored feedback to students as they move through different stages of writing. The current study was built on these two theories as its aim was to utilize ChatGPT as a formative feedback tool involving SA and PA, and assess its impact on students’ academic writing skills.
The study addressed the following two research questions:
In an intensive academic writing course, when the instructional hours and tasks are held constant, does the employment of ChatGPT as a feedback tool have any significant impact on undergraduate ESL students’ writing skills?
How do the experimental group students perceive the impact of ChatGPT as a feedback tool on their writing skills?
Mixed methods intervention design.
A mixed methods intervention design (Creswell & Plano-Clark, 2017 ) was adopted for the study. Since the study aimed to assess the impact of ChatGPT as a feedback tool and involved an intervention, a quasi-experimental design was an automatic choice for such a study, as with intervention studies in education (Gopalan et al., 2020 ). However, considering that qualitative data add to the validity of the claims and the strength of the study by providing in-depth details about how students used ChatGPT for self-and peer feedback during classroom assessments, it was logical to choose a mixed methods design. Figure 1 shows the design of the study.
Design of the study
An intact class of students randomly assigned to two sections was chosen for the study. This aligns with the sampling principle used for quasi-experimental studies in education and applied linguistics (Perry Jr., 2011 ). These were first-year science and engineering students in an elite private-run university in India. None of them had used ChatGPT to improve their writing skills before the intervention. However, the participants had the experience of using mobile phones, laptops, the Internet, and AI tools such as Grammarly. Most of them were from financially well-off backgrounds and had exposure to television, media, and books on various topics from an early age. They were informed about the nature of participation and what they were expected to do before the start of the intervention. Their participation was voluntary, and they were given the choice to opt out of the study at any point during the intervention. Finally, 78 people in the experimental group (EG) and 56 in the comparison group (CG) consented to participate in the study. Since they were in their first year, most students in CG did not know students from the EG. All of them studied in English medium schools before joining the undergraduate program, had English as their second language, and aged between 18 and 19 years. Only those who attended all the intervention classes, i.e., six hours and took the pre-, post-, and delayed post-tests, were included in the reported data. Thus, 35 students from the EG and 37 students from the CG were included in the study. Six students volunteered when invited to participate in focus group discussions (FGDs). However, only five students participated in all three FGDs. Table 1 presents the inclusion and exclusion criteria.
Data were collected for the study primarily through three tests of writing. Each test comprised three tasks focusing on process, comparison, and cause-effect (see “ Appendix ”). Since all students studied science before joining the undergraduate program, they were familiar with scientific contexts used in the tasks. The rationale behind the task choice was that the writing genres were frequently used for academic purposes by the target group of students and were also part of the regular syllabus. Rubrics were created by the researcher and another teacher, who also taught the course to other groups of students, for each writing task type and were validated by two experts in applied linguistics. The evaluation criteria in the rubrics included content, organization, grammar, and vocabulary. The researcher and the other teacher evaluated students’ writing performance using the rubrics. For all write-ups, Cohen’s Kappa was found to be more than 0.8, indicating a strong inter-rater reliability. The qualitative data for the study were collected through FGDs with five EG students. The FGDs focused on obtaining views about and experiences of using ChatGPT for self-and peer feedback purposes. They were also encouraged to share artefacts as screenshots during the FGDs.
Data were collected in various phases spanning almost an academic semester. First, students in the CG and EG took a pre-test. In the next phase, the EG was prepared through a short training program on using ChatGPT for SA and PA purposes in the writing classroom. In fact, Mathur and Mahapatra ( 2022 ) have recommended training for learners before using a digital tool in the classroom. After that, the intervention was undertaken in which the EG was taught process, comparison and cause-effect writing for six hours, and ChatGPT was used for SA and PA. Figure 2 presents the details about the intervention.
Intervention plan
During the intervention, which was completed in a month, two FGDs were organized to obtain information about students’ views on the employment of ChatGPT. The following prompts guided these discussions:
We are using ChatGPT to assess our own and our peers’ writing. How would you describe your experience with it?
We are getting feedback on the topic sentence, supporting details, concluding sentence, use of signposts, appropriateness of content, and grammar. How beneficial do you think this exercise is?
Do you have any suggestions for making the employment of ChatGPT more impactful?
In the fourth phase, a post-test was conducted for the CH and EG immediately after the end of the intervention. In the last phase, a delayed post-test was conducted for both groups and another FGD was conducted with five students from the EG. Both were organized almost two months after the post-test.
The quantitative and qualitative data were analyzed separately and then triangulated to obtain answers to the research questions. Statistical analyses were performed for the quantitative data, which comprised pre-test, post-test, and delayed post-test scores for the CG and the EG. In fact, Rose et al. ( 2020 ) recommend using delayed post-tests for the robust assessment of the intervention impact. It is also a practice in writing related interventions (Rezai et al., 2022 ). The data analysis involved a one-way RM ANOVA run on the EG’s scores across three tests to compare the corresponding mean scores. A post-hoc Bonferroni test (Loewen & Plonsky, 2017 ) was run to control the overall error rate due to RM ANOVA. Then, a one-tailed t -test was computed to compare the pre-test, post-test and delayed post-test mean scores of the CG and the EG. Before the t -tests were run, Levine’s test for equality of variance was calculated. The f -ratio value was 0.16078, and the p -value was 0.689658. The result was not significant at p < 0.05; thus, the homogeneity requirement is met. Also, a Shapiro–Wilk test was conducted to test normality. For the CG, it did not show a significant departure from normality, W (35) = 0.98, p = 0.675. For the EG too, no significant departure from normality was observed, W (37) = 0.96, p = 0.168. Grubb’s test, performed to identify outliers, did not find any.
The qualitative analysis involved coding the transcripts of the FGDs. A phronetic iterative approach (Tracy, 2019 ) was adopted in this case. The approach was found suitable because the coding was inductive, and at the same time, it was guided by the themes that emerged through the review of literature and a few known patterns.
The impact of ChatGPT as a feedback tool on students’ writing skills was positive and significant. The differences among the EG mean scores for the pre-test, post-test, and delayed post-test (see Table 2 ) indicate the trajectory of improvement in students’ writing skills.
The claim is strengthened by the results from the one-way RM ANOVA computations. The results (F [2, 72] = 330.704, p = 5.146e−37, η 2 = 0.902) indicate a significant difference among some of the mean scores across the tests. A Bonferroni post-hoc test was performed to trace any significant differences between pairs due to the intervention. The differences between the pre-test and post-test ( p < 0.001, d = − 3.300) and pre-test and delayed post-test ( p < 0.001, d = − 3.898) scores were found to be statistically highly significant. A significant difference was observed between the post-test and delayed post-test scores ( p < 0.01, d = − 0.598) (see Tables 3 , 4 and 5 ).
Since the findings from the one-way RM ANOVA offered little information about the comparative performance between the CG and the EG, two one-tailed independent sample t -tests were computed for both groups' post-test and delayed post-test scores. A significant difference was found between the post-test scores of the CG and the EG: t (70) = − 5.643, p = 3.297e−7, with the EG’s ( M = 19.216, SD = 2.485) mean score significantly higher than that of the CG ( M = 16.371, SD = 1.695). The difference continued to be statistically significant for the delayed post-test scores of the CG and the EG: t (70) = − 9.371, p = 5.544e−14, with EG’s ( M = 20.419, SD = 2.575) mean score significantly higher than that of the CG ( M = 15.400, SD = 1.897) (see Tables 6 , 7 and 8 ).
The FGDs were transcribed and coded. Table 9 presents the analysis.
The codes were classified under three main themes: content, organization, and grammar and two sub-themes: positive and specific and negative. When asked about their views on the impact of ChatGPT as a feedback tool, students in FGDs spoke in terms of content, organization, and grammar.
The way it guides us in obtaining the required information, arranging our ideas, and writing correctly is surprising. I was never aware that it could be a writing buddy. (S2, FGD 1) You see, when we were asking it to help us with organizing the ideas in writing, it gave us some directions. I guess that’s quite helpful. It’s like someone is constantly there to oversee your writing process. (S4, FGD 1) It’s actually better than Grammarly in the sense that it explains the grammar issues when asked. You have a choice, and you can also learn from it. (S1, FGD 2)
They seemed to be happy about how ChatGPT helped them generate ideas and focused information on the given topic and work independently.
The best part about ChatGPT is that you ask for information, and you get it. You can go as specific or detailed as you wish. This reduced our thinking time invested to get ideas and information. (S5, FGD 3) I felt that it was a handy support tool for writing without being dependent on anyone. When we write, we usually have queries regarding several aspects of writing. With ChatGPT, you have a reliable support system with you. I like that freedom. (S3, FGD 2)
They also highlighted how it promoted collaboration among peers, facilitated faster task completion, helped them create strong topic sentences and reduced brainstorming time.
When you use ChatGPT in a classroom with your classroom, you’re doing it with several people. So much talk going on simultaneously! It’s kinda cool. The conversations are so meaningful and without noticing, we are working together and writing. (S2, FGD 3) I absolutely love how we play with it together and how that fun is so productive. The process took much less time and there was this constant focused chatter which helped complete the tasks. We didn’t miss anything significant, for example, when cheating the topic sentence, because one or two people are working with me and giving me feedback on the topic and the strength of the controlling idea. (S4, SGD 2)
However, it was also pointed out on a few occasions that ChatGPT could lead to a lack of motivation to think and more machine dependence.
It might be a concern that my dependence might discourage me to do things on my own when writing. What if I won’t want to write on my own? It can be scary, but I don’t know. (S5, FGD 3)
In their comments on the impact of ChatGPT as a feedback tool on organization in writing, it was an overwhelming claim that ChatGPT made it easier to stay focused on the topic when writing.
We felt that it keeps us on our toes. You know it’s so easy to get diverted and include details unrelated to the topic. When you as ChatGPT, it tells you where you skid off the track. (S1, FGD 3) It’s unreal! You share the topic sentence and the supporting details and it tells you if and how you have adhered to the controlling idea in your details. Isn’t that cool? I don’t think we can do that so accurately on our own. (S3, FGD 3)
Students also mentioned that through feedback, they could add appropriate supporting details related to the main idea, use proper signposts, and write strong conclusions. More collaboration among peers when organizing the content was also highlighted.
When you asked us to write that paragraph on AI use in education, I created a topic sentence and added the required details along with a concluding sentence. When I asked GPT to tell me if my concluding sentence is a good one for the topic sentence, the feedback surprisingly good. I did the same when sharing feedback on my friends’ writing. (S5, FGD 2) I’m happy that I have improved my signpost use. In fact, most of my classmates have too. It made me conscious about the choice of signposts. The thread connecting information and ideas suddenly felt more robust. Sometimes, the explicit explanation with examples helped. (S4, FGD 3)
Though a minor, nonetheless, ChatGPT was claimed to impose a pattern on writing and hinder creativity in content organization.
I’m not sure, but sometimes it feels like I’m under a spell and I’m arranging information as directed. Though it’s my responsibility to choose and accept, I may be getting too lazy to use my own creativity to place things in order. (S2, FGD 3)
When talking about the impact of ChatGPT on grammar, students highlighted ChatGPT as a reliable source of grammar, a tool for improving accuracy in sentence structure and obtaining explanations for language errors.
I’ve been using Grammarly for a while, but it provides explanations for the grammar queries or when it identifies an error. Nothing like knowing the details about the issue. We kinda get sucked into curiosity by asking it questions on sentence structure, tense use and other aspects of grammar. It provides detailed explanations with examples. Good alternative to Grammarly, dictionary and other such stuff. (S1, FGD 3)
On several occasions, students shared artefacts showing how ChatGPT directs them to use of zero conditionals in scientific writing. Thus, when asked to verify ‘At first, we take a bowl full of water and heat it. When it boils, we will stop the stove. Then, we take it out.’ by a student, ChatGPT provides a polished version: ‘Initially, a bowl filled with water was taken and heated. Once the boiling point is reached, the stove was promptly turned off. Subsequently, the bowl was carefully removed.’ On some other occasions, students were encouraged by ChatGPT responses and sought further explanations related to the correct use of punctuation, articles, and sentence structures in formal contexts. In the above-mentioned case, ChatGPT explains that the use of past tense and passive voice are common in scientific writing, especially in the methods section and that passive voice adds to objectivity and clarity in writing.
The minor patterns included the claims related to helping with vocabulary choices, peer discussions and contributing to explicit knowledge of grammar. Two relatively minor patterns indicating negative impacts also emerged from the FGDs: lack of attention among students in terms of maintaining grammatical accuracy in writing and an increase in machine dependence.
This mixed methods intervention study assessed the impact of ChatGPT as a formative feedback tool on academic writing skills of undergraduate ESL students, which comprised the first research question. In addition, it also captured students’ views on the impact of ChatGPT on their writing skills, which was the focus of the second research question. The answer to the first question was obtained through the quasi-experimental study, and the FGD data was analyzed to find the answer to the second question. The findings from the experiment corroborated those from the FGDs. Few studies before this (published in mainstream journals) have empirically explored the impact of ChatGPT on academic writing skills. Thus, the current study bears significance. The study contributes to several areas of research on academic writing. First, it demonstrates the utilization of ChatGPT for formative feedback purposes in an academic writing classroom. Second, it is conducted in a natural setting without many intrusive measures. Last, the mixed methods intervention design employed for the study is relatively rare in academic writing research.
Though the CG and the EG students demonstrated improved writing skills during the period under consideration, the EG’s performance was significantly better than their CG peers across two post-intervention tests. Though there is little research on the impact of ChatGPT on students’ academic writing skills, the findings are consistent with those reported by researchers who focused on the impact of AI-driven AWE tools on tertiary-level students’ writing skills (Marzuki et al., 2023 ; Zhao, 2022 ). Many existing studies utilized these tools for formative purposes (Rudolph et al., 2023 ) and found similar results. Thus, the employment of generative AI only strengthens those claims. The positive impact was evident in students’ achievements in terms of generation of focused ideas, better connection among ideas and sentences, and improved grammatical accuracy, which were also claimed by previous researchers (Allagui, 2023 ; Kohnke et al., 2023 ; Su et al., 2023 ; Wang & Guo, 2023 ). The delayed post-test results in this study add to the generalizability of the positive impact claims (Rose et al., 2020 ). In fact, the literature on delayed post-tests highlights the sustainability of the impact and retention of writing skills (Rezai et al., 2022 ). The continued positive impact could be a result of various factors. First, planned training was organized for students before the intervention was undertaken, as advised by researchers who undertook similar interventions (Mathur & Mahapatra, 2022 ). Second, students were engaged in SA and PA, which have been proven effective strategies in writing classrooms (Mathur & Mahapatra, 2022 ). Third, the metalinguistic explanations as part of the corrective feedback could have made a difference, as claimed by many previous researchers (Kohnke et al., 2023 ). Fourth, the instant and personalized nature of the obtained feedback could have strongly impacted the continued positive impact (Gayed et al., 2022 ). Fifth, self-correction was made easy (Dai et al., 2023 ) Last, a major factor that might have shaped EG students’ performance in the study is their pre-intervention proficiency levels. They had to pass a challenging test of English to join the institution. Thus, future researchers may investigate language proficiency as a variable when determining the impact of ChatGPT. The fear regarding the loss of creativity and the imposition of a pre-decided pattern is an addition to the fear regarding the loss of ethicality and such issues reported by Yan ( 2023 ). Several other factors, like the affordances of ChatGPT as a writing tool and its ability to engage students in a dialogic feedback process, backed by theories of Barrot ( 2023 ) and Winstone and Carless ( 2020 ), also strengthened the theoretical foundations underpinning the use of ChatGPT. Through the empirical evidence on the utility of ChatGPT as a formative feedback tool in the academic writing classroom, this study establishes that the integration of ChatGPT into the academic writing instruction can yield positive impacts when the instructor is aware of the affordances of ChatGPT and knows how to guide students about its utilities. It also proves that the dialogic nature of ChatGPT can be fully put to use when students are adequately prepared.
The findings from the analysis of FGD data indicate an overall positive attitude towards the impact of ChatGPT. This finding is consistent with the literature on students’ views on the impact of ChatGPT and other AI-driven tools on their writing (Marzuki et al., 2023 ; Yan, 2023 ). The overall positive attitude can be explained by the enthusiasm for using ChatGPT in the classroom. The findings on how ChatGPT aids content generation align with Gayed et al.’s ( 2022 ), Guo et al.’s ( 2022 ) and Marzuki et al.’s ( 2023 ) claims. In fact, this confirms assertions in the education literature on ChatGPT. Staying focused on the topic is an added advantage which could be new to the literature.
On the other hand, the promotion of learner autonomy and peer collaboration are similar to findings in the AWE literature (Dai et al., 2023 ; Rudolph et al., 2023 ). The advantages of faster task completion and creating a more robust topic, and concluding sentences are attractive, as they are relatively new to the AWE and ChatGPT literature. They may need more microscopic investigation.
In terms of organization, the perceived impact confirms the findings of Allagui ( 2023 ) and Marzuki et al. ( 2023 ), who highlight the help with the organization of content in their study. Thi and Nikolov’s ( 2022 ) study on Grammarly reports negative perceptions related to organization, with which the current study disagrees. The reasons for this kind of perception may have to do with their ability to ask appropriate questions. It will be interesting to examine whether students with low proficiency levels can benefit from ChatGPT in terms of the organization of their content. Another overwhelming opinion that emerged from the study is that ChatGPT improves grammatical accuracy, which is in line with the claims by Ohio University ( 2023 ) and Wang and Guo ( 2023 ). Though it is an expected finding that strengthens results reported in Grammarly studies (Fitriana & Nurazani, 2022 ), the highlight here is the attention paid by students to the explicit metalinguistic feedback, which is also found in AWE literature (Kohnke et al., 2023 ). However, the lack of attention to accuracy-related details may need longitudinal-focused inquiries.
The study was an attempt to investigate the extent to which the employment of ChatGPT as a feedback tool impacts ESL students’ academic writing skills. It could be one of the earliest intervention-based empirical inquiries into the impact of ChatGPT on students’ academic writing skills. Conducted as a mixed methods intervention study, the study’s findings were on expected lines. The significant positive impact coupled with students' positive perception of the same can add a fresh perspective to the literature on ChatGPT and other AWE tools. The findings of the study add to the literature on AWE, especially the use of generative AI. They strengthen and further theories of feedback as a dialogic tool and ChatGPT as a formative feedback tool that can be harmoniously integrated into large writing classes. The findings of the study demonstrate that interactions facilitated by ChatGPT during the process of writing has a direct positive impact on student learning. It positively influences how students seek feedback, how they engage with it and how they make improvements in their academic writing. It enables students to overcome the anxiety involved in asking for and receiving the desired kind of feedback. In large classes, where feedback-related dialogue is a thorny issue, ChatGPT can be a potential game-changer. It can provide tailored feedback that goes beyond the barriers of language, time, and place. It may be safely claimed that students who may not be very proficient in English can ask for and receive help in their own language on ChatGPT. The study also makes a case for ChatGPT as a formative feedback tool that can drive writing forward through SA and PA. In a way, ChatGPT breaks the barrier between SA and PA and strengthens the role of a teacher as a facilitator because many time-consuming tasks in large size writing classrooms such as monitoring content, organization, vocabulary use and grammatical accuracy can be easily performed by ChatGPT.
The study establishes the potential of ChatGPT as a pedagogic tool for writing classrooms, especially in many Global South countries where students have access to portable computing devices and the Internet. It can be easily integrated into the regular teaching of academic writing skills in institutions of higher education. A major factor that needs mentioning is the teacher’s attitude towards ChatGPT and their ability to use it in a constructive manner in a large size classroom. The latter one includes self-and student-training. It is true that many webinars and workshops on the use of ChatGPT are being conducted for teachers working in Global South countries like India. However, without proper reflective planning and an analysis of the need for shunning traditional feedback strategies, the use of ChatGPT may not be as impactful. Thus, teacher education programs need to orient teachers towards utilizing ChatGPT in their writing classrooms.
Methodologically, using mixed methods intervention design, a potent way of conducting educational experiments, can be a significant addition to the applied linguistics literature. Though it is one of the first attempts to empirically investigate the impact of ChatGPT on students’ academic writing skills, the study has a few limitations. First, it focused on only three writing genres. Second, the intervention lasted for only six hours. Third, artefacts from students were not included in the study. Since the study used an intact classroom, which adds to the authenticity and validity of sampling, it was impossible to go beyond the prescribed syllabus, focus on more components and continue the intervention for more hours. The artefacts could have added to the study, but privacy and copyright issues were difficult to overcome. It may be difficult to ignore how the limitations could have shaped the findings. The findings could be true for only three genres, but a major genre like argumentative writing got ignored in the process. Thus, any generalization should be carefully worded. Also, the absence of artefacts hurts the validity of claims. The findings are entirely based on the tests and students’ opinions which could have been strengthened by the collection and analysis of artefacts from the classroom. Future researchers can investigate the impact of ChatGPT using an extended intervention period. More investigation is required to compare its impact on various writing genres and across various micro features. Another exciting area could be the impact of corrective metalinguistic written feedback given through ChatGPT on students’ writing skills. With ethical issues looming large, the future of writing research will nonetheless be dominated by generative AI writing tools like ChatGPT.
The data will be made available upon appropriate request to the author.
Artificial intelligence
English as a second language
English as a foreign language
Self-assessment
Peer-assessment
Automated writing evaluation
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by Joey Pitchford, North Carolina State University
A new study finds that science and social studies classes may also help young students learn English, even when those classes include difficult and technical vocabulary. The paper is published in the Journal of Educational Psychology .
The study, which observed first- and second-grade students in 30 elementary schools in North Carolina, encouraged teachers to keep their English-learning students in class during science and social studies lessons. Science and social studies textbooks in those grades are often relatively technical and difficult for students, so traditional teaching methods in North Carolina encourage teachers to remove English-learning students from those content classes to focus on their language skills instead.
By creating a 10-week literacy program—known as a Tier 1 intervention—which kept English-learners in science and social studies classes, researchers found that those students saw improvements in their ability to write argumentative essays and use new academic vocabulary. The study highlights the importance of giving English-learners access to academic content, said Jackie Relyea, corresponding author of the study and assistant professor of literacy education at North Carolina State University.
"This study shows how important it is to provide equitable opportunities for English-learners to build knowledge in science and history, and to apply that knowledge through informational texts alongside their peers," Relyea said. "What we found was that when English-learners have access to content-rich literacy instruction, they develop content knowledge as well as language, reading comprehension, and writing skills."
The program used methods like interactive read-alouds, collaborative research and concept mapping to build students' vocabulary and understanding of complex topics. Concept mapping refers to using diagrams or similar visual aids to depict connections between ideas.
Significantly, the study found that English-learners had similar levels of improvement in science and social studies vocabulary and argumentative writing as their English-proficient classmates across the 10-week program. Notably, the intervention did not lead to negative results elsewhere, which supports the idea that English-learning students can attend more complex classes without falling behind. This further suggests that content-rich literacy instruction may help narrow the achievement gap between English-learners and their peers.
The intervention also modified classes to cover individual subjects for longer. That way, Relyea said, English-learners could get comfortable with a subject early on and then continue to get value from that knowledge later.
"One thing we noticed is the importance of using coherent text sets that focus on a single topic. In more traditional literacy instruction, our study found that topics tended to change quickly and there wasn't always a consistent throughline that the students could grab on to," she said.
"By focusing on similar subjects for longer, kids can dig deeper and develop more in-depth knowledge. It may be challenging at first, but when students encounter the same new words day after day, they become familiar with them and expand their vocabulary network. Staying on a thematic unit for longer periods also helps them become experts in the subject matter, which greatly enhances their vocabulary and comprehension skills."
The study challenges widely held assumptions about English-learners' academic capabilities, and highlights their readiness to engage with complex subject material despite their developing English proficiency. Relyea said that further research into incorporating small-group supplemental instruction could be valuable, potentially enhancing the effectiveness of the program even further.
Journal information: Journal of Educational Psychology
Provided by North Carolina State University
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A state prosecutor has opted against filing charges against Brevard County Commissioner John Tobia , after investigating a series of allegations of wrongdoing brought by a former Tobia employee.
Florida Department of Law Enforcement reports of its staff's interviews with two current employees in Tobia's office appeared to back up some of former employee Christopher Davis' allegations, but did not address others.
The allegations are contained in a 247-page case file obtained by FLORIDA TODAY from the State Attorney's Office for the 7th Judicial Circuit, which handled the case. The investigation was transferred in November by Gov. Ron DeSantis from the 18th Judicial Circuit that includes Brevard to the Daytona Beach-area 7th Circuit, at the request of 18th Circuit State Attorney Phil Archer, who wanted to avoid a conflict of interest or any appearance of impropriety.
Davis, a former administrative aide in Tobia's Palm Bay office, alleges in sworn statements to investigators that Tobia:
Transferred to another district: County Commissioner John Tobia under investigation for alleged voter fraud
In response to the allegations and the state attorney's office's decision not to file charges, Tobia told FLORIDA TODAY: "This was a witch-hunt initiated by a disgruntled former employee terminated for cause and perpetuated by a desperate political opponent who believed this was his path to victory, while concealing his past as a registered Democrat."
Davis on March 20, 2023, was hired to the administrative aide position in Tobia's District 3 commission office. Tobia is completing his second four-year term as commissioner for District 3, which covers parts of South Brevard County.
Davis' personnel file shows that Davis submitted a letter of resignation to Tobia, dated June 27, 2023, indicating that his resignation would have been effective on July 12, 2023.
Tobia said he fired Davis because Davis took a list of personal passwords off Tobia's desk at his Palm Bay commission office. A July 3, 2023, letter from Tobia to Davis in Davis' personnel file said: "Due to recent events, your employment is henceforth terminated due to cause, effective immediately."
Tobia also filed a complaint about Davis with the Brevard County Sheriff's Office about the matter. There is no indication of the status of that matter in the state attorney's office file, and a previous FLORIDA TODAY inquiry to a BCSO spokesman was not answered.
According to FDLE investigative reports, Davis has contended that a list of Tobia's work-related and personal passwords and log-ons were part of an "information manual" provided to employees of Tobia's commission office, and that he did not take the passwords illegally. Davis said he maintained possession of the information manual with the belief the manual was given to him.
Responding to Tobia's contention that Bobanic is trying to hide his Democratic past, Bobanic told FLORIDA TODAY that he briefly switched his voter registration from Republican to Democratic in 2012, while he was working at the Hillsborough County Supervisor of Elections Office, Bobanic said that was so he could be eligible to vote in a Democratic primary there for his then-boss, who was running in that primary for supervisor of elections. After that primary was over, Bobanic said he switched his registration back to Republican.
In response to Davis' allegations contained in case file, Tobia said: "I categorically deny these baseless accusations."
In a document filed June 19 in County Court in Daytona Beach, 7th Judicial Circuit Assistant State Attorney Sarah Thomas said she did not intend to prosecute the case against Tobia on a charge of unlawful possession of personal identification information over Tobia's attempt to get Bobanic's hotel records. No other potential charges were listed in that document.
So far, Thomas has provided no further details in the case file related to her decision.
Bobanic questions the decision not to prosecute.
"It seems to be a clear-cut case of identity theft by Commissioner Tobia and his staff to make up an email impersonating me to try to get information on a hotel bill," Bobanic alleged.
The case file included a series of investigative reports written by staff of the Florida Department of Law Enforcement Office of Executive Investigations.
In one report, the investigator wrote that Davis said Tobia wanted him to obtain the receipts from the Fairmont Hotel in Washington, where Bobanic stayed during a work-related trip, "to determine if Bobanic was lavishly spending taxpayer money." Davis said Tobia asked him to call the hotel to get the information. When the hotel asked for an email request from the customer, Davis said he was instructed by Tobia to create a fake email account, write the email, and make it appear that it was coming from someone named Timothy or Tim.
Bobanic told investigators that his trip to Washington was at the request of the U.S. Election Assistance Committee so he could present on how Brevard County conducts post-election audits, and that it was financed by the U.S. Treasury, so no county taxpayer funds were used.
Two current staff members in Tobia's office also were interviewed by FDLE officials. But Tobia's attorney told an FDLE inspector on Nov. 7 that Tobia would not provide a statement to investigators.
Two FDLE inspectors on Sept. 27 interviewed both Bethany Prasad, chief of staff for Tobia, and Brian Bond, Tobia's legislative aide.
According to FDLE reports, "Prasad acknowledged that Tobia requested Davis to find out how much Bobanic paid" for the hotel room. She described Tobia "as fiscally concerned, saying Tobia believed travel was a frivolous, often-abused item. Prasad admitted she was the person who came up with the email for Davis to send to the hotel."
A Nov. 14 FDLE report indicated that, "based on the evidence gathered, there is probable cause to believe that the email address was created and sent to the Fairmont Hotel to obtain Bobanic's bill. It is also apparent that the author of the email made it appear there was an affiliation to Bobanic."
But they said the matter fell short of requirement for prosecution because there was no use of Bobanic's official state-issued driver's license number, Social Security number or other personal identification information.
Questions about deposition: Deposition alleges withholding of public records in lawsuit involving School Board members
According to one FDLE report, Prasad indicated that she assisted Tobia by logging into his Valencia College account, and "has assisted him in grading papers." She said Tobia was "technologically impaired," so she also helped him in setting up his new classes when the college made changes to its online system.
A separate FDLE report said Bond indicated that there were occasions when he assisted Tobia with his Valencia College work, including helping when there was a syllabus change and occasionally helping "cross-reference grades."
When investigators asked Prasad if there was anything illegal, immoral or unethical that she was aware of that had occurred at her office, Prasad "advised that she did not like doing Tobia's personal work, but did not feel that it rose to the level of being unethical," the report said.
The report on the Bond interview said Bond acknowledged that he used Tobia's account with webElect, a voter registration database, "in a limited capacity for constituent research. According to Bond, he used the program to better understand a voter, to determine their party and to know their affiliations."
Nevertheless, Bond told investigators that "each person who contacts Tobia's office gets a response, regardless," the FDLE report said.
That conflicts with an allegation by Davis that registered Democrats or those not having a high enough "score" were to be ignored.
Prasad also told investigators that she used webElect "to conduct informational research on Tobia's constituents," including "to research/verify if a constituent is in Tobia's district," according to an FDLE report.
The FDLE also investigated whether Tobia actually lived at the Palm Bay address he listed on voting documents as his home address. Davis alleged that Tobia actually lived outside his commission district.
According to an FDLE report, the owner of the Palm Bay home told FDLE inspectors that she lived there with her adult daughter, and that she rented a room to Tobia for $300 a month. She said, while some of Tobia's clothes and other belongings were in the rented room and in a garage at the home, Tobia was there only occasionally.
The FDLE concluded that "probable cause has not been established that a crime has been committed," related to the issue of Tobia's address.
Brevard County Attorney Morris Richardson sat in on the interviews with Bond and Prasad.
According to a report in the case file, Richardson said the county's view is that county officials "typically let commissioners run their offices at their discretion."
"As such, it would be necessary for county administrators to determine if the actions of any of the individuals within the District 3 commissioner's office constitute a violation," including if they are criminal in nature or would be more property addressed through county disciplinary procedures, the report said.
Dave Berman is business editor at FLORIDA TODAY. Contact Berman at [email protected] , on X at @bydaveberman and on Facebook at www.facebook.com/dave.berman.54
Dr Phyllisienne Gauci from the Department of Inclusion and Access to Learning within the Faculty of Education , presented a paper on the challenges of language integration in Malta at the Multidisciplinary Approaches in Language Policy and Planning Conference (LPP 2024). The conference took place at Carleton University in Ottawa, Canada, between 27 June and 1 July 2024. The paper delved into the intricate challenges of language integration in Malta, the smallest nation within the European Union, which has witnessed unparalleled migrant population growth over the last decade. The complexity arises from Malta's bilingual status, with Maltese and English serving as official languages, each differing markedly in their functions and domains of usage. In an attempt to address its rapidly changing socio-demographic landscape, Malta initiated the Migrant Integration Strategy & Action Plan in 2017 with the intention of setting up a stronger framework for the integration of migrants who were already working and living in Malta. As part of this initiative, the I Belong program was established, serving as a prerequisite for non-EU nationals aspiring to attain long-term residence status. The paper presents a scholarly examination, drawing upon data collected from over 350 students who completed the I Belong Stage 2 Maltese language integration program. Through rigorous analysis, this contribution illuminates the efficacy and relevance of the program and its ramifications within the context of Malta's evolving social fabric. By offering empirical insights, this research contributes substantively to the academic understanding of language integration strategies and informs future policy frameworks not only in Malta but also in comparable sociolinguistic contexts. The study was possible thanks to the University of Malta Research Seed Fund 2023.
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Resilience is the process and outcome of successfully adapting to difficult or challenging life experiences, especially through mental, emotional, and behavioral flexibility and adjustment to external and internal demands.
A number of factors contribute to how well people adapt to adversities, including the ways in which individuals view and engage with the world, the availability and quality of social resources, and specific coping strategies.
Psychological research demonstrates that the resources and skills associated with resilience can be cultivated and practiced.
Adapted from the APA Dictionary of Psychology
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59 Pages Posted: 18 Jul 2024
University of Pennsylvania - The Wharton School
University of Pennsylvania - Department of Computer and Information Science
Budapest British International School
Independent; Independent
Date Written: July 15, 2024
Generative artificial intelligence (AI) is poised to revolutionize how humans work, and has already demonstrated promise in significantly improving human productivity. However, a key remaining question is how generative AI affects learning , namely, how humans acquire new skills as they perform tasks. This kind of skill learning is critical to long-term productivity gains, especially in domains where generative AI is fallible and human experts must check its outputs. We study the impact of generative AI, specifically OpenAI's GPT-4, on human learning in the context of math classes at a high school. In a field experiment involving nearly a thousand students, we have deployed and evaluated two GPT based tutors, one that mimics a standard ChatGPT interface (called GPT Base) and one with prompts designed to safeguard learning (called GPT Tutor). These tutors comprise about 15% of the curriculum in each of three grades. Consistent with prior work, our results show that access to GPT-4 significantly improves performance (48% improvement for GPT Base and 127% for GPT Tutor). However, we additionally find that when access is subsequently taken away, students actually perform worse than those who never had access (17% reduction for GPT Base). That is, access to GPT-4 can harm educational outcomes. These negative learning effects are largely mitigated by the safeguards included in GPT Tutor. Our results suggest that students attempt to use GPT-4 as a "crutch" during practice problem sessions, and when successful, perform worse on their own. Thus, to maintain long-term productivity, we must be cautious when deploying generative AI to ensure humans continue to learn critical skills. * HB, OB, and AS contributed equally
Keywords: Generative AI, Human Capital Development, Education, Human-AI Collaboration, Large Language Models
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MINNEAPOLIS / ST. PAUL (7/18/2024) – Seven graduate students advised by Department of Chemistry faculty members were recently awarded the University of Minnesota’s Doctoral Dissertation Fellowship. The seven students honored by this prestigious award are Kaylee Barr, Brylon Denman, Madeline Honig, Chris Seong, Sneha Venkatachalapathy, Murphi Williams, and Caini Zheng.
Kaylee Barr , a Chemical Engineering and Materials Science PhD student, is entering her fifth year in the Reineke Group . Before making the move to Minnesota, she received her BS in Chemical Engineering from the University of Kansas. “I came to the University of Minnesota because of the department's developments in polymer science, and because I was interested in the intersection of polymer science and drug delivery in Theresa Reineke's lab,” she says. Here at UMN, Kaylee studies how bottlebrush polymer architecture affects pH-responsive oral drug delivery. This summer, she is excited to grow professionally and as a scientist in an intern position at Genentech.
Brylon Denman is a Chemistry PhD candidate in the Roberts Group . She joined the UMN community in 2020 after completing her BS in Biochemistry at St. Louis University. “My research in the Roberts group seeks to resolve regioselectivity and reactivity issues within aryne methodology via ligand control,” Brylon says. “To accomplish this task, I have taken a mechanistic and hypothesis driven approach to understand how key molecular parameters modify regioselectivity and reactivity. I hope to use the knowledge I have gained from these studies to both improve the synthetic utility of aryne intermediates, and improve the sustainability of aryne reactions.” Brylon is also passionate about sustainable and green chemistry. As a founding member of the Sustainable and Green Chemistry committee, Brylon strives to collaborate with other department teammates to strengthen the culture of green and sustainable chemistry through integration into teaching, research, and community engagement. “In my career I aim to continue this advocacy and use my breadth of knowledge to enact sustainable change at a major pharmaceutical company as emphasizing sustainability on such a large scale can lead to a large impact,” she says. As she works through her internship at AbbVie this summer, Brylon is looking towards the future to outline her next steps after graduation.
Madeline Honig first experienced Chemistry at UMN during a summer REU experience in the Bühlmann Lab . She formally joined the Prof. Bühlmann's team in Fall 2020 after earning her BA in Chemistry from Earlham College. Her research here at UMN has focused on the development and improved understanding of polymeric membrane-based ion-selective electrodes (ISEs). “One of my projects involves developing a quantitative parameter to better define the upper detection limits of these sensors which can be used to more accurately define sensor performance and predict the working range under different conditions,” Madeline says. “This research led us to investigate the unexplained 'super-Nernstian' responses of some pH-selective electrodes and expand the phase boundary model (the quantitative model that predicts ISE behavior) to include the formation of complexes between protonated ionophores and counter-ions in the sensing membrane. ISEs have been widely used for decades in clinical blood analysis among many other applications so it's exciting that I was still able to add to our fundamental understanding of how these sensors function.” One of Madeline’s goals is to use her research to enable the development of improved sensors that can be used in a wider range of conditions. Over the course of her graduate studies, Madeline has had the opportunity to be a graduate student mentor for two other students: Ariki Haba, a visiting master's student from Japan, and Katie O'Leary, a summer REU student, who both made significant contributions to the project. “Acting as a graduate mentor was really cool and I hope I can also make graduate-level chemistry research more approachable for everyone that I work with,” Madeline says. For her significant research efforts, Madeline was also recently selected in a national competition as one of the four winners of the 2024 Eastern Analytical Symposium Graduate Student Research Award. She will accept the award in November in Plainsboro NJ at the Eastern Analytical Symposium.
Chris Seong , an international student from New Zealand and PhD candidate in the Roberts Group, came to UMN after completing his BA with Distinction in Chemistry at St. Olaf College in 2020. Chris’ overarching chemistry interests involve the development of methods to utilize naturally abundant carboxylic acids as feedstock to synthesize medicinally relevant products, which are traditionally made with non-renewable starting materials derived from fossil fuels. “My earlier work has been focused on making alkyl-alkyl bonds through decarboxylation, but lately, in true Roberts Group fashion, I have turned my attention to using a similar mechanism to do aryne chemistry,” Chris says. He is currently working to publish a paper on the aryne project that he has been working on with two talented group mates; Sal Kargbo and Felicia Yu. “I am really excited to share this cool chemistry with the world,” he says. Outside of the lab, Chris is working on expanding his network to apply for jobs in the pharmaceutical industry – specifically in the early process space.
Sneha Venkatachalapathy is a member of the Distefano Group and an international student from India. She completed her BS in Chemistry with a minor degree in Biotechnology from Shiv Nadar University, Greater Noida, India in 2020. “Chemistry has always been my passion since high school. I still remember my first successful brown ring test that has left a remarkable fascination and interest towards chemistry,” Sneha says. “This early fascination has driven my academic journey, guided by mentors like Dr. Subhabrata Sen, who encouraged me to pursue a PhD in the United States.” Sneha was drawn towards working in the Chemical Biology research field where she could directly contribute to developing human life. “Joining Dr. Mark Distefano’s lab at UMN provided me with the chance to collaborate with Dr. Mohammad Rashidian from Dana Farber Cancer Institute. Together, we work towards expanding the scope of protein prenylation to construct protein-based cancer diagnostic tools,” she says. Sneha’s goal for her time in the UMN PhD program is to create innovative protein-based tools for cancer detection and treatment, aiming to enhance patient’s quality of life. She says she is looking forward to continuing to develop her leadership skills as she continues her doctorate, and is also exploring future opportunities beyond UMN. “One thing that motivates me daily is the belief that my research contributions to the scientific community would enhance our understanding of cancer diagnostic methods, ultimately leading to improved patient outcomes worldwide,” she says.
Murphi Williams completed her undergraduate studies at the University of Wisconsin-Eau Claire, then joined the Bhagi-Damodaran at UMN in 2020. When it comes to research, Murphi is interested in chemical biology, more specifically, looking into proteins involved in important biological problems. “One of my major projects is developing and characterizing a potential inhibitor for Mycobacterium tuberculosis , the bacteria that causes tuberculosis,” Murphi says. “Tuberculosis is the leading infectious disease so my projects center on understanding and inhibiting heme proteins important for the bacteria. Specifically, a previous lab member identified a small molecule that I've been characterizing the activity of in cells.” Her current research goal is to express and purify the protein targets for her small molecule inhibitor in the lab to further demonstrate the in vitro activity. She is also contemplating a future career in science communication. Outside of the lab, she enjoys working on her garden.
Caini Zheng joined the Chemistry at the UMN in 2019 after finishing her undergraduate studies at Shanghai Jiao Tong University. She is currently a sixth-year graduate student co-advised by Profs. Tim Lodge and Ilja Siepmann . Her research focuses on the phase behavior of soft materials, including polymers and oligomers. Her DDF statement is titled "Self-Assembly of Polymers and Amphiphiles into Bicontinuous Phases". Caini is currently working on a project to elucidate the self-assembly of glycolipids through molecular dynamics simulations coupled with machine learning methods. In the future, she wants to work in the industry on bridging data science with traditional material research.
COMMENTS
In English classes, teacher-student interactions in English are essential for fostering the students' intrinsic motivation and understanding of the importance of mastering the English language ...
The Development and Maintenance of The Internet TESL Journal. By Charles I. Kelly and Lawrence E. Kelly. Overcoming the Fear of Using Drama in English Language Teaching. By Judith Gray Royka. Virtual Reality for ESL Students. By Hee-Jung Jung. Integrating English into an Elementary School Life Course.
Library resources and information for students of English as a Second Language. Skip to Main Content. Library; LibGuides; ESL (English as a Second Language) Research Guide; Writing a Research Paper; ... Research Papers, Reports, Theses by Slade. Call Number: LB2369 .C3 1999. ISBN: 039595827X. Publication Date: 1999. Research Paper Fundamentals ...
A Review of the Literature on ESL Issues / v ©Alberta Education, Alberta, Canada 2008 Preamble The Language Research Centre at the University of Calgary was contracted by Alberta Education to produce an annotated bibliography on diverse aspects of education related to English as a Second Language (ESL) students.
1. Introduction1.1. Importance of motivation to learn EFL/ESL in the current world. Motivation to learn English as a second or foreign language (ESL/EFL) is an ever-quickening pulse in a world where English is the lingua franca (ELF) and where effective communication in global trading, policy, and diplomacy is crucial (Woodrow, 2016).However, national and international scenarios are increasing ...
PDF | On Dec 4, 2022, Nurul Intan Hipni Helen Kenol and others published Language Learning Strategies Used by ESL Students in Enhancing English Proficiency: A Systematic Review (2013-2022) | Find ...
This paper is a review of previous studies on learners' interactional feedback exchanges in face-to-face peer review (FFPR) and computer-assisted peer review (CAPR) of English as Second/Foreign Language (ESL/EFL) writing. The review attempted to (1) identify the patterns of interactional feedback, (2) search an empirical evidence of learners' incorporation of peer interactional feedback in ...
E-mail: [email protected]. Abstract - This paper sheds light on the reading practices of English as Second Language (ESL) Learners. It aimed at. identifying some of their basic reading ...
The Internet TESL Journal is a free online journal for teachers of English as a second language that includes lesson plans, classroom handouts, links of interest to ESL teachers and students, articles, research papers and other things that are of immediate practical use to ESL teachers.
The experience of teaching ESL varies greatly from country to country. Write a research paper comparing the salary, hours, case studies and living aspects of ESL teachers from three to five different locations. Or, write a persuasive essay comparing the details of teaching or studying ESL in the United States to teaching or studying ESL overseas.
This paper presents both a discussion of experimental-research paper organization and a method for teaching reading and writing of experimental-research articles to ESL students. ESL teachers are advised to teach students to analyze the reading purpose first, and then to select a reading strategy to meet that purpose.
Peer feedback is essential in writing English as a Second/Foreign Language (ESL/EFL). Traditionally, offline PF was more widely favored but nowadays online peer feedback (OPF) has become frequent in ESL/EFL learners' daily writing. This study is undertaken to probe into the gains of using OPF in ESL/EFL writing on the basis of 37 research ...
This article proposes to incorporate Freirean philosophy with a technique used in academic (monolingual) English courses: the multigenre research paper. When applying this technique in the ESL classroom, it is crucial to also use global and international texts of various genres in order to support students' cultural iden-tities and also ...
This paper presents both a discussion of experimental-research paper organization and a method for teaching reading and writing of experimental-research articles to ESL students. ESL teachers are advised to teach students to analyze the reading purpose first, and then to select a reading strategy to meet that purpose.
Reid T., Heck R.H. Exploring reading achievement differences between elementary school students receiving and not receiving English language services. AERA Online Paper Repositor. 2017 [Google Scholar] Richards-Tutor C., Baker D.L., Gersten R., Baker S.K., Smith J.M. The effectiveness of reading interventions for English learners: a research ...
Use this guide to find and evaluate information and resources related to learning English as a Second Language (ESL) or English for non-native speakers. It also includes resources for teachers of ESL. ... Research skills develop critical thinking and equip you to write better research papers and craft better speeches. You will also improve ...
These 74 students were second and third semester ESL students from various courses. The instrument developed for this study is the Online Research And Comprehension Strategies (ORACS) survey. The ORACS survey consisted of 37 items. Sixteen items were based on the five processes involved in online research and comprehension activities suggested ...
This paper presents a study on the impact of ChatGPT as a formative feedback tool on the writing skills of undergraduate ESL students. Since artificial intelligence-driven automated writing evaluation tools positively impact students' writing, ChatGPT, a generative artificial intelligence-propelled tool, can be expected to have a more substantial positive impact.
Paper−Use of I-Ready in Tiered Instruc ons for ESL Students: A Quan ta ve Case Study 94 there was a 5 % growth in the PH domain by the end of the y ear.
The paper is published in the Journal of Educational Psychology. A new study finds that science and social studies classes may also help young students learn English, even when those classes ...
Davis, a former administrative aide in Tobia's Palm Bay office, alleges in sworn statements to investigators that Tobia: Used staff in his commission office to help him grade papers of students he ...
Dr Phyllisienne Gauci from the Department of Inclusion and Access to Learning within the Faculty of Education, presented a paper on the challenges of language integration in Malta at the Multidisciplinary Approaches in Language Policy and Planning Conference (LPP 2024). The conference took place at Carleton University in Ottawa, Canada, between 27 June and 1 July 2024.
Dedicated student and administrator guidance hubs. Visit the Student hub area to locate student guidance. For students who access Turnitin via an LMS or VLE, check out the subsection Submitting to Turnitin. Visiting the Administrator hub area to locate administrator guidance and release notes.
Undoubtedly, due to continuous changes in time, environment, and demand, teaching techniques in science education should be constantly explored, reflected upon, and improved. This paper explores the current evidence related to secondary science teachers' perspectives about teaching inquiry skills in the United Arab Emirates (UAE). After a systematic Boolean search in online databases, a ...
Resources for students, teachers and psychologists at all levels to explore career growth in psychology. Education. Pre-K to 12; Undergraduate Psychology; ... Psychological research demonstrates that the resources and skills associated with resilience can be cultivated and practiced. Adapted from the APA Dictionary of Psychology.
That is, access to GPT-4 can harm educational outcomes. These negative learning effects are largely mitigated by the safeguards included in GPT Tutor. Our results suggest that students attempt to use GPT-4 as a "crutch" during practice problem sessions, and when successful, perform worse on their own.
This paper is therefore believed to make a great contribution to practical applications for RPW program developers, lecturers, undergraduate and postgraduate students in EFL/ESL contexts. Keywords: EFL/ESL undergraduate students, Research Paper Writing (RPW) program, Process Genre Approach (PGA) 1. Introduction.
MINNEAPOLIS / ST. PAUL (7/18/2024) - Seven graduate students advised by Department of Chemistry faculty members were recently awarded the University of Minnesota's Doctoral Dissertation Fellowship. The seven students honored by this prestigious award are Kaylee Barr, Brylon Denman, Madeline Honig, Chris Seong, Sneha Venkatachalapathy, Murphi Williams, and Caini Zheng.
Future research should focus on the CCC strategy application to improve their vocabulary skills for ESL students who also have LD. Discover the world's research 25+ million members
This brief is a continuation of NWEA's research series examining the impact of the COVID-19 pandemic on student achievement and progress toward academic recovery. Initiated in the early phase of the pandemic, this series has leveraged NWEA's large national sample of longitudinal MAP® Growth™ data to track .