In this study, we integrated corpus technology in pre-service TESOL (Teaching English to Speakers of Other Languages) teachers' technological pedagogical content knowledge (TPACK) development in corpus technology, termed corpus-based language pedagogy (CBLP), and highlighted the collaborative effort for knowledge building among participants for TPACK development. The study examined the role of online collaboration in facilitating how pre-service TESOL teachers developed their CBLP (TPACK in corpus technology) using a learning-by-design approach, enacted it in co-designing lessons, revised their lessons and reflected on their collective knowledge building processes. Using a case study approach involving 33 participants, the study focused on both intra- and inter-group interactions to understand the pre-service teachers' learning dynamics/changes and unpack the interaction mechanism involved in online collaborative learning. To these ends, we collected data including CBLP group lesson designs, intra-group data (interviews) and inter-group peer critical comments and analysed them based on the two stages (comprehension and transformation) of Shulman's pedagogical reasoning. The results suggest that engaging in online collaboration, facilitated by the learning-by-design approach, is instrumental in enabling pre-service teachers to learn corpus technology and expand their repertoire of teaching strategies. Our findings imply that both intra- and inter-group collaboration modes are important to help pre-service TESOL teachers holistically develop TPACK for language teaching. Similar implications may be applied to other subject-specific TPACK training.
{"title":"Learning by design: Enhancing online collaboration in developing pre-service TESOL teachers' TPACK for teaching with corpus technology","authors":"Qing Ma, Hiu Tung Hubert Lee, Xuesong (Andy) Gao, Ching-sing Chai","doi":"10.1111/bjet.13458","DOIUrl":"10.1111/bjet.13458","url":null,"abstract":"<p>In this study, we integrated corpus technology in pre-service TESOL (Teaching English to Speakers of Other Languages) teachers' technological pedagogical content knowledge (TPACK) development in corpus technology, termed corpus-based language pedagogy (CBLP), and highlighted the collaborative effort for knowledge building among participants for TPACK development. The study examined the role of online collaboration in facilitating how pre-service TESOL teachers developed their CBLP (TPACK in corpus technology) using a learning-by-design approach, enacted it in co-designing lessons, revised their lessons and reflected on their collective knowledge building processes. Using a case study approach involving 33 participants, the study focused on both intra- and inter-group interactions to understand the pre-service teachers' learning dynamics/changes and unpack the interaction mechanism involved in online collaborative learning. To these ends, we collected data including CBLP group lesson designs, intra-group data (interviews) and inter-group peer critical comments and analysed them based on the two stages (comprehension and transformation) of Shulman's pedagogical reasoning. The results suggest that engaging in online collaboration, facilitated by the learning-by-design approach, is instrumental in enabling pre-service teachers to learn corpus technology and expand their repertoire of teaching strategies. Our findings imply that both intra- and inter-group collaboration modes are important to help pre-service TESOL teachers holistically develop TPACK for language teaching. Similar implications may be applied to other subject-specific TPACK training.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13458","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140602904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Olga Viberg, Chantal Mutimukwe, Stefan Hrastinski, Teresa Cerratto-Pargman, Joakim Lilliesköld
Digital technologies are increasingly used in assessment. On the one hand, this use offers opportunities for teachers to practice assessment more effectively, and on the other hand, it brings challenges to the design of pedagogically sound and responsible digital assessment. There is a lack of validated instruments and models that explain, assess and support teachers' critical pedagogical practice of digital assessment. This explorative work first develops and validates a survey instrument to examine teachers' digital assessment practices. Secondly, we build a model to investigate to what extent teachers' pedagogical digital assessment knowledge is a foundation for the future of digital assessment (ie, authentic, accessible, automated, continuous and responsible). A total of 219 university teachers at a large European university participated in the survey study. Factor exploratory analysis and structural equation modelling were used to validate the reliability and validity of items and internal causal relations of factors. The results show the survey is a valid and reliable instrument for assessing teachers' digital assessment practice in higher education. Teachers' pedagogical knowledge and pedagogical content knowledge of digital assessment is critical, while teachers' technological pedagogical knowledge seems to have a more limited impact on the future of digital assessment.
{"title":"Exploring teachers' (future) digital assessment practices in higher education: Instrument and model development","authors":"Olga Viberg, Chantal Mutimukwe, Stefan Hrastinski, Teresa Cerratto-Pargman, Joakim Lilliesköld","doi":"10.1111/bjet.13462","DOIUrl":"10.1111/bjet.13462","url":null,"abstract":"<p>Digital technologies are increasingly used in assessment. On the one hand, this use offers opportunities for teachers to practice assessment more effectively, and on the other hand, it brings challenges to the design of pedagogically sound and responsible digital assessment. There is a lack of validated instruments and models that explain, assess and support teachers' critical pedagogical practice of digital assessment. This explorative work first develops and validates a survey instrument to examine teachers' digital assessment practices. Secondly, we build a model to investigate to what extent teachers' pedagogical digital assessment knowledge is a foundation for the future of digital assessment (ie, authentic, accessible, automated, continuous and responsible). A total of 219 university teachers at a large European university participated in the survey study. Factor exploratory analysis and structural equation modelling were used to validate the reliability and validity of items and internal causal relations of factors. The results show the survey is a valid and reliable instrument for assessing teachers' digital assessment practice in higher education. Teachers' pedagogical knowledge and pedagogical content knowledge of digital assessment is critical, while teachers' technological pedagogical knowledge seems to have a more limited impact on the future of digital assessment.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13462","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140363920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Helen Crompton, Adam Edmett, Neenaz Ichaporia, Diane Burke
<div> <section> <p>English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity. However, English learners face many challenges in gaining English language skills. Extant studies show that AI has affordances to support in English language teaching and learning ELT/L. This study answers the call to examine specific challenges and affordances for using AI in ELT/L. A systematic review method was used with PRISMA principles to identify 42 studies. Findings reveal the geographical locations of studies, learner ages and years of study. Grounded coding was then used to identify affordances of the use of AI in ELT/L in the areas of speaking, writing, reading, pedagogy and self-regulation. AI in ELT/L challenges uncovered were technology breakdowns, limited capabilities, fear and standardising language. Policymakers, funders, practitioners and educational leaders can use the information provided in this study to gain a holistic understanding of the current trend in the use of AI in ELT/L, and practical implications are provided to guide future use of AI.</p> </section> <section> <div> <div> <h3>Practitioner notes</h3> <p>What is already known about this topic </p><ul> <li>English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity.</li> <li>Empirical evidence shows that pupils can often face difficulties when learning English, with challenges such as irregularity in English spelling.</li> <li>AI has supported language teaching and learning with studies showing that AI can support language-specific skills.</li> </ul> <p>What this paper adds </p><ul> <li>Provides the scholarly community with a unique systematic review in the use of AI in ELT/L across learner levels.</li> <li>Identifies affordances of AI in ELT/L in speaking, writing, reading, pedagogy and self-regulation.</li> <li>Identifies challenges of AI in ELT/L in technology breakdowns, limited capabilities, fear and standardising language.</li> <li>Provides researchers with a review of the field with identification of gaps and future research opportunities.</li> </ul> <p>Implications for practice and/or policy </p><ul> <li>Pro
{"title":"AI and English language teaching: Affordances and challenges","authors":"Helen Crompton, Adam Edmett, Neenaz Ichaporia, Diane Burke","doi":"10.1111/bjet.13460","DOIUrl":"10.1111/bjet.13460","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity. However, English learners face many challenges in gaining English language skills. Extant studies show that AI has affordances to support in English language teaching and learning ELT/L. This study answers the call to examine specific challenges and affordances for using AI in ELT/L. A systematic review method was used with PRISMA principles to identify 42 studies. Findings reveal the geographical locations of studies, learner ages and years of study. Grounded coding was then used to identify affordances of the use of AI in ELT/L in the areas of speaking, writing, reading, pedagogy and self-regulation. AI in ELT/L challenges uncovered were technology breakdowns, limited capabilities, fear and standardising language. Policymakers, funders, practitioners and educational leaders can use the information provided in this study to gain a holistic understanding of the current trend in the use of AI in ELT/L, and practical implications are provided to guide future use of AI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity.</li>\u0000 \u0000 <li>Empirical evidence shows that pupils can often face difficulties when learning English, with challenges such as irregularity in English spelling.</li>\u0000 \u0000 <li>AI has supported language teaching and learning with studies showing that AI can support language-specific skills.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>Provides the scholarly community with a unique systematic review in the use of AI in ELT/L across learner levels.</li>\u0000 \u0000 <li>Identifies affordances of AI in ELT/L in speaking, writing, reading, pedagogy and self-regulation.</li>\u0000 \u0000 <li>Identifies challenges of AI in ELT/L in technology breakdowns, limited capabilities, fear and standardising language.</li>\u0000 \u0000 <li>Provides researchers with a review of the field with identification of gaps and future research opportunities.</li>\u0000 </ul>\u0000 <p>Implications for practice and/or policy\u0000\u0000 </p><ul>\u0000 \u0000 <li>Pro","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13460","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140363284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study was conducted to measure the digital parenting awareness, attitude and self-efficacy perceptions of parents of children with special needs and to determine whether they differ according to the disability status of their children. A total of 180 parents of children with special needs from various regions of Turkey participated in the study. This study was conducted using a relational screening model. Data were collected using digital parenting awareness, attitude and self-efficacy perception scales and analysed using descriptive and correlational statistical methods. The findings revealed that parents had moderate levels of awareness, positive attitudes and self-efficacy perceptions regarding digital parenting, but these variables showed significant differences according to the disability status of the children. In particular, parents of children with learning disabilities had higher digital parenting awareness than parents of other disability groups. In addition, a positive and significant relationship was found between parents' digital parenting awareness, attitudes and self-efficacy perception. The findings of this study are important and contribute to both the practical and theoretical perspectives. In applicable terms, this study revealed the needs and expectations of parents of children with special needs regarding digital parenting. Theoretically, this is a rare study that examines the situation and experiences of parents with children with special needs in digital parenting. This study emphasizes the need for further research on digital parenting.
{"title":"Exploring digital parenting awareness, self-efficacy and attitudes in families with special needs children","authors":"Özlem Altindağ Kumaş, Adile Emel Sardohan Yildirim","doi":"10.1111/bjet.13457","DOIUrl":"10.1111/bjet.13457","url":null,"abstract":"<p>This study was conducted to measure the digital parenting awareness, attitude and self-efficacy perceptions of parents of children with special needs and to determine whether they differ according to the disability status of their children. A total of 180 parents of children with special needs from various regions of Turkey participated in the study. This study was conducted using a relational screening model. Data were collected using digital parenting awareness, attitude and self-efficacy perception scales and analysed using descriptive and correlational statistical methods. The findings revealed that parents had moderate levels of awareness, positive attitudes and self-efficacy perceptions regarding digital parenting, but these variables showed significant differences according to the disability status of the children. In particular, parents of children with learning disabilities had higher digital parenting awareness than parents of other disability groups. In addition, a positive and significant relationship was found between parents' digital parenting awareness, attitudes and self-efficacy perception. The findings of this study are important and contribute to both the practical and theoretical perspectives. In applicable terms, this study revealed the needs and expectations of parents of children with special needs regarding digital parenting. Theoretically, this is a rare study that examines the situation and experiences of parents with children with special needs in digital parenting. This study emphasizes the need for further research on digital parenting.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, AI technologies have been developed to promote students' self-regulated learning (SRL) and proactive learning in digital learning environments. This paper discusses a comparative study between generative AI-based (SRLbot) and rule-based AI chatbots (Nemobot) in a 3-week science learning experience with 74 Secondary 4 students in Hong Kong. The experimental group used SRLbot to maintain a regular study habit and facilitate their SRL, while the control group utilized rule-based AI chatbots. Results showed that SRLbot effectively enhanced students' science knowledge, behavioural engagement and motivation. Quantile regression analysis indicated that the number of interactions significantly predicted variations in SRL. Students appreciated the personalized recommendations and flexibility of SRLbot, which adjusted responses based on their specific learning and SRL scenarios. The ChatGPT-enhanced instructional design reduced learning anxiety and promoted learning performance, motivation and sustained learning habits. Students' feedback on learning challenges, psychological support and self-regulation behaviours provided insights into their progress and experience with this technology. SRLbot's adaptability and personalized approach distinguished it from rule-based chatbots. The findings offer valuable evidence for AI developers and educators to consider generative AI settings and chatbot design, facilitating greater success in online science learning.
Practitioner notes
What is already known about this topic
AI technologies have been used to support student self-regulated learning (SRL) across subjects.
SRL has been identified as an important aspect of student learning that can be developed through technological support.
Generative AI technologies like ChatGPT have shown potential for enhancing student learning by providing personalized guidance and feedback.
What this paper adds
This paper reports on a case study that specifically examines the effectiveness of ChatGPT in promoting SRL among secondary students.
The study provides evidence that ChatGPT can enhance students' science knowledge, motivation and SRL compared to a rule-based AI chatbot.
{"title":"Empowering student self-regulated learning and science education through ChatGPT: A pioneering pilot study","authors":"Davy Tsz Kit Ng, Chee Wei Tan, Jac Ka Lok Leung","doi":"10.1111/bjet.13454","DOIUrl":"10.1111/bjet.13454","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <p>In recent years, AI technologies have been developed to promote students' self-regulated learning (SRL) and proactive learning in digital learning environments. This paper discusses a comparative study between generative AI-based (SRLbot) and rule-based AI chatbots (Nemobot) in a 3-week science learning experience with 74 Secondary 4 students in Hong Kong. The experimental group used SRLbot to maintain a regular study habit and facilitate their SRL, while the control group utilized rule-based AI chatbots. Results showed that SRLbot effectively enhanced students' science knowledge, behavioural engagement and motivation. Quantile regression analysis indicated that the number of interactions significantly predicted variations in SRL. Students appreciated the personalized recommendations and flexibility of SRLbot, which adjusted responses based on their specific learning and SRL scenarios. The ChatGPT-enhanced instructional design reduced learning anxiety and promoted learning performance, motivation and sustained learning habits. Students' feedback on learning challenges, psychological support and self-regulation behaviours provided insights into their progress and experience with this technology. SRLbot's adaptability and personalized approach distinguished it from rule-based chatbots. The findings offer valuable evidence for AI developers and educators to consider generative AI settings and chatbot design, facilitating greater success in online science learning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>AI technologies have been used to support student self-regulated learning (SRL) across subjects.</li>\u0000 \u0000 <li>SRL has been identified as an important aspect of student learning that can be developed through technological support.</li>\u0000 \u0000 <li>Generative AI technologies like ChatGPT have shown potential for enhancing student learning by providing personalized guidance and feedback.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>This paper reports on a case study that specifically examines the effectiveness of ChatGPT in promoting SRL among secondary students.</li>\u0000 \u0000 <li>The study provides evidence that ChatGPT can enhance students' science knowledge, motivation and SRL compared to a rule-based AI chatbot.</li>\u0000 \u0000 <li>The study offers insights into how ChatGPT can be ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13454","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140217821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Upvotes serve important purposes in online social annotation environments. However, limited studies have explored the influential factors affecting peer upvoting in online collaborative learning. In this study, we analysed the factors influencing students' upvotes received from their peers as 91 participants utilized Perusall, an online social annotation system, for collaborative reading. The participants were asked to collaboratively annotate 29 reading materials in a semester. We collected student reading behaviours and analysed their annotations with a text-mining tool of Linguistic Inquiry and Word Count (LIWC). Moreover, conditional inference tree was used to determine the relative importance of explanatory factors to the upvotes students received. The results showed that the high-upvote group made significantly more annotations, posted more responses to others' annotations and displayed fewer negative emotions in annotations than those who did not receive upvotes. The two groups of students had no significant differences in the upvotes given to others, as well as cognitive activities and positive emotions involved in annotations. Moreover, the number of annotations was the determining factor in predicting the upvotes that one could receive in social annotation activities. This study has significant practical implications regarding providing interventions in social annotation-based collaborative reading.
{"title":"Exploring influential factors in peer upvoting within social annotation","authors":"Shan Li, Xiaoshan Huang, Lijia Lin, Fu Chen","doi":"10.1111/bjet.13455","DOIUrl":"10.1111/bjet.13455","url":null,"abstract":"<p>Upvotes serve important purposes in online social annotation environments. However, limited studies have explored the influential factors affecting peer upvoting in online collaborative learning. In this study, we analysed the factors influencing students' upvotes received from their peers as 91 participants utilized Perusall, an online social annotation system, for collaborative reading. The participants were asked to collaboratively annotate 29 reading materials in a semester. We collected student reading behaviours and analysed their annotations with a text-mining tool of Linguistic Inquiry and Word Count (LIWC). Moreover, conditional inference tree was used to determine the relative importance of explanatory factors to the upvotes students received. The results showed that the high-upvote group made significantly more annotations, posted more responses to others' annotations and displayed fewer negative emotions in annotations than those who did not receive upvotes. The two groups of students had no significant differences in the upvotes given to others, as well as cognitive activities and positive emotions involved in annotations. Moreover, the number of annotations was the determining factor in predicting the upvotes that one could receive in social annotation activities. This study has significant practical implications regarding providing interventions in social annotation-based collaborative reading.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13455","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140151400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Complex dynamic systems offer a rich platform for understanding the individual or the person-specific mechanisms. Yet, in learning analytics research and education at large, a complex dynamic system has rarely been framed, developed, or used to understand the individual student where the learning process takes place. Individual (or person-specific) methods can accurately and precisely model the individual person, create person-specific models, and devise unique parameters for each individual. Our study used the latest advances in complex systems dynamics to study the differences between group-based and individual self-regulated learning (SRL) dynamics. The findings show that SRL is a complex, dynamic system where different sub-processes influence each other resulting in the emergence of non-trivial patterns that vary across individuals and time scales, and as such far from the uniform picture commonly theorized. We found that the average SRL process does not reflect the individual SRL processes of different people. Therefore, interventions derived from the group-based SRL insights are unlikely to be effective in personalization. We posit that, if personalized interventions are needed, modelling the person with person-specific methods should be the guiding principle. Our study offered a reliable solution to model the person-specific self-regulation processes which can serve as a ground for understanding and improving individual learning and open the door for precision education.
Practitioner notes
What is already known about this topic
Self-regulation is a catalyst for effective learning and achievement.
Our understanding of SRL personalization comes from insights based on aggregate group-based data.
What this paper adds
Every student has their own unique SRL process that varies from the average in non-trivial ways.
We offer a credible method for mapping the individualized SRL process.
SRL dynamics vary across time scales. That is, the trait dynamics are different from the state dynamics, and they should be supported differently.
Implications for practice and/or policy
Personalization can best be achieved if based on unique
{"title":"Mapping the self in self-regulation using complex dynamic systems approach","authors":"Mohammed Saqr, Sonsoles López-Pernas","doi":"10.1111/bjet.13452","DOIUrl":"10.1111/bjet.13452","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <p>Complex dynamic systems offer a rich platform for understanding the individual or the person-specific mechanisms. Yet, in learning analytics research and education at large, a complex dynamic system has rarely been framed, developed, or used to understand the individual student where the learning process takes place. Individual (or person-specific) methods can accurately and precisely model the individual person, create person-specific models, and devise unique parameters for each individual. Our study used the latest advances in complex systems dynamics to study the differences between group-based and individual self-regulated learning (SRL) dynamics. The findings show that SRL is a complex, dynamic system where different sub-processes influence each other resulting in the emergence of non-trivial patterns that vary across individuals and time scales, and as such far from the uniform picture commonly theorized. We found that the average SRL process does not reflect the individual SRL processes of different people. Therefore, interventions derived from the group-based SRL insights are unlikely to be effective in personalization. We posit that, if personalized interventions are needed, modelling the person with person-specific methods should be the guiding principle. Our study offered a reliable solution to model the person-specific self-regulation processes which can serve as a ground for understanding and improving individual learning and open the door for precision education.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Self-regulation is a catalyst for effective learning and achievement.</li>\u0000 \u0000 <li>Our understanding of SRL personalization comes from insights based on aggregate group-based data.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>Every student has their own unique SRL process that varies from the average in non-trivial ways.</li>\u0000 \u0000 <li>We offer a credible method for mapping the individualized SRL process.</li>\u0000 \u0000 <li>SRL dynamics vary across time scales. That is, the trait dynamics are different from the state dynamics, and they should be supported differently.</li>\u0000 </ul>\u0000 <p>Implications for practice and/or policy\u0000\u0000 </p><ul>\u0000 \u0000 <li>Personalization can best be achieved if based on unique","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140151541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Online courses are particularly attractive in continuing education because they offer a high degree of autonomy and flexibility, although this requires learners to take greater responsibility for self-regulating their learning. That can be challenging for adult learners as they need to handle other obligations in addition to learning. Thus, self-regulated learning (SRL) support might be needed. In the present study, we aimed to investigate how the specific SRL challenges that adult learners face in online courses can be supported adaptively. Main challenges for adult learners consist in managing learning resources (e.g., time, attention, learning environment). To address these challenges, we developed an adaptive support intervention comprising several features. To assess the effects of the adaptive support on the self-reported SRL strategy application of adult learners, we analysed data from five iterations of a continuing education online course comparing iterations with adaptive support (with a total of N = 36 participants) to iterations without (with a total of N = 35 participants). Results indicate that the adaptive support significantly improved environmental structuring but did not significantly affect other SRL strategies. Further analyses revealed that learners who did not use the support deteriorated in managing their learning time and in setting specific learning goals during the course.
Practitioner notes
What is already known about this topic
Adult learners are likely to face various challenges in self-regulated online learning, including managing conflicting responsibilities and maintaining focus.
Adult learners' successful application of SRL strategies can be challenging, underlining the need for support.
Adaptive support interventions have demonstrated positive effects in various educational contexts, indicating potential effectiveness for adult online learners as well.
What this paper adds
The study provides insights into the positive effects and potential pitfalls of designing an adaptive support intervention to improve adult learners' self-reported use of the SRL strategies of effort, attention, time management, environmental structuring, and goal setting.
{"title":"Meeting the challenges of continuing education online courses: Can we promote self-regulated learning strategies with adaptive support?","authors":"Katharina Teich, Vanessa Stefanie Loock, Nikol Rummel","doi":"10.1111/bjet.13453","DOIUrl":"10.1111/bjet.13453","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Online courses are particularly attractive in continuing education because they offer a high degree of autonomy and flexibility, although this requires learners to take greater responsibility for self-regulating their learning. That can be challenging for adult learners as they need to handle other obligations in addition to learning. Thus, self-regulated learning (SRL) support might be needed. In the present study, we aimed to investigate how the specific SRL challenges that adult learners face in online courses can be supported adaptively. Main challenges for adult learners consist in managing learning resources (e.g., time, attention, learning environment). To address these challenges, we developed an adaptive support intervention comprising several features. To assess the effects of the adaptive support on the self-reported SRL strategy application of adult learners, we analysed data from five iterations of a continuing education online course comparing iterations with adaptive support (with a total of <i>N</i> = 36 participants) to iterations without (with a total of <i>N</i> = 35 participants). Results indicate that the adaptive support significantly improved environmental structuring but did not significantly affect other SRL strategies. Further analyses revealed that learners who did not use the support deteriorated in managing their learning time and in setting specific learning goals during the course.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Adult learners are likely to face various challenges in self-regulated online learning, including managing conflicting responsibilities and maintaining focus.</li>\u0000 \u0000 <li>Adult learners' successful application of SRL strategies can be challenging, underlining the need for support.</li>\u0000 \u0000 <li>Adaptive support interventions have demonstrated positive effects in various educational contexts, indicating potential effectiveness for adult online learners as well.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>The study provides insights into the positive effects and potential pitfalls of designing an adaptive support intervention to improve adult learners' self-reported use of the SRL strategies of <i>effort</i>, <i>attention</i>, <i>time management</i>, <i>environmental structuring</i>, and <i>goal setting</i>.</li>\u0000 </ul>\u0000 <p>Implications for practice ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140117369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rebecca L. Matz, Mark Mills, Holly A. Derry, Benjamin T. Hayward, Caitlin Hayward
Mastery-based assignments typically provide students with multiple opportunities to improve their performance, but getting students to take advantage of these opportunities is difficult. We report on the implementation of a two-part series of nudges designed to improve students' engagement with and performance on mastery-based assignments in high-enrollment, introductory undergraduate courses. Students received one or two email-based nudges for each assignment, providing both decision information and decision assistance. Delivered via email by a digital coaching system that provides tailored support to students, we evaluated the effectiveness of viewing versus not viewing these personalized nudges across introductory courses in mathematics, computer science and engineering over five terms at our large, research-intensive university. We used multilevel modelling with a sample of 30,693 assignment scores nested within 79 assignments and 5349 undergraduate students to explore the relationship between students' viewing the nudges and their scores while controlling for performance in other courses and students' baseline proclivities to read email from the coaching system. We find that viewing versus not viewing nudges is significantly related to improved outcomes. Viewing the first of the two-part nudge series is associated with a 3% increase in scores on average. Importantly, we found a significant interaction with prior academic performance such that students with the lowest average academic performance across all courses are predicted to benefit the most—up to 9%—from nudging. Positive impacts are observed in most courses where nudges were implemented and are found to be most impactful for later versus earlier assignments within a term. We discuss the implications of these results for supporting students' decision-making within mastery-based assignment schemes and suggest future research for tailored nudges to support student success.
Practitioner notes
What is already known about this topic
Nudges are known to be broadly effective, but heterogeneity is observed especially in education where the research base is relatively limited.
Mastery-based grading is an alternative approach to grading that, among other features, emphasizes learning through an explicit feedback cycle of struggle and revision without penalty.
{"title":"Viewing tailored nudges is correlated with improved mastery-based assessment scores","authors":"Rebecca L. Matz, Mark Mills, Holly A. Derry, Benjamin T. Hayward, Caitlin Hayward","doi":"10.1111/bjet.13451","DOIUrl":"10.1111/bjet.13451","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Mastery-based assignments typically provide students with multiple opportunities to improve their performance, but getting students to take advantage of these opportunities is difficult. We report on the implementation of a two-part series of nudges designed to improve students' engagement with and performance on mastery-based assignments in high-enrollment, introductory undergraduate courses. Students received one or two email-based nudges for each assignment, providing both decision information and decision assistance. Delivered via email by a digital coaching system that provides tailored support to students, we evaluated the effectiveness of viewing versus not viewing these personalized nudges across introductory courses in mathematics, computer science and engineering over five terms at our large, research-intensive university. We used multilevel modelling with a sample of 30,693 assignment scores nested within 79 assignments and 5349 undergraduate students to explore the relationship between students' viewing the nudges and their scores while controlling for performance in other courses and students' baseline proclivities to read email from the coaching system. We find that viewing versus not viewing nudges is significantly related to improved outcomes. Viewing the first of the two-part nudge series is associated with a 3% increase in scores on average. Importantly, we found a significant interaction with prior academic performance such that students with the lowest average academic performance across all courses are predicted to benefit the most—up to 9%—from nudging. Positive impacts are observed in most courses where nudges were implemented and are found to be most impactful for later versus earlier assignments within a term. We discuss the implications of these results for supporting students' decision-making within mastery-based assignment schemes and suggest future research for tailored nudges to support student success.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Nudges are known to be broadly effective, but heterogeneity is observed especially in education where the research base is relatively limited.</li>\u0000 \u0000 <li>Mastery-based grading is an alternative approach to grading that, among other features, emphasizes learning through an explicit feedback cycle of struggle and revision without penalty.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>This study assesses the effectiv","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140107412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This descriptive study focuses on using voice activity detection (VAD) algorithms to extract student speech data in order to better understand the collaboration of small group work and the impact of teaching assistant (TA) interventions in undergraduate engineering discussion sections. Audio data were recorded from individual students wearing head-mounted noise-cancelling microphones. Video data of each student group were manually coded for collaborative behaviours (eg, group task relatedness, group verbal interaction and group talk content) of students and TA–student interactions. The analysis includes information about the turn taking, overall speech duration patterns and amounts of overlapping speech observed both when TAs were intervening with groups and when they were not. We found that TAs very rarely provided explicit support regarding collaboration. Key speech metrics, such as amount of turn overlap and maximum turn duration, revealed important information about the nature of student small group discussions and TA interventions. TA interactions during small group collaboration are complex and require nuanced treatments when considering the design of supportive tools.
Practitioner notes
What is already known about this topic
Student turn taking can provide information about the nature of student discussions and collaboration.
Real classroom audio data of small groups typically have lots of background noise and present challenges for audio analysis.
TAs have little training in how to productively intervene with students about collaborative skills.
What this paper adds
TA interaction with groups primarily focused on task progress and understanding of concepts with negligible explicit support on building collaborative skills.
TAs intervened with the groups often which gave the students little time for uptake of their suggestions or deeper discussion.
Student turn overlap was higher without the presence of TAs.
Maximum turn duration can be an important real-time turn metric to identify the least verbally active student participant in a group.
{"title":"Speech analysis of teaching assistant interventions in small group collaborative problem solving with undergraduate engineering students","authors":"Cynthia M. D'Angelo, Robin Jephthah Rajarathinam","doi":"10.1111/bjet.13449","DOIUrl":"10.1111/bjet.13449","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>This descriptive study focuses on using voice activity detection (VAD) algorithms to extract student speech data in order to better understand the collaboration of small group work and the impact of teaching assistant (TA) interventions in undergraduate engineering discussion sections. Audio data were recorded from individual students wearing head-mounted noise-cancelling microphones. Video data of each student group were manually coded for collaborative behaviours (eg, group task relatedness, group verbal interaction and group talk content) of students and TA–student interactions. The analysis includes information about the turn taking, overall speech duration patterns and amounts of overlapping speech observed both when TAs were intervening with groups and when they were not. We found that TAs very rarely provided explicit support regarding collaboration. Key speech metrics, such as amount of turn overlap and maximum turn duration, revealed important information about the nature of student small group discussions and TA interventions. TA interactions during small group collaboration are complex and require nuanced treatments when considering the design of supportive tools.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Student turn taking can provide information about the nature of student discussions and collaboration.</li>\u0000 \u0000 <li>Real classroom audio data of small groups typically have lots of background noise and present challenges for audio analysis.</li>\u0000 \u0000 <li>TAs have little training in how to productively intervene with students about collaborative skills.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>TA interaction with groups primarily focused on task progress and understanding of concepts with negligible explicit support on building collaborative skills.</li>\u0000 \u0000 <li>TAs intervened with the groups often which gave the students little time for uptake of their suggestions or deeper discussion.</li>\u0000 \u0000 <li>Student turn overlap was higher without the presence of TAs.</li>\u0000 \u0000 <li>Maximum turn duration can be an important real-time turn metric to identify the least verbally active student participant in a group.</li>\u0000 </ul>\u0000 <p>Implications for practice and/or ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13449","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140019447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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