Journal of Computer Assisted Learning最新文献

{"title":"Engagement Dynamics in AI-Mediated Informal Digital Learning of English: Effects on L2 Speaking Performance, Anxiety, and Sequential Behaviour Patterns","authors":"Yuting Chen,&nbsp;Qing Ma,&nbsp;Morris Siu-Yung Jong,&nbsp;Youlin Yang,&nbsp;Mutlu Cukurova,&nbsp;Ming Li","doi":"10.1002/jcal.70278","DOIUrl":"https://doi.org/10.1002/jcal.70278","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In Informal digital learning of English (IDLE) environments, recent advances in generative artificial intelligence (AI) have created new opportunities for self-directed second language (L2) speaking practise through responsive and low-stakes interaction. However, AI-mediated IDLE (AI-IDLE) is not experienced uniformly: learners differ in how they engage with AI, and such differences may be reflected not only in speaking performance and foreign language speaking anxiety (FLSA) but also in the sequential behaviours through which engagement is enacted.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aimed to investigate how different profiles of learner engagement in AI-IDLE are associated with L2 speaking performance, FLSA, and sequential behaviour patterns during AI-learner interaction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An AI-IDLE environment was developed to provide scaffolded, avatar-based speaking practise in contextualised scenarios. Sixty university L2 learners participated in this study. Latent profile analysis (LPA) was conducted based on self-reported engagement measures to identify distinct engagement profiles. Differences in speaking performance and FLSA were compared across profiles, and sequential behaviour analysis was employed to examine enacted engagement as reflected in AI-learner interaction sequences.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusion</h3>\u0000 \u0000 <p>Three engagement profiles were identified. Differences across profiles were observed in both speaking performance and FLSA. Sequential analysis further revealed that learners exhibited distinct patterns of interaction with AI, characterised by varying degrees of iteration and continuity in behaviour sequences. These findings suggest that distinct engagement profiles are associated not only with different learning outcomes but also with qualitatively different patterns of interaction with AI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Implications for Practise</h3>\u0000 \u0000 <p>The study contributes to AI-IDLE research by integrating person-centred and process-oriented perspectives, highlighting the importance of examining both perceived and enacted engagement. The findings offer implications for the design of AI-IDLE that support sustained interaction, adaptive feedback use, and reduced FLSA.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148647869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Engagement Dynamics in AI-Mediated Informal Digital Learning of English: Effects on L2 Speaking Performance, Anxiety, and Sequential Behaviour Patterns","authors":"Yuting Chen,&nbsp;Qing Ma,&nbsp;Morris Siu-Yung Jong,&nbsp;Youlin Yang,&nbsp;Mutlu Cukurova,&nbsp;Ming Li","doi":"10.1002/jcal.70278","DOIUrl":"https://doi.org/10.1002/jcal.70278","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In Informal digital learning of English (IDLE) environments, recent advances in generative artificial intelligence (AI) have created new opportunities for self-directed second language (L2) speaking practise through responsive and low-stakes interaction. However, AI-mediated IDLE (AI-IDLE) is not experienced uniformly: learners differ in how they engage with AI, and such differences may be reflected not only in speaking performance and foreign language speaking anxiety (FLSA) but also in the sequential behaviours through which engagement is enacted.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aimed to investigate how different profiles of learner engagement in AI-IDLE are associated with L2 speaking performance, FLSA, and sequential behaviour patterns during AI-learner interaction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An AI-IDLE environment was developed to provide scaffolded, avatar-based speaking practise in contextualised scenarios. Sixty university L2 learners participated in this study. Latent profile analysis (LPA) was conducted based on self-reported engagement measures to identify distinct engagement profiles. Differences in speaking performance and FLSA were compared across profiles, and sequential behaviour analysis was employed to examine enacted engagement as reflected in AI-learner interaction sequences.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusion</h3>\u0000 \u0000 <p>Three engagement profiles were identified. Differences across profiles were observed in both speaking performance and FLSA. Sequential analysis further revealed that learners exhibited distinct patterns of interaction with AI, characterised by varying degrees of iteration and continuity in behaviour sequences. These findings suggest that distinct engagement profiles are associated not only with different learning outcomes but also with qualitatively different patterns of interaction with AI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Implications for Practise</h3>\u0000 \u0000 <p>The study contributes to AI-IDLE research by integrating person-centred and process-oriented perspectives, highlighting the importance of examining both perceived and enacted engagement. The findings offer implications for the design of AI-IDLE that support sustained interaction, adaptive feedback use, and reduced FLSA.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148647870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Day Begins With Morning: How Morning Goal Motivation Profiles Shape Daily Emotions From a Complex Dynamic Systems Perspective","authors":"Meng-Ting Lo,&nbsp;Yen-Yu Chen,&nbsp;Shao-Hsuan Lin","doi":"10.1002/jcal.70284","DOIUrl":"https://doi.org/10.1002/jcal.70284","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Individuals pursue goals for autonomous or controlled reasons, and distinct combinations of these motivations form daily motivational profiles. Although such profiles have been studied, little is known about their day-to-day stability and variability, which is critical for understanding how motivation evolves over time. How motivational and emotional dynamics emerge in the daily lives of university students remains unclear, and person-oriented temporal analyses can reveal maladaptive patterns that mean-level analyses often obscure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aims to identify daily autonomous and controlled goal-pursuit motivation profiles, examine their day-to-day stability and variability and explore how these profiles relate to university students' emotional transitions throughout the day.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using the VaSSTra method, we identified profiles that summarise students' motivational states for each day, examined sequences of these profiles across days, and clustered students who exhibited similar patterns of transitions. Multilevel modelling and transition network analysis were employed to explore the relationship between these profiles and students' emotional experiences and transitions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Three profiles emerged: high controlled goals, moderate intrinsic goals, and autonomous and moderate controlled goals. Transition network analysis revealed that students with moderate intrinsic or autonomous and moderate controlled profiles tended to maintain more positive emotional states, exhibiting fewer systematic emotional transitions. In contrast, on days marked by a high controlled goal-pursuit profile, students were more likely to shift towards heightened negative emotions. This study extends theoretical perspectives on motivation and demonstrates the value of novel learning analytics for untangling the complex, interactive relationships between motivation and emotions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cumulative Presentation Enhances Learning Outcomes by Directing Learners' Visual Attention","authors":"Hikaru Ito,&nbsp;Hiroko Ichikawa","doi":"10.1002/jcal.70286","DOIUrl":"https://doi.org/10.1002/jcal.70286","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The Cognitive Theory of Multimedia Learning (CTML) has established fruitful principles to guide learners' attention and reduce their cognitive load. Although these principles have been shown to improve learning outcomes, it remains useful to examine learners' cognitive processes during learning using eye-tracking techniques.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To mitigate cognitive load by segmenting content and directing the learner's attention to visual elements synchronised with auditory narration, we cumulatively presented visual segments within a single PowerPoint slide. We referred to this format as a <i>cumulative presentation</i>.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Forty Japanese university students participated. They first completed a pre-test to assess their prior knowledge, and subsequently viewed a biology lesson slideshow accompanied by teacher narration. In the cumulative presentation condition, visual elements were incrementally revealed alongside the narration, whereas in the whole-slide presentation condition, all elements were presented simultaneously prior to narration. Throughout the session, we tracked the participants' eye movements. Following the lesson, all participants completed a post-test identical to the pre-test.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Learning outcomes were significantly higher in the cumulative presentation condition than in the whole-slide presentation condition (Cohen's <i>d</i> = 0.49). Participants in the cumulative presentation condition fixated earlier on visual elements congruent with the teacher's lecture (<i>d</i> = 1.76) and for longer durations (Cohen's <i>d</i> = 1.15). These findings demonstrate the effectiveness of cumulative presentation in enhancing learning and visual attention, provide empirical support for the segmenting principle, and suggest practical implications for designing multimedia instructional materials.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcal.70286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cumulative Presentation Enhances Learning Outcomes by Directing Learners' Visual Attention","authors":"Hikaru Ito,&nbsp;Hiroko Ichikawa","doi":"10.1002/jcal.70286","DOIUrl":"https://doi.org/10.1002/jcal.70286","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The Cognitive Theory of Multimedia Learning (CTML) has established fruitful principles to guide learners' attention and reduce their cognitive load. Although these principles have been shown to improve learning outcomes, it remains useful to examine learners' cognitive processes during learning using eye-tracking techniques.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To mitigate cognitive load by segmenting content and directing the learner's attention to visual elements synchronised with auditory narration, we cumulatively presented visual segments within a single PowerPoint slide. We referred to this format as a <i>cumulative presentation</i>.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Forty Japanese university students participated. They first completed a pre-test to assess their prior knowledge, and subsequently viewed a biology lesson slideshow accompanied by teacher narration. In the cumulative presentation condition, visual elements were incrementally revealed alongside the narration, whereas in the whole-slide presentation condition, all elements were presented simultaneously prior to narration. Throughout the session, we tracked the participants' eye movements. Following the lesson, all participants completed a post-test identical to the pre-test.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Learning outcomes were significantly higher in the cumulative presentation condition than in the whole-slide presentation condition (Cohen's <i>d</i> = 0.49). Participants in the cumulative presentation condition fixated earlier on visual elements congruent with the teacher's lecture (<i>d</i> = 1.76) and for longer durations (Cohen's <i>d</i> = 1.15). These findings demonstrate the effectiveness of cumulative presentation in enhancing learning and visual attention, provide empirical support for the segmenting principle, and suggest practical implications for designing multimedia instructional materials.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcal.70286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Day Begins With Morning: How Morning Goal Motivation Profiles Shape Daily Emotions From a Complex Dynamic Systems Perspective","authors":"Meng-Ting Lo,&nbsp;Yen-Yu Chen,&nbsp;Shao-Hsuan Lin","doi":"10.1002/jcal.70284","DOIUrl":"https://doi.org/10.1002/jcal.70284","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Individuals pursue goals for autonomous or controlled reasons, and distinct combinations of these motivations form daily motivational profiles. Although such profiles have been studied, little is known about their day-to-day stability and variability, which is critical for understanding how motivation evolves over time. How motivational and emotional dynamics emerge in the daily lives of university students remains unclear, and person-oriented temporal analyses can reveal maladaptive patterns that mean-level analyses often obscure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aims to identify daily autonomous and controlled goal-pursuit motivation profiles, examine their day-to-day stability and variability and explore how these profiles relate to university students' emotional transitions throughout the day.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using the VaSSTra method, we identified profiles that summarise students' motivational states for each day, examined sequences of these profiles across days, and clustered students who exhibited similar patterns of transitions. Multilevel modelling and transition network analysis were employed to explore the relationship between these profiles and students' emotional experiences and transitions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Three profiles emerged: high controlled goals, moderate intrinsic goals, and autonomous and moderate controlled goals. Transition network analysis revealed that students with moderate intrinsic or autonomous and moderate controlled profiles tended to maintain more positive emotional states, exhibiting fewer systematic emotional transitions. In contrast, on days marked by a high controlled goal-pursuit profile, students were more likely to shift towards heightened negative emotions. This study extends theoretical perspectives on motivation and demonstrates the value of novel learning analytics for untangling the complex, interactive relationships between motivation and emotions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How AI-Generated Feedback Hinders or Helps Learning: A Heterogeneous TNA Study of Learning Dynamics","authors":"Sonsoles López-Pernas,&nbsp;Kamila Misiejuk,&nbsp;Mohammed Saqr","doi":"10.1002/jcal.70285","DOIUrl":"https://doi.org/10.1002/jcal.70285","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Despite growing integration of generative AI in educational settings, little is known about whether and to what extent AI-generated real-time feedback can support first-grade students in solving multimodal mathematical tasks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Our study aims to examine student–AI feedback dynamics from a process-oriented perspective, focusing on how students interact with AI feedback after incorrectly solving multimodal mathematical tasks and which interaction patterns lead to successful re-attempts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyze data from 13,000 first-grade pupils across two countries who completed a single-session assessment of 16 foundational numeracy skills via multimodal tasks, where incorrect and correct responses triggered real-time feedback from a GPT-4.1-based system. All feedback instances were collected and qualitatively coded to investigate how student-AI interaction sequences differ between successful and unsuccessful re-attempts, and to what extent specific actions or interaction patterns predict successful attempts. Data were examined using Heterogeneous Transition Network Analysis and sequential pattern mining. Moreover, chi-squared tests and regression models were used to test the association between successful and unsuccessful attempts and interaction types and sequences thereof.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Findings revealed that feedback effectiveness depended not on type alone but on how it was embedded within broader interaction sequences. Successful re-attempts were more likely to follow clarification-oriented feedback, whereas unsuccessful ones were more commonly preceded by question-based prompts or direct orders, which reflect more highly anthropomorphic and authoritative forms of address. The absence of AI feedback was associated with poorer recovery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These findings are situated within the broader concern that misaligned generative AI scaffolding and feedback may deepen confusion or reinforce misconceptions instead of supporting learning.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcal.70285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How AI-Generated Feedback Hinders or Helps Learning: A Heterogeneous TNA Study of Learning Dynamics","authors":"Sonsoles López-Pernas,&nbsp;Kamila Misiejuk,&nbsp;Mohammed Saqr","doi":"10.1002/jcal.70285","DOIUrl":"https://doi.org/10.1002/jcal.70285","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Despite growing integration of generative AI in educational settings, little is known about whether and to what extent AI-generated real-time feedback can support first-grade students in solving multimodal mathematical tasks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Our study aims to examine student–AI feedback dynamics from a process-oriented perspective, focusing on how students interact with AI feedback after incorrectly solving multimodal mathematical tasks and which interaction patterns lead to successful re-attempts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyze data from 13,000 first-grade pupils across two countries who completed a single-session assessment of 16 foundational numeracy skills via multimodal tasks, where incorrect and correct responses triggered real-time feedback from a GPT-4.1-based system. All feedback instances were collected and qualitatively coded to investigate how student-AI interaction sequences differ between successful and unsuccessful re-attempts, and to what extent specific actions or interaction patterns predict successful attempts. Data were examined using Heterogeneous Transition Network Analysis and sequential pattern mining. Moreover, chi-squared tests and regression models were used to test the association between successful and unsuccessful attempts and interaction types and sequences thereof.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Findings revealed that feedback effectiveness depended not on type alone but on how it was embedded within broader interaction sequences. Successful re-attempts were more likely to follow clarification-oriented feedback, whereas unsuccessful ones were more commonly preceded by question-based prompts or direct orders, which reflect more highly anthropomorphic and authoritative forms of address. The absence of AI feedback was associated with poorer recovery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These findings are situated within the broader concern that misaligned generative AI scaffolding and feedback may deepen confusion or reinforce misconceptions instead of supporting learning.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcal.70285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Students' Learning Experiences in Blended Learning Environment Integrated With Interactive GeoGebra Applets: A Self-Determination Theory Perspective","authors":"Serpil Yorganci","doi":"10.1002/jcal.70283","DOIUrl":"https://doi.org/10.1002/jcal.70283","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Students' learning outcomes and experiences vary depending on the learning environment, and their reinforcement relies on meeting specific innate needs. In this context, self-determination is considered a key theory that fosters students' learning experiences. The self-determination theory (SDT) has been repeatedly addressed in the literature in online, blended, and face-to-face learning environments in both research and practice contexts. Despite a significant number of existing studies, little is still known about the potential reasons for this impact of learning environments on students, from the perspective of how learning environments integrating various dynamic and interactive technologies affect students' engagement levels and meet their various needs to maintain their motivation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objectives&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Therefore, in this study, interactive GeoGebra applets are conceptualized not only as teaching tools but also as need-supportive learning affordances that can transform how students interact with mathematical content. The instructional materials and learning activities were systematically designed in accordance with SDT to support students' autonomy, competence, and relatedness. Accordingly, the present research compares online, blended, and face-to-face learning environments, focusing particularly on how GeoGebra-supported instruction in blended and online settings differently supports psychological needs, student engagement, and learning performance.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using a quasi-experimental design in the study, three carefully defined instructional conditions were compared: a blended learning environment supported by interactive GeoGebra applets, a fully online learning environment with the same applications, and a traditional face-to-face learning environment without such interaction. A total of 400 preliminary undergraduate students participated in the study.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results and Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The results show that the BL setting supported by interactive GeoGebra applets, developed in line with Self-Determination Theory (SDT)-aligned teaching strategies, improves students' learning outcomes and engagement, and fulfils competence and relatedness needs, whereas autonomy satisfaction remained consistent across all instructional conditions. Findings show the promising effects of the BL environment, particularly for low-performing students. The study offers practical implications for educators and instructional designers","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcal.70283","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Students' Learning Experiences in Blended Learning Environment Integrated With Interactive GeoGebra Applets: A Self-Determination Theory Perspective","authors":"Serpil Yorganci","doi":"10.1002/jcal.70283","DOIUrl":"https://doi.org/10.1002/jcal.70283","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Students' learning outcomes and experiences vary depending on the learning environment, and their reinforcement relies on meeting specific innate needs. In this context, self-determination is considered a key theory that fosters students' learning experiences. The self-determination theory (SDT) has been repeatedly addressed in the literature in online, blended, and face-to-face learning environments in both research and practice contexts. Despite a significant number of existing studies, little is still known about the potential reasons for this impact of learning environments on students, from the perspective of how learning environments integrating various dynamic and interactive technologies affect students' engagement levels and meet their various needs to maintain their motivation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objectives&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Therefore, in this study, interactive GeoGebra applets are conceptualized not only as teaching tools but also as need-supportive learning affordances that can transform how students interact with mathematical content. The instructional materials and learning activities were systematically designed in accordance with SDT to support students' autonomy, competence, and relatedness. Accordingly, the present research compares online, blended, and face-to-face learning environments, focusing particularly on how GeoGebra-supported instruction in blended and online settings differently supports psychological needs, student engagement, and learning performance.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using a quasi-experimental design in the study, three carefully defined instructional conditions were compared: a blended learning environment supported by interactive GeoGebra applets, a fully online learning environment with the same applications, and a traditional face-to-face learning environment without such interaction. A total of 400 preliminary undergraduate students participated in the study.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results and Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The results show that the BL setting supported by interactive GeoGebra applets, developed in line with Self-Determination Theory (SDT)-aligned teaching strategies, improves students' learning outcomes and engagement, and fulfils competence and relatedness needs, whereas autonomy satisfaction remained consistent across all instructional conditions. Findings show the promising effects of the BL environment, particularly for low-performing students. The study offers practical implications for educators and instructional designers","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"42 4","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcal.70283","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}