Journal of Computer Assisted Learning最新文献

{"title":"Learning Programming With Augmented Reality-Based Editor: A Dynamic Code Visualisation Approach","authors":"Merve Aydin,&nbsp;Ünal Çakiroğlu","doi":"10.1111/jcal.13093","DOIUrl":"https://doi.org/10.1111/jcal.13093","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Students experience higher-order thinking skills by finding ways to solve the problem, debugging errors while applying the solution, and testing the solution in programming. However, the inability to create schemas that will characterise programming structures is one of the difficulties during this process.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aimed to create an augmented reality-based programming editor and evaluate its contributions to learning programming. Text-based programming codes developed by the students on the editor were instantly visualised through a traffic metaphor in dynamic visualisation via augmented reality. The findings of this study highlight the significance of a novel usage of augmented reality in shaping cognitive processes during the programming learning process.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An exploratory case study was adopted in the study. Participants voluntarily selected 15 students in the same secondary school's 4th and 5th grades. The data to determine the programming performances were collected via a programming performance test and analysed with the rubric created by the authors. Interviews and screen recordings were employed to determine the factors that had a role in the programming learning process.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>The results indicated that teaching programming using the augmented reality-based editor has positively contributed to learning programming. The editor's scenario, animation, and error display features incorporated with an authentic dynamic visualisation were remarkable in this contribution. The editor also contributed to reducing students' efforts to create schemas for programming by bringing the context closer to reality throughout the programming process.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862199","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":"The Effect of AI-Based Systems on Mathematics Achievement in Rural Context: A Quantitative Study","authors":"Rashmi Khazanchi,&nbsp;Daniele Di Mitri,&nbsp;Hendrik Drachsler","doi":"10.1111/jcal.13098","DOIUrl":"https://doi.org/10.1111/jcal.13098","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;Despite educational advances, poor mathematics achievement persists among K-12 students, particularly in rural areas with limited resources and skilled teachers. Artificial Intelligence (AI) based systems have increasingly been adopted to support the diverse learning needs of students and have been shown to enhance mathematics achievement through personalized learning experiences by adapting to student's needs. Existing studies have documented the positive impact of AI-based systems on mathematics achievement. However, there is a lack of research that has studied AI-based systems on students' mathematics achievement and engagement in rural settings. The present study addresses the existing literature gap by focusing on the AI-based Edmentum Exact Path, analyzing its effectiveness in enhancing mathematics achievement and engagement among 8th-grade students in rural schools in the Southern United States. By examining both cognitive and affective engagement, along with students' mathematics achievement, this research explores the role of AI-based systems in student learning.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study aims to explore the effectiveness of Edmentum Exact Path, an AI-based system, in improving 8th-grade students' mathematics achievement and affective and cognitive engagement in the Southern United States.&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;This study utilized a quasi-experimental design involving 78 students from socioeconomically disadvantaged backgrounds, comparing those receiving supplemental Edmentum Exact Path-led instruction and traditional teacher-led methods to a control group receiving only the teacher-led instructions. Mathematics achievement was measured through pre-tests and post-tests, while student engagement was assessed using the 5-point Student Engagement Instrument (SEI). Statistical analysis was performed using &lt;i&gt;t&lt;/i&gt;-tests and ANOVA.&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 findings revealed statistically significant improvements in mathematics achievement for both the experimental and control groups. However, the group using teacher-led instruction showed a statistically significant improvement in affective engagement, while no statistically significant differences were observed in cognitive engagement between groups.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Implications&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The findings suggest that integrating AI-based systems lik","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862058","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":"Eye Movement Modelling Examples as Cues to Guide Attention and Improve Learning in Short or Long Animations","authors":"Fuxing Wang,&nbsp;Xiaoxue Leng,&nbsp;Ziyi Kuang,&nbsp;Tingting Zhao","doi":"10.1111/jcal.13094","DOIUrl":"https://doi.org/10.1111/jcal.13094","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Both eye movement modelling examples (EMMEs) and cues guide attention and improve learning in multimedia learning environments. EMME can act as a special form of cue. However, no studies have directly examined whether EMME would be superior to visual cues.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The study was to investigate whether there were advantages of EMME over cues on visual attention, learning outcomes and subjective perception in a multimedia environment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>In Experiment 1, 67 college students were randomly assigned to the EMME group, cue group and control group and learned from animations explaining the synaptic transmission. In Experiment 2, we replicated Experiment 1 using longer learning material. Seventy-one college students were randomly assigned to three groups (EMME, cue and control) and learned from animations explaining the process of cell division.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>In Experiment 1, results indicated both EMMEs and cues guide attention and facilitate learning. Regarding learning outcomes and subjective perception, learners did not benefit more from EMMEs than cues. Eye movement indicators showed that EMMEs were better than cues. In Experiment 2, results were consistent with Experiment 1.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Implications</h3>\u0000 \u0000 <p>This study is the first to compare EMMEs and cues. We found that EMMEs and cues were equivalent in producing effects on learning outcomes and subjective perception. EMMEs were superior to cues in guiding attention and conveying strategies, as indicated by eye movements. Both theoretical and practical implications could be drawn.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862059","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":"Uncovering adults' problem-solving patterns from process data with hidden Markov model and network analysis","authors":"Xiaoxiao Liu,&nbsp;Okan Bulut,&nbsp;Ying Cui,&nbsp;Yizhu Gao","doi":"10.1111/jcal.13089","DOIUrl":"https://doi.org/10.1111/jcal.13089","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Process data captured by computer-based assessments provide valuable insight into respondents' cognitive processes during problem-solving tasks. Although previous studies have utilized process data to analyse behavioural patterns or strategies in problem-solving tasks, the connection between latent cognitive states and their theoretical interpretation in problem solving remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This research aims to investigate the connections between similar hidden response states and unfold respondents' transition paths in problem-solving processes. Analysing process data from the 2012 United States Programme for the International Assessment of Adult Competencies (PIAAC), this study seeks to discern patterns in problem solving among participants.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The hidden Markov model was first used to uncover the hidden states based on a sequence of observed actions. Next, Gaussian graphical network analysis was employed to analyse the relationships between hidden response states.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Results indicated that correct responders had simpler, clearer state relationships, while incorrect responders displayed more complex connections. Respondents who solved the tasks correctly had clearer thoughts about the problem-solving process, whereas incorrect respondents struggled to understand the problem and failed to figure out solutions. Cognitive state changes during problem solving also varied between groups. The correct groups showed cohesive, logical transitions, in contrast to the emerged isolated, erratic patterns of the incorrect groups.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861138","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":"The impact of frequency and stakes of formative assessment on student achievement in higher education: A learning analytics study","authors":"Okan Bulut,&nbsp;Guher Gorgun,&nbsp;Seyma Nur Yildirim-Erbasli","doi":"10.1111/jcal.13087","DOIUrl":"https://doi.org/10.1111/jcal.13087","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress. Optional assessments may encourage voluntary engagement, potentially leading to a more genuine reflection of student understanding. Also, frequent assessments provide continuous opportunities for feedback and adjustment, which can keep students actively engaged in the learning process.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aims to investigate two crucial facets of formative assessments: frequency and the level of stakes involved (mandatory vs. optional). We examine how modifying the frequency of formative assessments affects students' course performance. Additionally, we evaluate the impact of mandatory versus optional formative assessments on students' course performance in higher education.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The sample of this study consisted of undergraduate students (<i>n</i> = 336) enrolled in three sections of a large asynchronous course at a Canadian university. We extracted features associated with online formative assessments (e.g., the number of attempts and average scores) from the learning management system. Next, we used these features to predict students' performance in summative assessments (two midterms and a final exam).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Our findings indicated that increasing the frequency of online formative assessments did not consistently improve student performance. Also, participation frequency in online formative assessments seemed to vary depending on assessment stakes (i.e., optional vs. mandatory). We recommend that instructors examine what conditions can maximize the contribution of formative assessments to students' academic achievement before building predictive models.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861032","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 systematic review and meta-analysis of AI-enabled assessment in language learning: Design, implementation, and effectiveness","authors":"Angxuan Chen,&nbsp;Yuyue Zhang,&nbsp;Jiyou Jia,&nbsp;Min Liang,&nbsp;Yingying Cha,&nbsp;Cher Ping Lim","doi":"10.1111/jcal.13064","DOIUrl":"https://doi.org/10.1111/jcal.13064","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Language assessment plays a pivotal role in language education, serving as a bridge between students' understanding and educators' instructional approaches. Recently, advancements in Artificial Intelligence (AI) technologies have introduced transformative possibilities for automating and personalising language assessments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This article aims to explore the design and implementation of AI-enabled assessment tools in language education, filling the research gaps regarding the impact of assessment type, intervention duration, education level, and first language learner/second language learner (L1/L2) on the effectiveness of AI-enabled assessment tools in enhancing students' language learning outcome.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study conducted a systematic review and meta-analysis to examine 25 empirical studies from January 2012 to March 2024 from six databases (including EBSCO, ProQuest, Scopus, Web of Science, ACM Digital Library and CNKI).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The predominant design in AI-driven assessment tools is the structural AI architecture. These tools are most frequently deployed in classroom settings for upper primary students within a short duration. A subsequent meta-analysis showed a medium overall effect size (Hedges's <i>g</i> = 0.390, <i>p</i> &lt; 0.001) for the application of AI-enabled assessment tools in enhancing students' language learning, underscoring their significant impact on language learning outcomes. This evidence robustly supports the practical utility of these tools in educational contexts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The analysis of several moderator variables (i.e., assessment type, intervention duration, educational level and L1/L2 learners) and potential impacts on language learning performance indicates that AI-enabled assessment could be more useful in language education with a proper implementation design. Future research could investigate diverse instructional designs for integrating AI-based assessment tools in language education.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860795","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":"Mining teacher informal online learning networks: Community commitment in unstructured learning environments","authors":"Hanxiang Du,&nbsp;Gaoxia Zhu,&nbsp;Wanli Xing","doi":"10.1111/jcal.13090","DOIUrl":"https://doi.org/10.1111/jcal.13090","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Social media provides new opportunities for teachers to learn, communicate and develop professional relationships. It has been proved to be a valid and helpful resource for teachers' professional learning purposes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>While previous studies pursued questions like how participants feel, how to support interaction and why participants remain committed, we asked a more fundamental question: what is the structure of a massive informal online professional learning network and what dynamics can we expect regarding participants' commitment?</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This work presents an empirical study of massive informal online professional networks to investigate the dynamics of learning communities and participants' commitment over time. We employed social network analysis and data mining techniques on a longitudinal data set of more than 400,000 tweets published with the hashtag “#edchat.”</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>We found that around 30% of participants remained committed to the informal learning community over time. Meanwhile, as more and more people committed to the online learning community, participants tended to form smaller communities where the internal connection was stronger.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Takeaways</h3>\u0000 \u0000 <p>In informal online learning environments, participants can form stable connections. The 30% threshold can be used to measure massive informal online learning networks in terms of commitment or persistence.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860849","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":"The effects of embedded quizzes on self-regulated processes and learning performance during a multimedia lesson","authors":"Camille Tordet,&nbsp;Jonathan Fernandez,&nbsp;Eric Jamet","doi":"10.1111/jcal.13083","DOIUrl":"https://doi.org/10.1111/jcal.13083","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Previous research has demonstrated that quizzing can improve self-regulation processes and learning performances. However, it remains unclear whether quizzes in multimedia material bring similar benefits, and whether interindividual differences such as working memory capacity (WMC) modulate quizzing effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>This study aimed to examine the effects of embedded quizzes (multiple quizzes within the learning sequence) with feedback during a multimedia learning sequence on self-regulated processing (monitoring and control) and learning performances on repeated (material already tested) and new (untested) questions, and possible WMC moderation on performances.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Sample and Methods</h3>\u0000 \u0000 <p>Participants were 59 students who learned a multimedia neuroscience course module in either a no-quiz or embedded quizzes condition. With regard to self-regulated processing, control was assessed with eye-tracking measures (fixation durations and transitions between texts and illustrations), and monitoring by comparing self-reported judgements of learning with actual performances (calibration). At the end, students' WMC was measured, and learning performances were assessed with repeated and new questions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Quizzing improved learning performances on repeated and new questions, and enhanced monitoring (better calibration). Students with low WMC benefited more from quizzing for new questions than those with high WMC. However, contrary to our hypothesis, the embedded quizzes group allocated less time to the learning than the no-quiz group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Embedded quizzes are relevant tools to help students recalibrate their monitoring process and foster more effective self-regulated learning. Results confirm that the use of quizzes can be recommended to improve the learning of multimedia material, especially among students with low WMC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860848","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":"Impacts of interacting with an AI chatbot on preservice teachers' responsive teaching skills in math education","authors":"Dabae Lee,&nbsp;Taekwon Son,&nbsp;Sheunghyun Yeo","doi":"10.1111/jcal.13091","DOIUrl":"https://doi.org/10.1111/jcal.13091","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>The primary objective of this study is to examine whether interaction with a responsive AI-based chatbot that acts as a virtual student improves pre-service teachers' noticing abilities. The second objective is to compare how the presence or absence of chatbot responses affects changes in PSTs' questioning practices. Finally, the third objective is to investigate how the experience of interacting with the responsive virtual student affects PSTs' perceptions of the effectiveness of their questioning, their satisfaction with the interactions, and their confidence about interacting with a real student compared to the non-responsive chatbot.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A randomised controlled pre- and post-test design was used with 50 PSTs. PSTs' noticing, interaction with the chatbot, and post-survey data were collected, and a <i>t</i>-test was conducted to examine significant differences by group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusion</h3>\u0000 \u0000 <p>In the experimental group, the virtual student responded to PSTs' questions, while in the control group, she did not. Notable differences were observed in their questioning practices.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Takeaways</h3>\u0000 \u0000 <p>Overall, AI-based chatbots hold promise for enhancing PSTs' responsive teaching skills. Future research is needed to examine the long-term impact of responsive chatbot use on PSTs' noticing skills.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860651","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 learning analytics dashboard to support students' reflection on collaboration","authors":"Vanessa Echeverria,&nbsp;Gloria Fernandez Nieto,&nbsp;Linxuan Zhao,&nbsp;Evelyn Palominos,&nbsp;Namrata Srivastava,&nbsp;Dragan Gašević,&nbsp;Viktoria Pammer-Schindler,&nbsp;Roberto Martinez-Maldonado","doi":"10.1111/jcal.13088","DOIUrl":"https://doi.org/10.1111/jcal.13088","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Dashboards play a prominent role in learning analytics (LA) research. In collaboration activities, dashboards can show traces of team participation. They are often evaluated based on students' perceived satisfaction and engagement with the dashboard. However, there is a notable methodological gap in understanding how these dashboards support the nuanced process of student reflection.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This paper presents empirical evidence on how students from high and low-performing groups reflect individually on their performance while using a Learning Analytics Dashboard (LAD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We address this in the context of education in healthcare, wherein we captured actions and positioning data from a simulation-based collaborative activity and generated a collaborative LAD. A total of 41 nursing students were invited to participate in a post-hoc semi-structured individual interview to use a collaborative LAD while answering a set of prompts to reflect on their individual and group performance. Students' reflections were coded and analysed using Bain's 5R reflection framework. We used epistemic network analysis to capture the dynamic reflection process and to understand the connections between the reflection stages (from low to high). We compared how different these connections were for students in high and low-performing groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Our results revealed that most students were only able to achieve low and middle stages of reflection. Yet, students in low-performing groups predominantly followed low-to-middle stages of reflection. In contrast, students from high-performing groups demonstrated the ability to transition between low-to-middle and low-to-high stages of reflection. Based on these findings, we discuss implications for both research and practice, particularly emphasising the necessity to scaffold reflection when using LADs.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860480","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}