Computers & Education最新文献

{"title":"An intelligent recommender system based on K-nearest neighbors to foster self-regulated learning and reduce cognitive load in online higher education","authors":"Shao-Chen Chang ,&nbsp;Ngoc Diep Dao","doi":"10.1016/j.compedu.2025.105470","DOIUrl":"10.1016/j.compedu.2025.105470","url":null,"abstract":"<div><div>Higher education institutions worldwide are increasingly adopting online learning systems to improve instructional quality and offer students flexible, anytime-anywhere access to educational resources. Despite these benefits, online learning environments still face notable challenges. In this learning environment, the major challenge lies in the lack of personalized learning support. The “one-size-fits-all” approach ignores learners' diverse needs, making it difficult for students to regulate their learning effectively. Without tailored guidance, students especially low achievers are more likely to experience cognitive overload, reduced motivation, disengagement, and even dropout. In response to these issues, this study presents an interactive self-regulated learning system built on a comprehensive system architecture that integrates personalized learning path recommendations based on K-nearest Neighbors (KNN) for university students. The system consists of four main components: Content Management System (CMS), Evaluation System, Recommendation System, and User Interface application. This study evaluates the system's perceived effectiveness in the “Introduction to Database Systems” course at a university located in northern Taiwan. It further investigates the system's impact on students' learning behavior, self-regulated learning skills, learning achievement and perceived cognitive load in an online learning environment. The findings suggest that students using the interactive self-regulated learning system with personalized recommendation paths exhibited higher motivation, engagement, learning achievement and self-regulated learning skills. The system also contributed to a noticeable reduction in students'perceived cognitive load.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105470"},"PeriodicalIF":10.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of a human-robot collaborative teaching approach on preschoolers’ social-emotional competence and learning behaviors","authors":"Jian-Wen Fang ,&nbsp;Ting-Ting Ji ,&nbsp;Yun-Fang Tu ,&nbsp;Gwo-Jen Hwang ,&nbsp;Di Zou ,&nbsp;Jing Chen","doi":"10.1016/j.compedu.2025.105469","DOIUrl":"10.1016/j.compedu.2025.105469","url":null,"abstract":"<div><div>Preschoolers' social-emotional competence is key to their long-term academic success. Developing this competence requires meaningful social interactions and emotional support, which the conventional teaching (CT) approach may not fully provide. This study proposed a human-robot collaborative teaching (HRCT) approach to facilitate preschoolers' social-emotional learning (SEL). A human-robot collaborative teaching system was developed to foster preschoolers' social-emotional competence through collaboration between the humanoid intelligent robot and the teacher. To evaluate the effectiveness of this approach, 96 preschoolers with an average age of 4.6 years were recruited. Of these, 44 were randomly assigned to the experimental group, which utilized the HRCT approach, while 52 were assigned to the control group, which followed the conventional teaching approach. The results indicated that the experimental group outperformed the control group in terms of social interaction skills, emotion comprehension skills, and interpersonal problem-solving skills. Significant differences were also observed in the learning behaviors of preschoolers during activities related to social interaction, emotion comprehension, and interpersonal problem solving. Further analysis of the teacher's perceptions and reflections revealed that, despite some limitations of the robot, its anthropomorphic and embodied features effectively sparked preschoolers' interest and engagement. These features contributed to enhancing their social-emotional competence by simulating and practicing SEL processes.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105469"},"PeriodicalIF":10.5,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic literature review on designing self-regulated learning using generative artificial intelligence and its future research directions","authors":"Qi Xia ,&nbsp;Qian Liu ,&nbsp;Ahmed Tlili ,&nbsp;Thomas K.F. Chiu","doi":"10.1016/j.compedu.2025.105465","DOIUrl":"10.1016/j.compedu.2025.105465","url":null,"abstract":"<div><div>A growing body of research suggests that generative AI (GenAI) can significantly enhance self-regulated learning (SRL) through its immediacy and interactivity. Nevertheless, challenges remain, including the lack of clarity regarding the mechanisms by which generative AI influences SRL, as well as the difficulties teachers encounter when trying to incorporate it into their classrooms. This systematic review study investigates how to design SRL activities using GenAI. We examined 73 articles published over the past five years, drawn from four databases: Web of Science, ProQuest, ERIC, and Scopus. This study has three major empirical findings. First, six pedagogical affordances from GenAI across the three phases of SRL—forethought, Performance, and self-reflection—are (i) creating personalized learning objectives; (ii) searching for, analyzing, and integrating resources; (iii) monitoring and evaluating progress; (iv) recommending learning strategies; (v) recording progress and providing feedback; and (vi) generating new ideas and examples. Second, popular student learning activities using GenAI in each phase are information searching in the forethought; strategies for problem-solving in the performance, and obtaining feedback and conducting self-assessments in the self-reflection. Third, two major dimensions influencing student engagement in SRL using GenAI are individual and environmental. Finally, we visualize how the three empirical findings relate to each other. Our findings help us understand how AI as a human-machine collaborative tool affects the SRL process. This study provides practical recommendations for facilitating SRL in GenAI-enhanced environments and offers guidance for the design and development of personalized GenAI learning tools.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105465"},"PeriodicalIF":10.5,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing an AI learning companion for mathematics problem solving in elementary schools","authors":"Bor-Chen Kuo,&nbsp;Zong-En Bai,&nbsp;Chia-Hua Lin","doi":"10.1016/j.compedu.2025.105463","DOIUrl":"10.1016/j.compedu.2025.105463","url":null,"abstract":"<div><div>This study examined the impact of integrating the Taiwan Adaptive Learning Platform (TALP) with generative AI-based learning companion (TALPers) on fifth-grade students' mathematics learning performance. The integration was applied to both self-learning and remedial instruction, with both contexts incorporating Socratic dialogue and Pólya's problem-solving strategy. Results showed that video-based self-learning with TALPer support yielded the highest learning gains. In the remedial setting, students receiving TALPer support also demonstrated significantly better performance. Both approaches were particularly effective for low-achieving students. Lag Sequential Analysis (LSA) further revealed that high-achieving students engaged in more complex interaction patterns with TALPers, sustaining feedback cycles, whereas low-achieving students exhibited simpler interaction patterns. These findings provide empirical support for implementing AI-augmented learning systems in mathematics education and suggest that structured AI support can promote differentiated instruction and student engagement to help bridge achievement gaps.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105463"},"PeriodicalIF":10.5,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can virtual reality improve social-emotional learning among adolescents? An experimental study","authors":"Qinna Feng ,&nbsp;Gege Li ,&nbsp;Yanbei Chen ,&nbsp;Feng Zhang ,&nbsp;Wenhao Li ,&nbsp;Heng Luo","doi":"10.1016/j.compedu.2025.105462","DOIUrl":"10.1016/j.compedu.2025.105462","url":null,"abstract":"<div><div>The potential of virtual reality (VR) to support social-emotional learning (SEL) has been widely acknowledged, but design precedents for VR-based SEL interventions are still lacking in the literature. The effectiveness of such interventions also remains uncertain due to insufficient empirical evidence. To bridge this research gap, the present study adopted a between-subjects design to explore the impact of a VR-based intervention on enhancing SEL and learning experience. A total of 297 seventh-grade students in China were randomly assigned to one of three conditions: VR (n = 101), face-to-face (n = 107), and control (n = 89). Participants in both the VR and face-to-face conditions engaged in collaborative tasks designed to promote SEL, while the control condition received no such intervention. The findings revealed significant improvement in overall social-emotional competencies in the VR condition, especially in the subscales of task performance, collaboration, and engagement with others. The VR intervention also promoted a stronger sense of group cohesion and enriched social experiences. These findings offer practical implications for the design and implementation of VR-based SEL interventions in formal education settings.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105462"},"PeriodicalIF":10.5,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structured briefing: Towards meaningful learning experiences with simulation games","authors":"Maria Freese ,&nbsp;Heide K. Lukosch","doi":"10.1016/j.compedu.2025.105461","DOIUrl":"10.1016/j.compedu.2025.105461","url":null,"abstract":"<div><div>Simulation gaming is an interactive method to simulate complex problems, allowing learners to experience, explore, and experiment with dynamic situations and processes. Simulation gaming sessions usually consist of three key phases – briefing, gameplay, and debriefing. Often, debriefing is seen as the most important part of such a session. Even though the briefing is supposed to have a similar significance as the debriefing, it is still an underrepresented, and underexplored phase in simulation gaming research. The briefing is in many cases the first point of contact between the facilitator(s) and the learner(s), and has an influence on the learning experience and outcomes. It is therefore important to understand how to implement a meaningful briefing to support the objectives of a simulation game. However, an agreed understanding of the briefing phase does not yet exist. To address this problem, we conducted a systematic literature review and analysed existing briefing approaches. The results show that the briefing phase within a simulation gaming session can be conceptualized along its structure and content, related both to the learner(s) and the facilitator(s). Furthermore, briefing can be differentiated into three phases: pre-, main-, and post-briefing. At all phases of the briefing, the facilitator is given a significant amount of responsibility for the success of the simulation gaming session. As conclusion, we propose a new briefing framework to be used by gaming researchers and practitioners to design and evaluate briefing activities.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105461"},"PeriodicalIF":10.5,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Children's engagement with digital technology in educational spaces: A scoping review","authors":"Jacquelyn Harverson ,&nbsp;Chris Zomer ,&nbsp;Celine Chu ,&nbsp;Sharon Horwood ,&nbsp;Marcus Horwood ,&nbsp;Maria Nicholas ,&nbsp;Louise Paatsch","doi":"10.1016/j.compedu.2025.105454","DOIUrl":"10.1016/j.compedu.2025.105454","url":null,"abstract":"<div><div>Children's engagement in play and learning is becoming increasingly complex as educational spaces integrate digital experiences. While engagement is often seen as a multifaceted construct, there is often no clear and generally accepted definition or understanding of what is meant when the term ‘engagement’ is used. This scoping review synthesised the ways in which engagement has been conceptualised within young children's digital experiences in educational spaces. A systematic search of seven databases captured studies published between 2011 and September 2024. Studies reporting children's engagement with digital technology (e.g., in play or learning via any digital experience) that were conducted in a formal or semi-formal educational setting were included. A total of 2661 records were screened, resulting in the inclusion of 88 studies. The concept of <em>engagement</em> was explicitly defined in 18 studies (19.3 %), theorised in 8 studies (9.1 %), and measured in 31 studies (35.2 %). Theoretical foundations of engagement drew from digital and educational disciplines, primarily rooted in motivational theories. Thematic analysis demonstrated the multidimensional nature of engagement, synthesised through ten key themes drawn from the definitions and measures provided. The most prominent themes identified in definitions were <em>participation</em> (<em>n</em> = 8, 44.4 %), <em>effort</em> (<em>n</em> = 7, 38.9 %) and <em>interpersonal skills and behaviour</em> (<em>n</em> = 6, 33.3 %), while those found in measures of engagement were predominantly associated with <em>enjoyment</em> (<em>n</em> = 14, 45.2 %), <em>participation</em> (<em>n</em> = 11, 35.5 %), and <em>interest</em> (<em>n</em> = 8, 25.8 %). This review highlights the need for more consistent approaches in defining and measuring children's digital engagement.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105454"},"PeriodicalIF":10.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring characteristics of primary school students’ self-regulated learning (SRL) behaviors in human-GenAI collaborative programming learning environments: Insights from a proposed framework","authors":"Xuechun Ma ,&nbsp;Cuixin Li ,&nbsp;Jie Xu ,&nbsp;Shiyun Zhu ,&nbsp;Yan Li","doi":"10.1016/j.compedu.2025.105453","DOIUrl":"10.1016/j.compedu.2025.105453","url":null,"abstract":"<div><div>Programming education in primary school is vital for nurturing future-ready talents, yet primary school students often struggle with self-regulated learning (SRL), particularly in resource utilization and strategy regulation. Although human-generative AI (GenAI) collaborative programming learning might have the potential to enhance personalized programming education, GenAI's interplay with SRL processes remains underexplored. To address this gap, this study first proposed a SRL Behavior Analysis Framework for human-GenAI collaborative programming learning environments and then examined SRL behaviors of a group of sixth-grade students (n = 36) in such an environment using this framework, along with various learning analytics methods including cluster analysis, descriptive statistics and lag sequential analysis. The analysis yielded the following results: (1) Based on their learning performance, primary school students were identified as three distinct clusters: programming specialized unit (PSU), high performance unit (HPU), and low performance unit (LPU). (2) Regarding SRL behaviors, students prioritized self-control (65.8 %), followed by self-observation (19 %), task analysis (12.1 %), and behavior stagnation (3.2 %). (3) Students in PSU and HPU consistently adopted goal-oriented SRL strategies, whereas students in LPU exhibited passive dependence and fragmented strategy use. GenAI's facilitative effect in supporting learning correlated with users' SRL capabilities. (4) Students in PSU and HPU exhibited frequent transitions between SRL behaviors, whereas students in LPU had insufficient ability to switch strategies when facing programming difficulties. Based on these findings, this study proposed four forward-looking design recommendations: effectively integrating GenAI with the programming environment, utilizing multimodal data and AI for learning assessment and feedback, building a cluster-driven early warning mechanism, and conducting dynamic SRL analysis and guidance based on fine-grained time-series data.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105453"},"PeriodicalIF":10.5,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tailoring educational support with graph neural networks and explainable AI: Insights into online learners' metacognitive abilities","authors":"Hongjiang Wang ,&nbsp;Peiyu Chen ,&nbsp;Jinwen Luo ,&nbsp;Yunying Yang","doi":"10.1016/j.compedu.2025.105452","DOIUrl":"10.1016/j.compedu.2025.105452","url":null,"abstract":"<div><div>Metacognition—the awareness and regulation of one's thinking processes—plays a crucial role in self-regulated learning (SRL), yet traditional educational research methods struggle to capture how metacognitive abilities manifest in actual learning behaviors. While computer-assisted learning (CAL) environments offer rich opportunities to observe these processes in action, educational researchers have typically analyzed this data using approaches that fail to connect metacognitive abilities with the complex, sequential nature of SRL behaviors. Our study bridges this gap by examining how 49 university students' metacognitive abilities shaped their learning patterns over one semester. We introduced a novel methodological approach that transforms diverse digital traces into unified graph structures, allowing us to map connections between metacognitive abilities and the planning, monitoring, and evaluation phases of SRL. Using attributed graphs, we integrated both static indicators and sequential behavioral patterns to predict metacognitive abilities with significantly higher accuracy than traditional single-data approaches, including Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNN), Artificial Neural Networks (ANN), and Random Forest (RF). Through Explainable AI techniques, we revealed that high-metacognitive learners exhibited comprehension-centered, goal-oriented strategies across learning phases, while low-metacognitive learners focused primarily on task completion with limited strategic planning. These insights enabled us to develop personalized metacognitive profiles that can guide targeted educational interventions. Our approach demonstrates how advanced analytical methods can transform educational data into meaningful insights about cognitive processes, offering educators new ways to understand and support students' metacognitive development.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105452"},"PeriodicalIF":10.5,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaborative AI-in-the-loop pedagogical conversational agent to enhance social and cognitive presence in cMOOC","authors":"Jianjun Xiao ,&nbsp;Yulin Tian ,&nbsp;Cixiao Wang","doi":"10.1016/j.compedu.2025.105451","DOIUrl":"10.1016/j.compedu.2025.105451","url":null,"abstract":"<div><div>While connectivist MOOCs (cMOOCs) emphasize learner autonomy and peer interaction, the lack of structured facilitation often hinders the development of social and cognitive presence. This study investigates how Pedagogical Conversational Agents (PCAs) enhance learners' social and cognitive presence in cMOOC environments. Using a within-subjects quasi-experimental design, 344 learners (primarily in-service teachers, 93.60 %) participated in a cMOOC course over four weeks. The 54 discussion topics generated by learners were randomly assigned to experimental (with-PCA, <em>N</em> = 19) and control (without-PCA, <em>N</em> = 35) conditions. A collaborative AI-in-the-loop design was implemented where AI-generated content underwent human review before publication. Analysis of 5301 discussion posts using the Community of Inquiry framework revealed that PCAs significantly enhanced open communication (<em>p &lt; .001, r=-0.213</em>) and group cohesion (<em>p=.027, r=-0.106</em>) in social presence, while improving higher-order cognitive processes, including integration (<em>p=.011, r=-0.119</em>) and resolution (<em>p=.028, r=-0.145</em>). Direct interaction with PCAs yielded superior outcomes in affective expression (<em>p=.027, r=0.103</em>) and specific communication behaviors compared to co-present modes. The findings demonstrate that PCAs provide compensatory support by strengthening cMOOCs' relatively weak components of cognitive presence (integration and resolution) rather than providing comprehensive intervention; direct interaction modes with PCA yield more benefit for deep exploration and social engagement. This offers evidence-based design strategies for AI agent implementation in online education.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"240 ","pages":"Article 105451"},"PeriodicalIF":10.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}