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Xiaoxiao Liu; Okan Bulut; Ying Cui; Yizhu Gao – Journal of Computer Assisted Learning, 2025
Background: 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…
Descriptors: Adults, Problem Solving, Markov Processes, Network Analysis
Chun-Chun Chang; Gwo-Jen Hwang; Liang-Shiou Ou – Journal of Computer Assisted Learning, 2025
Background: Health education aims to encourage individuals to voluntarily take action to improve their health. Throughout this process, adult learners can make informed decisions to change their behaviours and enhance their well-being. In medical institutions, employing appropriate instructional strategies to facilitate changes in health…
Descriptors: Patients, Cognitive Processes, Robotics, Patient Education
Camille Tordet; Jonathan Fernandez; Eric Jamet – Journal of Computer Assisted Learning, 2025
Background: 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. Aims: This study aimed to…
Descriptors: Self Management, Academic Achievement, Cognitive Processes, Multimedia Materials
Peijian Paul Sun; Zeqi Ren; Xian Zhao – Journal of Computer Assisted Learning, 2025
Background: Student engagement has been conceptualised and operationalised in various learning environments. However, there is currently a lack of established scales to measure student engagement in synchronous online learning. One possible reason is the existence of the conceptual and structural ambiguity regarding student engagement. Objective:…
Descriptors: Student Participation, Second Language Learning, Synchronous Communication, Electronic Learning
Meiyan Huang; Tang Yongquan – Journal of Computer Assisted Learning, 2025
Aim: In recent years, the integration of cutting-edge technology into professional sports training (ST) has revolutionized the way athletes prepare for competition. The study aims to quantitatively analyse the impact of cutting-edge technology on enhancing performance, efficiency, and outcomes in professional ST programs. Purpose: The purpose of…
Descriptors: Athletics, Technology, Influence of Technology, Training
Cynthia Y. Delgado; Richard E. Mayer – Journal of Computer Assisted Learning, 2025
Background: In recent years, immersive virtual reality in education has garnered attention, however, there have been mixed findings on the efficacy of IVR in education. Thus, exploring which strategies are effective in transferring learning from IVR to real-world applications is imperative. Objective: This study aims to investigate the efficacy of…
Descriptors: Computer Simulation, Experiential Learning, Instructional Effectiveness, Transfer of Training
Lishan Zhang; Lili Liu; Shuwen Wang; Min Xu; Sixv Zhang; Yun Tang – Journal of Computer Assisted Learning, 2025
Background: Collaborative reading can facilitate students' understanding of complex learning materials. High-quality annotations provided by peer learners are essential for successful collaborative reading. However, it remains to be understood how annotation quality affects reading comprehension. Objectives: A simulated collaborative reading…
Descriptors: Educational Quality, Documentation, Reading Processes, Eye Movements
Jana Gonnermann-Müller; Jule M. Krüger – Journal of Computer Assisted Learning, 2025
Background: Despite the numerous positive effects of augmented reality (AR) on learning, previous research has shown ambiguous results regarding the cognitive demand on the learner arising from, for example, the overlay of virtual elements or novel interaction techniques. At the same time, the number of evidence-based guidelines on designing AR is…
Descriptors: Computer Simulation, Computer Assisted Design, Difficulty Level, Cognitive Processes
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Alfoncina Baeza; J. Enrique Hinostroza – Journal of Computer Assisted Learning, 2025
Background: After the mandated closure and reopening of schools during and after the coronavirus pandemic, online synchronous teaching and learning has emerged as an opportunity to expand the reach of K-12 education, however, there is a lack of understanding about the characteristics of the successful learning experiences during that period that…
Descriptors: Foreign Countries, Online Courses, Synchronous Communication, High School Students
Kshitij Sharma; Serena Lee-Cultura; Sofia Papavlasopoulou; Michail Giannakos – Journal of Computer Assisted Learning, 2025
Background: Effort measurement is essential for adaptation to interactive learning technologies. Most contemporary technologies measure effort through the log data (reaction time and correctness). Some adaptive technologies use facial expressions and attention to adapt. Objectives: We present a novel, complementary, and multimodal definition of…
Descriptors: Academic Persistence, Educational Technology, Technology Uses in Education, Assistive Technology
Rashmi Khazanchi; Daniele Di Mitri; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: 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…
Descriptors: Mathematics Achievement, Rural Areas, Artificial Intelligence, Individualized Instruction
Gwo-Jen Hwang; Jalil Fathi; Masoud Rahimi – Journal of Computer Assisted Learning, 2025
Background: The utilisation of video-dubbing tasks, wherein learners record their voices over video clips to practise pronunciation, fluency, grammatical accuracy, and vocabulary use, is relatively novel in the English language learning context. Exploring the effectiveness of video-dubbing tasks can lead to more innovative and effective speaking…
Descriptors: English (Second Language), Second Language Learning, Speech Skills, Cognitive Processes
Shunmeng Chen – Journal of Computer Assisted Learning, 2025
Background: Computer-mediated writing classes have experienced a significant increase in popularity in recent years, serving as an effective modality for enhancing writing skills within an online framework. Objectives: This study seeks to bridge the gap in the literature by investigating the effectiveness of cognitive, social, and group-awareness…
Descriptors: Cognitive Processes, Difficulty Level, Computer Assisted Instruction, Writing Instruction
Lion Sieg; Hendrik Eismann; Bertrand Schneider; Jan Karsten; Dogus Darici – Journal of Computer Assisted Learning, 2025
Background: Research in social cognition suggests that learning effectiveness in teacher-learner pairs may be influenced by how well their attention aligns with each other. However, we currently have limited understanding of how common distractions in real-world environments affect teacher-student interactions, specifically the synchronisation of…
Descriptors: Attention Control, Social Cognition, Teacher Student Relationship, Interaction
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