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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
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
Alejandra Ruiz-Segura; Andrew Law; Sion Jennings; Alain Bourgon; Ethan Churchill; Susanne Lajoie – Journal of Computer Assisted Learning, 2024
Background: Flying accuracy is influenced by pilots' affective reactions to task demands. A better understanding of task-related emotions and flying performance is needed to enhance pilot training. Objective: Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty…
Descriptors: Foreign Countries, Flight Training, Aviation Technology, Computer Simulation
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
Lanqin Zheng; Yunchao Fan; Zichen Huang; Lei Gao – Journal of Computer Assisted Learning, 2024
Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building,…
Descriptors: Cooperative Learning, Electronic Learning, College Students, Learning Strategies
Robert O. Davis; Yong-Jik Lee; Joseph Vincent; Lili Wan – Journal of Computer Assisted Learning, 2024
Background: Gestures are an integral component in human-to-human communication when the speaker is visually present to the listener. In the past several years, research has examined how computer-generated pedagogical agents can be designed to perform the four main gesture types and what this means for agent persona and learning outcomes. The…
Descriptors: Nonverbal Communication, Interpersonal Communication, Multimedia Instruction, Imagery
Akbar Bahari; Parviz Alavinia; Mohammad Mohammadi – Journal of Computer Assisted Learning, 2024
Background: This study investigates the effects of higher and lower-level text processing strategies on both higher and lower-level processing skills and cognitive load using the computer-assisted interactive reading model (CAIRM) as the educational intervention framework. Objectives: The objectives of this study are to examine the effects of the…
Descriptors: Computer Assisted Instruction, Experiential Learning, Reading, Cognitive Processes
Rafael Mellado; Claudio Cubillos – Journal of Computer Assisted Learning, 2024
Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with…
Descriptors: Engineering Education, College Students, Computer Software, Technical Occupations
Yuko Suzuki; Fridolin Wild; Eileen Scanlon – Journal of Computer Assisted Learning, 2024
Background: Cognitive load during AR use has been measured conventionally by performance tests and subjective rating. With the growing interest in physiological measurement using non-invasive biometric sensors, unbiased real-time detection of cognitive load in AR is expected. However, a range of sensors and parameters are used in various subject…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Physiology
Carolien A. N. Knoop-van Campen; Joep van der Graaf; Anne Horvers; Rianne Kooi; Rick Dijkstra; Inge Molenaar – Journal of Computer Assisted Learning, 2024
Background: Even though monitoring and control enactment are key aspects of self-regulated learning (SRL), Adaptive learning technologies (ALTs) may reduce the need for learners to monitor and control their learning. Personalized dashboards are effective in supporting learners' monitoring and can potentially support control behaviour. Allowing…
Descriptors: Elementary School Students, Grade 5, Educational Technology, Technology Uses in Education
Julius Moritz Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Journal of Computer Assisted Learning, 2024
Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can…
Descriptors: Video Technology, Models, Cues, Problem Solving
Ziyi Kuang; Fuxing Wang; Frank Andrasik; Xiangen Hu – Journal of Computer Assisted Learning, 2024
Background: Little is known about the effectiveness of instructors when presenting content in videos alone. In recent years, researchers have increasingly begun to explore the effects of instructors' social cues (e.g., eye gaze, body orientation, etc.) on learning. However, previous studies exploring the effects of eye gaze have confounded the…
Descriptors: Teacher Behavior, Eye Movements, Human Body, Teacher Effectiveness
Doug Kueker; Joi Moore – Journal of Computer Assisted Learning, 2024
Background: Learning to use software using screencast videos with worked examples in the corresponding practice files presents a classic split-attention problem that requires learners to mentally integrate information from the video with a target application. While there is evidence that splitting attention either temporally or spatially adversely…
Descriptors: Participant Observation, Interactive Video, Computer Peripherals, Attention Control
Xiu Xin; Meng Zhang – Journal of Computer Assisted Learning, 2024
Background: Some studies have researched the correlation between flipped learning and cognitive learning outcomes; however, there is a paucity of research elaborating on the effects of flipped language learning on cognitive load (CL). Objectives: This study investigates the effects of using flipped learning designs (student-led, teacher-led and…
Descriptors: Flipped Classroom, Second Language Learning, English (Second Language), Computer Assisted Instruction
Luciana Maria Cavichioli Gomes Almeida; Stefan Münzer; Tim Kühl – Journal of Computer Assisted Learning, 2024
Background: According to the personalization effect in multimedia learning, the use of personal and possessive pronouns in instructional materials (e.g., 'you' and 'your') is beneficial. However, current research suggests that the personalization effect is inverted for emotionally aversive content (e.g., illnesses). Objective: This study…
Descriptors: Foreign Countries, Health Education, Health Promotion, Information Sources
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