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Shilpi Harnal; Gaurav Sharma; Anupriya; Anand Muni Mishra; Deepak Bagga; Nikhil Saini; Pankaj Kumar Goley; Kumar Anupam – Journal of Computer Assisted Learning, 2024
Background: An innovative and interactive real-world environment can be presented with augmented reality (AR) that comprises digital visual elements, audio, or other sensory information delivered via technology to enhance one's experience. AR has numerous potential applications in various everyday fields. The education sector is one such arena…
Descriptors: Bibliometrics, Computer Simulation, Artificial Intelligence, Educational Technology
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Mangaroska, Katerina; Martinez-Maldonado, Roberto; Vesin, Boban; Gaševic, Dragan – Journal of Computer Assisted Learning, 2021
Multimodal data have the potential to explore emerging learning practices that extend human cognitive capacities. A critical issue stretching in many multimodal learning analytics (MLA) systems and studies is the current focus aimed at supporting researchers to model learner behaviours, rather than directly supporting learners. Moreover, many MLA…
Descriptors: Computer Science Education, Student Attitudes, Learning Modalities, Learning Analytics
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Greenberg, Kevin; Zheng, Robert; Gardner, Michael; Orr, Matthew – Journal of Computer Assisted Learning, 2021
The cognitive theory of multimedia learning postulates learning information in a dual-modality design is more effective than in a single modality, which is known as the modality effect. Research has found that the modality effect supports problem-solving learning, but not retention-based learning. This divergence in findings can be explained by…
Descriptors: Individual Differences, Spatial Ability, Visual Perception, Short Term Memory
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Weipeng Yang; Xinyun Hu; Ibrahim H. Yeter; Jiahong Su; Yuqin Yang; John Chi-Kin Lee – Journal of Computer Assisted Learning, 2024
Background: Artificial Intelligence (AI) literacy is a crucial part of digital literacy that all individuals should possess in today's technologically advanced world. Despite the potential benefits that AI education offers, little research has been done on how to teach AI literacy to children. Objectives: This study aimed to fill that gap by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Digital Literacy
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Ran Peleg; Orly Lahav; Noha Hagab; Vadim Talis; Sharona T. Levy – Journal of Computer Assisted Learning, 2024
Background: Students who are blind are integrated into public schools in many countries, yet are often excluded from full participation in science since most learning materials are visual. To create a compensatory route, an existing model-based inquiry-learning environment was adapted by means of sonification (addition of non-speech sounds that…
Descriptors: Audiovisual Aids, Blindness, Science Education, Students with Disabilities
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Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2018
Multimodality in learning analytics and learning science is under the spotlight. The landscape of sensors and wearable trackers that can be used for learning support is evolving rapidly, as well as data collection and analysis methods. Multimodal data can now be collected and processed in real time at an unprecedented scale. With sensors, it is…
Descriptors: Educational Research, Data Collection, Data Analysis, Learning Modalities
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Beardsley, M.; Hernández-Leo, D.; Ramirez-Melendez, R. – Journal of Computer Assisted Learning, 2018
Low-cost devices have widened the use of multimodal data in experiments providing a more complete picture of behavioural effects. However, the accurate collection and combination of multimodal and behavioural data in a manner that enables reproducibility is challenging and often requires researchers to refine their approaches. This paper presents…
Descriptors: Data Analysis, Learning Modalities, Measurement Equipment, Data Collection
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Magana, Alejandra J.; Serrano, Mayari I.; Rebello, N. Sanjay – Journal of Computer Assisted Learning, 2019
Virtual learning environments can now be enriched not only with visual and auditory information, but also with tactile and kinesthetic feedback. However, the way to successfully integrate haptic feedback on a multimodal learning environment is still unclear. This study aims to provide guidelines on how visuohaptic simulations can be implemented…
Descriptors: Sequential Learning, Student Development, Concept Formation, Electronic Learning
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Oberfoell, A.; Correia, A. – Journal of Computer Assisted Learning, 2016
The modality principle states that low-experience learners more successfully understand information that uses narration rather than on-screen text. This is due to the idea that on-screen text may produce a cognitive overload if it is accompanied by other visual elements. Other studies provided additional data and support for the modality principle…
Descriptors: Multimedia Instruction, College Students, Learning Modalities, Cognitive Processes
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Wang, Y.-H.; Young, S. S.-C. – Journal of Computer Assisted Learning, 2015
This paper presents a study on implementing the ASR-based CALL (computer-assisted language learning based upon automatic speech recognition) system embedded with both formative and summative feedback approaches and using implicit and explicit strategies to enhance adult and young learners' English pronunciation. Two groups of learners including 18…
Descriptors: Computer Assisted Instruction, Formative Evaluation, Summative Evaluation, Adults
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Moreno, R. – Journal of Computer Assisted Learning, 2006
Does the modality of instructional messages affect learning? How does it affect different media? In this paper, I offer an answer to these questions by first proposing a theoretical framework from which effective instructional methods can be derived. Then, I report a set of studies where one method, the modality principle, was tested across…
Descriptors: Teaching Methods, Learning Modalities, Instructional Effectiveness, Hypothesis Testing
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Konur, O. – Journal of Computer Assisted Learning, 2007
Computer-assisted teaching and assessment has become a regular feature across many areas of the curriculum in higher education courses around the world in recent years. This development has resulted in the "digital divide" between disabled students and their nondisabled peers regarding their participation in computer-assisted courses. However,…
Descriptors: Academic Freedom, Disabilities, Computer Assisted Instruction, Student Evaluation
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Perrotta, C. – Journal of Computer Assisted Learning, 2006
The paper reports a study that investigated the construction of a common identity in an online Italian forum of psychologists based on asynchronous CMC. Discourse analysis was carried out on 20 discussions, and three Interpretative Repertoires were identified: (i) Professional Boundaries, (ii) disempowered psychology and (iii) psychology and…
Descriptors: Discourse Analysis, Discussion, Psychology, Educational Environment
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Collis, B.; And Others – Journal of Computer Assisted Learning, 1996
Addresses the problems of adapting instructional courses for trans-European tele-learning and for enlarging the range of students and learning modalities in distance learning. Building on previous work on the portability of educational software, various dimensions of software adaptation are examined and their possible effects on course adaptation…
Descriptors: Computer Software, Course Content, Curriculum Development, Distance Education
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Bassili, J. N. – Journal of Computer Assisted Learning, 2006
When presented with the option to use a new instructional technology, students often face an approach-avoidance conflict. This study explored promotion and prevention orientations, concepts linked to approach and avoidance in Higgins's regulatory focus theory, in the choice to attend lectures or watch them online. Openness, a core disposition in…
Descriptors: Personality Assessment, Internet, Teaching Methods, Individual Differences