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Gerti Pishtari; María Jesús Rodríguez-Triana; Luis P. Prieto; Adolfo Ruiz-Calleja; Terje Väljataga – Journal of Computer Assisted Learning, 2024
Background: In the field of Learning Design, it is common that researchers analyse manually design artefacts created by practitioners, using pedagogically-grounded approaches (e.g., Bloom's Taxonomy), both to understand and later to support practitioners' design practices. Automatizing these high-level pedagogically-grounded analyses would enable…
Descriptors: Electronic Learning, Instructional Design, Active Learning, Inquiry
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Yu Gao; Linjing Wu; Xiaotong Lv; Xinqian Ma; Qingtang Liu – Journal of Computer Assisted Learning, 2024
Background: Both socially regulated learning and cognitive quality are important factors affecting collaborative knowledge building, but the current research lacks a joint quantified evaluation method that combines these two aspects. Objectives: Based on the existing framework, we proposed a joint evaluation method for regulated learning and…
Descriptors: Self Management, Cooperative Learning, Learning Strategies, Evaluation Methods
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Guo, Liming; Du, Junlei; Zheng, Qinhua – Journal of Computer Assisted Learning, 2023
Background: There is a strong association between interactions and cognitive engagement, which is crucial for constructing new cognition and knowledge. Although interactions and cognitive engagement have attracted extensive attention in online learning environments, few studies have revealed the evolution of cognitive engagement with interaction…
Descriptors: Cognitive Ability, Learner Engagement, Electronic Learning, Technology Uses in Education
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Liping Jiang; Menglei Lv; Mengmeng Cheng; Xia Chen; Changhong Peng – Journal of Computer Assisted Learning, 2024
Background: The introduction of Small Private Online Courses (SPOCs) in English as a Foreign Language (EFL) instruction at Higher Vocational Colleges (HVCs) signifies a shift in education. Understanding the factors that affect deep learning in this SPOC context is crucial for improving educational outcomes. Objectives: By employing grounded…
Descriptors: Higher Education, Vocational Education, College Students, Private Education
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Fatimah H. Aldeeb; Omar M. Sallabi; Monther M. Elaish; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: This paper examines the use of augmented reality (AR) as a concept-association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR-enriched learning, with some reporting reduced load and others indicating…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
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Tran-Duong, Quoc Hoa; Vo-Thi, Ngoc-Tram – Journal of Computer Assisted Learning, 2023
Background: Recent years have seen the proliferation of online courses that have been initiated either in accordance with the natural rhythms of educational technology growths or in force majeure situations. This adds complexity to understanding the influence of potential factors on online student engagement. Objectives: The present study…
Descriptors: Undergraduate Students, Electronic Learning, Learner Engagement, Social Media
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Zhan, Zehui; He, Guoqing; Li, Tingting; He, Luyao; Xiang, Siyu – Journal of Computer Assisted Learning, 2022
Background: Group size is one of the important factors that affect collaborative learning, however, there is no consensus in the literature on how many students should the groups be composed of during the problem-solving process. Objectives: This study investigated the effect of group size in a K-12 introductory Artificial Intelligence course by…
Descriptors: Cognitive Ability, High School Students, Cooperative Learning, Artificial Intelligence
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Huang, Weijiao; Hew, Khe Foon; Fryer, Luke K. – Journal of Computer Assisted Learning, 2022
Background: The use of chatbots as learning assistants is receiving increasing attention in language learning due to their ability to converse with students using natural language. Previous reviews mainly focused on only one or two narrow aspects of chatbot use in language learning. This review goes beyond merely reporting the specific types of…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Computer Mediated Communication
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Xie, Heping; Zhao, Tingting; Deng, Sue; Peng, Ji; Wang, Fuxing; Zhou, Zongkui – Journal of Computer Assisted Learning, 2021
Eye movement modelling examples (EMME) are computer-based videos displaying the visualized eye gaze behaviour of a domain expert person (model) while carefully executing the learning or problem-solving task. The role of EMME in promoting cognitive performance (i.e., final scores of learning outcome or problem solving) has been questioned due to…
Descriptors: Eye Movements, Attention, Cognitive Ability, Learning Processes
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Martin Merkt; Daniel Bodemer – Journal of Computer Assisted Learning, 2024
Background: When watching educational online videos, learners need to determine whether the videos' contents are suitable for learning. Whereas this may induce metacognitive monitoring processes, it may also distract learners from the learning materials. Objectives: In the current set of experiments, we investigated whether asking participants to…
Descriptors: Video Technology, Teaching Methods, Metacognition, Instructional Materials
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Liujie Xu; Xuefei Zou; Yuxue Hou – Journal of Computer Assisted Learning, 2024
Background: Data literacy (DL) is vital for teachers, as it enables them to build on data and improve teaching and learning. Therefore, developing DL among pre-service teachers is critical. Objectives: The purpose of this study is threefold: to evaluate whether a feedback visualisation of peer assessment-based teaching approach (FVPA-based…
Descriptors: Statistics Education, Comparative Analysis, Preservice Teachers, Teacher Education Programs
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Gu, Xiaoqing; Cai, Huiying – Journal of Computer Assisted Learning, 2019
A semantic diagram tool is proposed in this study in order to structure collaborative problem solving (CPS) based on cognitive load theory (CLT). To investigate its effects on transaction cost and the deepening of user understandings, a comparative quasi-experiment was designed and conducted with 49 participants from a university in East China.…
Descriptors: Semantics, Cooperative Learning, Cognitive Ability, Foreign Countries
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Wang, Tzu-Ling; Tseng, Yi-Kuan – Journal of Computer Assisted Learning, 2020
The purpose of this study was to investigate not only the effectiveness of dynamic versus static visualizations on learning star motions but also the influence of students' spatial abilities with these two types of visualizations on their learning. We assigned 155 fifth-grade students to either a dynamic or a static condition. We used a science…
Descriptors: Teaching Methods, Computer Assisted Instruction, Spatial Ability, Science Achievement
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Lange, C.; Costley, J. – Journal of Computer Assisted Learning, 2018
Highly interactive and complex content within e-learning induces high levels of intrinsic load. Self-regulated effort represents one strategy that may help learners overcome such issues within e-learning. Using intrinsic load items representative of content complexity, germane load items representative of learning, and self-regulated effort items…
Descriptors: Metacognition, Electronic Learning, Independent Study, Correlation
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Shadiev, Rustam; Wu, Ting-Ting; Huang, Yueh-Min – Journal of Computer Assisted Learning, 2018
We provided texts generated by speech-to text-recognition (STR) technology for non-native English speaking students during lectures in English in order to test whether STR-texts were useful for enhancing students' comprehension of lectures. To this end, we carried out an experiment in which 60 participants were randomly assigned to a control group…
Descriptors: English (Second Language), Second Language Learning, Pretests Posttests, Lecture Method
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