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Yuan Tian; Zhongjian Liu; Hainuo Liu; Min Fang – Journal of Computer Assisted Learning, 2025
Background: Online videos featuring human-generated drawing are increasingly popular in education. However, their effectiveness may vary depending on learners' prior knowledge, and further research is needed to confirm their advantages over other common instructional videos. Objectives: The primary goal of this study is to investigate the impact…
Descriptors: Video Technology, Educational Technology, Instructional Films, Freehand Drawing
Ankora, Carlos; Bolatimi, Stephen Oladagba; Bensah, Lily; Mahama, Francois; Kuadey, Noble Arden; Adu, Adolph Sedem Yaw; Adjei, Laurene – Journal of Computer Assisted Learning, 2023
Background: The degree to which Computer Science (CS) and Information Communication Technology (ICT) students are motivated to learn greatly impacts their study habits, academic achievement in school and ultimately their job prospects. In recent times, skills in programming languages have become vital in searching for employment. Objective: This…
Descriptors: College Students, Student Motivation, Course Selection (Students), Programming Languages
Ameloot, Elise; Rotsaert, Tijs; Schellens, Tammy – Journal of Computer Assisted Learning, 2022
Background: Although blended learning (BL) has multiple educational prospects, it also poses challenges such as keeping students motivated. Objectives: This study investigates students' perceptions of how learning analytics (LA) can be used to support the design of a BL environment in order to promote students' basic need for relatedness, which is…
Descriptors: Learning Analytics, Blended Learning, Student Attitudes, Need Gratification
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Lee, Yuan-Hsuan – Journal of Computer Assisted Learning, 2022
Background: Processing and comprehending information from multiple sources have been a primary means of learning and are essential 21st-century skills to construct knowledge for a deeper understanding. Objectives This study examined students' individual differences in search strategies and internet epistemic beliefs as well as the effect of…
Descriptors: Reading Comprehension, Search Strategies, Online Searching, Internet
Angelica Ronconi; Lucia Mason; Lucia Manzione; Anne Schüler – Journal of Computer Assisted Learning, 2025
Background: During digital reading on internet-connected devices, students may be exposed to a variety of on-screen distractions. Learning by reading can therefore become a fragmented experience with potentially negative consequences for reading processes and outcomes. Objectives: This study investigated the effects of on-screen distractions, as…
Descriptors: Eye Movements, Electronic Learning, Computer Uses in Education, Reading
Arslan-Ari, I. – Journal of Computer Assisted Learning, 2018
The purpose of this study was to investigate the effects of cueing and prior knowledge on learning and mental effort of students studying an animation with narration. This study employed a 2 (no cueing vs. visual cueing) × 2 (low vs. high prior knowledge) between-subjects factorial design. The results revealed a significant interaction effect…
Descriptors: Animation, Prior Learning, Prompting, Learning
Gurlitt, J.; Renkl, A. – Journal of Computer Assisted Learning, 2008
We investigated whether and how prior knowledge activation improves learning outcomes for high school (less experienced learners) and university students (experienced learners) in a hypertext environment. Map coherence was defined as the extent to which relationships between the concepts in the map were made explicit. Therefore, we classified the…
Descriptors: High School Students, College Students, Concept Mapping, Learning Strategies