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Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Slaviša Radovic; Niels Seidel; Joerg M. Haake; Regina Kasakowskij – Journal of Computer Assisted Learning, 2024
Background: Self-assessment serves to improve learning through timely feedback on one's solution and iterative refinement as a way to improve one's competence. However, the complexity of the self-assessment process is widely recognized, as well as that students can benefit from it only if their assessment is accurate enough. Objectives: In order…
Descriptors: Self Evaluation (Individuals), Distance Education, Student Behavior, Accuracy
Araos, Andrés; Damsa, Crina; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: The surge of online platforms has generated interest in how specialized platforms support formal and informal learning in various disciplinary domains. Knowledge is still limited regarding how undergraduate students navigate and use platforms to learn. Objectives: This study explores computer and software engineering students' learning…
Descriptors: Computer Science Education, Computer Software, Learning Activities, Undergraduate Students
Qin, Chao; Liu, Yanjia; Zhang, Hemei – Journal of Computer Assisted Learning, 2023
Background: Being easy to learn and fun, block-based programming tools are widely used to teach students introductory programming. Scratch and LEGO robots are two popular block-based programming tools. However, the objects they manipulate are completely different. Scratch manipulates graphical virtual sprites, whereas LEGO robots manipulate…
Descriptors: Foreign Countries, Undergraduate Students, Learner Engagement, Robotics
Ahmad Uzir, Nora'ayu; Gaševic, Dragan; Matcha, Wannisa; Jovanovic, Jelena; Pardo, Abelardo – Journal of Computer Assisted Learning, 2020
This paper aims to explore time management strategies followed by students in a flipped classroom through the analysis of trace data. Specifically, an exploratory study was conducted on the dataset collected in three consecutive offerings of an undergraduate computer engineering course (N = 1,134). Trace data about activities were initially coded…
Descriptors: Time Management, Blended Learning, Learning Analytics, Undergraduate Students
Sitthiworachart, J.; Joy, M. – Journal of Computer Assisted Learning, 2008
Active learning is considered by many academics as an important and effective learning strategy. Assessment is integrated in learning as a tool for learning, but traditional assessment methods often encourage surface learning (passive learning) rather than deep learning (active learning). Peer assessment is a method of motivating students,…
Descriptors: Peer Evaluation, Learning Strategies, Active Learning, Programming