NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 7 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Liu, Cheng-Ye; Li, Wei; Huang, Ji-Yi; Lei, Lu-Yuan; Zhang, Pei-Rou – Journal of Computer Assisted Learning, 2023
Background: Socially shared regulation is a vital factor that affects students' collaborative programming performance. However, students' weak group metacognitive skills or inability to adopt shared regulation mechanisms lead to unsatisfactory collaborative programming learning. Objectives: This study proposes an approach to support socially…
Descriptors: Cooperative Learning, Programming, Academic Achievement, Metacognition
Peer reviewed Peer reviewed
Direct linkDirect link
Abed, Fayez; Barzilai, Sarit – Journal of Computer Assisted Learning, 2023
Background: YouTube is widely used for learning about scientific issues in and out of school. However, much of the scientific information on YouTube is inaccurate. Prior studies have mostly focused on how students evaluate textual online information sources and have not yet systematically examined how they evaluate authentic scientific YouTube…
Descriptors: Video Technology, Web Sites, Evaluative Thinking, Scientific and Technical Information
Peer reviewed Peer reviewed
Direct linkDirect link
Eniko Orsolya Bereczki; Zsofia K. Takacs; J. Elizabeth Richey; Huy A. Nguyen; Michael Mogessie; Bruce M. McLaren – Journal of Computer Assisted Learning, 2024
Background: Mindfulness practices enhance executive function skills and academic achievement, spurring interest in integrating mindfulness interventions into education. Embedding mindfulness practice into a digital math game may provide a low-cost, scalable way to induce mindfulness and boost game-based learning, yet this approach remains…
Descriptors: Metacognition, Educational Games, Video Games, Game Based Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Aydin Bulut; Mustafa Yildiz – Journal of Computer Assisted Learning, 2024
Background: The use of computer-assisted reading comprehension is of critical importance in the context of promoting effective and engaging literacy education in the digital age. It provides students with the opportunity to work at their own pace and convenience, thereby facilitating self-directed learning and accommodating various learning…
Descriptors: Computer Assisted Instruction, Direct Instruction, Reading Comprehension, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Hadad, Shlomit; Watted, Abeer; Blau, Ina – Journal of Computer Assisted Learning, 2023
Background: Integration of digital technologies in schools raises the need of students to master technological, cognitive, and social digital literacy (DL) competencies. Objectives: Based on Hofstede's dimensional paradigm for defining culture, we address the cultural context and examine perceived and actual DL of Arabic-speaking minority students…
Descriptors: Cultural Background, Digital Literacy, Cultural Context, Arabic
Peer reviewed Peer reviewed
Direct linkDirect link
Zhang, Yining; Lin, Chin-Hsi – Journal of Computer Assisted Learning, 2021
This study extends the community of inquiry (CoI) framework and self-regulated learning (SRL) theory through an exploration of the structural relationships among existing CoI variables, learning presence (i.e., self-efficacy and online SRL strategy) and learning outcomes in the context of K-12 online learning. To help understand the influence of…
Descriptors: Mentors, Communities of Practice, Metacognition, Self Efficacy
Peer reviewed Peer reviewed
Direct linkDirect link
Chang, Wen-Hui; Liu, Yuan-Chen; Huang, Tzu-Hua – Journal of Computer Assisted Learning, 2017
The purpose of this study is to develop a multi-dimensional scale to measure students' awareness of key competencies for M-learning and to test its reliability and validity. The Key Competencies of Mobile Learning Scale (KCMLS) was determined via confirmatory factor analysis to have four dimensions: team collaboration, creative thinking, critical…
Descriptors: Test Construction, Multidimensional Scaling, Electronic Learning, Test Reliability