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Ghada ElSayad – Education and Information Technologies, 2024
In student-centric learning environments, such as blended learning, students' metacognitive self-regulation is required to plan, monitor, and control their learning processes and achieve positive learning outcomes. The lack of metacognitive self-regulation may lead students to encounter difficulties that, eventually, affect their learning…
Descriptors: Undergraduate Students, Student Attitudes, Blended Learning, Metacognition
Jinhee Kim; Rita Detrick; Seongryeong Yu; Yukyeong Song; Linda Bol; Na Li – Education and Information Technologies, 2025
Supporting learners in achieving high-level socially shared regulation of learning (SSRL) in the online collaborative learning (OCL) context presents challenges that the utilization of artificial intelligence (AI) technologies may help solve. However, the effective uses of AI to support multifaceted areas (cognition, metacognition, and motivation)…
Descriptors: Artificial Intelligence, Technology Uses in Education, Electronic Learning, Cooperative Learning
Lilian Anthonysamy; Poovilashini Sugendran; Lim Ooi Wei; Teoh Sian Hoon – Education and Information Technologies, 2024
Enhancing students' analytical thinking skills holds great promise for bolstering a nation's economic growth, fostering a dynamic learning culture, and nurturing human capital development. It is especially critical in today's rapidly changing landscape, where the demand for skilled, adaptable graduates is high. Achieving and sustaining these…
Descriptors: Metacognition, Competence, Logical Thinking, College Students
Regina Sutarmina; Jamie Costley; Anna Gorbunova; Christopher Lange – Education and Information Technologies, 2025
This study examines relationships among several variables within the context of online learning in higher education including self-regulated effort, maintained situational interest, gender differences, and age-related factors. Analyzing data from a diverse Open Cyber University of Korea student sample, the research highlights a positive…
Descriptors: Online Courses, Learning Motivation, Metacognition, Age Differences
Wei Chen; Lijia Lin; Weiguo Pang – Education and Information Technologies, 2025
A video lesson with generative learning activities has the potential to improve learning by engaging learners. However, existing literature regarding designing and implementing an interactive video lesson is insufficient. In the present study, we aimed to investigate: a) whether the use of the summarizing strategy would benefit learning via video…
Descriptors: Learning Processes, Video Technology, Learning Activities, Writing Skills
Fuhai An; Linjin Xi; Jingyi Yu – Education and Information Technologies, 2024
The current study assessed 495 middle school students in China using self-report questionnaires, to examine the multiple mediating effects of intrinsic motivation and learning engagement (vitality, dedication and absorption) in the relations between technology acceptance and students' self-regulated learning. The results indicated that technology…
Descriptors: Learner Engagement, Middle School Students, Metacognition, Learning Motivation
Xue Yang – Education and Information Technologies, 2024
Mobile devices have increased exponentially in the past decades and the rapid development of digital technology has provided rich soil for the growth of mobile learning (m-learning), which is a more convenient means of learning because of no limitations of space and time. Applying the stimulus-organism-response (S-O-R) framework, this study…
Descriptors: Electronic Learning, Learning Processes, Stimuli, Attention Span
Li, Wei; Liu, Cheng-Ye; Tseng, Judy C. R. – Education and Information Technologies, 2023
Collaborative programming can develop computational thinking and knowledge of computational programming. However, the researchers pointed out that because students often fail to mobilize metacognition to regulate and control their cognitive activities in a cooperation, this results in poor learning effects. Especially low-achieving students need…
Descriptors: Correlation, Metacognition, Thinking Skills, Programming
Dindar, Muhterem; Malmberg, Jonna; Järvelä, Sanna; Haataja, Eetu; Kirschner, Paul A. – Education and Information Technologies, 2020
This study investigated the interplay of temporal changes in self-regulated learning processes (i.e., behavioral, cognitive, motivational and emotional) and their relationship with academic achievement in computer-supported collaborative learning. The study employed electrodermal activity and self-report data to capture the dynamicity of…
Descriptors: Metacognition, Learning Processes, Academic Achievement, Computer Assisted Instruction
de Boer, Jelle; Kommers, Piet A. M.; de Brock, Bert; Tolboom, Jos – Education and Information Technologies, 2016
Video is increasingly used as an instructional tool. It is therefore becoming more important to improve learning of students from video. We investigated whether student learning effects are influenced through an instruction about other viewing behaviours, and whether these learning effects depend on their prior knowledge. In a controlled…
Descriptors: Prior Learning, Video Technology, Cognitive Style, Photography
Anthonysamy, Lilian; Koo, Ah Choo; Hew, Soon Hin – Education and Information Technologies, 2020
This paper aims to examine how self-regulated learning strategies (SRLS) can foster the enhancement of digital literacy in digital learning to increase efficiencies in human capital for sustainable development in lifelong learning. Digital disruption in the education sector is unavoidable. The results of this study will be useful for educators and…
Descriptors: Case Studies, Metacognition, Learning Strategies, Human Capital
Achuthan, Krishnashree; Francis, Saneesh P.; Diwakar, Shyam – Education and Information Technologies, 2017
Learning theories converge on the principles of reflective learning processes and perceive them as fundamental to effective learning. Traditional laboratory education in science and engineering often happens in highly resource-constrained environments that compromise some of the learning objectives. This paper focuses on characterizing three…
Descriptors: Computer Simulation, Retention (Psychology), Transfer of Training, Metacognition