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Edward Osang Ayuk – ProQuest LLC, 2021
The purpose of this study was to identify differences in metacognitive and self-regulated learning strategies used by students in a self-paced, computer-based developmental mathematics program (DMP) and how these strategies accounted for differences in persistence and performance observed among the students. Five research questions guided the…
Descriptors: Metacognition, Self Management, Computer Assisted Instruction, Developmental Studies Programs
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Chih-Chang Yu; Leon Yufeng Wu – Educational Technology & Society, 2024
This study presents a new blended learning model that combines a computer-assisted learning system called Cognitive Apprenticeship Programming Learning System (CAPLS) with instructor co-teaching in an introductory programming course. CAPLS, as its unique aspect, functions as a master in cognitive apprenticeship, guiding learners throughout their…
Descriptors: Programming, Computer Science Education, College Entrance Examinations, Mathematics Tests
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Cuervo-Cely, Karen D.; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2022
Aim/Purpose: The purpose of this research is to examine the effect of computer-assisted gamification on the learning motivation of computer programming students. Background: The teaching-learning of computer programming involves challenges that imply using learning environments in which the student is actively involved. Gamification is an…
Descriptors: Game Based Learning, Student Motivation, Computer Science Education, Programming
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George Hanshaw; Joanna Vance; Craig Brewer – Open Praxis, 2024
This study examines the impact of AI course assistants on student learning experiences in online undergraduate courses at Los Angeles Pacific University. A controlled experiment involving 92 students across treatment and control groups was conducted to evaluate the effectiveness of AI assistants developed by Nectir. The treatment group had access…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Student Experience, Undergraduate Students
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Sullins, Jeremiah; Acuff, Samuel; Neely, Daniel; Hu, Xiangen – Journal of Educational Multimedia and Hypermedia, 2018
Is it possible to teach a learner to become a better question asker in as little as 25 minutes? Given that many teachers and school districts do not have the resources to provide individualized question training to students, the current study sought to explore the benefits of using animated pedagogical agents to teach question-asking skills in a…
Descriptors: Prior Learning, Questioning Techniques, Training, Intelligent Tutoring Systems
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Lao, Andrew Chan-Chio; Cheng, Hercy N. H.; Huang, Mark C. L.; Ku, Oskar; Chan, Tak-Wai – Journal of Educational Computing Research, 2017
One-to-one technology, which allows every student to receive equal access to learning tasks through a personal computing device, has shown increasing potential for self-directed learning in elementary schools. With computer-supported self-directed learning (CS-SDL), students may set their own learning goals through the suggestions of the system…
Descriptors: Computer Assisted Instruction, Independent Study, Learning Strategies, Student Motivation
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Panadero, Ernesto; Klug, Julia; Järvelä, Sanna – Scandinavian Journal of Educational Research, 2016
Measurement is a central issue for the self-regulated learning (SRL) field as SRL is a phenomenon difficult to measure in a reliable and valid way. Here, 3 waves in the history of SRL measurement are identified and profiled. Our focus lies on the third and newest one, which combines measurement and intervention within the same tools. The basis for…
Descriptors: Measurement Techniques, Metacognition, Intervention, Guidelines
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Pardo, Abelardo; Han, Feifei; Ellis, Robert A. – IEEE Transactions on Learning Technologies, 2017
Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…
Descriptors: Student Centered Learning, Learning Theories, College Students, Academic Achievement