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Meng-Ting Lo; Fang-Hsin Hsu; Wen-Lan Chen – Educational Psychology, 2024
This study presents a tool to capture students' academic activities and engagement dynamics in university settings. It explores how strategies to manage time and study environments interact with contextual factors (i.e. study time, learning events, and study locations) in predicting students' concentration and cognitive learning strategies in 81…
Descriptors: Self Management, Learner Engagement, Time Management, Study Habits
Sager, Turan; Kalaycioglu, Sükrü Göktug; Zahal, Onur – International Online Journal of Education and Teaching, 2022
In this study, it is aimed to determine the effects of active learning activities on viola students' performance and motivation. One group pretest-posttest experimental design was used in the study. The study group consist of 10 students, 7 of them receiving Viola training within the scope of the Individual Instrument course at Gaziosmanpasa…
Descriptors: Active Learning, Learning Activities, Music Education, Musical Instruments
Peter Pavlis – Online Submission, 2025
This quantitative, quasi-experimental study aimed to propose research-based AI constructivist learning activities by measuring students' self-perceptions of their critical thinking using the Motivational Strategies and Learning Questionnaire (MSLQ). The study utilized the input-experience-output framework to evaluate how these learning pursuits…
Descriptors: Critical Thinking, Artificial Intelligence, Constructivism (Learning), Learning Activities
Han, Feifei; Ellis, Robert A. – Education and Information Technologies, 2023
This study investigated the extent to which self-report and digital-trace measures of students' self-regulated learning in blended course designs align with each other amongst 145 first-year computer science students in a blended "computer systems" course. A self-reported Motivated Strategies for Learning Questionnaire was used to…
Descriptors: Computer Science Education, Independent Study, College Freshmen, Blended Learning