TY - GEN
T1 - Exploring Students’ Problem-Solving Challenges in Self-regulated Learning Through Training Video Prompts
AU - Cohen, Guy
AU - Cohen, Anat
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - In the rapidly changing digital era, schools face the challenge of developing self-regulated learning (SRL) skills, particularly problem-solving, which is crucial for lifelong learning. Literature often discusses learners’ difficulties in problem-solving and measuring SRL strategies. This study explores students’ challenges during the problem-solving process. A video-assisted SRL training program was developed, including a digital toolkit with materials like checklists, interactive videos, and problem-solving tasks. Analyzing 1,417 responses from 13–16-year-old students, the study revealed difficulties in time planning, problem identification, exploration, providing solutions, and solution evaluation. Interestingly, there were significant differences between students’ pre-questionnaire reports and their video prompt responses. These findings can inform the development of feedback-based technologies like chatbots and virtual assistants to enhance efficient problem-solving for learners.
AB - In the rapidly changing digital era, schools face the challenge of developing self-regulated learning (SRL) skills, particularly problem-solving, which is crucial for lifelong learning. Literature often discusses learners’ difficulties in problem-solving and measuring SRL strategies. This study explores students’ challenges during the problem-solving process. A video-assisted SRL training program was developed, including a digital toolkit with materials like checklists, interactive videos, and problem-solving tasks. Analyzing 1,417 responses from 13–16-year-old students, the study revealed difficulties in time planning, problem identification, exploration, providing solutions, and solution evaluation. Interestingly, there were significant differences between students’ pre-questionnaire reports and their video prompt responses. These findings can inform the development of feedback-based technologies like chatbots and virtual assistants to enhance efficient problem-solving for learners.
KW - K-12 Education
KW - Problem-Based Learning
KW - Self-Regulated Learning
KW - Video-Based Learning
KW - Video-Based Prompt
UR - http://www.scopus.com/inward/record.url?scp=85172023997&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-42682-7_38
DO - 10.1007/978-3-031-42682-7_38
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AN - SCOPUS:85172023997
SN - 9783031426810
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 536
EP - 541
BT - Responsive and Sustainable Educational Futures - 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings
A2 - Viberg, Olga
A2 - Jivet, Ioana
A2 - Muñoz-Merino, Pedro J.
A2 - Perifanou, Maria
A2 - Papathoma, Tina
PB - Springer Science and Business Media Deutschland GmbH
T2 - Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023
Y2 - 4 September 2023 through 8 September 2023
ER -
