TY - GEN
T1 - Adaptive Practicing Design for Self-paced Online Learning
AU - Yan, Hongxin
AU - Ives, Cindy
AU - Lin, Fuhua
N1 - Publisher Copyright:
Copyright 2021 Asia-Pacific Society for Computers in Education. All rights reserved.
PY - 2021/11/22
Y1 - 2021/11/22
N2 - Self-paced online learning (SPOL) provides great flexibility of learning anytime, anywhere and at any pace, yet it brings some inherent learning barriers because of the distance between students and instructors. This study recognizes two major learning barriers: challenges for instructors to provide proactive support and the need for higher self-directed learning skills in students. Such learning barriers can lead to students' academic struggle and failure. This study suggests three key learning strategies to alleviate learning barriers: a) increasing students' self-awareness of learning, b) identifying struggling students, and c) facilitating students' mastery learning. Focusing on the domain of Data Structures and Algorithms in the computer science discipline, this study proposes systematically designing and embedding adaptive formative assessment in SPOL courses to implement these strategies. Formative assessment is a fundamental process within the learning process. With an adaptive mechanism embedded, it can detect a student's knowledge state more accurately and efficiently. Furthermore, adaptive formative assessment can facilitate students' mastery learning if adaptive formative assessment is designed for practicing. During this mastery learning process with adaptive practicing, it is possible to identify one kind of struggling student - wheel-spinning students, who persistently work on problems or exercises without progressing towards mastery. Different from the research on adaptive assessment that mainly focuses on Intelligent Tutoring Systems, this study investigates an effective adaptive practicing mechanism in the context of self-paced online learning. A prototype of an adaptive practicing system is being created to test the effectiveness of this mechanism in implementing those suggested learning strategies.
AB - Self-paced online learning (SPOL) provides great flexibility of learning anytime, anywhere and at any pace, yet it brings some inherent learning barriers because of the distance between students and instructors. This study recognizes two major learning barriers: challenges for instructors to provide proactive support and the need for higher self-directed learning skills in students. Such learning barriers can lead to students' academic struggle and failure. This study suggests three key learning strategies to alleviate learning barriers: a) increasing students' self-awareness of learning, b) identifying struggling students, and c) facilitating students' mastery learning. Focusing on the domain of Data Structures and Algorithms in the computer science discipline, this study proposes systematically designing and embedding adaptive formative assessment in SPOL courses to implement these strategies. Formative assessment is a fundamental process within the learning process. With an adaptive mechanism embedded, it can detect a student's knowledge state more accurately and efficiently. Furthermore, adaptive formative assessment can facilitate students' mastery learning if adaptive formative assessment is designed for practicing. During this mastery learning process with adaptive practicing, it is possible to identify one kind of struggling student - wheel-spinning students, who persistently work on problems or exercises without progressing towards mastery. Different from the research on adaptive assessment that mainly focuses on Intelligent Tutoring Systems, this study investigates an effective adaptive practicing mechanism in the context of self-paced online learning. A prototype of an adaptive practicing system is being created to test the effectiveness of this mechanism in implementing those suggested learning strategies.
KW - Adaptive formative assessment
KW - Adaptive practicing
KW - Mastery learning
KW - Reinforcement learning
KW - Selfpaced online learning
KW - Wheel-spinning
UR - http://www.scopus.com/inward/record.url?scp=85122916781&partnerID=8YFLogxK
M3 - Published Conference contribution
AN - SCOPUS:85122916781
T3 - 29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings
SP - 765
EP - 768
BT - 29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings
A2 - Rodrigo, Maria Mercedes T.
A2 - Iyer, Sridhar
A2 - Mitrovic, Antonija
A2 - Cheng, Hercy N. H.
A2 - Kohen-Vacs, Dan
A2 - Matuk, Camillia
A2 - Palalas, Agnieszka
A2 - Rajenran, Ramkumar
A2 - Seta, Kazuhisa
A2 - Wang, Jingyun
T2 - 29th International Conference on Computers in Education Conference, ICCE 2021
Y2 - 22 November 2021 through 26 November 2021
ER -