TY - GEN
T1 - Visual Analysis of the Time Management of Learning Multiple Courses in Online Learning Environment
AU - He, Huan
AU - Dong, Bo
AU - Zheng, Qinghua
AU - Di, Dehai
AU - Lin, Yating
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Self-paced online learning not only provides the opportunities of learning anytime but also chanllenges students' time management, especially in the context of learning multiple courses at same time. The inappropriate scheduling of multiple courses may affect student engagement and learning performance, thus how to arrange the study time of multiple courses is a concern of both instructors and students. Existing studies related to student engagement and time management in online learning mainly focus on providing self-regulated learning strategies and evaluating learning performance. However, these methods have limited abilities to gain intuitive understanding of the time management of multi-course learning. To address this issue, we present LearnerVis to help users analyze how students schedule their multi-course learning. LearnerVis visualize the temporal features of learning process, and it enables users to customize student groups to compare the differences in student engagement and time management. A case study is conducted to demonstrate the usefulness of the system with real-word dataset.
AB - Self-paced online learning not only provides the opportunities of learning anytime but also chanllenges students' time management, especially in the context of learning multiple courses at same time. The inappropriate scheduling of multiple courses may affect student engagement and learning performance, thus how to arrange the study time of multiple courses is a concern of both instructors and students. Existing studies related to student engagement and time management in online learning mainly focus on providing self-regulated learning strategies and evaluating learning performance. However, these methods have limited abilities to gain intuitive understanding of the time management of multi-course learning. To address this issue, we present LearnerVis to help users analyze how students schedule their multi-course learning. LearnerVis visualize the temporal features of learning process, and it enables users to customize student groups to compare the differences in student engagement and time management. A case study is conducted to demonstrate the usefulness of the system with real-word dataset.
KW - E-learning
KW - Human-centered computing
KW - Visual analytics; Applied computing
KW - Visualization
UR - https://www.scopus.com/pages/publications/85078052899
U2 - 10.1109/VISUAL.2019.8933778
DO - 10.1109/VISUAL.2019.8933778
M3 - 会议稿件
AN - SCOPUS:85078052899
T3 - 2019 IEEE Visualization Conference, VIS 2019
SP - 56
EP - 60
BT - 2019 IEEE Visualization Conference, VIS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Visualization Conference, VIS 2019
Y2 - 20 October 2019 through 25 October 2019
ER -