TY - JOUR
T1 - Missing Piece in Understanding Student Learning
T2 - Out-of-School Computer Use
AU - Gu, Xiaoqing
AU - Xu, Hongjin
N1 - Publisher Copyright:
© The Author(s) 2018.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Advancements in learning analytics allow teachers to track student learning progress and promote learning by providing necessary intervention and support. Multiple data sources are involved in learning analytics, and the major ones are systems that students use in school. To fully comprehend the progress of student learning, out-of-school learning behaviors should be considered an important part of the academic lives of students. In this study, out-of-school learning behaviors of students, particularly home computer use, were measured using four online behavior indicators of students, which were tracked and collected. The learning performance data of the students were analyzed. Results suggested that the out-of-school computer use behaviors of students, such as mutual follow-up and the sharing of learning experiences, were positively related to their academic performance level, regardless of the age and gender of the students. This study provides insight into what may be the missing piece in understanding student learning, that is, out-of-school computer use. With such insights, learning analytics may be enhanced to improve the understanding of learning without being restricted to schools.
AB - Advancements in learning analytics allow teachers to track student learning progress and promote learning by providing necessary intervention and support. Multiple data sources are involved in learning analytics, and the major ones are systems that students use in school. To fully comprehend the progress of student learning, out-of-school learning behaviors should be considered an important part of the academic lives of students. In this study, out-of-school learning behaviors of students, particularly home computer use, were measured using four online behavior indicators of students, which were tracked and collected. The learning performance data of the students were analyzed. Results suggested that the out-of-school computer use behaviors of students, such as mutual follow-up and the sharing of learning experiences, were positively related to their academic performance level, regardless of the age and gender of the students. This study provides insight into what may be the missing piece in understanding student learning, that is, out-of-school computer use. With such insights, learning analytics may be enhanced to improve the understanding of learning without being restricted to schools.
KW - academic performance
KW - computer use
KW - learning analytics
KW - learning behavior
KW - learning experience
KW - out-of-school
UR - https://www.scopus.com/pages/publications/85042090468
U2 - 10.1177/0735633118755494
DO - 10.1177/0735633118755494
M3 - 文章
AN - SCOPUS:85042090468
SN - 0735-6331
VL - 57
SP - 320
EP - 342
JO - Journal of Educational Computing Research
JF - Journal of Educational Computing Research
IS - 2
ER -