TY - GEN
T1 - Exploring self-regulated learning behaviors in a negotiated online reading assessment
AU - Cheng, Hercy N.H.
AU - Jia, Liansheng
AU - Zhang, Xiaotong
AU - Liao, Calvin C.Y.
AU - Sun, Jianwen
N1 - Funding Information:
This study was financially supported by Self-determined Research Funds of Central China Normal University from the Colleges Basic Research and Operation of Ministry of Education of China (CCNU16GD003).
Publisher Copyright:
© 2018 Asia-Pacific Society for Computers in Education.
PY - 2018/11/24
Y1 - 2018/11/24
N2 - This study designed a negotiated online reading assessment in order to facilitate students' self-monitoring and self-reflection on reading abilities. After taking a reading assessment, students are allowed to negotiate with the system, so that they may further understand their abilities and likely take actions to improve the abilities. This study also conducted a preliminary evaluation to explore the online behaviors of students with different self-regulated learning abilities. For this purpose, a lag sequential analysis approach was applied to identify significant transitions between actions in the negotiation process. The preliminary results showed that low self-regulated learners tended to directly explain their abilities, while high self-regulated learners tended to query the system before explanation. Besides, high self-regulated learners also tended to take the assessment again.
AB - This study designed a negotiated online reading assessment in order to facilitate students' self-monitoring and self-reflection on reading abilities. After taking a reading assessment, students are allowed to negotiate with the system, so that they may further understand their abilities and likely take actions to improve the abilities. This study also conducted a preliminary evaluation to explore the online behaviors of students with different self-regulated learning abilities. For this purpose, a lag sequential analysis approach was applied to identify significant transitions between actions in the negotiation process. The preliminary results showed that low self-regulated learners tended to directly explain their abilities, while high self-regulated learners tended to query the system before explanation. Besides, high self-regulated learners also tended to take the assessment again.
KW - Negotiated learner models
KW - Self-regulated learning
KW - Sequential analysis
UR - http://www.scopus.com/inward/record.url?scp=85060108608&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060108608&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85060108608
T3 - ICCE 2018 - 26th International Conference on Computers in Education, Work-in-Progress Poster Proceedings
SP - 13
EP - 15
BT - ICCE 2018 - 26th International Conference on Computers in Education, Work-in-Progress Poster Proceedings
A2 - Rodrigo, Ma. Mercedes T.
A2 - Amalathas, Sagaya
A2 - Coronel, Andrei D.
A2 - Yang, Jie Chi
A2 - Song, Yanjie
A2 - Ding, Jihong
A2 - Chang, Maiga
A2 - Wong, Lung-Hsiang
PB - Asia-Pacific Society for Computers in Education
T2 - 26th International Conference on Computers in Education, ICCE 2018
Y2 - 26 November 2018 through 30 November 2018
ER -