摘要
在线讨论是在线课程的核心组成部分，为学习者提供便利地互动交流的个性化学习体验，促使学习者突破时空间限制，有目的地参与学习，形成众多的生成性资源。在线学习中学习者若无法在第一时间获得教师的反馈与提醒，则会使学习者无法及时明确自身的学业危险。当学习者获得即时的学习预警与反馈时，可以帮助学习者建立信心，督促学习者及时参与互动交流，帮助教师及时了解学习者对课程的参与度。本研究旨在探讨在在线课程中实施学习预警措施，分析对学习者学习行为、学习参与度、学业拖延水平产生的影响，帮助学习者积极参与在线课程。
关键词： 在线课程；在线讨论；学习预警；学习影响
Abstract
Online discussion is the core component of online courses. It provides learners with a personalized learning experience that facilitates interactive communication, encourages learners to break through time and space constraints, participate in learning purposefully, and form numerous generative resources. In online learning, if learners cannot get feedback and reminders from teachers in the first time, they will not be able to identify their own academic risks in time. When learners get immediate learning warning and feedback, it can help learners build confidence, urge learners to participate in interactive communication in a timely manner, and help teachers understand learners’ participation in courses in a timely manner. This research aims to explore the implementation of early warning measures in online courses, analyze the impact on learners' learning behavior, learning participation, and academic procrastination, and help learners actively participate in online courses.
Key words： Online courses; online discussion; learning early warning; learning impact
参考文献 References
[1] Song L , Singleton E S , Hill J R , et al. Improving online learning: Student perceptions of useful and challenging characteristics[J].Internet & Higher Education,2004;7
(1)
: 59-70.
[2] Picciano A G. Beyond student perceptions: Issues of interaction, presence, and performance in an online course[J].Journal of Asynchronous Learning Networks,2002;6
(1)
.
[3] Huey-Min W. Online individualised tutor for improving mathematics learning: a cognitive diagnostic model approach[J].Educational Psychology,2018;
: 1-16.
[4] 姜跃. 数据挖掘在网络教学平台中的应用[J].软件导刊,2011;10
(10)
: 151-152.
[5] 高鹏. 基于数据挖掘的个性化网络教学平台研究[D].西北大学,2005;
.
[6] 赵慧琼,姜强,赵蔚,李勇帆,赵艳. 基于大数据学习分析的在线学习绩效预警因素及干预对策的实证研究[J].电化教育研究,2017;38
(01)
: 62-69.
[7] 宋楚平,李少芹,蔡彬彬. 高职院校学习预警平台的构建及其实证分析[J].现代教育技术,2020;30
(05)
: 94-100.
[8] Sinclair M F , Christenson S L , Evelo D L , et al. Dropout Prevention for Youth with Disabilities: Efficacy of a Sustained School Engagement Procedure[J].Exceptional Children,1998;65
(1)
: 7-21.
[9] Arnold K E, Pistilli M D. Course signals at Purdue: using learning analytics to in crease student success[C].International Conference on Learning Analytics and Knowledge,ACM,2012;
: 267-270.
[10] Trussel J M , Burke-Smalley L. Demography and student success: Early warning tools to drive intervention[J].Journal of Education for Business,2018;
: 1-10.
[11] Mei, Jianyang. Learning Management System Calendar Reminders and Effects on Time Management and Academic Performance[J].International Research and Review,2016;
: 29-45.
[12] Mol V, Christof. Improving web survey efficiency: the impact of an extra reminder and reminder content on web survey response[J].International Journal of Social Research Methodology,2016;
: 1-11.
[13] Iver M A M , Stein M L , Davis M H , et al. An Efficacy Study of a Ninth-Grade Early arning Indicator Intervention[J].2019;12
(3)
: 363-390.
[14] 王林丽. 基于大数据的在线学习预警机制设计[D].江苏师范大学,2017;
.
[15] 刘冬梅. 提升在线讨论参与度的策略研究[D].华中师范大学,2017;
.
[16] Sun C Y , Yu S J , Chao C H. Effects of intelligent feedback on online learners' engagement and cognitive load: the case of research ethics education[J].Educational Psychology,2018;
: 1-18.
[17] Steel, P. he nature of procrastination: A meta-analytic and theoretical review of quintessential self regulatory failure[J].Psychological Bulletin,2007;133
(1)
: 65-94.
[18] Klassen R M, Krawchuk L L , Rajani S. Academic procrastination of undergraduates: Low self-efficacy to self-regulate predicts higher levels of procrastination[J].Contemporary Educational Psychology,2008;33
(4)
: 915-931.
[19] Korstange, Ryan; Craig, Maxwell; Duncan, Matthew D. Understanding and ddressing Student Procrastination in College[J].Learning Assistance Review,2019;24
(1)
: 57-70.