摘 要:文章首先分析了学习预警模型现状;其次通过专家访谈和文献调研,分析影响学习预警的因素,利用德尔菲专家咨询法和层次分析法构建基于智慧校园学习数据的学习预警模型;最后利用智慧树平台上“Java 程序设计”课程的学生学习行为数据对所构建的预警模型进行验证。结果表明,该学习预警模型能够对学生的学习起到预警和干预作用,能够提高学生的课程学习质量。
关键词:学习预警模型;智慧校园;学习数据
DOI:10.19850/j.cnki.2096-4706.2021.23.050
基金项目:河南省教育科学规划一般课题: 智慧校园背景下民办本科学生课程学习精准预警 实证研究(2021YB0360)
中图分类号:TP391;G434 文献标识码:A 文章编号:2096-4706(2021)23-0195-04
Construction and Practice of Students’ Course Learning Early Warning Model under the Background of Smart Campus
YU Haiyan
(School of Information Engineering, Zhengzhou University of Science and Technology, Zhengzhou 450064, China)
Abstract: Firstly, this paper analyzes the current situation of learning early warning model; then analyzes the factors affecting learning early warning through expert interview and literature research, and constructs a learning early warning model based on smart campus learning data by using Delphi expert consultation method and analytic hierarchy process; finally, the constructed early warning model is verified by using the students’ learning behavior data of“Java programming” course in the smart tree platform. The results show that the learning early warning model can play an early warning and intervention role in students’ learning and improve the quality of students’ course learning.
Keywords: learning early warning model; smart campus; learning data
参考文献:
[1] MCKAY T,Miller K,TRITZ J. What to Do with Actionable Intelligence:E 2Coach as an Intervention Engine [C]//Proceedings of the 2nd International Conference on Learning Analytics and Knowledge. NewYork:ACM,2012:88-91.
[2] MAZZA R,DIMITROVA V. CourseVis:A Graphical Student Monitoring Tool for S upporting Instructors in Web -based Distance Courses [J].International Journal of Human-Computer Studies,2007,65(2):125-139.
[3] ARNOLD K E,PISTILLI M D. Course Signals at Purdue: using Learning Analytics to Increase Student Success [C]//Proceedings of the 2nd International Conference on Learning Analytics and Knowledge. New York:ACM,2012:267-270.
[4] ESSA A,AYAD H.Improving Student Success Using Predictive Models and Data Visualisations [J].Research in Learning Technology,2012,20:58-70.
[5] 王芳,梁鹰.基于 MOOC 的大数据学习预警模型在混合教学中的应用 [J].中华医学图书情报杂志,2019,28(7):63 - 71.
[6] 胡建红,张晓丽,袁培鑫,等 . 基于雨课堂智慧教学模式的学习预警分析 [J]. 中国成人教育,2019(21):64-66.
[7] 牟智佳,李雨婷,严大虎 . 混合学习环境下基于学习行为数据的学习预警系统设计与实现 [J]. 远程教育杂志,2018,36(3): 55-63.
[8] 赵慧琼,姜强,赵蔚,等.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(1):62 - 69.
[9] 宋楚平,李少芹,蔡彬彬 . 一种R BF 神经网络改进算法在高校学习预警中的应用 [J]. 计算机应用与软件,2020,37(8): 39-44.
[10] 宗晓萍,陶泽泽 . 改进的K-近邻算法及其在学习预警中的应用 [J]. 河北大学学报(自然科学版),2020,40(2): 193-199.
作者简介:于海燕(1983—),女,汉族,河南范县人,副教授,硕士研究生,研究方向:计算机教育教学