Curriculum Pacing: A New Approach to Discover Instructional Practices in Classrooms

被引：0
|
作者：
Patel, Nirmal [1 ]
Sharma, Aditya [1 ]
Sellman, Collin [2 ]
Lomas, Derek [3 ]
机构：
[1] Playpower Labs, Gandhinagar, India
[2] Arizona State Univ, Tempe, AZ USA
[3] Delft Univ Technol, Delft, Netherlands
来源：
INTELLIGENT TUTORING SYSTEMS, ITS 2018 | 2018年 / 10858卷
关键词：
Curriculum analytics; Curriculum pacing; Sequence mining; Clustering; Visualization;
D O I：
10.1007/978-3-319-91464-0_38
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper examines the use of "pacing plots" to represent variations in student learning sequences within a digital curriculum. Pacing plots are an intuitive and flexible data visualizations that have a potential for revealing the diversity of blended classroom instructional models. By using curriculum pacing plots, we identified several common implementation patterns in real-world classrooms. After analyzing two years' worth of data from over 150,000 students in a digital math curriculum, we found that a PCA and K-Means clustering approach was able to discover pedagogically relevant instructional practices.
引用
收藏
页码：345 / 351
页数：7
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