Experiential Learning in Data Science: Developing an Interdisciplinary, Client-Sponsored Capstone Program

被引:23
作者
Allen, Genevera I. [1 ,2 ,3 ,4 ,5 ]
机构
[1] Rice Univ, Ctr Transforming Data Knowledge, Houston, TX 77251 USA
[2] Rice Univ, Dept Elect & Comp Engn, Houston, TX 77251 USA
[3] Rice Univ, Dept Stat, Houston, TX 77251 USA
[4] Rice Univ, Dept Comp Sci, Houston, TX 77251 USA
[5] Baylor Coll Med, Jan & Dan Duncan Neurol Res Inst, Houston, TX 77030 USA
来源
PROCEEDINGS OF THE 52ND ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2021 | 2021年
关键词
data science; machine learning; capstone; experiential learning; client-sponsored projects; team-based projects; STUDENTS;
D O I
10.1145/3408877.3432536
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Interest in data science education and degree programs has rapidly expanded over the past several years. An integral part of many degree programs is a capstone experience, where students complete a major research or real-world project at the culmination of their educational program. In engineering and computer science, many have shown that client-sponsored projects lead to better student engagement and improved training. In this paper, we discuss experiences with developing an interdisciplinary, client-sponsored capstone program in data science and machine learning. We show how we set up the capstone program, including how the program is structured, how projects are set up, how the course is managed, how students are assessed, and outline the newly developed capstone curriculum. Finally, we report results from a cohort of students participating in this capstone program and discuss lessons learned as well as best practices when developing data science capstone programs.
引用
收藏
页码:516 / 522
页数:7
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