A data science pipeline for educational data : a case study using learning catalytics in the active learning classroom.

data science;data science pipeline;visualization;exploratory factor analysis;educational data mining

Asuman Cagla Acun Sener

University:University of Louisville

Department:Computer Engineering and Computer Science

关键词: data science;    data science pipeline;    visualization;    exploratory factor analysis;    educational data mining;   

Others  :  https://ir.library.louisville.edu/cgi/viewcontent.cgi?article=3942&context=etd

美国|英语

来源: The Universite of Louisville's Institutional Repository

【 摘 要 】

This thesis presents an applied data science methodology on a set of University of Louisville, Speed School of Engineering student data. We used data mining and classic statistical techniques to help educational researchers quickly see the data trends and peculiarities. Our data includes scores and information about two Engineering Fundamental Class. The format of these classes is called an inverted classroom model or flipped class. The purpose of this study is to analyze the data in order to uncover potentially hidden information, tell interesting stories about the data, examine student learning behavior and learning performance in an active learning environment, including collaborative learning in a flipped classroom model.