Treffer: Discovering Educational Data Mining: An Introduction

Title:
Discovering Educational Data Mining: An Introduction
Language:
English
Authors:
Zachary K. Collier, Joshua Sukumar, Roghayeh Barmaki
Source:
Practical Assessment, Research & Evaluation. 2024 29.
Availability:
University of Massachusetts Amherst Libraries. 154 Hicks Way, Amherst, MA 01003. e-mail: pare@umass.edu; Web site: https://openpublishing.library.umass.edu/pare/
Peer Reviewed:
Y
Page Count:
13
Publication Date:
2024
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Evaluative
Descriptors:
Educational Indicators, School Statistics, Data Analysis, Information Retrieval, Pattern Recognition, Content Analysis, Information Technology, Research Methodology, Measurement, Statistics, Artificial Intelligence, Context Effect, Educational Environment, Intellectual Disciplines, Vocabulary, Comparative Analysis
ISSN:
1531-7714
Entry Date:
2024
Accession Number:
EJ1443517
Database:
ERIC

Weitere Informationen

This article introduces researchers in the science concerned with developing and studying research methods, measurement, and evaluation (RMME) to the educational data mining (EDM) community. It assumes that the audience is familiar with traditional priorities of statistical analyses, such as accurately estimating model parameters and inferences from those models. Instead, this article focuses on data mining's adoption of statistics and machine learning to produce cutting-edge methods in educational contexts. It answers three questions: (1) What are the primary interests of EDM and RMME researchers?; (2) What is their discipline-specific vocabulary?; and (3) What are the similarities and differences in how the EDM and RMME communities analyze similar types of data?

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