White Papers

Improving the Prospects for Educational Data Mining

Overview Data mining is an important paradigm for educational assessment. The usual assumption is that mining is performed after educational activity with that activity having been designed without regard for the mining process. This paper discusses how the prospects for successful mining can be improved by imposing constraints or biases on the activities and instruments that generate the data. These biases involve one or more of the following: encouraging, requiring or training students to communicate effectively and often during the course of learning activities, building more instrumentation into the learning environment to enable capturing more kinds of data, including evidence of student attention.

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Publisher
University of Washington
File Format
PDF
Date Published
Sep 19, 2008
Format
White Papers
Topics
Online - Distance Education, Learning Management Systems, Data Mining - Analysis

University of Washington White Papers

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