Author(s):
Online learning resources are able to gather detailed data as students engage with the materials. This is distinct from data gathered from pre and post tests, or similar assessments, which instead provide snapshots of what the student knows before and after engaging with learning opportunities. By revealing information on the process of learning, such data may allow us to better understand how the online resources promote, or fail to promote, learning for all students. This workshop will enable sharing of experiences and best practices for gathering, curating and analyzing the rich educational data sets collected in online environments. The workshop will begin with a brief discussion of approaches the presenters have found to be useful. For gathering and curation, we will discuss ways to ethically gather data, flexibly label the data against a knowledge model, and anonymize data in a manner that supports secondary analyses. For analysis, we will consider approaches, such as learning curves, that provide information on students’ progress along specific learning objectives. We will also share a set of tools designed to aid such efforts. The workshop will then use these approaches as a starting point for discussions among attendees on the needs of their projects, the approaches that they have found most useful, and the challenges that remain to be addressed.
Coauthors
Thomas Holme (taholme@iastate.edu)
