Issues and topics derived from instructional design job announcements: A structural topic modeling analysis

• In Event: Academic Publishing and Trends in the Field

Short Description

The purpose of this research was to examine instructional design job announcements using a text mining approach known as structural topic modeling. We collected 1,030 instructional design job announcements from three popular job databases and analyzed these data using a variety of techniques. Results from the topic modeling showed five primary topics and a range of relevant keywords associated with each topic. The presentation will illustrate our method, results, and interpretation of these data.

Authors

• Presenter: Xiaoman Wang, University of Florida

• Contributor: Dongho Kim, University of Florida

• Presenter: Yan Chen, University of New Mexico

• Presenter: Albert Dieter Ritzhaupt, University of Florida

• Presenter: Florence Martin, University of North Carolina Charlotte