Using Classical Item Analysis to Validate Learning Paths in an Online Course
Save to My Collections
Tidwell Scheuring, S., Niemi, D. & Rudman, L. (2011). Using Classical Item Analysis to Validate Learning Paths in an Online Course. In Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2011 (pp. 452-457). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/38750.
This study compares the instructional sequences defined by experts for an online course with the learning paths indicated by measurement data. The goal was to determine which of the expert-identified topic sequences were supported by total population statistics and which were not. In the cases where the expert sequence was not supported, relationships were modified through expert judgment to incrementally discover a sequence (precedence structure) that was supported both by experts and by the measurement data for the total population. Additional side benefits to item alignment quality and grouping of skills within curriculum will be discussed.
- Designing with and for Technological Pedagogical Content Knowledge: The Evolution of GeoThentic
- Using e-Learning Technologies in Developing Remeditainment Products for the Treatment of Children with Central Auditory Processing Disorder (CAPD)
- Post degree online course in Haematopathology and e-Learning: description of an innovative curriculum in e-Learning
- Podcasts in Higher Education: What Students Want, What They Really Need, and How This Might be Supported
- Using RSS in Collaborative Course Development
- Teaching for Success: Technology and Learning Styles in Preservice Teacher Education
- Reducing E-Learning Development Costs Using a Streamlined XML-based Approach
- Using Authentic Situations and Avatars to Build Knowledge in an E-Learning Environment
- Inspiring Learning and Teaching: Using e-tools to Facilitate Change
- Scenario making support in PBL
Comments & Discussion
Comment on the paper above. You must be registered to participate. Registration is free.