Penn State University - Berks Campus - Reading, Pennsylvania
October 6, 2017
October 6, 2017
October 7, 2017
Mid-Atlantic Section Fall Conference
The latent variable modeling technique in education assessment is illustrated using problem solving examples in first semester physics for engineering and technology students. The regression modeling of data in the Newton second law laboratory class has equivalence to an analysis with the internal force serving as the latent variable. A path diagram would contain the internal force as a latent variable which manifest its influence on the observed datasets, namely, acceleration and force. Similarly, the pre-score and post-score data collected for education assessment can be studied with latent variable modeling to broaden the scope beyond regression which requires an independent variable. The numerical and flexibility advantages of latent variable modeling versus regression modeling in education assessment are presented. Free LISREL student version working details and free confirmatory factor analysis Microsoft Excel software from university faculty are presented. The adaptation of Queensborough Community College Physics faculty education research into Queensborough NSF-REU projects for engineering students is discussed.
Cheung, T., & Dehipawala, S., & Taibu, R., & Shekoyan, V. (2017, October), Latent variable modeling with applications to education assessment and NSF-REU projects for engineering students Paper presented at 2017 Mid-Atlantic Section Fall Conference, Penn State University - Berks Campus - Reading, Pennsylvania. https://peer.asee.org/29384
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