The Gain-Loss Model: Bias of the Parameter Estimates |
| |
| Affiliation: | 1. Department of Physics, College of William and Mary,Box 8795, Williamsburg, VA, USA;2. Department of Environmental, Earth, and Atmospheric Sciences, University of Massachusetts Lowell, Lowell MA, USA;3. Laboratoire de Météorologie Dynamique, IPSL, CNRS UMR 8539, Sorbonne Universités, UPMC Univ. Paris 06, Paris 75252, France;4. Science Directorate, NASA Langley Research Center, Hampton, VA, USA;5. Pacific Northwest National Laboratory, Richland, WA, USA |
| |
| Abstract: | The gain-loss model is a formal model developed within Knowledge Space Theory. It consists of five parameters (initial probabilities of the skills, effects of learning objects on gaining and losing skills, careless error and lucky guess probabilities of the items) that are estimated by maximum likelihood. Three simulation studies show that high values of both initial and final probabilities of an item lead to a systematic overestimation of the lucky guess parameter of that item. A re-parameterization of the model is proposed, in which a joint probability of lucky guess is introduced. |
| |
| Keywords: | knowledge space theory gain-loss model maximum likelihood estimation bias |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
