Abstract
Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item selection based on Kullback-Leibner information is an alternative
| Original language | English |
|---|---|
| Title of host publication | Psychometrics in practice at RCEC |
| Editors | T.J.H.M. Eggen, B.P. Veldkamp |
| Place of Publication | Enschede |
| Publisher | RCEC |
| Pages | 14-25 |
| Number of pages | 180 |
| ISBN (Print) | 9789036533744 |
| DOIs | |
| Publication status | Published - 2012 |