Literaturnachweis - Detailanzeige
| Autor/inn/en | Vervliet, Bram; Iberico, Carlos; Vervoort, Ellen; Baeyens, Frank |
|---|---|
| Titel | Generalization Gradients in Human Predictive Learning: Effects of Discrimination Training and within-Subjects Testing |
| Quelle | In: Learning and Motivation, 42 (2011) 3, S.210-220 (11 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0023-9690 |
| DOI | 10.1016/j.lmot.2011.03.004 |
| Schlagwörter | Animals; Research Design; Testing; Conditioning; Discrimination Learning; Generalization; Training; Experiments; Behavior Modification |
| Abstract | Generalization gradients have been investigated widely in animal conditioning experiments, but much less so in human predictive learning tasks. Here, we apply the experimental design of a recent study on conditioned fear generalization in humans (Lissek et al., 2008) to a predictive learning task, and examine the effects of a number of relevant procedural parameters drawn from the generalization literature in animal conditioning. Experiment 1 shows that prior discrimination learning and steady-state testing procedures sharpen the gradient; Experiment 2 shows that within-subjects testing of the range of generalization stimuli also sharpens the gradient. In addition, Experiment 2 shows that, in case of very flat initial generalization, an orderly gradient can reveal itself through differential rates of extinction learning. Finally, Experiment 2 also evidenced an orderly gradient of generalization-of-extinction. These results suggest that discrimination processes have an important effect on the generalization of predictive learning in humans, and highlight behavioral analogies between animal conditioning and human predictive learning. (Contains 5 figures.) (As Provided). |
| Anmerkungen | Elsevier. 6277 Sea Harbor Drive, Orlando, FL 32887-4800. Tel: 877-839-7126; Tel: 407-345-4020; Fax: 407-363-1354; e-mail: usjcs@elsevier.com; Web site: http://www.elsevier.com |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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