Artificial neural network-based performance assessments.
Part of a special issue on computer-based performance assessment of problem solving. The writers examine the ability of artificial neutral network technologies to generate performance models of complex problem-solving tasks without detailed a priori knowledge of the nature of the task. They then a...
| Publicado en: | Computers in Human Behavior Vol. 15; no. 3-4; pp. 295 - 314 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Elsevier Science
May/July 1999
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=507631068&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 507631068 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: May/July 1999 vid: 15 iid: 3-4 pid: 2410 pub: Elsevier Science artinfo: ui: 507631068 10.1016/S0747-5632(99)00025-4 ppf: 295 ppct: 19 formats: tig: atl: Artificial neural network-based performance assessments. aug: au: Stevens, R. Ikeda, J. Casillas, A. su: Problem solving Artificial neural networks sug: subj: Problem solving Artificial neural networks ab: Part of a special issue on computer-based performance assessment of problem solving. The writers examine the ability of artificial neutral network technologies to generate performance models of complex problem-solving tasks without detailed a priori knowledge of the nature of the task. They then apply this analysis to two different content domains—clinical patient management and high school genetics—in order to test the generalizability of the approach. Their analysis indicates that in both domains, the artificial neural networks, which used only the sequence of actions taken while performing the task, generated multiple classification groups defining different levels of competence. They point out that the good concordance of these classifications with independently derived expert ratings further establishes the validity of these neutral network performance groupings. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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