Back to Search
Start Over
Cognitive abilities that predict success in a computer-based training program
- Source :
- The Gerontologist. April, 2008, Vol. 48 Issue 2, p170, 11 p.
- Publication Year :
- 2008
-
Abstract
- Purpose: The purposes of this study were (a) to identify cognitive abilities and other factors related to successful completion of training for computer-based tasks that simulated real jobs and (b) to create a brief assessment battery useful in assessing older adults for these kinds of jobs. Design and Methods: Participants from three age groups (young, middle-aged, and older) completed a battery of cognitive measures. They then trained on one of three computer-based tasks that simulated actual jobs and were asked to perform the tasks for 3 days. We recorded whether they completed training and whether and how well they did the tasks. In a series of logistic regressions, we evaluated the ability of a subset of cognitive measures drawn from a larger battery to predict participants' ability to successfully complete training and go on to task performance. Results: Results confirmed theory-based expectations that measures of domain knowledge, crystallized intelligence, memory, and psychomotor speed would predict success in computer-based activities. A brief battery was able to predict older adults' successful completion of training for one task but was less useful for another. Implications: A brief battery of cognitive measures may be useful in evaluating individuals for job selection. Different measures are related to job-related criteria depending on task and group evaluated, although it was not possible to identify a reduced battery for one task. The specific cognitive abilities related to participants' success have implications for task and interface design for the elderly population. Key Words: Neuropsychological tests, Computers, Cognition, Older worker
Details
- Language :
- English
- ISSN :
- 00169013
- Volume :
- 48
- Issue :
- 2
- Database :
- Gale General OneFile
- Journal :
- The Gerontologist
- Publication Type :
- Academic Journal
- Accession number :
- edsgcl.179533484