Leadership and educational policy studies

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Date
1995-08
Authors
Wan Ismail, Wan Mohamad Fauzy Bin
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Abstract
A prominent theme in the professional literature today concerns how computers can be used more effectively for personalized instruction. Issues of use have focused not only on the content of the software but also on its physical appearance, i.e. the user interface. The appearance of instructional software may influence the interaction process between the computer and the user, as may the user's personal learning style preference. Most software today uses a graphical interface, in which a user selects different icons to execute and accomplish specific tasks. However, the research literature offers no guidelines concerning whether these icons should be labeled or not. Both labeled and nonlabeled icons are commonly found in instructional software. The purpose ofthis study was to investigate the effects of labeled and non-labeled icons and also personal learning style preference on user performance white interacting with instructional software. The subjects were 48 college students from a general education class. ANOVA results indicated that labeled icons seemed to aid the user to more effectively utilize the software. Subjects who were exposed to labeled icons took significantly less time, fewer steps, and made fewer errors while interacting with the software to complete an assigned task. Personal learning style preference seemed also to influence subject performance. Subjects who had a visual learning style preference took significantly fewer steps and made fewer t errors, but did not require significantly less time to complete the task when compared to subjects who did not have a visual learning style preference. Based on the findings, it can be concluded that adding a label to icons used as a human computer interface in instructional software will aid the user. The effects for learning style preference on performance were not totally consistent. Recommendations for further research include a more holistic approach in evaluating the performance of the subjects, consideration of computer experience, gender, age, user satisfaction, and preferences. Other suggestions include multiple task assignments and lengthier treatment times.
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Educational policy studies
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