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Research in Higher Education - Across disciplines, male faculty spend more time on research than female faculty. Yet, women tend to teach and mentor students more hours than men (Misra et al. in... 相似文献
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Several researchers have suggested that the computer holds much promise as a tool for science teachers for use in their classrooms (Bork, 1979, Lunetta & Hofstein, 1981). It also has been said that there needs to be more research in determining the effectiveness of computer software (Tinker, 1983). This study compared the effectiveness of microcomputer simulated experiences with that of parallel instruction involving hands-on laboratory experiences for teaching the concept of volume displacement to junior high school students. This study also assessed the differential effect on students' understanding of the volume displacement concept using sex of the students as another independent variable. In addition, it compared the degree of retention, after 45 days, of both treatment groups. It was found that computer simulated experiences were as effective as hands-on laboratory experiences, and that males, having had hands-on laboratory experiences, performed better on the posttest than females having had the hands-on laboratory experiences. There were no significant differences in performance when comparing males with females using the computer simulation in the learning of the displacement concept. This study also showed that there were no significant differences in the retention levels when the retention scores of the computer simulation groups were compared to those that had the hands-on laboratory experiences. However, an ANOVA of the retention test scores revealed that males in both treatment conditions retained knowledge of volume displacement better than females. 相似文献
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Eugene Sadler‐Smith 《教育心理学》1997,17(1-2):51-63
In both education and training an important aspect of the design, development and delivery of learning is the role of individual differences between learners in terms of their ‘learning styles’. One may identify four broad categories of what have been termed ‘learning style’: (i) ‘cognitive personality elements’ (e.g. Witkin et al. 1977; Riding, 1991); (ii) ‘information‐processing style’ (e.g. Kolb, 1984; Honey & Mumford, 1992); (iii) ‘approaches to studying’ (e.g. Entwistle & Tait, 1994); (iv) ‘instructional preferences’ (e.g. Riechmann & Grasha, 1974). A study of 245 university undergraduates in business studies aimed to: (i) describe the range of individual differences present within the sample; (ii) investigate the relationship between learners’ cognitive styles, learning styles, approaches to studying and learning preferences; (iii) consider the implications of ‘learning style’ for teaching and learning in higher education. The present study suggested some overlap between the dimensions measured by the Learning Styles Questionnaire (Honey & Mumford, 1986; 1992) and the Revised Approaches to Studying Inventory (Entwistle & Tait, 1994). No statistically significant correlations were found between cognitive style, as measured by the Cognitive Styles Analysis (Riding, 1991) and any of the other ‘style’ constructs used. Further research is required to investigate these relationships, as is a large‐scale factor analytical study of the Honey and Mumford and Kolb instruments. The notions of whole brain functioning, integra‐tive approaches to studying and degree of learning activity are discussed. 相似文献