Accessibility of Analysis of Algorithms: from programming to problem solving
Journal of Computing Sciences in Colleges
Establishing a Probabilistic Model for Cognitive Learning Style
Proceedings of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation
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Two types of instructional (Text and Web) that had been used in a previous study [1] were adapted to accommodate Cognitive Style preferences for Witkin's Field-dependent [2] and Riding's Imager [3]. Ninety six Information Systems students were randomly allocated to each of these environments and their Cognitive Styles were assessed. The students studied an Introductory Course in Artificial Intelligence one hour per week for six weeks after which they were assessed by a one hour exam. It was found that Field-dependents and Field-independents performed similarly in both environments as indicated by their examination scores demonstrating the success of the adaption of both environments for Field-dependents. The adaptation for Imagers as measured by Riding's CSA [3] was not successful as Verbalisers performed better than Imagers in both Text and Web. This raises questions about the stability of Riding's Verbaliser/Imager dimension. People performed significantly better in the Text environment than in the Web environment.