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    Teaching psychology to computing students

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    The aim of this paper is twofold. The first aim is to discuss some observations gained from teaching Psychology to Computing students, highlighting both the wide range of areas where Psychology is relevant to Computing education and the topics that are relevant at different stages of students’ education. The second aim is to consider findings from research investigating the characteristics of Computing and Psychology students. It is proposed that this information could be considered in the design and use of Psychology materials for Computing students. The format for the paper is as follows. Section one will illustrate the many links between the disciplines of Psychology & Computing; highlighting these links helps to answer the question that many Computing students ask, what can Psychology offer to Computing? Section two will then review some of the ways that I have been involved in teaching Psychology to Computing students, from A/AS level to undergraduate and postgraduate level. Section three will compare the profiles of Computing and Psychology students (e.g. on age, gender and motivation to study), to highlight how an understanding of these factors can be used to adapt Psychology teaching materials for Computing students. The conclusions which cover some practical suggestions are presented in section four

    Semantic Modeling for Group Formation

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    Group formation has always been a subject of interest in collaborative learning research. As it is concerned with assigning learners to the groups that maximize their benefits, computer-supported group formation can be viewed in this context as an active personalization for the individual as an entity within the group. While applying this personalization to all students in the class can cause conflicts due to the differences of needs and interests between the individuals, negotiating the allocations to groups to reach consensus can be a very challenging task. The automated process of grouping students while preserving the individual’s personalization needs to be supported by an appropriate learner model. In this paper, we propose a semantic learner model based on the Friend of Friend (FOAF) ontology, a vocabulary for mapping social networks. We discuss the model as we analyse the different types of groups and the learners’ features that need to be modeled for each of these types
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