Title: Diagnostic Learning: Using Web-Based Self Diagnostic Tools for Learning Abstract Concepts in Data Network Education
Abstract: Subjects such as data networking rely heavily on a ‘building block’ approach – deep understanding of the simpler concepts are essential if the learner is to be able to appreciate the more complex and abstract concepts upon which data communication protocols are built. For this reason, students’ levels of anxiety could increase if the earlier concepts are not grasped adequately – thereby discouraging future engagement with the subject.
This paper describes the historical background to teaching data networks, including feedback and reflection opportunities provided to students via a suite of dynamic, web-based tutorials in a QUT subject. These tutorials utilise context sensitive help screens to aid students’ self-diagnosis of their understanding of the subject material. It reports a preliminary investigation into (i) variation in students’ learning of abstract concepts (ii) what strategies are employed by learners in their effective use of a formative web-based tutorial, (iii) variation in learning outcomes from use of the tutorial. The results indicate that students focus on the parts of networks, and not the holistic picture. They also do not focus on how the network functions. We suggest that these results indicate that new ways of using technology in learning should be pursued as well as a deeper understanding of students’ learning outcomes.
Publication Year: 2005
Publication Date: 2005-01-01
Language: en
Type: article
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Cited By Count: 1
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