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Li, Juan; Li, Zhe; Liu, Shuo-Fang; Cheng, Meng – Interactive Learning Environments, 2020
Traditional methods for conducting performance evaluations of academic courses are somewhat limited in that they are unable to account for both quantitative and qualitative data. For example, the data used to assess student performance in a typical industrial design course are generally complex, multi-criteria, multi-variable, and frequently vague…
Descriptors: Student Evaluation, College Students, Industrial Education, Design
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Wong, Lung-Hsiang; Looi, Chee-Kit – Interactive Learning Environments, 2012
The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…
Descriptors: Electronic Learning, Entomology, Educational Technology, Individualized Instruction
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Lazarinis, Fotis; Green, Steve; Pearson, Elaine – Interactive Learning Environments, 2011
In this article, we present the characteristics and the design of a modular personalized multimedia testing tool based fully on XML learning specifications. Personalization is based on the characteristics of the individual learners, thus the testing paths are tailored to their needs and goals. The system maintains learner profiles rich in content…
Descriptors: Multimedia Materials, Computer Assisted Testing, Computer Software Evaluation, Computer Software