Abstract
To help students better understand abstract information retrieval (IR) concepts and encourage students to explore new concepts, an existing Web-based IR tool called Infret was enhanced. Based on the feedback from a previous evaluation, the need for additional IR concepts and user tracking functionality was identified. The expanded Infret version was evaluated in a class of experienced students who were studying an information search and retrieval course and a class of novice students who were studying a database design and development course. Both groups were working in different learning environments and were given two similar text statistics-based learning activities and four term weighting-based learning activities. At the end of the activities, both groups completed a multi-part survey. The results indicate that the novice students were more inclined to explore unrelated IR concepts after using Infret. Additionally, both groups agreed that exploring the concepts using visualisations helped them more than just calculating the formulae manually. Furthermore, the results show that Infret successfully helps students understand concepts of text statistics and term weighting and was seen as useful by most students. The average system usability score (SUS) for the experienced students was 69.8 and for novice students 57.7. These results indicate that Infret supports exploration and helps students get a better understanding of concepts, however, further improvements are required.
This work was carried out while Justin Filippou was employed by RMIT University.
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Acknowledgment
We would like to acknowledge and thank Graz University of Technology for funding and RMIT University’s School of Business IT and Logistics for hosting Aleksandar Bobić. We would also like to thank for participants for volunteering in our research project.
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Bobić, A., Cheong, C., Filippou, J., Cheong, F., Guetl, C. (2020). Infret: Enhancing a Tool for Explorative Learning of Information Retrieval Concepts. In: Auer, M., Hortsch, H., Sethakul, P. (eds) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-030-40274-7_7
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