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International Conference on Remote Engineering and Virtual Instrumentation

REV 2020: Cross Reality and Data Science in Engineering pp 849–865Cite as

Infret: Preliminary Findings of a Tool for Explorative Learning of Information Retrieval Concepts

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1231)

Abstract

To help students better understand concepts in an information search and retrieval (ISR) class using the Motivational Active Learning (MAL) pedagogical approach, a tool called Infret was developed. It serves as the interactive experimentation and visualization component of MAL. The design of Infret is based on feedback collected from a testing session with a first proof of concept tool built in Java a year earlier. Infret was developed using Web technologies in order to have a simpler update process and be accessible from any Internet connected device with reasonable screen sizes (PC or tablet) without the need for manual installation. It was used and evaluated as part of a text statistics exercise in which students explored different properties of a text-based document collection. When students completed the exercise, they filled out a multi-part survey about Infret. Findings revealed that Infret helped participants gain a better understanding of text statistics and that the activity was well received by them. The usability score of Infret was 76.9, which indicates a usability level that is slightly above average and the emotions scale results were mostly positive. Additionally, the most commonly experienced emotion by students was happiness followed by negative emotions such as sadness, anxiety and anger which were experienced almost none of the time. There were multiple improvement suggestions such as improving the responsiveness of the UI on small screens, offering the option to see the content of text collections and the addition of formula explanations. These suggestions will be considered for improving Infret in future versions. Additionally, students expressed they would like to use Infret in other areas of information retrieval and also in other subjects.

Keywords

  • Information retrieval
  • Active learning
  • Interactive visualisation tool
  • Web-based learning
  • Explorative learning

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Notes

  1. 1.

    https://angular.io/.

  2. 2.

    https://reactjs.org/.

  3. 3.

    https://www.typescriptlang.org/.

  4. 4.

    http://nvd3.org/.

  5. 5.

    https://nodejs.org/en/.

  6. 6.

    https://hapijs.com/.

  7. 7.

    The Friday after Thanksgiving in the United States (US) which marks the start of the Christmas shopping season in the US.

  8. 8.

    https://www.mysql.com/.

  9. 9.

    https://www.mongodb.com/.

  10. 10.

    https://webpack.js.org/.

  11. 11.

    A dataset consisting of 1400 text documents used for testing and evaluation purposes.

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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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Authors and Affiliations

  1. Graz University of Technology, Graz, Austria

    Aleksandar Bobić & Christian Gütl

  2. RMIT University, Melbourne, Australia

    Christopher Cheong

Authors
  1. Aleksandar Bobić
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  2. Christian Gütl
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  3. Christopher Cheong
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Corresponding author

Correspondence to Aleksandar Bobić .

Editor information

Editors and Affiliations

  1. Carinthia University of Applied Sciences, Villach, Austria

    Prof. Dr. Michael E. Auer

  2. College of Engineering, University of Georgia, Athens, GA, USA

    Prof. Dr. Dominik May

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Bobić, A., Gütl, C., Cheong, C. (2021). Infret: Preliminary Findings of a Tool for Explorative Learning of Information Retrieval Concepts. In: Auer, M., May, D. (eds) Cross Reality and Data Science in Engineering. REV 2020. Advances in Intelligent Systems and Computing, vol 1231. Springer, Cham. https://doi.org/10.1007/978-3-030-52575-0_70

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