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Using Web Analytics Methods to Design Open Web-Based University Courses: Case Study on Creative Work with Information Course

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New Media Pedagogy: Research Trends, Methodological Challenges and Successful Implementations (NMP 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1916))

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Abstract

Hypertext-based or web-based courses are a specific category of e-learning courses for which students do not have to register anywhere. For the actual operation, content management systems (CRM systems) are used to structure the content graphically and efficiently, work quickly with the universal design concept, or ensure responsive course design. While with conventional e-learning platforms or MOOC course tools, content creators can work with relatively well-structured data from their analytical tools and rely on standard web analytics methods. The study analyses the use of Google Analytics for the design of web-based courses using the example of one hypertext course (Creative Information Work). The study answers questions about how web analytics metrics can be used to design course content and format and to support the search for appropriate synchronous educational supplements. The study highlights the variability of each category and the potential of Google Analytics to serve as a tool for a design approach to developing educational objects of this kind.

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Acknowledgements

I want to thank Barbora Fukárková for creating the graphic design of the course and the tutors who take care of the students during the course. Without their help, this study could not have been made.

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Authors and Affiliations

  1. Masaryk University in Brno, Brno, Czech Republic

    Michal Černý

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  1. Michal Černý
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Correspondence to Michal Černý .

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  1. Jagiellonian University, Kraków, Poland

    Łukasz Tomczyk

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Černý, M. (2023). Using Web Analytics Methods to Design Open Web-Based University Courses: Case Study on Creative Work with Information Course. In: Tomczyk, Ł. (eds) New Media Pedagogy: Research Trends, Methodological Challenges and Successful Implementations. NMP 2022. Communications in Computer and Information Science, vol 1916. Springer, Cham. https://doi.org/10.1007/978-3-031-44581-1_16

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  • DOI: https://doi.org/10.1007/978-3-031-44581-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-44580-4

  • Online ISBN: 978-3-031-44581-1

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