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Public Internet Data Mining Methods in Instructional Design, Educational Technology, and Online Learning Research

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Abstract

We describe the benefits and challenges of engaging in public data mining methods and situate our discussion in the context of studies that we have conducted. Practical, methodological, and scholarly benefits include the ability to access large amounts of data, randomize data, conduct both quantitative and qualitative analyses, connect educational issues with broader issues of concern, identify subgroups/subpopulations of interest, and avoid many biases. Technical, methodological, professional, and ethical issues that arise by engaging in public data mining methods include the need for multifaceted expertise and rigor, focused research questions and determining meaning, and performative and contextual considerations of public data. As the scientific complexity facing research in instructional design, educational technology, and online learning is expanding, it is necessary to better prepare students and scholars in our field to engage with emerging research methodologies.

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Author notes

  1. Royce Kimmons and George Veletsianos contributed equally to this work.

Authors and Affiliations

  1. Brigham Young University, 150J MCKB, BYU, Provo, UT, 84602, USA

    Royce Kimmons

  2. Royal Roads University, 2005 Sooke Rd, Victoria, BC, V9B 5Y2, Canada

    George Veletsianos

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  1. Royce Kimmons
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  2. George Veletsianos
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Correspondence to Royce Kimmons.

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This article does not report on a study with human participants performed by any of the authors.

Conflict of Interest

Royce Kimmons declares that he has no conflict of interest. George Veletsianos declares that he has no conflict of interest.

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Kimmons, R., Veletsianos, G. Public Internet Data Mining Methods in Instructional Design, Educational Technology, and Online Learning Research. TechTrends 62, 492–500 (2018). https://doi.org/10.1007/s11528-018-0307-4

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