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Computing research in the academy: insights from theses and dissertations

Author

Listed:
  • Sung Kim

    (Brigham Young University)

  • Derek Hansen

    (Brigham Young University)

  • Richard Helps

    (Brigham Young University)

Abstract

Computational technologies have become increasingly pervasive in recent decades. Computing research in academia has commensurately seen dramatic increases, both in computing-specific research and research using computing. This article maps out the academic computing landscape by examining the connections between computing-related keywords used to describe theses and dissertations. Specifically, data from 29,435 dissertations and theses found in the ProQuest Theses and Dissertation database in the years 2009–2014 were analyzed. Results identify interdisciplinary clusters, as well as identify key differences in connections between the four computing disciplines in the database: computer science (CS), computer engineering (CE), information technology (IT), and information science (ISci). For example, authors who primarily identify with CS rarely list secondary keywords, while authors from a high variety of other disciplines list CS as a secondary keyword. CE is tightly focused and growing, but rarely seen as a relevant secondary keyword by other fields. Meanwhile, the highly interdisciplinary nature of IT and ISci is shown, along with different subgroups within those areas. While the total number of unique theses with computing-related keywords has remained steady, they have shifted dramatically between specific computing fields (e.g., away from CS toward CE and IT). Visualizations present information on the growth and change in focus of computing-related theses and dissertations, as well as networks of keywords that co-occur. We discuss potential explanations of the patterns, as well as their implications on the future of graduate work in computing disciplines.

Suggested Citation

  • Sung Kim & Derek Hansen & Richard Helps, 2018. "Computing research in the academy: insights from theses and dissertations," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 135-158, January.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:1:d:10.1007_s11192-017-2572-y
    DOI: 10.1007/s11192-017-2572-y
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    Cited by:

    1. Xiaoguang Wang & Hongyu Wang & Han Huang, 2021. "Evolutionary exploration and comparative analysis of the research topic networks in information disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4991-5017, June.
    2. Inés M. Fernández-Guerrero & Zoraida Callejas & David Griol & Antonio Fernández-Cano, 2020. "Longitudinal patterns in Spanish doctoral theses on scientific medical information: a tertiary study," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1241-1260, August.

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    More about this item

    Keywords

    Computing disciplines; Theses and dissertations; Network analysis; Co-word analysis;
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    JEL classification:

    • Y80 - Miscellaneous Categories - - Related Disciplines - - - Related Disciplines

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