IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v102y2015i2d10.1007_s11192-014-1453-x.html
   My bibliography  Save this article

Coherence analysis of research and education using topic modeling

Author

Listed:
  • Hoyeop Lee

    (Yonsei University)

  • Jueun Kwak

    (Yonsei University)

  • Min Song

    (Yonsei University)

  • Chang Ouk Kim

    (Yonsei University)

Abstract

Research and education are organically connected in that lectures convey the results of research, which is frequently initiated by inspiring lectures. As a result, the contents of lecture materials and research publications and the research capabilities of universities should be considered in the investigations of the relationships between research and teaching. We examine the relationship between research and teaching using automatic text analysis. In particular, we scrutinize the relatedness of the content of research papers with the content of lecture materials to investigate the association between teaching and research. We adopt topic modeling for the correlation analysis of research capabilities and the reflectiveness of research topics in lecture materials. We select the field of machine learning as a case study because the field is contemporary and because data related to teaching and research are easily accessible via the Internet. The results reveal interesting characteristics of lecture materials and research publications in the field of machine learning. The research capability of an institute is independent of the lecture materials. However, for introductory courses, teaching and research measures showed a weak negative relationship, and there is little relationship between the measures for advanced courses.

Suggested Citation

  • Hoyeop Lee & Jueun Kwak & Min Song & Chang Ouk Kim, 2015. "Coherence analysis of research and education using topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1119-1137, February.
    • Handle: RePEc:spr:scient:v:102:y:2015:i:2:d:10.1007_s11192-014-1453-x
    DOI: 10.1007/s11192-014-1453-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-014-1453-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-014-1453-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bornmann, Lutz & Mutz, Rüdiger & Hug, Sven E. & Daniel, Hans-Dieter, 2011. "A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants," Journal of Informetrics, Elsevier, vol. 5(3), pages 346-359.
    2. Herbert W. Marsh & John Hattie, 2002. "The Relation between Research Productivity and Teaching Effectiveness," The Journal of Higher Education, Taylor & Francis Journals, vol. 73(5), pages 603-641, September.
    3. Shengbo Liu & Chaomei Chen, 2013. "The differences between latent topics in abstracts and citation contexts of citing papers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(3), pages 627-639, March.
    4. Costas, Rodrigo & Bordons, María, 2007. "The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level," Journal of Informetrics, Elsevier, vol. 1(3), pages 193-203.
    5. Shengbo Liu & Chaomei Chen, 2013. "The differences between latent topics in abstracts and citation contexts of citing papers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(3), pages 627-639, March.
    6. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ebadi, Ashkan & Tremblay, Stéphane & Goutte, Cyril & Schiffauerova, Andrea, 2020. "Application of machine learning techniques to assess the trends and alignment of the funded research output," Journal of Informetrics, Elsevier, vol. 14(2).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pantea Kamrani & Isabelle Dorsch & Wolfgang G. Stock, 2021. "Do researchers know what the h-index is? And how do they estimate its importance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5489-5508, July.
    2. Bornmann, Lutz & Marx, Werner, 2012. "HistCite analysis of papers constituting the h index research front," Journal of Informetrics, Elsevier, vol. 6(2), pages 285-288.
    3. Lorna Wildgaard & Jesper W. Schneider & Birger Larsen, 2014. "A review of the characteristics of 108 author-level bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 125-158, October.
    4. Hu, Zhigang & Chen, Chaomei & Liu, Zeyuan, 2013. "Where are citations located in the body of scientific articles? A study of the distributions of citation locations," Journal of Informetrics, Elsevier, vol. 7(4), pages 887-896.
    5. Petr Praus, 2019. "High-ranked citations percentage as an indicator of publications quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 319-329, July.
    6. Cerovšek, Tomo & Mikoš, Matjaž, 2014. "A comparative study of cross-domain research output and citations: Research impact cubes and binary citation frequencies," Journal of Informetrics, Elsevier, vol. 8(1), pages 147-161.
    7. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    8. Zhao Qu & Shanshan Zhang & Chunbo Zhang, 2017. "Patent research in the field of library and information science: Less useful or difficult to explore?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 205-217, April.
    9. Anatoliy G. Goncharuk, 2018. "Efficiency vs Effectiveness: Alternative Metrics for Research Performance," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 7(1), pages 24-37, February.
    10. Shahryar Rahnamayan & Sedigheh Mahdavi & Kalyanmoy Deb & Azam Asilian Bidgoli, 2020. "Ranking Multi-Metric Scientific Achievements Using a Concept of Pareto Optimality," Mathematics, MDPI, vol. 8(6), pages 1-46, June.
    11. Corey J A Bradshaw & Justin M Chalker & Stefani A Crabtree & Bart A Eijkelkamp & John A Long & Justine R Smith & Kate Trinajstic & Vera Weisbecker, 2021. "A fairer way to compare researchers at any career stage and in any discipline using open-access citation data," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-15, September.
    12. Cabrerizo, F.J. & Alonso, S. & Herrera-Viedma, E. & Herrera, F., 2010. "q2-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the Hirsch core," Journal of Informetrics, Elsevier, vol. 4(1), pages 23-28.
    13. Li, Xin & Xie, Qianqian & Jiang, Jiaojiao & Zhou, Yuan & Huang, Lucheng, 2019. "Identifying and monitoring the development trends of emerging technologies using patent analysis and Twitter data mining: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 687-705.
    14. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    15. James C. Ryan, 2016. "A validation of the individual annual h-index (hIa): application of the hIa to a qualitatively and quantitatively different sample," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 577-590, October.
    16. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    17. Yu Liu & Wei Zuo & Ying Gao & Yanhong Qiao, 2013. "Comprehensive geometrical interpretation of h-type indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 605-615, August.
    18. Kun Sun & Haitao Liu & Wenxin Xiong, 2021. "The evolutionary pattern of language in scientific writings: A case study of Philosophical Transactions of Royal Society (1665–1869)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1695-1724, February.
    19. Kuan, Chung-Huei & Huang, Mu-Hsuan & Chen, Dar-Zen, 2011. "Ranking patent assignee performance by h-index and shape descriptors," Journal of Informetrics, Elsevier, vol. 5(2), pages 303-312.
    20. Anna Tietze & Philip Hofmann, 2019. "The h-index and multi-author hm-index for individual researchers in condensed matter physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 171-185, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:102:y:2015:i:2:d:10.1007_s11192-014-1453-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.