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Innovations in Smart Learning pp 19–22Cite as

A New MOOCs’ Recommendation Framework based on LinkedIn Data

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Part of the book series: Lecture Notes in Educational Technology ((LNET))

Abstract

We propose a new framework for recommending Massive Open Online Courses (MOOCs) to lifelong learners. Our approach can be summarized in two steps: (1) recommending MOOCs to potential learners according to their curricular information by relying on their LinkedIn profiles, and (2) recommending topics of interest to MOOCs’ providers by considering the job market needs. We also provide some insights about MOOCs of our Coursera dataset, thus to be taken into account during the decision process.

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References

  1. RĂDOIU, D.: Organization and constraints of a recommender system for MOOCs. Scientific Bulletin of the “Petru Maior” University of Tîrgu Mure, 11, 51-59 (2014)

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  2. Dai, K., Nespereira, C. G., Vilas, A. F., & Redondo, R. P. D.: Scraping and Clustering Techniques for the Characterization of LinkedIn Profiles. In: proceedings of the Fourth International Conference on Information Technology Convergence & Services. 1-15 (2015)

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  3. Coursera, https://blog.coursera.org/post/142363925112 (last accessed: 04/06/2016)

  4. Schafer, J. B., Frankowski, D., Herlocker, J., & Sen, S.: Collaborative filtering recommender systems. In The adaptive web. 291-324. Springer Berlin Heidelberg (2007)

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Author information

Authors and Affiliations

  1. Information & Computing Lab., AtlantTIC Research Center, University of Vigo, Vigo, Spain

    Kais Dai, Ana Fernández Vilas & Rebeca P. Díaz Redondo

Authors
  1. Kais Dai
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  2. Ana Fernández Vilas
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  3. Rebeca P. Díaz Redondo
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Corresponding author

Correspondence to Kais Dai .

Editor information

Editors and Affiliations

  1. University of Craiova, Craiova, Romania

    Elvira Popescu

  2. Athabasca University , Edmonton, Alberta, Canada

    Kinshuk

  3. Cultural and Scientific Organization, Arab League Educational Cultural and Scientific Organization, Tunis, Tunisia

    Mohamed Koutheair Khribi

  4. Faculty of Education, Beijing Normal University Faculty of Education, Beijing, China

    Ronghuai Huang

  5. Arab League Educational, Cultural and Scientific Organization, Tunis, Tunisia

    Mohamed Jemni

  6. National Sun Yat-sen University , Kaohsiung, Taiwan

    Nian-Shing Chen

  7. School of Education, 00301J, Curtin University School of Education, 00301J, Perth, West Australia, Australia

    Demetrios G. Sampson

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© 2017 Springer Science+Business Media Singapore

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Cite this paper

Dai, K., Vilas, A.F., Díaz Redondo, R.P. (2017). A New MOOCs’ Recommendation Framework based on LinkedIn Data. In: Popescu, E., et al. Innovations in Smart Learning. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-2419-1_3

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  • DOI: https://doi.org/10.1007/978-981-10-2419-1_3

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2418-4

  • Online ISBN: 978-981-10-2419-1

  • eBook Packages: EducationEducation (R0)

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