Advertisement

Learning Analytics for Professional and Workplace Learning: A Literature Review

  • Adolfo Ruiz-Calleja
  • Luis P. Prieto
  • Tobias Ley
  • María Jesús Rodríguez-Triana
  • Sebastian Dennerlein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10474)

Abstract

Despite the ubiquity of learning in the everyday life of most workplaces, the learning analytics community only has paid attention to such settings very recently. One probable reason for this oversight is the fact that learning in the workplace is often informal, hard to grasp and not univocally defined. This paper summarizes the state of the art of Workplace Learning Analytics (WPLA), extracted from a systematic literature review of five academic databases as well as other known sources in the WPLA community. Our analysis of existing proposals discusses particularly on the role of different conceptions of learning and their influence on the LA proposals’ design and technology choices. We end the paper by discussing opportunities for future work in this emergent field.

Keywords

Workplace Learning Professional development Learning Analytics Learning metaphors 

Notes

Acknowledgements

This research has been partially funded by the European Union in the context of CEITER and the Next-Lab (Horizon 2020 Research and Innovation Programme, grant agreements no. 669074 and 731685).

References

  1. 1.
    AbuKhousa, E., Atif, Y.: Virtual social spaces for practice and experience sharing. In: Li, Y., Chang, M., Kravcik, M., Popescu, E., Huang, R., Kinshuk, Chen, N.-S. (eds.) State-of-the-Art and Future Directions of Smart Learning. LNET, vol. 9240, pp. 86–104. Springer, Singapore (2016). doi: 10.1007/978-981-287-868-7_49
  2. 2.
    Ahn, J., Weng, C., Butler, B.S.: The dynamics of open, peer-to-peer learning: what factors influence participation in the P2P university? In: Proceedings of the 46th Hawaii International Conference on System Sciences (HICSS), Hawaii, USA, pp. 3098–3107 (2013)Google Scholar
  3. 3.
    Attwell, G., Kieslinger, B., Blunk, O., Schmidt, A., Schaefer, T., Jelonek, M., Kunzmann, C., Prilla, M., Reynard, C.: Workplace learning analytics for facilitation in European public employment services. In: Proceedings of the CrossLAK 2016: Learning Analytics Across Physical and Digital Spaces, Edinburgh, UK, pp. 91–97. CEUR (2016)Google Scholar
  4. 4.
    Bereiter, C.: Education and Mind in the Knowledge Age. Routledge, Hillsdale (2005)Google Scholar
  5. 5.
    Berendt, B., Vuorikari, R., Littlejohn, A., Margaryan, A.: Learning analytics and their application in technology-enhanced professional learning. In: Littlejohn, A., Margaryan, A. (eds.) Technology-Enhanced Professional Learning: Processes, Practices and Tools, pp. 144–157. Routledge, London (2014)Google Scholar
  6. 6.
    Biehl, J.T., Czerwinski, M., Smith, G., Robertson, G.G.: FASTDash: a visual dashboard for fostering awareness in software teams. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, San Jose, California, USA, pp. 1313–1322. ACM (2007)Google Scholar
  7. 7.
    Bieke, S., Maarten, D.L.: Network awareness tool - learning analytics in the workplace: detecting and analyzing informal workplace learning. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK), pp. 59–64. ACM, New York (2012)Google Scholar
  8. 8.
    Blikstein, P., Worsley, M.: Multimodal learning analytics and education data mining: using computational technologies to measure complex learning tasks. J. Learn. Anal. 3(2), 220–238 (2016)CrossRefGoogle Scholar
  9. 9.
    Buckingham-Shum, S., Crick, R.D.: Learning dispositions and transferable competencies: pedagogy, modelling and learning analytics. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK), pp. 92–101. ACM, New York (2012)Google Scholar
  10. 10.
    Buckingham-Shum, S., Ferguson, R.: Social learning analytics. J. Educ. Technol. Soc. 15(3), 3–26 (2012)Google Scholar
  11. 11.
    Cambridge, D., Pérez López, K.: First steps towards a social learning analytics for online communities of practice for educators. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK), pp. 69–72. ACM, New York (2012)Google Scholar
  12. 12.
    Chen, G., Clarke, S.N., Resnick, L.B.: Technology and teacher professional development: promoting teachers’ reflection on orchestrating classroom discussions. In: Proceedings of the 20th Global Chinese Conference on Computers in Education, Hong Kong, China, pp. 947–950 (2016)Google Scholar
  13. 13.
    de Laat, M., Schreurs, B., Sie, R.: Utilizing informal teacher professional development networks using the network awareness tool. In: Carvalho, L., Goodyear, P. (eds.) The Architecture of Productive Learning Networks, pp. 239–256. Routledge, London (2014)Google Scholar
  14. 14.
    De Laat, M.F., Schreurs, B.: Professional development networks: building a case for learning analytics in the workplace. Am. Behav. Sci. 57(10), 1421–1438 (2013)CrossRefGoogle Scholar
  15. 15.
    Derntl, M., Günnemann, N., Klamma, R.: A dynamic topic model of learning analytics research. In: Proceedings of the LAK Data Challenge, held at the 3rd Conference on Learning Analytics and Knowledge (LAK), Leuven, Belgium, pp. 1–5 (2013). CEURGoogle Scholar
  16. 16.
    Donnelly, P.J., Blanchard, N., Samei, B., Olney, A.M., Sun, X., Ward, B., Kelly, S., Nystran, M., D’Mello, S.K.: Automatic teacher modeling from live classroom audio. In: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization (UMAP), pp. 45–53. ACM, New York (2016)Google Scholar
  17. 17.
    Eraut, M.: Informal learning in the workplace. Stud. Contin. Educ. 26(2), 247–273 (2004)CrossRefGoogle Scholar
  18. 18.
    Gašević, D., Dawson, S., Siemens, G.: Let’s not forget: learning analytics are about learning. TechTrends 59(1), 64–71 (2015)CrossRefGoogle Scholar
  19. 19.
    Gray, K., Elliott, K., Barnett, S., Chang, S., Li, X.: A conceptual model for analysing informal learning in online social networks for health professionals. Stud. Heal. Technol. Inf. 204, 80–85 (2014)Google Scholar
  20. 20.
    Hilem, Y., Futtersack, M.: COMPANION: an interactive learning environment based on the cognitive apprenticeship paradigm for design engineers using numerical simulations. In: Proceedings of the World Conference on Educational Multimedia and Hypermedia, Vancouver, British Columbia, Canada, pp. 281–286 (1994)Google Scholar
  21. 21.
    Khousa, E.A., Atif, Y., Masud, M.M.: A social learning analytics approach to cognitive apprenticeship. Smart Learn. Environ. 2(1), 1–23 (2015)CrossRefGoogle Scholar
  22. 22.
    Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Technical report, Keele University (UK) (2007)Google Scholar
  23. 23.
    Klamma, R.: Community learning analytics – challenges and opportunities. In: Wang, J.-F., Lau, R. (eds.) ICWL 2013. LNCS, vol. 8167, pp. 284–293. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-41175-5_29 CrossRefGoogle Scholar
  24. 24.
    Kooken, J., Ley, T., de Hoog, R.: How do people learn at the workplace? investigating four workplace learning assumptions. In: Duval, E., Klamma, R., Wolpers, M. (eds.) EC-TEL 2007. LNCS, vol. 4753, pp. 158–171. Springer, Heidelberg (2007). doi: 10.1007/978-3-540-75195-3_12 CrossRefGoogle Scholar
  25. 25.
    Kump, B., Seifert, C., Beham, G., Lindstaedt, S., Ley, T.: Seeing what the system thinks you know - visualizing evidence in an open learner model. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK), pp. 153–157, Vancouver, Canada. ACM (2012)Google Scholar
  26. 26.
    Lee, H., Weerasinghe, A., Barnes, J., Oakden-Rayner, L., Gale, W., Carneiro, G.: CRISTAL: adapting workplace training to the real world context with an intelligent simulator for radiology trainees. In: Micarelli, A., Stamper, J., Panourgia, K. (eds.) ITS 2016. LNCS, vol. 9684, pp. 430–435. Springer, Cham (2016). doi: 10.1007/978-3-319-39583-8_52 Google Scholar
  27. 27.
    Ley, T., Klamma, R., Lindstaedt, S., Wild, F.: Learning analytics for workplace and professional learning. In: Proceedings of the 6th International Conference on Learning Analytics & Knowledge (LAK), pp. 484–485. ACM, New York (2016)Google Scholar
  28. 28.
    Ley, T., Kump, B.: Which user interactions predict levels of expertise in work-integrated learning? In: Hernández-Leo, D., Ley, T., Klamma, R., Harrer, A. (eds.) EC-TEL 2013. LNCS, vol. 8095, pp. 178–190. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40814-4_15 CrossRefGoogle Scholar
  29. 29.
    Paavola, S., Hakkarainen, K.: The knowledge creation metaphor-an emergent epistemological approach to learning. Sci. Educ. 14(6), 535–557 (2005)CrossRefGoogle Scholar
  30. 30.
    Prieto, L.P., Sharma, K., Dillenbourg, P., Rodríguez, M.J.: Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors. In: Proceedings of the 6th International Conference on Learning Analytics & Knowledge (LAK), pp. 148–157, Edinburgh, UK. ACM (2016)Google Scholar
  31. 31.
    Rajagopal, K., van Bruggen, J.M., Sloep, P.B.: Recommending peers for learning: matching on dissimilarity in interpretations to provoke breakdown. Br. J. Educ. Technol. 48(2), 385–406 (2017)CrossRefGoogle Scholar
  32. 32.
    Ruiz-Calleja, A., Dennerlein, S., Ley, T., Lex, E.: Visualizing workplace learning data with the SSS Dashboard. In: Proceedings of the CrossLAK 2016: Learning Analytics Across Physical and Digital Spaces, pp. 79–86, Edinburgh, UK. CEUR (2016)Google Scholar
  33. 33.
    Ruiz-Calleja, A., Dennerlein, S., Tomberg, V., Ley, T., Theiler, D., Lex, E.: Integrating data across workplace learning applications with a social semantic infrastructure. In: Li, F.W.B., Klamma, R., Laanpere, M., Zhang, J., Manjón, B.F., Lau, R.W.H. (eds.) ICWL 2015. LNCS, vol. 9412, pp. 208–217. Springer, Cham (2015). doi: 10.1007/978-3-319-25515-6_19 CrossRefGoogle Scholar
  34. 34.
    Santos, P., Dennerlein, S., Theiler, D., Cook, J., Treasure-Jones, T., Holley, D., Kerr, M., Attwell, G., Kowald, D., Lex, E.: Going beyond your personal learning network, using recommendations and trust through a multimedia question-answering service for decision-support: a case study in the healthcare. J. Univers. Comput. Sci. 22(3), 340–359 (2016)Google Scholar
  35. 35.
    Schoefegger, K., Seitlinger, P., Ley, T.: Towards a user model for personalized recommendations in work-integrated learning: a report on an experimental study with a collaborative tagging system. Procedia Comput. Sci. 1(2), 2829–2838 (2010)CrossRefGoogle Scholar
  36. 36.
    Schwendimann, B.A., Rodríguez, M.J., Vozniuk, A., Prieto, L.P., Boroujeni, M.S., Holzer, A., Gillet, D., Dillenbourg, P.: Perceiving learning at a glance: a systematic literature review of learning dashboard research. IEEE Trans. Learn. Technol. 10(1), 30–41 (2017)CrossRefGoogle Scholar
  37. 37.
    Sfard, A.: On two metaphors for learning and the dangers of choosing just one. Educ. Res. 27(1), 4–13 (1998)CrossRefGoogle Scholar
  38. 38.
    Siadaty, M., Gašević, D., Hatala, M.: Associations between technological scaffolding and micro-level processes of self-regulated learning: a workplace study. Comput. Hum. Behav. 55(1), 1007–1019 (2016)CrossRefGoogle Scholar
  39. 39.
    Siadaty, M., Gašević, D., Hatala, M.: Measuring the impact of technological scaffolding interventions on micro-level processes of self-regulated workplace learning. Comput. Hum. Behav. 59, 469–482 (2016)CrossRefGoogle Scholar
  40. 40.
    Siadaty, M., Gašević, D., Jovanović, J., Milikić, N., Jeremić, Z., Ali, L., Giljanović, A., Hatala, M.: Learn-B: a social analytics-enabled tool for self-regulated workplace learning. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK), pp. 115–119. ACM, New York (2012)Google Scholar
  41. 41.
    Song, E., Petrushyna, Z., Cao, Y., Klamma, R.: Learning analytics at large: the lifelong learning network of 160,000 European teachers. In: Kloos, C.D., Gillet, D., García, R.M.C., Wild, F., Wolpers, M. (eds.) EC-TEL 2011. LNCS, vol. 6964, pp. 398–411. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-23985-4_31 CrossRefGoogle Scholar
  42. 42.
    Southavilay, V., Yacef, K., Reimann, P., Calvo, R.A.: Analysis of collaborative writing processes using revision maps and probabilistic topic models. In: Proceedings of the 3rd International Conference on Learning Analytics and Knowledge (LAK), pp. 38–47, Leuven, Belgium. ACM (2013)Google Scholar
  43. 43.
    Suthers, D.: Collaborative knowledge construction through shared representations. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS), pp. 1–10, Hawaii, USA. IEEE (2005)Google Scholar
  44. 44.
    Vuorikari, R., Scimeca, S.: Social learning analytics to study teachers’ large-scale professional networks. In: Ley, T., Ruohonen, M., Laanpere, M., Tatnall, A. (eds.) Open and Social Technologies for Networked Learning. IFIP AICT, vol. 395, pp. 25–34. Springer, Berlin (2013). doi: 10.1007/978-3-642-37285-8_3 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Adolfo Ruiz-Calleja
    • 1
  • Luis P. Prieto
    • 1
  • Tobias Ley
    • 1
  • María Jesús Rodríguez-Triana
    • 1
    • 2
  • Sebastian Dennerlein
    • 3
  1. 1.Tallinn UniversityTallinnEstonia
  2. 2.École Polytechnique Fédérale de LausanneLausanneSwitzerland
  3. 3.Graz University of TechnologyGrazAustria

Personalised recommendations