Human-Centred Learning Analytics


Abstract


The design of effective learning analytics extends beyond sound technical and pedagogical principles. If these analytics are to be adopted and used successfully to support learning and teaching, their design process needs to take into account a range of human factors, including why and how they will be used. In this editorial, we introduce principles of human-centred design developed in other, related fields that can be adopted and adapted to support the development of Human-Centred Learning Analytics (HCLA). We draw on the papers in this special section, together with the wider literature, to define human-centred design in the field of learning analytics and to identify the benefits and challenges that this approach offers. We conclude by suggesting that HCLA will enable the community to achieve more impact, more quickly, with tools that are fit for purpose and a pleasure to use.


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References

Ahn, J., Campos, F., Hays, M., & Digiacomo, D. (2019). Designing in context: Reaching beyond usability in learning analytics dashboard design. Journal of Learning Analytics, 6 (2), 70–85. http://dx.doi.org/10.18608/jla.2019.62.5

Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P., Inkpen, K., Teevan, J., Kikin-Gil, R., & Horvitz, E. (2019). Guidelines for human-AI interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’19), 4–9 May 2019, Glasgow, U.K. (pp. 1–13). New York: ACM. https://dx.doi.org/10.1145/3290605.3300233

Buckingham Shum, S. (2018). Transitioning education’s knowledge infrastructure: Shaping design or shouting from the Touchline? Keynote Address, In Proceedings of the 13th International Conference of the Learning Sciences, 23–27 June 2018, London, U.K. (p. 5). Online video: https://vimeo.com/282320963

Buckingham Shum, S., & Luckin, R. (2019, in press). Learning analytics and AI: Politics, Pedagogy and Practices. British Journal of Educational Technology (Special Issue).

Buckingham Shum, S. J., and McKay, T. A. (2018), Architecting for learning analytics: Innovating for sustainable impact. EDUCAUSE Review, March/April 2018, pp. 25–37. https://er.educause.edu/articles/2018/3/architecting-for-learning-analytics-innovating-for-sustainable-impact

Chen, B., & Zhu, H. (2019). Towards value-sensitive learning analytics design. In Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK ’19), 4–8 March 2019, Tempe, AZ, U.S.A. (pp. 343–352). New York: ACM. https://dx.doi.org/10.1145/3303772.3303798

CHI (2019). Guide to a successful submission. http://chi2019.acm.org/authors/papers/guide-to-a-successful-submission/

Crick, R. (2017). Learning analytics: Layers, loops and processes in a virtual learning infrastructure. In Lang, C., Siemens, G., Wise, A. F., & Gasevic, D. (Eds.), The Handbook of Learning Analytics (1st edition), pp. 291–308. Edmonton, AB, Canada: Society for Learning Analytics Research. http://dx.doi.org/10.18608/hla17.025

Dawson, S., Poquet, O., Colvin, C., Rogers, T., Pardo, A., & Gasevic, D. (2018). Rethinking learning analytics adoption through complexity leadership theory. In Proceedings of the 8th International Conference on Learning Analytics Knowledge (LAK ’18), 7–9 March 2018, Sydney, Australia (pp. 236–244). New York: ACM. https://dx.doi.org/10.1145/3170358.3170375

Dollinger, M., Liu, D., Arthars, N., & Lodge, J. (2019). Working together in learning analytics toward the co-creation of value. Journal of Learning Analytics, 6(2), 10–26. http://dx.doi.org/10.18608/jla.2019.62.2

Engelbart, D. C. (1963). A conceptual framework for the augmentation of man’s intellect. In Howerton, P. W., & Weeks, D. C. (Eds.), Vistas in Information Handling, pp. 1–29. Washington, DC: Spartan Books. http://dougengelbart.org/content/view/382/000/

Ferguson, R., Macfadyen, L. P., Clow, D., Tynan, B., Alexander, S., & Dawson, S. (2015). Setting learning analytics in context: Overcoming the barriers to large-scale adoption. Journal of Learning Analytics, 1(3), pp. 120–144. https://dx.doi.org/10.18608/jla.2014.13.7

Fitzpatrick, G. (2018). A short history of human computer interaction: A people-centred perspective. In Proceedings of the 2018 ACM SIGUCCS Annual Conference, 7–10 October 2018, Orlando, FL, U.S.A. (p. 3). New York: ACM. https://dx.doi.org/10.1145/3235715.3242569

Giacomin, J. (2014). What is human centred design?, The Design Journal, 17(4), pp. 606–623. http://dx.doi.org/10.2752/175630614X14056185480186

Grudin, J. (2017). From Tool to Partner: The Evolution of Human-Computer Interaction. Synthesis Lectures on Human-Centered Informatics. San Rafael, CA, U.S.A.: Morgan & Claypool. http://dx.doi.org/10.2200/S00745ED1V01Y201612HCI035

Holbrook, J. (2017). Human-Centered Machine Learning. Google Blog Post (10 July 2017). https://medium.com/google-design/human-centered-machine-learning-a770d10562cd

Holstein, K., McLaren, B. M., & Aleven, V. (2019). Co-designing a real-time classroom orchestration tool to support teacher-AI complementarity. Journal of Learning Analytics, 6(2), 27–52. http://dx.doi.org/10.18608/jla.2019.62.3

Horvitz, E. (1999). Principles of mixed-initiative user interfaces. In Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems (CHI 1999), 15–20 May 1999, Pittsburgh, PA, U.S.A. (pp. 159–166). New York: ACM. https://dx.doi.org/10.1145/302979.303030

Jivet, I., Scheffel, M., Drachsler, H. & Specht, M. (2018). License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK ’18), 7–9 March 2018, Sydney, Australia (pp. 31–40). New York: ACM. https://dx.doi.org/10.1145/3170358.3170421

Kuniavsky, M., Churchill, E., & Steenson, M. W. (Eds.). (2017). Designing the user experience of machine learning systems. In AAAI Spring Symposium Proceedings (Technical Report SS-17-04), 27–29 March 2017, Stanford, CA, U.S.A. Palo Alto, CA, U.S.A.: The AAAI Press. https://www.aaai.org/Library/Symposia/Spring/ss17-04.php

Matcha, W., Gasevic, D., & Pardo, A. (2019). A systematic review of empirical studies on learning analytics dashboards: A self-regulated learning perspective. IEEE Transactions on Learning Technologies. Published online 14 May 2019. https://dx.doi.org/10.1109/TLT.2019.2916802

Prieto-Alvarez, C., Anderson, T., Martinez-Maldonado, R., Kitto, K., McPherson, J., & Dollinger, M. (2018a). Participatory design and co-design in learning analytics. Workshop at the 9th International Conference of Learning Analytics & Knowledge (LAK ’18), 7–9 March 2018, Sydney, Australia. http://pdlak.utscic.edu.au

Prieto-Alvarez, C. G., Martinez-Maldonado, R., & Shum, S. B. (2018b). Mapping learner-data journeys: Evolution of a visual co-design tool. In Proceedings of the 30th Australian Conference on Computer-Human Interaction (OzCHI 2018), 4–7 December 2018, Melbourne, Australia (pp. 205–214). New York: ACM. https://dx.doi.org/10.1145/3292147.3292168

Rehrey, G., Shepard, L., Hostetter, C., Reynolds, A., & Groth, D. (2019). Engaging faculty in learning analytics: Agents of institutional culture change. Journal of Learning Analytics, 6(2),86–94. http://dx.doi.org/10.18608/jla.2019.62.6

Rogers, Y. (2012). HCI Theory: Classical, Modern, and Contemporary. Synthesis Lectures on Human-Centered Informatics. San Rafael, CA, U.S.A.: Morgan & Claypool. https://dx.doi.org/10.2200/S00418ED1V01Y201205HCI014

Scanlon, E., Sharples, M., Fenton-O’Creevy, M., Fleck, J., Cooban, C., Ferguson, R., Cross, S., & Waterhouse, P. (2013). Beyond Prototypes: Enabling Innovation in Technology-Enhanced Learning. ESRC/EPSRC Technology Enhanced Learning Programme, UK. http://oro.open.ac.uk/41119/1

Selwyn, N. (2019, in press). What’s the problem with learning analytics? Journal of Learning Analytics, Commentary Special Section based on LAK ’18 Keynote Address: https://youtu.be/rsUx19_Vf0Q

Sharp, H., Preece, J., & Rogers, Y. (2019). Interaction Design: Beyond Human-Computer Interaction (5th edition), New York: John Wiley & Sons. ISBN: 978-1-119-02075-2

Siemens, G., & Baker, R. S. J. D. (2012). Learning analytics and educational data mining: Towards communication and collaboration. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK ’12), 29 April–2 May 2012, Vancouver, BC, Canada (pp. 252–254). New York: ACM. https://dx.doi.org/10.1145/2330601.2330661

Teasley, S. D. (2017). Student facing dashboards: One size fits all? Technology, Knowledge and Learning, 22(3), pp. 377–384. https://doi.org/10.1007/s10758-017-9314-3

Wise, A. F., & Jung, Y. (2019). Teaching with analytics: Toward a situated model of instructional decision-making. Journal of Learning Analytics, 6(2), 53–69. http://dx.doi.org/10.18608/jla.2019.62.4

Wobbrock, J. O., & Kientz, J. A. (2016). Research contributions in human-computer interaction. Interactions, 23(3), pp. 38–44. https://dx.doi.org/10.1145/2907069



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DOI: https://doi.org/10.18608/jla.2019.62.1

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