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Radical Solutions and Learning Analytics pp 37–55Cite as

Research Ethics Guidelines for Personalized Learning and Teaching Through Big Data

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

Abstract

Any implementation of personalized learning and teaching through big data will have implications for research ethics. This chapter considers the research ethics implications in certain key regulatory documents and the scholarship on research ethics and learning analytics. Finally, the chapter provides guidelines for use by researchers and research ethics review committees—within the field of education in the South African context—specifically focusing on personalized learning and teaching through big data and learning analytics.

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References

  • Beardsley, M., Santos, P., Hernández-Leo, D., & Michos, K. (2019). Ethics in educational technology research: Informing participants on data sharing risks. British Journal of Educational Technology, 50(3), 1019–1034.

    Article  Google Scholar 

  • Beattie, S., Woodley, C., & Souter, K. (2014). Creepy analytics and learner data rights. Rhetoric and reality: Critical perspectives on educational technology. Proceedings ascilite, 421–425.

    Google Scholar 

  • Chen, B., Chen, C. M., Hong, H. Y., & Chai, C. S. (2018). Learning Analytics: Approaches and cases from Asia. In K. J. Kennedy & J. C.-K. Lee (Eds.), Routledge international handbook of schools and schooling in Asia (pp. 419–432). London: Routledge.

    Google Scholar 

  • Chen, X., & Liu, C. Y. (2015). Big data ethics in education: Connecting practices and ethical awareness. Journal of Educational Technology Development and Exchange, 8(2), 81–98.

    Article  Google Scholar 

  • Corrin, L., Kennedy, G., French, S., Buckingham Shum S., Kitto, K., Pardo, A., West, D., Mirriahi, N., & Colvin, C. (2019). The ethics of learning analytics in australian higher education. A discussion paper. Retrieved December 5, 2019, from https://melbourne-cshe.unimelb.edu.au/__data/assets/pdf_file/0004/3035047/LA_Ethics_Discussion_Paper.pdf.

  • Cormack, A. N. (2016). A data protection framework for learning analytics. Journal of Learning Analytics, 3(1), 91–106.

    Article  Google Scholar 

  • Department of Health. (2015). Ethics in health research: Principles, processes and structures (2nd ed.). Pretoria: Department of Health.

    Google Scholar 

  • Department of Health, Education, and Welfare. (1979). The Belmont Report. Ethical principles and guidelines for the protection of human subjects of research. Retrieved December 4, 2019, from https://www.hhs.gov/ohrp/sites/default/files/the-belmont-report-508c_FINAL.pdf.

  • Ferguson, R. (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304–317.

    Article  Google Scholar 

  • Hoel, T., Griffiths, D., & Chen, W. (2017). The influence of data protection and privacy frameworks on the design of learning analytics systems. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference (pp. 243–252). ACM.

    Google Scholar 

  • Kitto, K., & Knight, S. (2019). Practical ethics for building learning analytics. British Journal of Educational Technology, 50(6), 2855–2870.

    Article  Google Scholar 

  • Lawson, C., Beer, C., Rossi, D., Moore, T., & Fleming, J. (2016). Identification of ‘at risk’students using learning analytics: the ethical dilemmas of intervention strategies in a higher education institution. Educational Technology Research and Development, 64(5), 957–968.

    Article  Google Scholar 

  • Mandinach, E. B., & Jackson, S. S. (2012). Transforming teaching and learning through data-driven decision making. Thousand Oaks, CA: SAGE.

    Book  Google Scholar 

  • Pardo, A., & Siemens, G. (2014). Ethical and privacy principles for learning analytics. British Journal of Educational Technology, 45(3), 438–450.

    Article  Google Scholar 

  • Republic of South Africa. (1996). Constitution of the Republic of South Africa Act, No 108 of 1996. Pretoria: Government Printer.

    Google Scholar 

  • Republic of South Africa. (2000). Promotion of Access to Information Act, No 2 of 2000 (p. 20852). No: Government Gazette.

    Google Scholar 

  • Republic of South Africa. (2013). Protection of Personal Information Act, No 4 of 2013 (p. 37067). No: Government Gazette.

    Google Scholar 

  • Saqr, M., Fors, U., & Tedre, M. (2017). How learning analytics can early predict under-achieving students in a blended medical education course. Medical Teacher, 39(7), 757–767.

    Article  Google Scholar 

  • Scholes, V. (2016). The ethics of using learning analytics to categorize students on risk. Educational Technology Research and Development, 64(5), 939–955.

    Article  Google Scholar 

  • Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 46(5), 30–40.

    Google Scholar 

  • Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510–1529.

    Article  Google Scholar 

  • Steiner, C. M., Kickmeier-Rust, M. D., & Albert, D. (2015). Let’s Talk Ethics: Privacy and Data Protection Framework for a Learning Analytics Toolbox. In LAK′15: International Conference on Learning Analytics and Knowledge. New York: Poughkeepsie.

    Google Scholar 

  • West, D., Huijser, H., & Heath, D. (2016). Putting an ethical lens on learning analytics. Educational Technology Research and Development, 64(5), 903–922.

    Article  Google Scholar 

  • Willis, J. E., Slade, S., & Prinsloo, P. (2016). Ethical oversight of student data in learning analytics: A typology derived from a cross-continental, cross-institutional perspective. Educational Technology Research and Development, 64(5), 881–901.

    Article  Google Scholar 

  • World Conference on Research Integrity. (2010). Singapore Statement on Research Integrity. Retrieved December 4, 2019, from https://wcrif.org/documents/327-singapore-statement-a4size/file.

  • Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2013). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107.

    Google Scholar 

  • Zimmer, M. (2018). Addressing conceptual gaps in big data research ethics: An application of contextual integrity. Social Media + Society, 1–11.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Research Unit Self-Directed Learning and UNESCO Chair on Multimodal Learning and Open Educational Resources, Faculty of Education, North-West University, Potchefstroom, South Africa

    Jako Olivier

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  1. Jako Olivier
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Correspondence to Jako Olivier .

Editor information

Editors and Affiliations

  1. Research Institute for Innovation & Technology in Education (UNIR iTED), Universidad Internacional de La Rioja (UNIR), Logroño, La Rioja, Spain

    Daniel Burgos

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Olivier, J. (2020). Research Ethics Guidelines for Personalized Learning and Teaching Through Big Data. In: Burgos, D. (eds) Radical Solutions and Learning Analytics. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-15-4526-9_3

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  • DOI: https://doi.org/10.1007/978-981-15-4526-9_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4525-2

  • Online ISBN: 978-981-15-4526-9

  • eBook Packages: EducationEducation (R0)

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