Developing a Code of Practice for Using Data in Wellbeing Support

Authors

DOI:

https://doi.org/10.18608/jla.2022.7533

Keywords:

learning analytics, wellbeing, data protection, practical report

Abstract

With student and staff wellbeing a growing concern, several authors have asked whether existing data might help institutions provide better support. By analogy with the established field of Learning Analytics, this might involve identifying causes of stress, improving access to information for those who need it, suggesting options, providing rapid feedback, even early warning of problems. But just investigating the possibility of such uses can create significant risks for individuals: feelings of creepiness or surveillance making wellbeing worse, inappropriate data visibility destroying trust, assessments or interventions becoming self-fulfilling prophecies. To help institutions decide whether and how to explore this area, and to reassure individuals that this is being done safely, we propose a Wellbeing Analytics Code of Practice. This starts from an existing Learning Analytics Code, confirms that its concerns and mitigations remain relevant, and adds additional safeguards and tools for the wellbeing context. These are derived from a detailed analysis of European and UK data protection law, extracting all rules and safeguards mentioned in relation to health data. We also develop context-specific tools for managing risk and evaluating data sources. Early feedback suggests that these documents will indeed increase confidence that this important area can be safely explored.

References

Abdi, S., Khosravi, H., Sadiq, S., & Gašević, D. (2020). Complementing educational recommender systems with open learner models. Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 23–27 March 2020, Frankfurt, Germany (pp. 360–365). ACM. https://doi.org/10.1145/3375462.3375520

Ahern, S. J. (2017, November 17). Learning analytics as a tool for supporting student wellbeing: Identifying student mental ill-health. University College of London. https://blogs.ucl.ac.uk/digital-education/2017/11/20/learning-analytics-as-a-tool-for-supporting-student-wellbeing-identifying-student-mental-ill-health/

Ahern, S. J. (2018). The potential and pitfalls of learning analytics as a tool for supporting student wellbeing. Journal of Learning and Teaching in Higher Education, 1(2), 165–172. https://journals.le.ac.uk/ojs1/index.php/jlthe/article/view/2812

Ahern, S. J. (2020). Making a #Stepchange? Investigating the alignment of learning analytics and student wellbeing in United Kingdom higher education institutions. Frontiers in Education 5:531424. https://doi.org/10.3389/feduc.2020.531424

AMOSSHE. (2015, May 29). Where’s the line? How far should universities go in providing duty of care for their students? https://www.amosshe.org.uk/futures-duty-of-care-2015

Article 29 Working Party. (2007). Working document on the processing of personal data relating to health in electronic health records (EHR) (Report no. WP131). https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2007/wp131_en.pdf

Article 29 Working Party. (2014). Opinion 06/2014 on the notion of legitimate interests of the data controller under Article 7 of Directive 95/46/EC (Report no. WP 217). https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2014/wp217_en.pdf

BBC. (2019, October 5). Stressed students “seeking help” amid fears for academic record. https://www.bbc.co.uk/news/uk-england-bristol-49852548

Binns, R. (2019, October 15). Enabling access, erasure, and rectification rights in AI systems. ICO AI blog. https://ico.org.uk/about-the-ico/news-and-events/ai-blog-enabling-access-erasure-and-rectification-rights-in-ai-systems/

CNIL. (n.d.). Privacy impact assessment (PIA). https://www.cnil.fr/en/privacy-impact-assessment-pia

Cormack, A. N. (2016). Downstream consent: A better legal framework for big data. Journal of Information Rights, Policy and Practice, 1(1). http://doi.org/10.21039/irpandp.v1i1.9

Cormack, A. N., & Reeve, D. (2020). Code of practice for wellbeing and mental health analytics. Jisc. https://www.jisc.ac.uk/guides/code-of-practice-for-wellbeing-and-mental-health-analytics

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. University of Melbourne. https://melbourne-cshe.unimelb.edu.au/research/research-projects/edutech/the-ethical-use-of-learning-analytics

D’Ignazio, C., & Klein, L. F. (2020). Data Feminism. MIT Press.

Education Policy Institute. (2018, September 10). Prevalence of mental health issues within the student aged population. https://epi.org.uk/publications-and-research/prevalence-of-mental-health-issues-within-the-student-aged-population/

Edwards, L., & Veale, M. (2017). Slave to the algorithm: Why a “right to an explanation” is probably not the remedy you are looking for. Duke Law & Technology Review, 16, 18–84. https://dltr.law.duke.edu/2017/12/04/slave-to-the-algorithm-why-a-right-to-an-explanation-is-probably-not-the-remedy-you-are-looking-for/

Ferguson, R. (2019). Ethical challenges for learning analytics. Journal of Learning Analytics, 6(3), 25–30. https://doi.org/10.18608/jla.2019.63.5

Ferguson, R., Clow, D., Griffiths, D., & Brasher, A. (2019). Moving forward with learning analytics: Expert views. Journal of Learning Analytics, 6(3), 43–59. https://doi.org/10.18608/jla.2019.63.8

Gil, N. (2015, December 14). Majority of students experience mental health issues, says NUS survey. The Guardian. https://www.theguardian.com/education/2015/dec/14/majority-of-students-experience-mental-health-issues-says-nus-survey

Griffiths, D., Drachsler, H., Kickmeier-Rust, M., Steiner, C., Hoel, T., & Greller, W. (2016). Is privacy a show-stopper for learning analytics? A review of current issues and solutions. Learning Analytics Review, 6. http://www.laceproject.eu/learning-analytics-review/is-privacy-a-show-stopper/

Hall, M. (2019). Student wellbeing and mental health: The opportunities in learning analytics. Jisc. http://repository.jisc.ac.uk/6916/1/student-wellbeing-and-mental-health-the-opportunities-in-learning-analytics.pdf

Hughes, G., & Spanner, L. (2019). The university mental health charter. StudentMinds. https://www.studentminds.org.uk/uploads/3/7/8/4/3784584/191208_umhc_artwork.pdf

Information Commissioner’s Office. (n.d.). How do we document our processing activities? Guide to the GDPR. https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/documentation/how-do-we-document-our-processing-activities/

Information Commissioner’s Office. (2019a, May 22). Data protection impact assessments. Guide to the General Data Protection Regulation (GDPR). https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/accountability-and-governance/data-protection-impact-assessments/

Information Commissioner’s Office. (2019b, May 22). How do we apply legitimate interests in practice? Guide to the General Data Protection Regulation (GDPR). https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/legitimate-interests/how-do-we-apply-legitimate-interests-in-practice/

Information Commissioner’s Office. (2019c, May 22). Public task. Guide to the Data Protection Regulation. https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/lawful-basis-for-processing/public-task/

Information Commissioner’s Office. (2019d, May 22). Special category data. Guide to the General Data Protection Regulation (GDPR). https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/lawful-basis-for-processing/special-category-data/

Information Commissioner’s Office. (2019e, May 22). What are the substantial public interest conditions? Guide to the General Data Protection Regulation (GDPR). https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/special-category-data/what-are-the-substantial-public-interest-conditions/

Information Commissioner’s Office. (2020, June). Regulatory sandbox final report: Jisc. https://ico.org.uk/media/for-organisations/documents/2618023/jisc-regulatory-sandbox-final-report.pdf

Inkster, B., & Digital Mental Health Data Insights Group. (2021). Early warning signs of a mental health tsunami: A coordinated response to gather initial data insights from multiple digital services providers. Frontiers in Digital Health (10 February 2021). https://doi.org/10.3389/fdgth.2020.578902

Jisc. (n.d.). Who we are and what we do. https://www.jisc.ac.uk/about/who-we-are-and-what-we-do

Jisc. (2019). Horizons report on emerging technologies and education. https://www.jisc.ac.uk/reports/horizons-report-emerging-technologies-and-the-mental-health-challenge

Jones, L. (2019). Using LA to inform student wellbeing and have better conversations with students. Paper presentation to the Jisc LA Cymru User Group, 3 April 2019.

Jutting, C. (2016, August 3). Universities are tracking their students. Is it clever or creepy? The Guardian. https://www.theguardian.com/higher-education-network/2016/aug/03/learning-analytics-universities-data-track-students

Kaliisa, R., Kluge, A., & Mørch, A. (2020). Combining checkpoint and process learning analytics to support learning design decisions in blended learning environments. Journal of Learning Analytics, 7(3), 33–47. https://doi.org/10.18608/jla.2020.73.4

Kitchener, S. (2016, January 12). OccupEye sensors: A sinister exercise in Big Brother-style management or a 21st-century way to monitor workers’ needs? Independent. https://www.independent.co.uk/news/media/occupeye-sensors-sinister-exercise-big-brother-style-management-or-21st-century-way-monitor-workers-needs-a6808281.html

Lang, C., Woo, C., & Sinclair, J. (2020). Quantifying data sensitivity: Precise demonstration of care when building predictive models. Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 23–27 March 2020, Frankfurt, Germany (pp. 655–664). ACM. https://doi.org/10.1145/3375462.3375506

Mack, D., DaSilva, A., Rogers, C., Hedlund, E., Murphy, E., Vojdanovski, V., Plomp, J., Wang, W., Nepal, S., Holtzheimer, P., Wagner, D., Jacobson, N., Meyer, M., Campbell, A., & Huckins, J. (2021). Mental health and behavior of college students during the COVID-19 pandemic: Longitudinal mobile smartphone and ecological momentary assessment study. Journal of Medical Internet Research, 23(6). https://doi.org/10.2196/28892

McKie, A. (2019, April 14). Could student mental health apps be doing more harm than good? Times Higher Education. https://www.timeshighereducation.com/news/could-student-mental-health-apps-be-doing-more-harm-good

Mulenda, H. (2020, September 4). Harnessing the power of technology can help vulnerable students. Times Higher Education. https://www.timeshighereducation.com/opinion/harnessing-power-technology-can-help-vulnerable-students

Neves, J., & Hillman, N. (2017). Student academic experience survey. Higher Education Authority/Higher Education Policy Institute. https://www.hepi.ac.uk/wp-content/uploads/2017/06/2017-Student-Academic-Experience-Survey-Final-Report.pdf

National Union of Students. (2015, August). Learning analytics: A guide for students’ unions. https://www.nusconnect.org.uk/resources/learning-analytics-a-guide-for-students-unions

Office for National Statistics. (2021, March). Coronavirus and higher education students: England, 19 February to 1 March 2021. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandwellbeing/bulletins/coronavirusandhighereducationstudents/19februaryto1march2021

Perkins, D., Gray, C., Ritsos, P., & Kuncheva, L. (2020). Jisc/Bangor University learning analytics project summary & case study. Jisc. http://research.academicanalytical.com/jspui/handle/1471/31

Prinsloo, P., & Slade, S. (2016). Student vulnerability, agency and learning analytics: An exploration. Journal of Learning Analytics, 3(1), 159–182. https://doi.org/10.18608/jla.2016.31.10

Sclater, N. (2016). Developing a code of practice for learning analytics. Journal of Learning Analytics, 3(1), 16–42. https://doi.org/10.18608/jla.2016.31.3

Sclater, N., & Bailey, P. (2018). Code of practice for learning analytics. Jisc. https://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics

Selwyn, N. (2019). What’s the problem with learning analytics? Journal of Learning Analytics, 6(3), 11–19. https://doi.org/10.18608/jla.2019.63.3

Sladdin, J. (2018, Oct 17). Duty to care for student mental health has legal implications for universities. Out-Law. https://www.pinsentmasons.com/out-law/analysis/duty-to-care-student-mental-health-legal-implications-universities

Slade, S., & Prinsloo, P. (2014). Student perspectives on the use of their data: Between intrusion, surveillance and care. Challenges for Research into Open & Distance Learning: Doing Things Better – Doing Better Things, 291–300. https://www.eden-online.org/proc-2485/index.php/PROC/article/view/1326

Slade S., Prinsloo, P., & Khalil, M. (2019). Learning analytics at the intersections of student trust, disclosure and benefit. Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 23–27 March 2020, Frankfurt, Germany (pp. 235–244). ACM. https://doi.org/10.1145/3303772.3303796

Thorley, C. (2017). Not by degrees: Improving student mental health in the UK’s universities. IPPR. https://www.ippr.org/research/publications/not-by-degrees

UCISA. (n.d.). Privacy impact assessment toolkit. https://www.ucisa.ac.uk/PIAToolkit

UHI. (2017). Mental health conditions toolkit. https://staffresources.uhi.ac.uk/mhc/

Universities UK. (2015). Student mental wellbeing in higher education: Good practice guide. https://www.m25lib.ac.uk/wp-content/uploads/2021/02/student-mental-wellbeing-in-he.pdf

Universities UK. (2020). Stepchange: Mentally healthy universities. https://www.universitiesuk.ac.uk/policy-and-analysis/reports/Documents/2020/uuk-stepchange-mhu.pdf

Universities UK. (2021). Minding our future: Starting a conversation about the support of student mental health. https://www.universitiesuk.ac.uk/what-we-do/policy-and-research/publications/minding-our-future-starting-conversation

University of Leeds. (2019, May 24). Code of practice on learning analytics. https://forstaff.leeds.ac.uk/info/30402/university_news/1882/code_of_practice_on_learning_analytics

University of South Wales. (n.d.). Progression advice team. https://progression.southwales.ac.uk/

Verbert, K., Ochoa, X., De Croon, R., Dourado, R., & De Laet, T. (2020). Learning analytics dashboards: The past, the present and the future. Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 23–27 March 2020, Frankfurt, Germany (pp. 35–40). ACM. https://doi.org/10.1145/3375462.3375504

Wachter, S., & Mittelstadt, B. (2019). A right to reasonable inferences: Re-thinking data protection law in the age of big data and AI. Columbia Business Law Review, 2019(2), 494–620. https://doi.org/10.7916/cblr.v2019i2.3424

Woodward, M. (2021). 16 countries with GDPR-like privacy laws. https://securityscorecard.com/blog/countries-with-gdpr-like-data-privacy-laws

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Published

2022-08-31

How to Cite

Cormack, A. N., & Reeve, D. (2022). Developing a Code of Practice for Using Data in Wellbeing Support. Journal of Learning Analytics, 9(2), 253-264. https://doi.org/10.18608/jla.2022.7533

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Section

Practical Reports