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Beyond the Dashboard: a practical workshop for ethical, human-centred data-informed advising

Helen McCormick (Manchester Metropolitan University)
siobhan Barry (Manchester Metropolitan University)

Monday, April 13, 2026 2:30 PM - 3:15 PM

STUDENT SUCCESS AND GRADUATE OUTCOMES

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Session Outline

Institutions increasingly ask tutors and advisors to act on dashboards to record attendance, engagement patterns and assessment signals, yet many staff experience a tension: metrics can flatten context, amplify bias, and unintentionally encourage deficit narratives. This interactive workshop equips delegates with a practical method to use data without losing the human.

Participants will learn a repeatable Advising Sensemaking Canvas that reframes analytics as conversation prompts rather than labels. Working through realistic anonymised scenarios, delegates will practise:

• identifying what a metric can and cannot legitimately claim

• generating multiple context hypotheses (academic, structural, personal) without pathologizing students

• selecting an appropriate advising stance (coaching / directive guidance / referral) within professional boundaries;

• designing one next-step action that strengthens agency and belonging.

The workshop includes a short ethics-and-equity checkpoint so that “helpful” interventions do not drift into surveillance, over-reach, or inequitable assumptions.

Outputs are intentionally practical: delegates leave with a one-page canvas, a set of “safe” coaching prompts that work across disciplines and cultures, and a micro-evaluation template that captures outcomes dashboards miss, for example felt trust, confidence to act, and clarity of next steps. The approach is designed for adaptation to different institutional contexts and supports advising in a time of change by raising data literacy and ethical confidence among tutors and advisors.

Learning Outcomes

1. Evaluate advising metrics to identify valid claims and avoid deficit narratives or bias.
2. Use the advising sensemaking canvas to reframe analytics through a student-centered, nuanced lens.

Bibliography

Festinger, L. (1954) ‘A theory of social comparison processes’, Human Relations, 7(2), pp. 117–140.
Zimmerman, B.J. (2002) ‘Becoming a self-regulated learner: An overview’, Theory Into Practice, 41(2), pp. 64–70.
Bandura, A. (1997) Self-efficacy: The exercise of control. New York: Freeman.
Heckman, J.J. and Kautz, T. (2012) ‘Hard evidence on soft skills’, Labour Economics, 19(4), pp. 451–464.
Kautz, T. et al. (2014) Fostering and measuring skills: improving cognitive and non-cognitive skills. OECD.
Sailer, M. and Homner, L. (2020) ‘The gamification of learning: A meta-analysis’, Educational Psychology Review, 32, pp. 77–112.
Jisc (2015) Code of practice for learning analytics.
Jisc (2020) Code of practice for wellbeing and mental health analytics.
Walton, G.M. and Cohen, G.L. (2011) ‘A brief social-belonging intervention…’, Science, 331, pp. 1447–1451.
Yeager, D.S. et al. (2020) ‘What can be learned from growth mindset controversies?’, American Psychologist.

Competencies
This session addresses the following competencies of the UKAT Professional Framework for Advising and Tutoring
C3 - Academic advising and tutoring approaches and strategies
R2 - Communicate in an inclusive and respectful manner
I7 - Data and information technology applicable to tutoring