Learning gain metrics and personal tutoring: Opportunities and ethics

1. Learning gain metrics and personal tutoring: Opportunities and ethics Dr Camille B. Kandiko Howson Academic Head of Student Engagement @cbkandiko King’s College London camille.Kandiko_howson@kcl.ac.uk

2. Overview • Learning gain metrics • Uses of learning gain • Enhancement and Ethics

3. Learning Gain Pilot Projects HEFCE/OfS funded 13 mixed method projects involving 70 institutions over three years, using: • Learner analytics/Grades • Self-reported surveys • Standardised tests • Multiple measures of a specific theme • National Mixed Methodology Learning Gain Project (NMMLGP) • Higher Education Learning Gain Analysis (HELGA)

4. Affective measures • Transition experience • Self efficacy • Well-being • Disposition to learning • Confidence • Resilience • Satisfaction

5. Behavioural measures • Student engagement • Placements/ work-based learning • Employability experiences • Co-curricular activities • Skills self-assessment • VLE engagement • Learner analytics

6. Cognitive measures • General cognitive gain • Disciplinary cognitive gain • Critical Reasoning Skills • Situational judgement • Research methods

7. Outcome measures • What have your students gained? • Grades, progression • Employability skills (Affective, Behavioural, Cognitive) • Other outcome measures • Back to purposes… • Is it critical thinking, generic graduate skills, disciplinary mastery, developing employability or something more holistic?

8. Learning Gain Findings • What is measured depends on view of purpose of higher education • Learning gain encompasses affective, behavioural and cognitive aspects • Balance between methodological precision and practical collection and application of data • Students need support, advice and guidance to make sense of the data • Engagement depends on use of data

9. Uses of learning gain data

13. Learning gain and enhancement and ethics >

14. Learning gain and enhancement • Support student learning • Personalised dashboards • Instruments that are reflective pedagogical tools • Evaluate classroom intervention • Innovative pedagogies • Embedding research into teaching • Enhance course experience • From ‘module-mania’ to larger curriculum focus • Target institutional initiatives • Attainment gaps • Careers services interventions

15. Enhancement and tutoring • Students need support, advice and guidance to make sense of and use data for their learning • Tutors best placed for interventions focused on specific groups of students (e.g. data used to tackle attainment gaps) • Opportunities for “evidence-based” individual and group tutoring sessions • Tutors can feedback on student engagement

16. Triangle of Doom • Data protection • Data sharing • Ethics Concerns at Student, Inter-institutional, Intra-institutional, and Governmental/ Corporate levels

17. Student engagement (-) • Challenges of getting students to complete tests, surveys, etc • Students making sense of and acting on data • ‘Pact of disengagement’ • What students ‘want’ versus ‘what is good for them’

18. Student engagement (+) • Opportunities for students to be part of: • Evaluation planning • Data gathering • Data analysis • Data sharing • Actioning data • Enhancement • Feedback and follow-up

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20. Raising Awareness,Raising Aspiration