Learner- centred LA: the case for single case analysis.

1. Learner-centred LA: the case for single case analysis. Workshop “Learning-centred analytics: mission possible” Ascilite 2019 Peter Reimann, Sydney University

2. Setting the scene • Running example: An intervention for developing Self-Regulated Learning capacities in Year 1 students. • Integrated into all Year 1 courses, delivered as a workshop at Week 5. • Focus on “planning your learning”. • How would we evaluate if the intervention was “effective”? What would we do with students for whom it was not? • Three approaches: • Correlational • (Quasi-)Experimental (when control group available) • Single-case/within subject

3. Structure • The frequentist approach and its problems • The case method • Single-case experimental designs Main claim: Small is beautiful: single-case methodology is a promising approach to “learning-centered” and “learner-centered” LA

4. Frequentist-Correlational approach Status Process

5. Key characteristics of correlational methods • they focus on the value distributions of variables rather than on cases as combinations of values; • they focus on patterns of relationships between value distributions that are covariational, linear and, for the most part, additive; • they are, contrary to common assumptions, not good at detecting, elaborating or demonstrating asymmetrical or causal relationships; • they are limited in their ability to handle causal complexity in complex systems.

6. Focus on value distributions Case Variable 5 4 3 2 1 … 1 2 3 4 5 10 15 Login Frequency

7. Case methods • Two main types: • Case study as a form or qualitative research • Single-case experimental designs as part of quantitative research Case

8. Two kinds of experimental designs Population Control Control Randomised Sampling ? Experimental Experimental Intervention ? Post intervention baseline Intervention

9. Reversal designs

10. Alternate treatment designs

11. Multiple Baseline Designs

12. SCD is learner- and learning-centred • Intervention-oriented • Teachers and/or students should have expectations what will change and how strongly so. • Learning trajectories • Teachers and/or students should expectations when change/learning will ensue • Inter-individual differences are the norm • Not everybody will react to the same extent/in the same way to an intervention, no matter what.

13. Contribution to theories of learning • Aggregate across cases and analyse quantitatively • Frequentist-correlational • Temporal patterns • Analyse single cases • Qualitatively • Quantitatively • Computational Modeling • Comparative case analysis • Quantitative • Qualitative

14. Summary • The case method gives agency to people, not to variables. • Thinking in terms of reactions to pedagogical-technical interventions aligns learning data with pedagogy. • Inter-individual variation is to be expected and is a key pedagogical concern. • Well-aligned with the ‘scientific method’. • Open to quantitative and qualitative data and analysis.