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Smarter Learning: Enhancing Student Engagement and Outcomes

Explore planning considerations and case studies to improve engagement and outcomes in higher education. Dive into assessment models and factors shaping quality and productivity. Empower institutions to evaluate, act, and adapt for better results.

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Smarter Learning: Enhancing Student Engagement and Outcomes

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  1. Smarter Learning: Improving student engagement and outcomesProfessor Hamish Coates • hamishc@unimelb.edu.au

  2. Growing momentum Planning considerations Case study large-scale surveys Generalisable assessment model

  3. What is the best university in the the country?  How do you know?

  4. Plan • Improve • Act • Evaluate • Hunch

  5. 95% 75%

  6. Shaping rationales Cost and pricing pressures Ensuring quality outcomes New generation faculty Need for multidimensional perspectives Nuanced quality parameters New robotic teaching Blended forms of learning Simplistic rankings constraining growth Learner expectations and segments Rapid increases in scale Big data analytic opportunities Institutional competitive positioning Hybrid business models and providers Diversification and stratification Faster, better, cheaper management Institutional competitive positioning Pervasive internationalisation

  7. Little data • Happiness data • Effectiveness data • Elite • Mass • Universal

  8. Institution inputs • Teaching inputs and processes • Student processes and outcomes

  9. Growing momentum Planning considerations Case study large-scale surveys Generalisable assessment model

  10. Quality and productivity frontiers As getting-in gets easier, getting-out gets harder (or it should)  Engineering an engaged experience  Assessing learning outcomes

  11. Growing momentum Planning considerations Case study large-scale surveys Generalisable assessment model

  12. Assessment collaborations • Stage 1: Establish assessment partnerships • Stage 2: Define and produce assessment specifications and tasks • Stage 3: Develop shared processes • Stage 4: Reporting and benchmarking

  13. Using this model to improve assessment? Best single change to make? What’s required to make change work? • Stage 1: What sort of partnerships can you establish, and with who? • Stage 2: What work is required to define learning outcomes, and collaborate on the production of assessment tasks? • Stage 3: How might any assessment processes be shared? • Stage 4: What improvements could be made to reporting? What benchmarking options are available?

  14. Review and improve • Accountants? • IT? • Historians? Benchmark and interpret • Psychologists? Administer items Analyse and report • Doctors Capture/produce items • Economists • Civil/mechanical engineers Build frameworks • “Generic skills” Share definitions • Engagement • Biomedical scientists Find colleagues Don’t wait

  15. Growing momentum Planning considerations Case study large-scale surveys Generalisable assessment model

  16. Who owns data? International? Transparent? Relevance? Verifiability? Population? Validity? Reliability? Meaningful reports? Quality assured? Consequences? Implementation?

  17. (Technical and operational matters) Governance, funding and ownership Leadership, management and advisory architectures Building institutional and professional capacity Competitive relativities for institutions and ‘research’ System, institution, faculty, student and stakeholder engagement Varying participation rationales and expectations Imposed, collaborative or bottom-up model/ethos Generalisability and contextuality Monitoring, improvement or enhancement rationales

  18. Smarter Learning: Improving student engagement and outcomesProfessor Hamish Coates • hamishc@unimelb.edu.au

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