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Do cross-sectional student assessment data make a reasonable proxy for longitudinal data?

Do cross-sectional student assessment data make a reasonable proxy for longitudinal data?. Elena Zaitseva and Mantz Yorke Liverpool John Moores University HEIR Conference, University of Liverpool. 2nd year underperformance

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Do cross-sectional student assessment data make a reasonable proxy for longitudinal data?

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  1. Do cross-sectional student assessment data make a reasonable proxy for longitudinal data? Elena Zaitseva and Mantz Yorke Liverpool John Moores University HEIR Conference, University of Liverpool

  2. 2nd year underperformance 2nd year students are characterised as a cohort where ‘many suffer from reduced motivation or apathy, declining grade point averages, or a letdown from their first year’ (Pattengale & Schreiner, 2000) Underperformance of 2nd year students is well researched by North American scholars; the topic receives less attention in the UK and Europe ‘The Forgotten Year: Tackling the ‘Sophomore Slump’ is a HEA funded institutional research project http://secondyearexperience.ljmu.ac.uk/

  3. Project: • Examines patterns in student performance across the levels of study and longitudinal dynamics of slump (quantitative research) • Investigates underlying factors behind the 2nd year students’ underperformance and diminished engagement (qualitative research ) • Develops and evaluates interventions to enhance experience of the 2nd year cohort

  4. Slump is a dynamic phenomenon • Longitudinal performance of programmes with 20+ students

  5. Instead of waiting for a programme’s longitudinal data, can we use cross-sectional student performance data to predict slump?

  6. The data used Data from 08-09 and 09-10 Data from 09-10 and 10-11 Number of valid records (56 programmes, N=20+ students) 08-09 Level 1 3006 08-09 Level 2 2519 09-10 Level 1 2975 Number of valid records (49 programmes, N=20+ students) 09-10 Level 1 2807 09-10 Level 2 2385 10-11 Level 1 2984 Valid records: Students who were awarded marks in respect of 120 credits at the Level stated Exception to the above: Social Work where 36 credits are awarded on pass/fail basis, i.e. 84 credits with marks

  7. The analytical frame AY2008-09 AY2009-10 AY2010-11 Starters AY2008-09 Year 1 Year 2 True cohort Longit B X-sect A Starters AY2009-10 Year 1 Year 2 True cohort Longit C X-sect Starters AY2010-11 Year 1 Quasi- cohort Quasi- cohort

  8. Calculating the match – Analysis A

  9. The outcomes AY2008-09 AY2009-10 AY2010-11 Starters AY2008-09 Year 1 Year 2 Longit 69.4% match 69.6% match X-sect Starters AY2009-10 Year 1 Year 2 Longit 69.4% match X-sect Starters AY2010-11 Year 1

  10. A complexity AY2008-09 AY2009-10 AY2010-11 Starters AY2008-09 Year 1 Year 2 Longit X-sect + 1.49% + 1.40% + 1.53% Starters AY2009-10 Year 1 Year 2 Longit X-sect Starters AY2010-11 Year 1

  11. Revised outcomes Acad Year 2008-09 Acad Year 2009-10 Acad Year 2010-11 Starters AY2008-09 Year 1 Year 2 Longit 67.3% match 73.2% match X-sect Starters AY2009-10 Year 1 Year 2 Longit 81.6% match X-sect Starters AY2010-11 Year 1

  12. A paradox (not the only one) Year 1 mean Mark Year 2 mean Longitudinal rise Year 1 mean Cross-sectional slump Year 2 mean Academic Year 2008-09 Academic Year 2009-10

  13. The question of homogeneity What proportion of students enrolled on the programme are ‘captured’ by the most popular 120 credits?

  14. A worked example

  15. Selected results from homogeneity analysis

  16. Selected results from homogeneity analysis

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