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Developments in Economics Education Conference

Developments in Economics Education Conference. MBA students and threshold concepts in Economics. Dr Keith Gray, Peri Yavash & Dr Mark Bailey* Coventry University & *University of Ulster. 1. Main Aims. Examine ‘economic awareness’ of MBA students Identify most problematic threshold concepts

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Developments in Economics Education Conference

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  1. Developments in Economics Education Conference MBA students and threshold concepts in Economics Dr Keith Gray, Peri Yavash & Dr Mark Bailey* Coventry University & *University of Ulster

  2. 1. Main Aims • Examine ‘economic awareness’ of MBA students • Identify most problematic threshold concepts • Design materials to enhance understanding and performance • Identify factors affecting student performance in general

  3. 2. Primary Research Tool Multiple–choice test devised which included the three categories of threshold concepts: • Discipline: economic systems, opportunity cost, gains from trade, the margin, welfare • Personal: profits, incentives, price/cost, economic definitions • Procedural: competition, externalities, elasticity, competition

  4. 2.1 Research Time Horizon(Cohort 1 Sept 2006 & Cohort 2 Feb 2007) Baseline Multi-choice test (week 1) End Multi-choice test (week 10)

  5. 2.2 Comparability of Cohorts Comparable re • Minimum qualifications • Minimum graduate experience • Minimum English scores • Tutor • Kolmogorov-Smirnov test

  6. 2.3 Data Collection • Cohort 1 - answered the same multiple choice questions at the beginning and end of their course • Most problematic threshold concepts identified • New teaching materials devised • Cohort 2 – answered the same multiple choice questions at the beginning and end of their course, but new teaching materials and learning environment included

  7. 2.4 Performance for different types of threshold concepts Table 2.1: Cohort 1 – Performance for Discipline Threshold Concepts ( % of students who achieved the correct answer).

  8. Table 2.2: Cohort 1 – Performance for Personal Threshold Concepts ( % of students who achieved the correct answer).

  9. Table 2.3: Cohort 1 – Performance for Procedural Threshold Concepts ( % of students who achieved the correct answer).

  10. 2.5 The most problematic threshold concepts? • Defined as all questions (concepts) which had negative value added Table 2.4: Problematic threshold concepts (negative value added)

  11. Additional problem questions? • Questions which less than 40% of students answered correctly Q9 Price/Cost Q14 competition (both already included) • Questions which only 40-50% of students answered correctly Q12 Elasticity (already included) • Questions which only 50-60% of students answered correctly Q10 Margin Q8 Externalities For all other questions, 60-94% of students obtained the correct answer.

  12. Most Problematic Threshold Concepts • Opportunity Cost • Price/Cost • Competition • Margin • Elasticity • Externalities

  13. 3. Pedagogical Developments in teaching materials for Cohort 2 • Bespoke mini–cases in seminars, e.g. Pricing and Costs in Airline Industry • Integration of seamless video clips in lectures, e.g. Work/Leisure Balance (opportunity cost and margin) • Integration of more Q & A sessions in lectures, covering all “problematic” threshold Concepts

  14. 4. Comparison of results for Cohort 1 and Cohort 2

  15. 4.1 Overall comparison of value added for Cohort 1 and Cohort 2 Graph 4.1: Comparison of Value Added for cohorts 1 and 2

  16. 4.2 Comparison of results for problematic threshold concepts Table 4.2: Comparison of value added for Cohort 1 and Cohort 2

  17. 5. Performance Indicators and Models 5.

  18. Table 5.1: Cohort 1 & Cohort2: Pearson Correlations Note: ** or** = Highly significant at 99% confidence level • Commentary: Baseline Correlations • Relatively strong (+) correlation between Base & End mc for Cohort 1 • Highly sig. relationship Base & End mc for Cohort 1 only • b) Strong (+) correlation & highly sig. relationship re Base & Formative test • for both cohorts • c) No clear pattern re other assessments or statistically sig. relationships

  19. Table 5.2: Cohort 1 & 2: Pearson Correlations: Note: ** = Highly significant at 99% confidence level * or * = Significant at 95% confidence level

  20. Other Comments on Table 5.2: • Sig. relationship between Baseline & End mc for Personal categories only for Cohort 2 • Notable that strength of correlation & sig. lower across the board for Cohort 2 • Why? ....... performance models

  21. Performance Model • Present a Tobit regression model • Module mark as dependent variable • General to specific approach • Following table records a range of included variables/ results

  22. Coefficient t - value Table 5.3: Tobit Model

  23. Tobit Model Commentary: Highlights • Ceteris paribus, females score 3.24% higher than males • Having a science degree raises scores by 11.8% • Having an economics degree raises scores by 9% • Notably, studying in Semester 1 lowers scores by 2% • No threshold concept related variables significantly affected performance • Large constant may hide the effect of the teaching strategies used

  24. 6. Conclusions • Revised pedagogy focusing on the most problematic threshold concepts appears, ceteris paribus, to have had a positive impact on the understanding of these threshold concepts (re multi-choice test performance) • This finding may reflect the nature of Coventry University MBA students, limiting its general applicability

  25. The weakness of threshold concept related variables in explaining overall performance may reflect the characteristics of the chosen dependent variable (module mark) • Available data will allow regression of threshold concept related variables and other independent variables against other dependent variables, e.g. summative components

  26. Short Bibliography • Davies, P. & Mangan, J. (2005) Embedding Threshold Concepts: from theory to pedagogical principles to learning activities, Working Paper 3, Embedding Threshold Concepts http://www.staffs.ac.uk/schools/business/iepr/info/Economics(2).html • Maddala, G.(1992), Limited Dependent & Qualitative Variables in Econometrics, Cambridge UniversityPress

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