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

• Design materials to enhance understanding and performance

• Identify factors affecting student performance in general

• Discipline: economic systems, opportunity cost, gains from trade, the margin, welfare

• Personal: profits, incentives, price/cost, economic definitions

• Procedural: competition, externalities, elasticity, competition

2. Primary Research Tool

Multiple–choice test devised which included the three categories of threshold concepts:

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)

2.2 Comparability of Cohorts

Comparable re

– Minimum qualifications– Minimum graduate experience– Minimum English scores– Tutor– Kolmogorov-Smirnov test

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

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).

Discipline Threshold Concepts

Question 1 3 5 10 11 15 18 19 20 Ave Beginning 92 72 74 52 76 54 84 90 74 74

End 94 60 80 58 88 82 80 86 76 78 % change

(value added)

2.2 -16.7 8.1 11.5 15.8 51.9 -4.8 -4.4 2.7 2.7

Opp

ortu

nity

Cos

t

Eco

nom

ic s

yste

ms

Mar

gin

Mar

gin O

ppor

tuni

ty C

ost

Gai

ns f

rom

trad

e

Gai

ns f

rom

trad

e

Wel

fare

Opp

ortu

nity

Cos

t

Opp

ortu

nity

Cos

t

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

Personal

Threshold Concepts

Question Number

2 4 6 9 13 16 Ave %

Beginning of course

86 78 84 82 66 44 73

End of course

70 90 90 30 92 82 75

% change (value added)

-18.6 15.4 7.1 -63.4 39.4 86.8 5.4

Pro

fit

Ince

ntiv

es

Eco

nom

ic

Def

init

ions

Pri

ce/C

ost

Pri

ce/C

ost

Pri

ce/C

ost

Procedural Threshold Concepts

Question

7 8 12 14 17 Ave %

Beginning

16 56 76 80 50 56

End

80 58 46 20 78 57

% change (value added)

400 3.6 -39.5 -75 56 1.8

Ext

erna

litie

s

Ela

stic

ity

Com

peti

tion

Com

peti

tion

Com

peti

tion

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

2.5 The most problematic threshold concepts?

• Defined as all questions (concepts) which had negative value added

Problem

Threshold Concepts

Question 3 18 19 2 9 12 14 % change

(value added)

-16.7 -4.8 -4.44 -18.6 -63.4 -39.5 -75

Opp

ortu

nity

Cos

t

Opp

ortu

nity

Cos

t

Pric

e/C

ost

Com

petit

ion

Opp

ortu

nity

Cos

t

Pric

e/C

ost

Ela

stic

ity

Table 2.4: Problematic threshold concepts (negative value added)

Additional problem questions?

• Questions which less than 40% of students answered correctlyQ9 Price/Cost

Q14 competition (both already included)

• Questions which only 40-50% of students answered correctlyQ12 Elasticity (already included)

• Questions which only 50-60% of students answered correctlyQ10 Margin Q8 Externalities

For all other questions, 60-94% of students obtained the correct answer.

Most Problematic Threshold Concepts

• Opportunity Cost

• Price/Cost

• Competition

• Margin

• Elasticity

• Externalities

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

4. Comparison of results for Cohort 1 and Cohort 2

4.1 Overall comparison of value added for Cohort 1 and Cohort 2

0

2

4

6

8

10

12

Discipline Procedural Personal

Cohort 1

Cohort 2

Graph 4.1: Comparison of Value Added for cohorts 1 and 2

4.2 Comparison of results for problematic threshold concepts

Threshold Concepts

Question Number

3 18 19 2 9 12 14 10 8

% change (value added)

Cohort 1

-16.7

-4.8

-4.44

-18.6

-63.4

-39.5

-75

11.5%

3.6%

Cohort 2

6.7% 3.6% 10.7% 5.26% 5.26% 25% 19.2% 10.7% 20%

Opp

ortu

nity

C

ost

Opp

ortu

nity

C

ost

Pri

ce/C

ost

Com

peti

tion

Opp

ortu

nity

C

ost

Pri

ce/C

ost

Ela

stic

ity

Mar

gin

Ext

erna

liti

es

Table 4.2: Comparison of value added for Cohort 1 and Cohort 2

5. Performance Indicators and Models

5.

Baseline

Multi –choice (mc)

(week 1)

End Multi –choice

(week 10)

Formative Test

(week 5)

Phase

Test

(week 8)

Essay

(week 10)

Mod

Mark

Cohort 1

Cohort 2

.589**

.275

.460**

.526**

.229

.177

.022

.141

.170

.179

Cohort 1

Cohort 2

N=

N=

50

38

45

34

57

35

57

35

57

35

Table 5.1: Cohort 1 & Cohort 2: Pearson Correlations

Commentary: Baseline Correlations

a) Relatively strong (+) correlation between Base & End mc for Cohort 1Highly 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

Note: ** or ** = Highly significant at 99% confidence level

Table 5.2: Cohort 1 & 2: Pearson Correlations:

N=50

N=38Personal End

Discipline End

Procedural End

Personal Baseline

.506**

.324*

Discipline Baseline

.470**

.160

Procedural Baseline

.312*

.198Note: ** = Highly significant at 99% confidence level * or * = Significant at 95% confidence level

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

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

Gender 3.246 1.68

Econ education 9.005 3.18

Business Education 7.795 3.08

Science Education 11.829 4.23

Higher degree 4.776 2.11

Semester 1 - 1.999 -1.37

S. E. Asia - 5.694 -2.74

Baseline Personal -.001 -.02

Baseline Procedural . 061 1.65

Baseline Discipline .037 .91

Constant 43.039 9.45

Coefficient t - value

Nos. observations 84Chi – squared 33.16Pseudo – R2 0.3114

Table 5.3: Tobit Model

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

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

• 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

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 University Press