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
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
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
18
84
80
-4.8
Margin
15
54
82
51.9
Opportunity
Cost
Opportunity
Cost
10
11
52
76
58
88
11.5 15.8
Opportunity Cost
5
74
80
8.1
Welfare
3
72
60
-16.7
Gains from trade
1
92
94
2.2
Margin
Gains from trade
Question
Beginning
End
% change
(value
added)
Opportunity Cost
Discipline
Threshold
Concepts
Economic systems
2.4 Performance for different types of
threshold concepts
19
90
86
-4.4
20
74
76
2.7
Ave
74
78
2.7
Table 2.1: Cohort 1 – Performance for Discipline Threshold Concepts ( % of
students who achieved the correct answer).
Incentives
Price/Cost
Economic
Definitions
2
4
6
9
13
16
Ave %
86
78
84
82
66
44
73
70
90
90
30
92
82
75
-18.6
15.4
7.1
-63.4
39.4
86.8
5.4
Price/Cost
Profit
Question
Number
Beginning
of course
End of
course
% change
(value
added)
Price/Cost
Personal
Threshold
Concepts
Table 2.2: Cohort 1 – Performance for Personal Threshold Concepts ( % of
students who achieved the correct answer).
Procedural
Threshold
Concepts
Competition
Externalities
Elasticity
Competition
Competition
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
Table 2.3: Cohort 1 – Performance for Procedural Threshold Concepts ( % of
students who achieved the correct answer).
2.5 The most problematic threshold
concepts?
Competition
19
-4.44
Elasticity
18
-4.8
Price/Cost
3
-16.7
Price/Cost
Opportunity Cost
Question
% change
(value
added)
Opportunity Cost
Problem
Threshold
Concepts
Opportunity Cost
• Defined as all questions (concepts) which had
negative value added
2
-18.6
9
-63.4
12
-39.5
14
-75
Table 2.4: Problematic threshold concepts (negative value added)
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.
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
12
10
8
Cohort 1
Cohort 2
6
4
2
0
Discipline
Procedural
Personal
Graph 4.1: Comparison of Value Added for cohorts 1 and 2
Externalities
Competition
3
18
19
2
9
12
14
10
8
-16.7
-4.8
-4.44
-18.6
-63.4
-39.5
-75
11.5%
3.6%
Cohort 2
6.7%
3.6%
19.2% 10.7%
20%
10.7% 5.26% 5.26%
25%
Margin
Price/Cost
Question
Number
% change
(value
added)
Cohort 1
Elasticity
Price/Cost
Opportunity
Cost
Opportunity
Cost
Threshold
Concepts
Opportunity
Cost
4.2 Comparison of results for
problematic threshold concepts
Table 4.2: Comparison of value added for Cohort 1 and Cohort 2
5. Performance Indicators and
Models
Table 5.1: Cohort 1 & Cohort 2: Pearson Correlations
Baseline
Multi –choice
(mc)
(week 1)
End Multi – Formative
choice
Test
(week 10)
(week 5)
Phase
Test
(week 8)
Essay
Cohort 1
Cohort 2
.589**
.275
.460**
.526**
.229
.177
.022
.141
.170
.179
45
34
57
35
57
35
57
35
Cohort 1
Cohort 2
N= 50
N= 38
Mod
Mark
(week 10)
Note: ** or ** = Highly significant at 99% confidence level
Commentary: Baseline Correlations
a) 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
Table 5.2: Cohort 1 & 2: Pearson Correlations:
N=50
N=38
Personal
End
Personal
Baseline
.506**
.324*
Discipline
Baseline
Procedural
Baseline
Discipline
End
Procedural
End
.470**
.160
.312*
.198
Note: ** = 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
Coefficient
t - value
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
Nos. observations
Chi – squared
84
33.16
Pseudo – 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/Econo
mics(2).html
• Maddala, G.(1992), Limited Dependent & Qualitative
Variables in Econometrics, Cambridge University Press