Evaluating the performance of university course units using data envelopment analysis

Figures & data

Table 1. The Main PIs Used in the Six-Mentioned Studies

Study	Applied on	Inputs based on	Outputs based on
Beasley (1995)	Departments in different universities	Academic personnel budget, other expenses budget, research income	No of undergraduates, no. of taught postgraduates, no. of research postgraduates, research income, department rating
Hanke and Leopoldseder (1998)	Different universities	No. of students, academic personnel budget, other expenses budget	No of graduates, no. of courses held, no. of publications
Johnes (2006a)	Different universities (economics only)	Mean of score in A-level exams, gender, type of secondary school attended	Standings of graduates
Bobe (2009)	Faculties within single university	Academic personnel expenses, other expenses	Total teaching load, no. of publications, research grants
Tzeremes and Halkos (2010)	Departments within single university	No. of academic personnel, no. of students (incl. post-graduates), total budget funds	No. of graduates (post-graduates weighed more), no. of publications^a
Alwadood et al. (2011)	Departments within single university	Department utilisation^b, no. of courses offered	Quality of graduates^c, quality of research^d, quality of staff service^e

^a Papers in foreign journals were given more weight than conference and discussion papers.

^b Department utilisation includes faculty to student ratio, mean student credit hours and the number of graduate students.

^c The quality of graduates takes into account the percentage of employers surveyed who are satisfied with the work of the graduate, the percentage of graduates surveyed who are themselves satisfied with their current position along with the GPA of graduate students.

^d The quality of research includes the number of publications and conference papers, the number of research grants and the number of supervised graduate students.

^e The quality of staff takes into account the number of short courses organised for staff, the number of consultancy jobs and the percentage of staff who are taking part in industrial consultancy.

Table 2. The Mappings of the Six-scale Grading to Their Letter Equivalents

	5	4	3	2	1	0
Letter grade equivalent	A excellent (91–100%)	A− very good (81–90%)	B good (71–80%)	C satisfactory (61–70%)	D adequate (60–52%)	F failure (below 52%)

Table 3. An Example in Calculating the Performance of Some Imaginary Course Units

Student id	Course C1 grade	Course C2 grade	Course C3 grade	Student’s WGPA	PCOURSE for course C1	PCOURSE for course C2	PCOURSE for course C3
901	3	2	1	2.3	0.7 + 5 = 5.7	−0.3 + 5 = 4.7	−1.3 + 5 = 3.7
952	5	3	2	3.3	1.7 + 5 = 6.7	−0.3 + 5 = 4.7	−1.3 + 5 = 3.7
973	5	4	5	4.1	0.9 + 5 = 5.9	−0.1 + 5 = 4.9	0.9 + 5 = 5.9
Mean	4.3	3.3	2.7	3.7	6.1	4.7	3.7

Table 4. The Two Inputs and the Output for the Efficiency Study

Factor	Type
WPCOURSE*	Output	Level of easiness for course unit (10 = easiest)
PCMATHS	Input	Percentage completing math pre-requisites before taking unit
PTGRADE3	Input	Percentage who obtained grade ‘3’ or better in pre-requisites

Table 5. Descriptive Statistics for the 343 Students Who Took the Modules

Student count (all students: mean GPA, its standard deviation and coefficient of variation)	Female student count (female students only: mean GPA, its standard deviation and coefficient of variation)	Male student count (male students only: mean GPA, its standard deviation and coefficient of variation)
n =343 (mean = 2.89, std. dev. = 0.63, cv = 22%)	108 (mean = 3.05, std. dev. = 0.60, cv = 20%)	235 (mean = 2.81, std. dev. = 0.63, cv = 22%)

Table 6. The Data along with the Obtained Efficiency

Unit	PCMATHS (%)	PTGRADE3 (%)	WPCOURSE*	Teaching efficacy (efficiency, %)
GED-101A	56.6	63.2	4.98	60.8
GED-101B	69.3	77.8	4.46	44.4
GED-101AB	64.3	72.3	4.70	50.4
GED-102	53.3	63.0	5.21	66.8
GED-103	64.9	63.5	4.90	53.3
GED-204	53.1	58.6	3.41	44.4
GED-205	53.3	58.6	4.97	64.5
GED-206	46.0	60.6	4.26	62.1
GED-310	42.1	78.6	6.81	100
GED-310*	48.5	82.1	6.18	80.7
GED-311	38.5	23.1	5.12	100
GED-318	34.8	60.0	5.0	90.7
Mean	52.1	63.4	5.0	68.2

Table 7. Two Different Sets of Target Values that Both Render Inefficient Unit GED-205 as Relatively Efficient

HCE unit	Target for PCMATHS (%)	Target for PTGRADE3 (%)	Target for WPCOURSE*	Coordinates of HCE unit for GED-205	Relative efficiency (teaching efficacy, %)
GED-205′	54.6	60	7.89	(7.61, 6.92)	100
GED-205′	53.3	58.6	7.7	(7.61, 6.92)	100

Table 8. The Number of Credits Awarded, the Number of Participants, and the Required Pre-requisites for Each Unit

Unit ID	Credits awarded	Number of students enrolled in unit	Module pre-requisites {(Maths); (GED)}
GED-101A	4	122	{(MATH-1110); None}
GED-101B	4	189	{(MATH-1110); None}
GED-101AB	4	311	{(MATH-1110); None}
GED-102	3	122	{(MATH-1110); None}
GED-103	3	77	{(MATH-1110); None}
GED-204	3	32	{(MATH-1110), (MATH-1131); GED-102}
GED-205	3	30	{(MATH-1110), (MATH-1131); GED-103}
GED-206	4	37	{(MATH-1110), (MATH-1131), (MATH-1262); GED-101}
GED-310	6	19	{(MATH-1110), (MATH-1131), (MATH-1262); GED-205}
GED-310*	6	33	{(MATH-1110), (MATH-1131), (MATH-1262); GED-205}
GED-311	6	13	{(MATH-1110), (MATH-1131), (MATH-1262), (MATH-2104); GED-204}
GED-318	2	23	{(MATH-1110), (MATH-1131), (MATH-2104); GED-203}

Figure 1. Visualisation the performance of the twelve units.

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Tzeremes, N., & Halkos, G. (2010). A DEA approach for measuring university departments’ efficiency. MPRA Paper 24029. University Library of Munich, Germany.

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Alwadood, Z., Noor, N. M., & Kamarudin, M. F. (2011, September 25–28). Performance measure of academic departments using data envelopment analysis. Paper presented at the 2011 IEEE Symposium on Business Engineering and Industrial Applications, Langkawi, Malaysia.

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