Academic Disciplines and Level of
Academic Challenge
Gary R. Pike
University of Missouri–Columbia
1
The Opportunity
• The MU benchmark score for Level of
Academic Challenge was significantly
lower than the benchmark score for our peer
institutions (AAU Public Research
Universities).
• This was particularly true for our seniors.
2
Step 1: Item Analysis
• Items with substantial differences:
– Spending significant amounts of time studying (0.10)
– Number of written papers of 20 pages or more (0.19)
– Coursework emphasis: Analysis (0.08)
– Coursework emphasis: Synthesis (0.12)
– Coursework emphasis: Evaluation (0.17)
3
Step 2: Identifying Disciplinary
Differences
• Rationale
– There is a large body of literature indicating
that different types of academic challenges are
posed by different academic disciplines.
– By identifying disciplinary differences it may
be possible to target specific improvement
actions.
4
The Approach
• Ratcliff, Jones, and their colleagues
developed a method of linking specific
patterns of course taking with gains in
general education.
• It should be possible to use a variation of
this approach to identify disciplinary
differences in Level of Academic Challenge
items.
5
The Method
• Calculate mean scores on each item for each
discipline using AAU data and self-reported
major.
– Majors are variables
– Items are observations
• Cluster together majors with similar response
profiles.
• Use discriminant analysis to identify how the
clusters differ.
6
The Method (Continued)
• Calculate parallel cluster means for each
item using only the MU data.
• Compare AAU and MU means
– Are the response profiles similar?
– Are there substantive differences in means
between the AAU and MU clusters?
7
Results: Cluster Analysis
• Cluster 1: Science, Math, Engineering
– Biological Sciences, Computer & Information Sciences,
Engineering, Health-Related Fields, Mathematics,
Physical Sciences, & Visual Arts.
• Cluster 2: ?
– Agriculture, Business, Communication, General
Studies, Public Administration, & Social Sciences.
• Cluster 3: ?
– Education, Foreign Languages, Humanities,
Interdisciplinary, & Parks and Recreation.
8
Results:
Discriminant Analysis
• Function 1 (Cluster 1):
– High on studying, class preparation, and
application.
– Low on number of texts, writing, and
evaluation.
• Function 2 (Cluster 3 vs. Cluster 2):
– (3) High on class preparation and synthesis.
– (3) Low on analysis and application.
9
Results for MU Seniors
• Cluster 1 (MU lower):
–
–
–
–
–
–
Time spent studying (0.18)*
Preparing for class (0.11)*
Papers of 20 or more pages (0.23)
Analysis (0.12)
Synthesis (0.23)
Evaluation (0.20)
• Cluster 1 (MU higher):
– Assigned texts (0.10)
10
Results for MU Seniors
• Cluster 2 (MU lower):
– Papers of 20 or more pages (0.13)*
– Evaluation (0.11)
• Cluster 2 (MU higher):
– Class preparation (0.15)*
– Application (0.08)*
11
Results for MU Seniors
• Cluster 3 (MU lower):
–
–
–
–
–
–
–
–
–
Time spent studying (0.16)
Class preparation (0.07)*
Assigned texts (0.28)
Papers of 20 or more pages (0.29)
Papers of less than 20 pages (0.16)
Analysis (0.27)*
Synthesis (0.19)*
Evaluation (0.28)
Application (0.14)*
• Cluster 3 (MU higher)
– Worked harder than you expected (0.16)
12
Conclusions
• Disciplines do make a difference and the results for
MU were generally consistent with the results for
other AAU institutions.
• MU’s cluster 2 students not different from cluster 2
students from other AAU institutions.
• MU’s cluster 1 students somewhat lower than cluster 1
students from other AAU institutions.
• MU’s cluster 3 students were substantially lower than
cluster 3 students from other AAU institutions.
13