OPINION

English or a Science (Figure 3). All students who held Computing or Mathematics qualifications (Higher or Intermediate 2) passed the exam with a Grade ‘C’ or better.

Examining the prior qualifications of grade ‘C’ achieving students in isolation, we identified a factor which to our knowledge has not been highlighted anywhere else previously in association with computing science examination. The student entry qualification of Higher English was conspicuous by its absence in our ‘C’ grade students. Only one student with a ‘C’ grade in the exam held a Higher English qualification. We wondered if reading, comprehension, and writing skills could be key factors in determining performance in the computing exam?

A search for the relationship between
English qualifications and computer
science bore little fruit. Most articles we
found related to English as a second
language. However, we found one author,
Chmura [ 6], who had conducted research
with Computer Science students, albe-
it tenth to twelfth graders, and found
“reading comprehension as a key factor in
determining a student’s level of success
in computer science.” Examining program-
ming performance against comprehen-
sion, Chmura observed that “the more
successful students had 90+ percentile on
their standardized reading comprehension
tests.” The author planned to introduce
reading strategies to students based
upon the findings. It is precisely this age
group that makes up most our direct entry
students and this has led us to question
whether it might be possible that reading
comprehension could be more important
than a prior computer science qualification
in determining a student’s exam grade.

We next considered possible links be-
tween our findings and Bloom’s Taxonomy
[ 4]. The six levels of the taxonomy are all
applicable to our HNC Computing exam
content:
• Remember - Recall information learned
• Understand - List, explain, and demon-
strate understanding of concepts and
knowledge gained
• Apply - Examine problem scenarios,
troubleshoot, and justify
• Analyze - Solve problems, categorize
existing knowledge, and apply to new
scenarios
• Evaluate - Discuss and contrast using
existing knowledge and understanding
• Create – Consider and plan a series
of tasks, explaining decision-making
rationale
Bloom et al. [ 4] devised a hierarchy
of cognitive skills (Figure 4), founded on
knowledge, and rising through simple con-
crete abilities to complex abstract abilities,
with each level in the hierarchy relying on
the underlying level as a prerequisite for
attainment [ 5].

The taxonomy proposed by Bloom et al. has provided a foundation for educationalists and many introductory computer programming courses have been modelled around it [ 4], delivering learning opportunities to match the various stages [ 8]. Although the taxonomy could be viewed as a generic template for modelling any course structure, the ascendancy through the stages equates significantly with learning and assessment in computer programming [ 7, 10], more so with the revised taxonomy presented by Anderson et al. [ 1].

It could be contended that all levels of the hierarchy require good reading and writing skills to understand exam questions correctly and to be able to provide a coherent meaningful response. We consider that at the analyze and evaluate levels of the hierarchy, students with

Figure 3: ‘A’ Grade Student Qualifications

Figure 4: Bloom’s Taxonomy