Subject matter learning at the university level is not all
about memorising isolated facts but understanding concepts
and drawing connections between them. To facilitate university
students’ learning, more authentic problems which provoke
the use of so-called higher-order cognitive skills (HOCS)
(Roth, 1995) should be assigned instead of structured exercises.
With the widespread availability of modern computing and networking
facilities, computers are now widely used in education. In
chemistry, spreadsheets and visualisation platforms are useful
tools for data analysis and illustrating chemistry ideas.
In particular, computer-assisted instruction (CAI) which takes
the form of virtual tutorials can be utilised for intensive
teaching of conceptual chemistry (Lower, 1997). Furthermore,
it is proposed that the use of CAI as a supplementary teaching
tool could foster the development of HOCS in individual students.
The CAI, through careful sequencing of instructions, while
acknowledging the differences in students’ abilities,
makes it possible for the instructions to be customised to
stimulate any individual student to first remember and review
what one already knows and later, guide one to solve authentic
problems by analysing and evaluating the knowledge.
This article aims at reporting the initial design and evaluation
of an Organic Chemistry (specifically in nucleophilic substitution
reaction mechanisms) CAI software in NUS. Suggestions for
future work are included.
The initial schematic describes an ‘ideal’ situation
whereby any individual user’s progress in learning could
be reasonably accommodated. Challenges that had arisen during
the development of the CAI prototype based on the initial
schematic prompted further development according to the revised
After attempting to develop the CAI software from scratch,
we realised that it would be difficult, although not impossible,
to have numerous though finite paths of learning in the CAI
software. Hence, the revised schematic took into consideration
that the general distribution of learning abilities of students
would follow more or less the normal distribution. In addition,
an assessment was administered to a small sample of NUS students
in Organic Chemistry to determine the prior knowledge of the
targeted main branch students so that it was possible to gauge
the appropriate level of difficulty of the questions in the
main branch, the fast and slow tracks.
Figure 1: Initial CAI Schematic
A number of possible ‘paths’
of learning with the flexibility for a user to ‘jump’
from one path to another are offered. As a user progresses
from the basic to the advanced questions, one’s HOCS
is gradually developed.
Figure 2: Revised CAI Schematic
Most users would be expected to progress
along the main branch. The ‘fast track’ bypasses
certain easier questions to allow for more rapid development
in HOCS. The slower track accommodates users who need more
help with basic understanding of concepts. Flexibility to
‘jump’ between the branches is retained.
15 first-year undergraduate students were asked for their
opinions after they each had been given an opportunity to
spend time using the trial version of the CAI software. Responses
indicated a mixed assessment of the CAI. Some students’
positive comments on the CAI were that it stimulated thinking
(see Table 1) and helped reinforce concepts. In addition,
the interactivity available on the CAI was something which
the textbooks could not offer. Since time was not a factor,
the learning with the CAI could be reviewed at one’s
own pace which is an advantage over time-critical lectures.
With regard to features that the students disliked, one
user claimed that the content, which was initially too easy
for her, subsequently became too challenging. Others suggested
that more personalised feedback could be included. The lack
of ability for the user to pose questions (not available in
the trial version of the software) constituted another drawback
as the users were restricted to the contents available within
Users were also asked to select from a list of CAI features
(Hannafin & Peck, 1988)—with associated cognitive
basis not revealed to the users—that they felt would
be useful to incorporate into the CAI to teach chemistry via
HOCS (see Table 2).
Most users (80%) indicated that the ability to stimulate
recall of prior knowledge should be incorporated into the
CAI. Users also ranked features such as the ability to assess
performance, guided learning, interactivity and distinctive
stimulation as important. Incidentally, these mentioned features
could be regarded important in the development of lower-order
cognitive skills (LOCS). Few users selected features like
individualisation, allowance of appropriate degree of user
control, enhancement of learning as well as provision of user
feedback which would in fact be more useful towards the development
of HOCS. Such results might indicate that students still believed
that they were expected to grasp the subject matter by knowing
the facts using only LOCS.
Table 1: Types of cognitive skills used
as reported by the fifteen students in the trials
On a numeric scale of 1(slow)—5(fast),
users rated the pace of general learning and pace of learning
chemistry. E.g. (1, 5) indicates that the user rated pace
of general learning as slow (1) but pace of learning chemistry
as fast (5).
Table 2: CA1 features with associated
Based on our experience with the initial design
and evaluation of the CAI software, we would like to make
the following recommendations for future development and enhancement
of the CAI software:
- The CAI prototype had some limitations due to the few
and restrictive nature of the features incorporated. It
was lacking especially in the ability to provide sufficient
personalised feedback that goes beyond pointing out mistakes.
Such features are essential to the development of HOCS as
it allows one to analyse, evaluate and learn from one’s
- Users also had limited means of backtracking to review
information on previous frames. Such allowance should be
taken into consideration in the design process because one
needs to consolidate what he/she already knows in order
to receive new information.
- More captivating visual and audio effects might aid in
the understanding of how organic reactions occur and this
would improve assimilation of knowledge and synthesis of
- A potential difficulty would be that to obtain an accurate
trend of user’s knowledge standards, one would have
to evaluate numerous statistical samples over a period of
time. However this would render the CAI obsolete by the
time the statistical result is produced based on past sampling.
It is envisioned that further development and enhancement
of the proposed CAI may be carried out by building upon its
merits and using feedback drawn from this study to enhance
its effectiveness as a (supplementary) teaching instrument.
Other future work may include reviewing the effectiveness
of commercially developed CAI to stay current with the advancements
in CAI software development.
Roth, W.M. (1995). ‘What Happens to a Rock When you
Throw it in the Water? Doing High School Physics the Physicists’
Way’. In Lavoie, D.R. (Ed.), Toward a Cognitive-Science
Perspective for Scientific Problem Solving: A Monograph of
the National Association for Research in Science Teaching. Number Six. Manhattan, KS: Ag Press. pp. 80–111.
Lower, S.K. (1997). ‘Computer-Assisted Instruction
in Chemistry’. In Zielinski, T.J. & Swift, M.L.
(Eds.), Using Computers in Chemistry and Chemical Education. Washington, DC: American Chemical Society. Chapter 19, pp.
Hannafin, M.J. & Peck, K.L. (1988). The Design,
Development, and Evaluation of Instructional Software. New York: Macmillian Publishing Company.
* The study reported in
this article is based on an Honours Year project in Chemistry
completed by Nah Wee Kiak, Daniel