Introduction

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.

Design Process

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 schematic.

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.

Trials

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 the programme.

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 cognitive bases

Recommendations

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 own mistakes.
  
  
• 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 the concepts.
  
  
• 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.

Concluding Remarks

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.

References

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. 355–376.

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