For most NUS freshmen, the matriculation maze is usually the first 'maze' they need to get through and the first semester, their second 'labyrinth'. Hence, during my first lesson on problem-solving, I would show the freshmen a maze problem (see Figure 1) and ask about 300-500 students in the lecture theatre to devise an algorithm or an idea that allows the mouse to get to the cheese.

Getting the attention of such a large class is certainly no mean feat given that students have an attention span of only 15-20 minutes (Anderson, 1995). To break the lecture's monotony, I use a number of "change-up" activities (Schoenfeld & Magnan, 1994; Middendorf & Kalis, 1996), including switching the mode of delivery (e.g. putting aside the PowerPoint slides to show the class an animated algorithm, showing students a program development process from design to coding, or even getting some students to go in front of the class to perform some practical tasks). Punctuating the lecture with short breaks and fun tasks such as the maze problem (see Figure 1) also helps to engage students. Similarly, using interesting activities (e.g. how many times can you fold a sheet of paper?) (Peterson, 2004) to illustrate important concepts (e.g. algorithmic exponential growth) can also help students learn better.

Figure 1: Can you help the mouse get to the cheese?

In addition, managing students' short attention span and their diverse academic backgrounds and learning styles not only necessitates some degree of flexibility and balance in my teaching approach (Brightman, 1998; Felder, 1998), but also warrants an instructional design that takes into account students' varied learning needs, especially those of weaker students. This problem is compounded especially in a large class-the lecturer could either end up making the stronger students feel bored or intimidating the weaker ones.¹ Moreover, how many tricks can a teacher pull in a lecture without turning it into a circus act?

Taking these factors into consideration, I incorporate the following three elements into my instructional design:

1. Design tutorials and lectures to provide a progressive coverage of course material;
   
   
2. Provide timely feedback to students through the virtual classroom; and
   
   
3. Emphasise on the assessment of problem solving skills.

Due to space constraints, I shall elaborate only on the first point in the next section.

Designing Tutorials and Lectures to Provide a Progressive Coverage of Course Material

Apart from regular tutorial questions, I usually include additional materials such as an exploration section to inculcate independent learning, a check-it-out section for quick answers, a learn-from-your-mistake section and an optional challenger section. The aim of this mix is to cater to students' diverse learning needs. Knowing that students would often need time to make sense of knowledge before they can internalise it, I use two strategies in my teaching. The first is to provide a progressive coverage of a particularly difficult topic (e.g. introducing the topic first with its intricacies stripped, then revisiting it for a more complete treatment the second time or a third time towards the end of the course to address more complex issues). In this way, students are exposed to the topic a few times. Such a strategy, which plays on the effect of repetition and spaced-out learning, has been found to be more effective than extra lessons or remedial classes, especially for problem-solving modules. However, the instructor has to plan and organise the course material carefully. Another strategy is to cover a difficult topic over two separate days. For example, I would start teaching the topic during the second hour of a lecture and continue with it in the next lecture.

Most of our students do see the value of quality education. Despite the occasional complaints whenever they face a tough assignment or tight deadline, some students do yearn for challenges.² As teachers, we should provide students with an environment that is conducive for them to take up challenges.

Figure 2: Getting the mouse to the cheese.

Self-reflection applies to teachers and learners alike (Dewey, 1933 ). Not only can we learn from the insights of more experienced teachers, we can also save ourselves from the misery of ignorance or complacency. To avoid getting stuck in the 'maze' of teaching, one should pause, ponder and assess our position from time to time. Understanding our strengths and weaknesses could serve as a prelude to reviewing our strategies.

Returning to the maze problem at the beginning of the article, a simple way for the mouse to get to the cheese is to keep its left paw on the wall as illustrated in Figure 2. However, the ability to turn this idea into a code is, of course, another matter. Still, more often than not, students would be amazed by the simplicity of such an idea and the realisation of a way-albeit not the best-to get out of a maze, should they find themselves in one.

References

Anderson, J.R. (1995). Cognitive Psychology and its Implications. (4th edition). New York: W.H. Freeman.

Brightman, H.J. (1998). 'GSU Master Teacher Program: On Learning Styles', Master Teacher Programs: Improving University-Level Teaching and Learning, Georgia State University, (Last accessed: 19 September 2005).

Dewey, J. (1993). How We Think: A Restatement of the Relation of Reflective Thinking to the Educative Process. Boston: D.C. Health.

Felder, R.M. (1998). 'How Students Learn, How Teachers Teach, and What Goes Wrong with the Process'. Tomorrow's Professor, (Last accessed: 19 September 2005).

Middendorf, J. & Kalis, A. (1996). 'The "Change-Up" in Lectures'. The National Teaching & Learning Forum (NTLF). Vol. 5 No. 2. (Last accessed: 19 September 2005).

Peterson, I. (2004). 'Champion Paper-Folder'. Muse, July/August, pp. 33. (Last accessed: 19 September 2005).

Schoenfeld, A.C. & Magnan, R. (1994). 'Minimizing Mental Lapses during a Lecture', in Mentor in a Manual, Climbing the Academic Ladder to Tenure. Madison, WI: Magna Publications, Inc. pp. 173-174.

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² Based on a survey on reduction of curriculum intensity conducted by School of Computing, National University of Singapore in 2005.