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Designing teaching strategy to enhance student learning

Salim A. Siddiqui, S. R. Yeo, M. G. Zadnik
Physics Education Research and Development Group
Department of Applied Physics, Curtin University of Technology
This study investigates how the prior knowledge of the students can be used to develop an effective teaching and learning strategy. First- year university science students come from a variety of teaching and learning cultures with a wide range of academic abilities. Moreover several studies have shown that student had been pre-exposed to misconceptions that are hard to change. These combining factors pose a daunting challenge for the instructor to teach such a class of varying abilities and mixed concepts. Traditional mode of teaching in many cases is not suitable and may result in an increased drop out rate. Developing an effective learning environment primarily depends on the instructor. Before embarking on a full teaching program, it is therefore, useful to develop a teaching and learning strategy that is suitable for the whole class.


The transition from school to university life for first-year students is not always smooth. This is partly because of a sudden change in the teaching/learning environment and partly because of exposure to new social environment. Developing familiarity with new teachers and colleagues takes a couple of weeks. This process may be full of thrills and joy for some students and stress and anxiety for other students. Learning new subject matter, meeting deadlines for various assignments and preparing for on-course tests, all adds up to increasing work load for first-year students. The situation becomes more stressful if the subject matter has not been well understood in lectures and tutorials, which normally is the case. This further adds to student's frustrations and as a result many potentially capable students drop out.

We all know that students enter university with great expectations to pursue their career and would like to graduate with high quality attributes normally required by employers in the job market. In order to produce quality graduates the universities are continually encouraging and supporting practitioners to adopt quality teaching and learning practices. Therefore, to generate an effective teaching and learning environment becomes the ultimate responsibility of the instructor.

Teaching methods and strategy

Our experience shows that there is not a single unique teaching and learning strategy that could effectively produce complete student satisfaction in the class. Teaching strategies depends on many factors, eg., student's attitude towards the subject, learning habits of individuals, year to year intake with wider ranges of student academic abilities associated with their background teaching and learning cultures[1]. Some of these students come from schools that maintain very high teaching standards and develop conceptual learning, while the others come from schools with normal teaching standards where subject may have been taught in a passive learning environment. Usually no deep learning and reasoning is excited in such classes, as a result of which students may develop their own model of fundamental concepts normally based on prior misconceptions.

We all know that conceptual teaching and learning is a difficult task and it varies from student to student. It also depends on the teaching style of the instructor. Moreover, science education research [2,3] shows that many students construct their own concepts that are termed as misconceptions by experts. Such misconceptions or alternate conceptions are hard to change.

Traditional mode of lecturing assumes that students already have the pre-requisite physical concepts and therefore, the instructor can proceed on to deliver new contents at tertiary level. In general this method may be suitable for a small number of students in the class, but is not suitable for majority of the students whose concepts are not strong enough to understand the new contents. This is quite evident in first-year science classes where most of the students are staring at the board with a question mark on their face expressing dissatisfaction and disbelief in the contents being delivered. Therefore, this method is ineffective and unattractive to students particularly for large class sizes. Such teaching practices simply promote superficial learning leading to wrong interpretation and wrong concepts. Moreover, students do not enjoy such learning practices because it does not create any motivation but confusion and thus hinders conceptual learning.

These combining factors pose a daunting challenge for the instructor as how to develop an optimum effective teaching learning strategy that is suitable for the entire class of varying abilities and mixed concepts. A carefully designed pre-test questionnaire may provide the instructor with some guidelines in designing his/her teaching strategy and eventually assess the effectiveness of such a technique and learning gains achieved by student [4,5].

Pre-test questionnaire to assess student's prior knowledge

In order to determine an optimum introduction level for the contents, a pre-test questionnaire was designed for the first-year medical imaging science students to assess their prior knowledge about the subject. The pre-test questionnaire was based on the pre-requisite knowledge, Tertiary Entrance Examination syllabus and student's performance in the Tertiary Entrance Examination. The pre-test questionnaire had 16 questions addressing various components of the unit contents. (Copy of the questionnaire is appended) We believe that to teach a unit effectively, the instructor should not assume that the students already have the pre-requisite knowledge of the unit content.

The pre-test was conducted during the very first lecture in the class. The students marked their responses on the questionnaire and returned the completed questionnaire to the instructor in the class. No time limit was imposed to complete the questionnaire so that student could think carefully before answering the questions.

The analyses of the pre-test exposed the weakness and strength of the class. From this information an optimum level for the content delivery was determined which formed the bases on which the subsequent teaching material was constructed. Weaker concepts were often repeated in the class at the expense of the stronger concepts.

After 5 weeks of teaching, a post-test was conducted. [The contents of the post-test were exactly the same as that of the pre-test]. Generally students memorise difficult concepts and regurgitate in the test. Therefore, the test was conducted with out any advance warning to the students to exclude rote learning assessment. The idea was to assess the student learning and concept retaining abilities over a period of 5 weeks. The student performance is then compared with the on-course test and final exam.

The questions in the on-course test and the final exams were different to those in the pre and post-tests, but were based on the conceptual knowledge acquired in the post-test.


The data of the pre- and post-test is shown in Figure 1. This graph shows the number of students who correctly answered the questions in the pre-and post-tests versus the question number. Comparison of the result shows that after 5 weeks of teaching, the student conceptual learning and retention has improved significantly for most of the questions, given that the post-test was administered with out any advance warning to avoid rote learning.

The graph also shows that post-test responses to question 4, 5, 9 and 11 were still not satisfactory. We believe that ten hours of teaching (that is two hours lecture per week) was not enough to cover a wide range of content material and conduct a test. The post-test should have been conducted at least after 7 weeks of teaching. This step will be carried out in 2002.

Figure 1
Figure 1: Bar graph of the pre and post-test (red and blue bars respectively), comparing % of student's improvement over pre-test score for each question. This graph shows significant improvement in student learning for most of the questions reflecting concept retention.
Comparison of pre and post-test scores is shown in Figure 2. The large shift in the mean score of the post-test distribution indicates that the new method has improved student learning.

Figure 2
Figure 2: Histogram of pre and post-test (red and blue bars respectively). The large horizontal shift in the graph is showing improvement in student learning. Mean pre-test = 24.9 ± 12.9, Mean post-test = 57.4 ± 14.0
The pass rate and average mark for the 2001 class is tabulated in Table 1. Since no systematic study of this kind was conducted in previous years, therefore, it is not possible to compare these results with previous year's result. Whether this strategy has really improved student learning as reflected in the final results, can not be claimed with certainty. In order to be sure that such strategy is really effective we plan to conduct this study to a different group of students in 2002.

Table 1: Pass rate and average mark scored in pre-test, post-test,
on-course test and final exam for 2001 class.

Pre-testPost-testOn-courseFinal exam
Pass rate6%76%90%93%
Average mark25%57%70%65%

Table 2: Comparison with previous year's result

YearNo. of studentsAverage final markFinal exam pass rate


This study shows that a two-part strategy consisting of assessing the prior knowledge of students and then developing teaching material to address the weaknesses of the class has improved student learning to some extent. The attendance in the class through out the semester has been around 90% indicating student's interest and subject satisfaction. The post-test with out prior warning provides a measure of students learning and concept retaining abilities. Although the final result shows a 10% improvement over the previous year's result, further research is still needed to test the effectiveness of such strategy on a different group of students.


  1. M. G. Zadnik and S. R. Yeo, "Improving Teaching and Learning in Undergraduate Science: Some Research and Practice," Invited paper presented at the 2001 Uniserve Workshop on Research and Development into University Science, University of Sydney.

  2. R. T. White and R. F. Gunstone, "Metalearning and conceptual change," International Journal of Science Education, 11, 577-586 (1989).

  3. D. Hestenes, M. Wells, and G. Swackhamer, "Force Concept inventory," The Physics Teacher, 30 (1992).

  4. R. K. Thornton and D. R. Sokoloff, "Assessing student learning of Newton's laws: The force and motion conceptual evaluation and the evaluation of active learning laboratory and lecture curricula," American Journal of Physics, 66, 338-351 (1998).

  5. R. R. Hake, "Interactive-engagement versus traditional methods: A six-thousand student survey of mechanics test data for introductory physics courses," American Journal of Physics, 66, 64-74 (1998).

Appendix: Pre/post-test questionnaire

Appendix: Pre/post-test questionnaire

Contact person: Salim Siddiqui PhD (Nuclear Physics), Department of Applied Physics, Curtin University of Technology. s.siddiqui@curtin.edu.au

Please cite as: Siddiqui, S. A., Yeo, S. R. and Zadnik, M. G. (2002). Designing teaching strategy to enhance student learning. In Focusing on the Student. Proceedings of the 11th Annual Teaching Learning Forum, 5-6 February 2002. Perth: Edith Cowan University. http://lsn.curtin.edu.au/tlf/tlf2002/siddiqui.html

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