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Data and analysis of knowledge items for the groups With CS and Without CS of Test 2K.

(a) Independent samples t-test for Test2K. Given that the homogeneity of variance by the Levene’s test, F(1, 101) = 3.25, p = .07 (p > .05) was upheld, a test assuming equality of variances was calculated (see Table 19). The result of this test indicated that there was a significant difference in the scores t(101) = -3.45; p = .001 (see Table 19) and d = 0.68 (medium effect see section 4.2.2.7). These results suggest that those learners in the groups Without CS (M =3.35, SD =1.57) and With CS (M = 4.32, SD = 1.28) conditions were significantly different (see Appendix HH). A difference in the two groups was indicated after the intervention. It is important to note the Levene’s test for Test1 had indicated that the two groups had the equality of variance.

Data and analysis for research questions 5 and 6 for the cognitive load forcthe Without CS and With CS groups.

Cognitive load is experienced as one learns old and new things. If what is being learnt cannot be understood well, or has many pieces of knowledge that have to be understood then it becomes hard and it can be said that the cognitive load is high. Cognitive load can be reduced by instruction. In this research the cognitive load was measured at the beginning of the week so that it could be ascertained how the participants perceived the cognitive load (Paas, Tuovinen, Tabbers, & Van Gerven, 2003; Mayer, 2004). In the theoretical framework, the cognitive load is discussed (see section 2.8). When the cognitive load decreases the germane load increases (see section 2.7.1) and this means more knowledge and skills will be sent to the long term memory and will be easily remembered.

Pearson’s correlation for the cognitive loads and performance on items of

TDRV-GO. A Pearson correlation was used to determine if the cognitive load changed or not and the relationship to the use of CS with the related instrument to assess understanding and acquisition of knowledge and skills. It was important to determine if there was any causal relationship. An analysis is based on Pearson’s correlation between the cognitive load 1, 2 3 and 4 and the performance in the TDRV-GO tests written that is Test1, Test2 and Test3 (see Appendix SSS). Since the cognitive load measures were written twice in the first week and also twice in the second week, all the correlations were done to check which were significant. The significance with respect to the correlations was taken at p = 0.05 where the chances that the result was obtained by chance was 5%. The analysis was done using SPSS version 19. Group Without CS. There was a Pearson correlation of .47 between the cognitive load 1 (beginning of week 1) and cognitive load 3 (beginning of week 2) the significance was p = .001 indicating a strong positive relationship (see Table 45 and Appendix SSS).

5 Effect sizes for research question 5 and 6.

Effect sizes for the non-parametric equation using r (see section 3.9.1.6) where the effect size may be considered under the following guidelines if r = 0.1 it is small; r = 0.3 it is medium and r = 0.5 it is a large effect size (Field, 2009, pp. 539-583). The effect sizes as indicated in Table 46 are derived from the use of non-parametric equations. Lower cognitive loads are found when CS are used. Effect sizes are larger where the CS are used when the female learners are involved, see Table 46 and compare with for the Mann-Whitney U test for CL1 effect size 0.30 compared to the male of 0.07; in the Wilcoxon signed ranked test where the effect sizes for the male and female are compared the female are higher. The highest effect size is a CS one of 0.57 and it was a large effect size.

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Research question 2 and summary of findings.

What is the effect on Grade 11 learners in terms of gender (male/female) when the topic geometrical optics is taught using a teacher centred approach in the acquisition of knowledge without the use of computer simulations? Next, the researcher gives a week-by-week summary. Week 1. There was a registered improvement from a mean 2.95 in the pre-test to 3.35 in the test after the intervention. There was a 0.45 effect size in improvement (section 4.2.3.3 and Table 23). This is when the CS were not being used and it was the teacher alone. With regard to the gender and how it worked out, it was found that the male learners improved from a low mean of 3.09 to 4.09 which was significant and a 0.72 medium effect size (see section 4.2.3.3 and Table 25). On the other hand, the female learners who were not using CS improved from a low mean of 2.81 to 2.90 not significant and a very small effect size of 0.07. Indeed there was an improvement but a very small one for the female learners

Table of Contents :

Declaration
Abstract
Acknowledgements
Summary of the study
Table of contents
List of tables
List of Abbreviations and Glossary of terms
Chapter 1 Introduction
- 1.1 Background of the Study
- 1.2 Context of the study
- 1.3 Aim of the study
- 1.4 Statement of the problem
- 1.5 Rationale of the study
- 1.6 Research questions
- 1.7 Significance of the study
- 1.8 Limitations
- 1.9 Definition of Key Terms/Phrases
- 1.10 Structure of the thesis
Chapter 2 Literature review
- 2.1 Introduction
- 2.2 Knowledge and skills
  - 2.2.1 Knowledge
  - 2.2.2 Skills
- 2.3 Geometrical optics
  - 2.3.1 Definition of geometrical optics
- 2.4 The teacher-centred approach
  - 2.4.1 Definition of teacher-centred approach
  - 2.4.2 Advantages of teacher-centred approach
  - 2.4.3 Disadvantages of teacher-centred approach
  - 2.4.4 Challenges experienced in Vhembe district in the teaching of physical science
- 2.5 Computer simulations
  - 2.5.1 Description of computer simulations
  - 2.5.2 Physics Education Technology (PhET) Project
  - 2.5.3 Using computer simulations for acquisition of knowledge
  - 2.5.4 Using computer simulations for skills
  - 2.5.5 Advantages of computer simulations
  - 2.5.6 Disadvantages of computer simulations
- 2.6 Information processing model
  - 2.6.1 Description of the Information Processing Model
  - 2.6.2 The main elements of the Information processing model
- 2.7 Relevant theories to the study
Chapter 3 Research Methodology
- 3.1 Introduction
- 3.2 Research Sample
  - 3.2.1 Schools
- 3.3 Research design
  - 3.3.1 Non-equivalent group design
  - 3.3.2 Switching replications design and description
- 3.4 Instruments
  - 3.4.1 Test of Describing Relationships between Variables in Geometrical Optics (TDRVGO)
  - 3.4.2 Cognitive Load Rating Scale
  - 3.4.3 Split timer
- 3.5 Validity and reliability of the instruments
Chapter 4 Data and analysis for Knowledge and Skills items
Chapter 5 Data and analysis of Cognitive load and speed
Chapter 6 Summary, implications and recommendations