vii TABLE OF CONTENTS
CHAPTER PAGE
ACKNOWLEDGMENTS ... i
DECLARATION ... iv
ABSTRACT ... v
ABSTRAK ... vi
TABLE OF CONTENTS ... vii
LIST OF FIGURES ... x
LIST OF TABLES... xiv
LIST OF APPENDICES ... xvii
CHAPTER 1 INTRODUCTION ... 1
1.1. Background ... 1
1.2. Statement of Problem and Research Question ... 9
1.3. Research Objectives ... 10
1.4. Advantages of Research ... 10
1.5. Definition of Important Terms ... 12
CHAPTER 2 LITERATURE REVIEW ... 14
2.1. The Concept of Multiple Representation ... 14
2.2. Representation Use from Dual-Coding Theory (DCT) ... 24
2.3. The Role of Multiple Representation in Learning Sciences ... 27
2.4. The Multiple Representations in Learning and Teaching Physics: Some Benefits ... 39
2.5. Previous research Focusing on Quantum Physics Concept ... 47
2.6. Quantum Physics Concepts and Its Representation ... 51
2.6.1 The Photoelectric Effect... 54
2.6.2 Bohr’s Atom Model ... 57
2.6.3 The Schrodinger Equation Concept ... 62
2.7. The Concept of Critical Thinking Disposition (CTD) ... 66
viii
CHAPTER 3 METHODOLOGY ... 74
3.1. Research Paradigm and Design ... 74
3.2. The Population and the Sample of the Research ... 82
3.3. The Description of Variables of Study ... 83
3.4. Instruments ... 84
3.4.1 Pilot Study of Quantum Physics Concept Achievement... 85
3.4.2 Pilot Study of Generic Science Skills-Concept Integrated .... 89
3.4.3 Pilot Study of Critical Thinking Disposition-Concept Integrated ... 89
3.4.4 Pilot Study of Re-representation Skills Inventory ... 89
3.4.5 Focus Group Discussion Guide Question and Interview Task Protocol (ITP) ... 90
3.5. The Design of Quantum Physics Instruction Based on Multiple Representation ... 92
3.6. Data Analysis Procedure ... 99
3.6.1 Quantitative Data Analyses ... 102
3.6.2 Qualitative Data Analyses ... 102
CHAPTER 4 RESULTS AND DISCUSSION ... 104
4.1. Quantitative Data Analyses Results ... 104
4.1.1. Descriptive Analyses Results for Students’ Quantum Physics Mastery ... 104
4.1.2. Descriptive Analyses Results for Student’s Generic Skills ... 113
4.1.3. Descriptive Analyses Result for Students’ Critical Thinking Disposition ... 123
4.1.4 Descriptive Analyses Results for Students’ Re- Representation Skills Inventory (RSI) ... 134
4.1.5. Inferential Statistics Analyses for Students’ Quantum Physics Concept Achievements and Findings ... 138
ix 4.1.7. Inferential Statistics Analyses for Students’ Critical Thinking
Disposition and Findings ... 145
4.1.8. Inferential Statistics Analyses for Re-representation Skills and Findings ... 150
4.2. Qualitative Data Analyses ... 151
4.2.1. The Results of Focus Group Discussion ... 152
4.2.2. The Results of Open-Ended Semi Structure Interview ... 155
4.3. Discussion of the Research Results ... 157
4.3.1. Discussion of Results for Quantitative Study ... 158
4.3.2. Discussion of Results for Qualitative Investigation ... 184
CHAPTER 5 CONCLUSION AND IMPLICATION ... 199
5.1. Conclusion ... 199
5.2. Implications of Study ... 200
5.3. Recommendation for Future Research ... 204
REFERENCES ... 206
x LIST OF FIGURES
FIGURE PAGE
Figure 2.1 A Function Taxonomy of MERs ... 15
Figure 2.2 Pictorial Representation of Two Cars ... 19
Figure 2.3 Alternative Meanings Derived from a Single Representation 19 Figure 2.4 Peirce’s Triadic Model ... 20
Figure 2.5 Four Different Representation of a car ... 24
Figure 2.6 A Model of Cognition using Multiple Representation Based on Dual Coding Theory ... 25
Figure 2.7 Teacher Imposition ... 33
Figure 2.8 Teacher Abdication ... 34
Figure 2.9 Teacher as Domain Novice ... 35
Figure 2.10 Teacher in Trialogue ... 36
Figure 2.11 Triadic Pedagogical Model ... 37
Figure 2.12 The Proposal for a Starting Point of a Novel Course for Quantum Physics ... 50
Figure 2.13 Nearly Isomorphic Problem in Graphical and Pictorial/ Diagrammatic Format Bohr-Model Electron Orbit Radii ... 51
Figure 2.14 A Schematic Representation of the Photoelectric Effect ... 55
Figure 2.15 Graphical representation that showed dependency of Photocurrent (i) on light Intensity (I) ... 56
Figure 2.16 Graphical Representation for V0 vs υ ... 57
Figure 2.17 Pictorial Representation for Hydrogen Atom’s Spectral ... 59
Figure 2.18 Pictorial Representations for Spectral Lines ... 62
Figure 3.1 Reasoning Diagram of Framework of the Research ... 76
Figure 3.2 Embedded Research Design ... 78
Figure 3.3 The Visual Representation of Research design for Quantitative Study ... 78
xi Figure 3.5 The Characteristic of the Instructional Environmental
Design of a Multiple Representation based on IF-So
Framework ... 93 Figure 3.6 The Multiple Representation of some phenomenon Photoelectric Effect ... 95 Figure 3.7 Sequential Mixed Method Data Analyses Procedure ... 101 Figure 4.1 Average Score of Students’ concepts mastery for
Control Group (CG) ... 107 Figure 4.2 Average Score of Students’ concepts mastery
for Experimental Group (EG) ... 108 Figure 4.3 N-gain Score of Students’ concepts mastery
for CG and EG ... 109 Figure 4.4 Clustered boxplot of the Pre and Post score of photoelectric
Effect concepts for CG and EG... 109 Figure 4.5 Clustered boxplot of the Pre and Post score of Bohr’s atom
model for CG and EG ... 110 Figure 4.6 Clustered boxplot of the Pre and Post score of Schrodinger
Equation concepts for CG and EG ... 111 Figure 4.7 Clustered boxplot of the N-gain of students’ concepts Achievement for the EG and CG ... 112 Figure 4.8 Pre and Post Average Score of GSSPE for both
EG and CG ... 113 Figure 4.9 N-gain Score of GSSPE for EG and CG ... 114 Figure 4.10 Clustered boxplot of the GSSPE for the CG and EG... 116 Figure 4.11 Pre and Post Average Score of GSSBA for both
EG and CG ... 117 Figure 4.12 N-gain Score of GSSBA for EG and CG ... 118 Figure 4.13 Clustered boxplot of the GSSBA for CG and EG ... 119 Figure 4.14 Pre and Post Average Score of GSSSE for both
xii Figure 4.17 Pre and Post Average Score of CTDPE for both
EG and CG ... 124
Figure 4.18 N-gain Score for CTDPE ... 125
Figure 4.19 Clustered boxplot of the CTDIPEC for CG and EG ... 126
Figure 4.20 Pre and Post Average Score of CTDBA for both EG and CG ... 127
Figure 4.21 N-gain Score for CTDBA ... 128
Figure 4.22 Clustered boxplot of the CTDBA for CG and EG ... 129
Figure 4.23 Pre and Post Average Score of CTDSE for both EG and CG ... 131
Figure 4.24 N-gain Score for CTDSE ... 132
Figure 4.25 Clustered boxplot of the CTDSE for CG and EG... 133
Figure 4.26 Pre and Post Average Score of RSI for EG and CG ... 136
Figure 4.27 N-gain Score of RSI for both EG and CG ... 136
Figure 4.28 Clustered boxplot of the RSI for CG and EG ... 137
Figure 4.29 Clustered boxplot of the N-gain RSI for EG and CG ... 138
Figure 4.30 Photoelectric Effect Simulation from PhET ... 161
Figure 4.31 Students’ Activity in Virtual Laboratory For Photoelectric Effect Experiment ... 162
Figure 4.32 Students’ multiple Representations embedded in their arguments ... 163
Figure 4.33 Students’ Written Analogy to explain Photoelectric Effect . 165 Figure 4.34 Virtual Experiment of Hydrogen’s atom ... 167
Figure 4.35 Students’ written analogy to explain why the atom has Different energy level ... 168
Figure 4.36 Students’ Written on Bohr’s Atom Model related to other Model ... 170
Figure 4.37 Students’ Written an embedded Multiple Representation in Explaining Electron Energy in Transition (verbal, mathematical, bar-chart energy) ... 171
xiii Figure 4.39 (A) Square Barrier and (B) students’ sketch wave function
In region A, B, and C... 173
Figure 4.40 Students’ respond for tunneling energy concept ... 176 Figure 4.41 Students’ self Confidence observation ... 181
xiv LIST OF TABLES
TABLE PAGE Table 3.1 Summary of Research design ... 80 Table 3.2 Classification of Variables... 83 Table 3.3 Internal Validity of and Difficulty Indices of QPS related to
photoelectric effect concepts ... 86 Table 3.4 Internal Validity of and Difficulty Indices of QPS related to
Bohr’s atom model concepts... 87 Table 3.5 Internal Validity of and Difficulty Indices of QPS related to
Schrodinger’s equation concepts ... 88 Table 3.6 The Construct of Lesson Plan for Experimental Group ... 98 Table 4.1 Descriptive statistics related to the scores from photoelectric
effect concepts , Bohr’s atom model concepts , and Schrodinger’s equation concepts for experimental and
control groups ... 106 Table 4.2 Descriptive Statistic Related to the Scores of RSI
for both Experimental Group and Control Group ... 135 Table 4.3 Mann-Whitney U Test Statisticsfor Pre-measure of QPS
for students’ quantum physics achievement
(α=0.05, 2-tailed) ... 139 Table 4.4 Mann-Whitney U Test Statisticsfor Post- measure of QPS
for students’ quantum physics achievement
(α=0.05, 2-tailed) ... 139 Table 4.5 Mann-Whitney U Test Statisticsfor N-gain of QPS
for students’ quantum physics achievement
(α=0.05, 2-tailed) ... 140 Table 4.6 Mann-Whitney U Test Statistics for Pre-GSSPE
(α=0.05, 2-tailed) ... 140 Table 4.7 Mann-Whitney U Test Statistics for Post-GSSPE
(α=0.05, 2-tailed) ... 141 Table 4.8 Mann-Whitney U Test Statistics for N-gain of GSSPE
xv Table 4.9 Mann-Whitney U Test Statistics for Pre-GSSBA
(α=0.05, 2-tailed) ... 142 Table 4.10 Mann-Whitney U Test Statistics for Post-GSSBA
(α=0.05, 2-tailed) ... 143 Table 4.11Mann-Whitney U Test Statistics for N-gain of GSSBA
(α=0.05, 2-tailed) ... 143 Table 4.12 Mann-Whitney U Test Statistics for Pre-GSSSE
(α=0.05, 2-tailed) ... 144 Table 4.13 Mann-Whitney U Test Statistics for Post-GSSSE
(α=0.05, 2-tailed) ... 144 Table 4.14Mann-Whitney U Test Statistics for N-gain of GSSSE
(α=0.05, 2-tailed) ... 145 Table 4.15 Mann-Whitney U Test Statistics for Pre-CTDPE
(α=0.05, 2-tailed) ... 146 Table 4.16 Mann-Whitney U Test Statistics for Post-CTDPE
(α=0.05, 2-tailed) ... 146 Table 4.17 Mann-Whitney U Test Statistics for N-gain of CTDPE
(α=0.05, 2-tailed) ... 147 Table 4.18 Mann-Whitney U Test Statistics for Pre-CTDBA
(α=0.05, 2-tailed)... 147 Table 4.19 Mann-Whitney U Test Statistics for Post-CTDBA
(α=0.05, 2-tailed)... 148 Table 4.20 Mann-Whitney U Test Statistics for N-gain of CTDBA
(α=0.05, 2-tailed)... 148 Table 4.21 Mann-Whitney U Test Statistics for Pre-CTDSE
(α=0.05, 2-tailed)... 149 Table 4.22 Mann-Whitney U Test Statistics for Post-CTDSE
(α=0.05, 2-tailed)... 149 Table 4.23 Mann-Whitney U Test Statistics for N-gain of CTDSE
xvi Table 4.24 Mann-Whitney U Test Statistics for Pre, Post, and N-gain
xvii LIST OF APPENDICES
APPENDIX PAGE
Appendix A Lesson Plan ... 214
Appendix B Students Worksheet ... 221
Appendix C Quantum Physics Survey (QPS) ... 227
Appendix D Re-representation Skill Inventory (RSI) ... 284
Appendix E Rubrics ... 289
Appendix F Focus Group Discussion Questions List ... 292
Appendix G Interview Task Protocol ... 294
Appendix H Mann-Whitney U Test Statistics Analyze for Concept Mastery ... 296
Appendix I Mann-Whitney U Test Statistics Analyze for GSS ... 299
Appendix J Mann-Whitney U Test Statistics Analyze for CTD ... 308
CHAPTER 1 INTRODUCTION
1.1 Background
Since the 1970’s, there has been significantly increased number of systematic investigations into students understanding of physics. A large number of empirical studies completed in the past three decades could be categorized into three areas in terms of their primary emphasis: research about student conceptual understanding and reasoning; research about student problem solving; and research about student attitudes and beliefs (McDermott & Redish, 1999). Investigation of student difficulties in conceptual understanding have been more comprehensively documented than both about student problem solving and about beliefs and attitudes. Many of the researches into student conceptual understanding have been in classical physics such as kinematics, Newtonian dynamics, electric circuits, thermodynamics, work and energy, and geometrical optics.
In that period, some physicists found that there existed a great difference between what was taught and what was learned (McDermott, 1993). Since then, systematic investigations done by physicists about how students learn physics have been growing in number and sophistication. Forming a new community and building a new area in physics, researchers have gained deep insight both into students’ difficulties understanding physics and into how to help students learn more effectively (McDermott & Redish, 1999).
real world workplace wants employees in science and engineering to have: for example, knowing how to learn, scientific investigation skills, problem solving ability, communication and teamwork skills, and others. Therefore, the goals of physics education research are varied and different. Some focus more on understanding of physics knowledge, some emphasize developing procedural skills to meet the needs of the workplace, and some do both until students’ attitudes and beliefs. In fact all of these attributes refer to how to design learning systems as a main focus of discourses about learning physics, including learning materials, instructional strategies, instructors, classroom implementations, and so forth.
Recent research in learning and teaching physics strategies has increased greatly (Rebello & Zollman, 2005). Some researchers have investigated traditional methods of learning, while others have developed and assessed techniques such as hands-on experiments and interactive computer visualizations. Over the past ten years a number of researchers have been involved in these efforts, especially in the modern physics field. Their work is now showing some good results that can help us understand how to teach quantum physics and, perhaps, other abstract scientific concepts (Zollman, 1999; Asikainen, et al, 2005)
have a weak level of the understanding of quantum physics. In terms of assessing students difficulties in quantum physics, several conceptual surveys have been developed, though most are appropriate for advanced undergraduate and beginning graduate students since they address topics such as the calculation of expectation values, or the time-evolution of quantum states (Baily & Finkelstein, 2009). Wuttiprom et al (2009) reported that students had the most difficulty with six questions which they classified as interpretive; for example, the two survey items with the lowest percentage of correct responses ask whether, “according to the standard interpretation of quantum mechanics,” light (or an electron) is behaving like a wave or a particle when traveling from a source to a detector. The authors reported that only ~20% of students chose the correct response for each of these two questions.
Quantum physics can be built on a classical base theory, using many classical concepts and so can be rich in representations. If student understanding is weak in these areas, the learning of quantum physics may still be difficult (Bao & Redish, 2002). Although quantum physics is representationally very rich but it seems almost certain that traditional teaching ignores these richness. Student ability to build different kinds of physics representations for quantum physics can help them understand and use key physics concepts. Therefore, quantum physics lectures based on multimodality or multiple representations is an alternative way to enhance students’ understanding of quantum physics concepts.
teachers, this can result in novice teachers not fully understanding how the complex process of teaching and learning occurs (Ballet, Kelchtermans, & Loughran, 2006; Loughran, et al, 2001). Similarly, students’ thinking is not often adequately explored within the classroom. We utilized an approach (Waldrip, Prain & Carolan, 2010) that conceptualizes facilitation of student learning in terms of Roberts’ (1996) “trialogue”, a three-way reciprocal linkage between teacher, student and content knowledge. In this paper, we suggest that exploration of students’ thinking combined with teacher facilitation can lead to improved student understanding of the challenges entailed in representing concepts and processes in chemistry. This exploration entails teacher recognition that students’ thinking often diverges from the teacher’s expert domain knowledge, and that there is a need to make explicit students’ thinking around representational adequacy to facilitate learning. In many classrooms, the teacher is seen as the source of knowledge, and teaching is characterized as timely imparting of this knowledge. We see that it is important for students to generate their own understandings (Ehrlen, 2009; Creagh, 2008) through making representations of their emerging understandings, including drawing, modeling, discussions, tables, graphs, multi-media products, role plays, and photographs, in a process of guided inquiry.
between their own and authorised multiple and multimodal representations of science concepts and processes. diSessa (2004) suggested that secondary students are capable of discerning criteria by which an effective representation can be judged, criteria such as:
• Adequacy, in that all relevant information is shown.
• Conciseness, with a focus on pertinent points and avoiding distraction. • Comprehensibility, in that a representation is self-sufficient in making its
claims clear.
• Alignment, in that linkages between different parts of a representation are
shown clearly.
• Conventionality, in that accepted conventions are observed.
He pointed out that judging the value of a representation is complex and content-dependent, where fit for purpose is also an important element in effectiveness. In comparing how expert chemists and chemistry students construct and use representations, Kozma (2003) noted that students had difficulty translating between representations, and connecting them. Kozma and Russell (2005) proposed a five stage conceptual structure of representational competence. It is clear that they are seeing high-level competence in using representations as a thinking tool to be used for more re-interpretive thinking.
different representations of scientific knowledge. Ainsworth (1999) stated that learner engagement with expert-generated representations could support learning in three ways. These are (a) when the new representation complements past understanding by confirming past knowledge, (b) the new representation constrains interpretation by limiting the learners’ focus on key conceptual features, (c) the different representations enable learners to identify an underlying concepts or abstraction across modes or within the same mode of representation.
There are several innovative ongoing research and educational projects, especially on visual representation of quantum physics. For example, Zollman, Rebello, & Hogg (2002) have integrated quantum physics as a part of introductory level physics with developed Visual Quantum Mechanics (VQM) visualization materials. Based on the preliminary results VQM material is suitable for the teaching of quantum physics also for novice physics students or engineering students. Also Robblee, Garik, & Abegg (1999) have achieved good learning results by using Quantum Science Across Disciplines (QSAD) software in the upper secondary school teacher education. Based on the results of these studies it seems that different kinds of computer based visualization techniques can enhance the students’ understanding of quantum physics.
representations, (2) using appropriate strategies for solving physics problems. Thus, in the science class, students should be able not only translate language about the topic between science and everyday language in the text-dominant classroom, but also have experience at re-representing the concepts discussed across the various modes used within the topic (Gunel, Hand, & Gunduz, 2007).
Besides understanding physics concepts, there is another goal in learning physics which is very important for students as the rising generation to meet their challenges and capitalize on their opportunities in future. Many instructors clearly fail in the “hidden curriculum” category to leave students with a positive attitude towards physics, especially for pre-service physics teacher students. This should be beyond simply “liking” physics; it encompasses an appreciation of how physicists think and operate, the value of physics as it applies to other fields such as engineering, biology, medicine, etc., and the applicability of physics to everyday life and various jobs in society (Brotosiswojo, 2001; Duda & Garret, 2007).
Students’ generic science skills could be built through learning physics that is encouraging higher order thinking process, like critical thinking. Therefore, critical thinking skills as a higher order thinking is considered an important variable in the process of students’ learning science (Liliasari, 2007). Students’ ability to think critically has become a major concern among educators and psychologists as they try to study the factors influencing the acquisition of thinking skills. Much recent research focuses on the relationship of several variables, the students’ critical thinking dispositions, students’ perceptions towards teachers’ teaching approaches, the learning approaches students employ in the process of learning, and critical thinking skills as the learning outcome (Facione, 1995; Wan Sulaeman, Abdul Rahman, & Dzulkifli, 2007).
The development of critical thinking is an important step in achieving the goals of holistic education, not only through helping students gain knowledge but above all through ensuring that they think effectively. The learning of thinking skills will be even more meaningful when it is reinforced in the lessons taught. When thinking skills are infused and weaved into the lesson instruction, students are able to gain a deeper understanding of the content they are learning, resulting in meaningful and transferable knowledge (Ennis, 1996; Rutherford and Ahlgren, 1990; Costa, 1985).
Facione, Facione & Giancarlo (2000) have hypothesized that skills in critical thinking is positively correlated with the consistent internal motivation to think; and, moreover, that specific critical thinking skills are matched with specific critical thinking dispositions. If true, these assumptions suggest that a thinking skill-focused curriculum would lead persons to be both willing and able to think.
This research has been done with focus on designing learning and teaching quantum physics with rich environment based on multimodal representation and its influence toward quantum physics concepts mastery, generic science skills, critical thinking disposition for pre-service physics teacher students.
1.2Statement of Problem and Research Questions
The main problem of this research is how to design quantum physics instructional strategies based on multiple representation for enhancing concepts mastery, critical thinking disposition, and generic science skills. This study has attempted to answer the following research questions:
a) How do the students prefer certain physics representations before experiencing the unit of quantum physics instruction based on multiple representations? b) How are the students’ conceptions about quantum physics concepts before
and after getting the unit of quantum physics instruction based on multiple representations?
c) What are the characteristics of quantum physics instruction designs based on multiple representations?
e) What are the different effects of the multiple representations-based instructions compared to the conventional teaching method on pre-service physics teacher students to enhance re-representation skills?
f) How do the students use multiple representations when they encounter a quantum physics learning situation and solve quantum physics problem? g) What are students’ perceptions about teaching and learning quantum physics
based on multiple representations? 1.3 Research Objectives
The primary purpose of this study is to design and descript the impact of an instruction strategy based on multiple representations on pre-service physics teacher students to quantum physics concepts understanding, critical thinking disposition, and generic science skills. An embedded mixed method will be used in this research. Furthermore, this study seeks to attain the following purposes: a) to enhance quality of teaching and learning on quantum physics through
multiple representation-based instructions
b) to enhance students’ performance in quantum physics concept mastery c) to develop students’ generic science skills
d) to develop students’ high order thinking skill, especially in critical thinking disposition
e) to supply examples of how pre-service physics teachers student design innovative instruction based on multiple representations.
1.4 Advantages of Research
framework for analyzing and describing how students understand and use multiple representations in the context of quantum physics. The practical framework of this dissertation offers educators and researchers a technical language capable of describing students’ (correct and incorrect) use of multimodal representations in quantum physics. Also, include that no study has investigated this unique combination of representations, reasoning framework including critical thinking and generic science skills.
The advantages of the research detail were following:
a) That is, this practical framework offers a new vocabulary for pre service physics teachers (definition of the relevant internal and external representation) and grammar (relationship between internal and external representation) for analyzing and describing students’ quantum physics concepts mastery, critical thinking disposition, and generic science skills. It is useful for researchers and educators in three important ways: it synthesizes previous research into one coherent framework, it can be used as a diagnostic tool during instruction, and it can be used as a guide for future instruction and curriculum development.
physics or quantum physics-mediated representations of science consistent with, rather than a deviation from, this evolution of science as a discipline. c) By implication, students need to learn about the multi-modal nature of the
representations entailed in scientific inquiry, and the different modes in which the same concepts in physics can be represented as part of students’ general development of science literacy.
1.5 Definitions of the Important Terms
a) Multimodality refers to the integration in science discourse of different modes to represent scientific reasoning and findings (Waldrip, Prain & Carolan, 2006).
b) Internal representations can be defined as “individual cognitive configurations inferred from human behavior describing some aspects of the process of thinking and problem solving that formed mental configurations on students’ minds (Lasry & Aulls, 2007).
c) External representations can be defined as “structured physical situations that can be seen as embodying physics ideas that stands for, depicts, symbolizes or represents objects and/or processes. Examples in physics include words, diagrams, equations, graphs, simulation, sketches, etc (Meltzer, 2005). d) The representational mode is viewed as a cognitive mode that is dealing with
e) Generic science skills: Fundamental skills that could be generated through innovation in learning science, such as a quantum physics class. There are eight indicators of scientific generic skills including: direct and indirect observation, sense of scale, using symbolic language, developing need for logical self-consistency, developing logical inference, understanding causality, developing mathematical modeling, and developing concepts (Brotosiswojo, 2001).
f) Critical Thinking Disposition: We propose to use the word “dispositions” as applied to humans to refer to characterological attributes of individuals. As such, a human disposition is a person’s persistent internal motivation to act toward, or to respond to, persons, events, or circumstances in habitual, and yet potentially malleable, ways. There are seven aspects of the overall disposition toward Critical Thinking: truth-seeking, open-mindedness, analyticity, systematicity, self-confidence, inquisitiveness, and cognitive maturity (Facione, Facione, & Giancarlo, 2000).
g) Multiple representations-based instructions: It is a kind of instructions strategy that involves multiple representations in concepts explanations. This means that in order to explain a concepts, a variety of external representations such as tables, graphs, pictures, symbols, equations, analogy etc. for comprehending the concepts are used (Kohl & Finkelstein, 2006) h) Conventional-based Instructions: It is a kind of instructional strategy which
CHAPTER 3 METHODOLOGY
This chapter presents the procedures for the study. It includes descriptions of the overall research design, the population and the sample, the description of the variables, the data collection instruments, the design of the instruction, the pilot study of the instruction, the treatment procedure and data analyses approach used to address each research.
3.1 Research Paradigm and Design
Recent, the issues of what instructional approaches should be used in physics classes have not been solved yet. No matter which instructional approach is used, the primary goal of physics instruction should be to help students in forming conceptual understanding. Kohl & Finkelstein (2007) suggest that if the teachers enrich their physics classrooms by using multiple representations, the students can more efficiently make connections between the meaning of physics concepts and the way of representing them, therefore they simply “go for the meaning, beware of the syntax” which results in conceptual understanding.
developing logical inference, understanding causality, developing mathematical modeling, and developing concepts, are considered essential for undergraduate physics students. Since many of these skills are an indispensable part of the lifelong learning process, some even consider them more valuable than subject matter (Brotosiswojo, 2001).
The concern for teaching thinking skills is penetrating the education system everywhere in the world. All levels of society agree that thinking skills are crucial for one to remain relevant and proficient in this fast-paced and competitive world (Lang, 2006). Physics is considered abstract, difficult, boring, unattractive, not very meaningful to students and detached from every day life. Many students who begin their physics lesson with a certain level of enthusiasm and eagerness soon change their attitude and consider the subject uninteresting and even develop aversions (Euler, 2004). However, preparing pre-service physics teachers student to teach thinking skills requires more than the generic attitude, skills, and knowledge components for effective teaching. This dispositional component is closely related to the affective dimension of a particular thinking skill, i.e., the willingness and inclination to think in a particular way (Lang, 2006).
Figure 3.1 Reasoning Diagram of Framework of the Research
Actional Representation Quantum Physics
Concepts
Essential Topics in Quantum Physics
• The nature of physics • The nature of
quantum physics • Competence
standard for learning quantum physics for pre-service physics teacher student Cognitive Theory encoding Dual Coding Theory n-coding theory Internal representation External Representation
Representations Format for Quantum physics concepts
The research was conducted using the mixed method approach. Mixed methods research is formally defined here as the class of research where the
researcher mixes or combines quantitative and qualitative research techniques,
methods, approaches, concepts or language into a single study (Teddlie &
Tashakkori, 2009). Philosophically, it is the “third wave” or third research
movement, a movement that moves past the paradigm wars by offering a logical
and practical alternative. Philosophically, mixed research makes use of the
pragmatic method and system. Its logic of inquiry includes the use of induction
(or discovery of patterns), deduction (testing of theories and hypotheses), and
abduction (uncovering and relying on the best of a set of explanations for
understanding one’s results). Mixed methods research also is an attempt to
legitimate the use of multiple approaches in answering research questions, rather
than restricting or constraining researchers’ choices (i.e., it rejects dogmatism). It
is an expansive and creative form of research, not a limiting form of research. It is
inclusive, pluralistic, and complementary, and it suggests that researchers take an
eclectic approach to method selection and the thinking about and conduct of
research (Johnson & Onwuegbuzie, 2004).
Figure 3.2 Sequential Embedded Research Design (Creswell & Clark, 2007)
The main purpose of this study was to create and test the effect of instructional design based on multiple representation for quantum physics concepts. The effect of treatment will be examined through a quasi-experimental research design since this study does not include the use of random assignment of participants to both experimental and control groups (Creswell & Clark, 2007; Borg, Borg & Gall, 2003; Creswell, 2008). This research design can be visualized as in Figure 3.3.
Group A O1 X O2
Group B O 1 O2
Figure 3.3 The visual representation of research design for the quantitative study Qualitative
before intervention (Focus Group
Discussion )
Quantitative premeasure
intervention
Quantitative postmeasure
Qualitative after intervention
(in-depth interview)
Qualitative during intervention (informal Observation)
Interpretation based on Quantitative and Qualitative results
[image:30.595.119.465.537.680.2]In Figure 3.3, the symbol of O1 represented the scores obtained through the instruments that would be used as pretests. The experimental class is represented as Group A which experienced the treatment (X) that used instructional based on multiple representations, called experiment group (EG). The Group (B) received only traditional instruction and is represented as control group (CG). The symbols O2 represent scores of the post administration test using the instruments on both experimental and control groups.
The number of focus group discussions have been conducted depends on the project needs and resources and whether different views from separate groups are still emerging. In general, at least two focus group discussions should be conducted among each specific target group. Each group consisted of 6-12 persons. The focus group was conducted between 75 to 90 minutes (Gruden, et al., 2002).
In this study has been formed 5 groups, each group consist of 7-8 persons. The students that will be member of group are pre-service physics teachers who have taken quantum physics concept course.
[image:32.595.105.519.521.751.2]The second qualitative step used informal observation during intervention of the class, and the last step used think aloud semi-structured interviews to know how the students use multiple representations when they encounter a quantum physics learning situation and students’ perception and view about learning quantum physics based on multiple representations. In semi-structured interview engaged about 6 students. Two students from high level understanding of quantum physics concept mastery, two students from medium level, and two students from low level were engaged in the interview. In overall of design of the research was summarized in Table 3.1.
Table 3.1 Summary of research design General Initial Teaching and Learning Design
Proposed Strategy Resources Outcome
Focus group discussions (FGD)
Pre-service Physics teacher students
Literature Review
Proposed Strategy Resources Outcome
Review a wide selection of related research articles in science education, especially physics education research using multiple representation
Library databases, research
articles
Clear understanding of the scope of related research
Identify Key Themes, Ideas and Concepts
Proposed Strategy Resources Outcome
Enter the field with open and responsive research outlook
Lecturer within the Physics Education Program of Mathematics and Science Education Department
Adaptation of an appropriate research methodology
Collect and analyse data from a wide range of sources
Lecturers, students, researchers, examination scripts, lectures, tutorials, virtual laboratories
Adaptation of appropriate data collection and analysis
tools
Identify key categories Analysis software Awareness of emerging concepts
Develop an Interview Based Research Instrument
Proposed Strategy Resources Outcome
Progressively focus toward the initial research questions
Adaptation of appropriate data analysis tools
Isolate the key areas of interest and the key aspects of quantum physics concept learning based on multiple representation
Conduct Interviews
Proposed Strategy Resources Outcome
Interview students
6 Students Development of a
responsive interview protocol
Analyse interview data to identify themes
Categorization of responses
Investigate the Variation in Understanding of Key Quantum Physics Concepts
Proposed Strategy Resources Outcome
Step back from the data and refocus on isolating a set of key concepts relating to the teaching and learning of quantum physics concept
Interview transcripts Adaptation of appropriate research methodology and analysis tools. Mapping the variations in understanding
Link Results
Proposed Strategy Resources Outcome
Analyse the results for trends and connections
Analysis software tools (using SPSS v 16)
Research findings
3.2 The Population and Sample of The Research
3.3 The description of variables of study
[image:35.595.108.509.206.530.2]In this study there were 5 variables that can be classified as dependent and independent variables. Table 3.2 presents a list of those variables.
Table 3.2 Classification of the variables
Variable Type Name Value type Scale type
Dependent Students’ concepts mastery score on Photoelectric effect, Bohr’s atom model, and Schrodinger equation.
continuous interval
Dependent Students’ Generic Science Skills score which integrated photoelectric effect concepts, Bohr’s atom model concepts, and Schrodinger equation concepts.
continuous interval
Dependent Students’ Critical Thinking Disposition score which integrated photoelectric effect concepts, Bohr’s atom model concepts, and Schrodinger equation concepts.
continuous interval
Dependent Re-representation Skill Inventory score
continuous interval
Independent Treatment categorical nominal
Critical Thinking Disposition which include Critical Thinking Disposition-Integrated Photoelectric Effect Scores, Critical Thinking Disposition-Disposition-Integrated Bohr’s Atom Model Concept score, and Critical Thinking Disposition-Integrated Schrodinger Equation Concept scores. The last one of dependent variable is the students re-representation skill score.
The independent variables of this study is the treatment (Multiple representations-based instructions was experienced to experimental group and conventional instructions was experienced to control group) that considered as categorical variable.
3.4 Instruments
Two instruments were used in quantitative study for this research. There were Quantum Physics Survey (QPS) and Re-representation Skills Inventory (RSI). Quantum Physics Survey (QPS) contains 60 multiple choice items which consist of 20 items related to Photoelectric Effect Concepts, 20 items related to Bohr’s Atom Model Concepts and 20 items related to Schrodinger’s Equations Concepts. The QPS was used to measure students’ quantum physics concept mastery achievement and integrated with this also generic science skills and critical thinking disposition (see appendix C). Whereas, the Re-representation Skills Inventory (RSI) is used to assess students’ re-representation ability which it contained 9 essay items.
pre-conception and understanding of using multiple representations in quantum concepts teaching and learning situation and physics problems solving.
3.4.1 Pilot Study of Students’ Quantum Physics Concept Achievement One of the instruments measuring students’ quantum physics performance was the Quantum Physics Survey (QPS). To analyze students’ answers more deeply and to explore their understanding and problem solving skills intensively, multiple choice type questions were used in QPS. QPS consists of 60 multiple choice items: 20 items related to photoelectric effect, 20 items related to Bohr’s atom model, and 20 items related to Schrodinger’s Equations. Almost all of the test items were developed by the researcher and several items were taken from the related literature. These instruments are presented in Appendix D.
Table 3.3 Internal validity of instruments and Difficulty Indices of QPS related to photoelectric effect concept
Item
Pearson
Correlation Sig.(2-tailed) Validity
Difficulty Index
Inferred
q1 0.413 0.010 sig. 0.63 Ok
q2 0.661 0.000 sig. 0.55 Ok
q3 0.406 0.012 sig. 0.53 Ok
q4 0.648 0.000 sig. 0.58 Ok
q5 0.477 0.002 sig. 0.47 Ok
q6 0.587 0.000 Sig. 0.55 Ok
q7 0.512 0.001 sig. 0.58 Ok
q8 0.537 0.001 Sig. 0.58 Ok
q9 0.425 0.008 sig. 0.58 Ok
q10 0.334 0.041 sig. 0.34 modified
q11 0.349 0.032 sig. 0.50 Ok
q12 0.550 0.000 sig. 0.47 Ok
q13 0.390 0.016 sig. 0.26 Ok
q14 0.512 0.001 sig. 0.58 Ok
q15 0.011 0.947 Not sig. 0.34 Replaced
q16 0.618 0.000 sig. 0.50 Ok
q17 0.437 0.006 sig. 0.37 Ok
q18 0.501 0.001 sig. 0.37 Ok
q19 0.063 0.708 Not sig. 0.34 Replaced
q20 0.376 0.020 sig. 0.26 Ok
*. Correlation is significant at the 0.05 level (2-tailed) **
Table 3.4 Internal validity of instruments and Difficulty Indices of QPS related to Bohr’s atom model concepts
Item
Pearson
Correlation Sig.(2-tailed) Validity
Difficulty Index
Inferred
q1 0.415 0.010 sig. 0.68 Ok
q2 0.516 0.001 sig. 0.79 Ok
q3 0.433 0.007 sig. 0.45 Ok
q4 0.253 0.216 sig. 0.45 modified
q5 0.533 0.001 sig. 0.47 Ok
q6 0.700 0.000 sig. 0.47 Ok
q7 0.479 0.002 sig. 0.42 Ok
q8 0.494 0.002 sig. 0.84 Ok
q9 0.388 0.016 sig. 0.63 Ok
q10 0.489 0.002 sig. 0.66 Ok
q11 0.747 0.000 sig. 0.53 Ok
q12 0.394 0.014 sig. 0.50 Ok
q13 0.346 0.033 sig. 0.42 Ok
q14 0.418 0.009 sig. 0.42 Ok
q15 0.176 0.289 Not sig. 0.42 Modified
q16 0.562 0.000 sig. 0.50 Ok
q17 0.373 0.01 sig. 0.45 Ok
q18 0.436 0.006 sig. 0.53 Ok
q19 0.466 0.003 sig. 0.39 Ok
q20 0.526 0.001 sig. 0.50 Ok
N 38
*. Correlation is significant at the 0.05 level (2-tailed). **
Table 3.5 Internal validity of instruments and Difficulty Indices of QPS related to Schrodinger’s equation concepts
Item
Pearson
Correlation Sig.(2-tailed) Validity
Difficulty Index
Inferred
q1 0.552 0.000 sig. 0.68 Ok
q2 -0.094 0.576 Not sig. 0.26 Replaced
q3 0.788 0.000 sig. 0.55 Ok
q4 0.383 0.018 sig. 0.55 Ok
q5 0.513 0.001 sig. 0.71 Ok
q6 0.507 0.001 sig. 0.55 Ok
q7 0.665 0.000 sig. 0.63 Ok
q8 0.496 0.002 sig. 0.58 Ok
q9 0.338 0.038 sig. 0.61 Ok
q10 0.495 0.002 sig. 0.45 Ok
q11 0.822 0.000 sig. 0.55 Ok
q12 0.543 0.000 sig. 0.66 Ok
q13 0.439 0.006 sig. 0.71 Ok
q14 0.361 0.026 sig. 0.61 Ok
q15 0.608 0.000 sig. 0.55 Ok
q16 0.541 0.000 sig. 0.53 Ok
q17 0.417 0.009 sig. 0.55 Ok
q18 0.666 0.000 sig. 0.50 Ok
q19 0.642 0.000 sig. 0.53 Ok
q20 -0.059 0.725 Not sig. 0.47 Replaced
N 38
*. Correlation is significant at the 0.05 level (2-tailed). **
.Criteria for Difficulty index : 0-0.3 difficult; 0.3-0.7 middle; 0.7-1.0 easy
3.4.2 Pilot Study of Generic Science Skills (GSS)-Concepts Integrated
Internal consistency reliability estimate for the GSS was measured by Cronbach alpha using SPSS v.16 to be 0.806 for GSS-photoelectric concepts integrated, 0.841 for GSS-Bohr’s atom model concepts integrated, and 0.852 GSS-Schrodinger’s equation concepts integrated respectively. A reliability coefficient of 0.70 or higher allows a norm-referenced test to be used with confidence. Whereas, validity analyses using Pearson correlation showed that the instruments have significance internal validity.
3.4.3 Pilot Study of Critical Thinking Disposition (CTD)-Concepts Integrated Internal consistency reliability estimate for the CTD was measured by Cronbach alpha using SPSS v.16 to be 0.739 for CTD-integrated photoelectric concepts, 0.709 for CTDI- Bohr’s atom model concepts integrated, and 0.805 for CTD-Schrodinger’s equation concepts integrated respectively. A reliability coefficient of 0.70 or higher allows a norm-referenced test to be used with confidence. Whereas, validity analyses using Pearson correlation showed that the instruments have significance internal validity.
3.4.4 Pilot Study of Re-representation Skills Inventory (RSI)
mathematical) of representing the problem. They were asked to choose difference of the representations to solve the given problem. The crucial point of this survey was that the students were required to translate representation mode the problems to other representation in solving the solutions of problems.
The pilot study of RSI was carried out with 38 pre-service physics student. Internal consistency reliability estimate for the RSI was measured by Cronbach alpha using SPSS v.16 to be 0.747. A reliability coefficient of 0.70 or higher allows a norm-referenced test to be used with confidence. Whereas, validity analyses using person correlation showed that the instruments have significance internal validity.
3.4.5 Focus Group Discussion Guiding Question and Interview Task Protocol (ITP)
In general, there were three types of questions, the aim of asking the first type of questions is to know about students’ pre-conception and representation context in physics.
Four type of questions were aimed to obtain information about their use of multiple representations in quantum physics concept teaching and learning. Each question had one quantum physics concept context and needed generalization. The students were questioned on why they chose one type of representation over others both to engaged in learning and solve physics problem.
3.5 The design of Quantum Physics Concept Instruction based on Multiple Representation
[image:44.595.119.508.369.683.2]The research has reformed an environment lecture of quantum physics concept course for pre-service physics teacher students by gradually changing both the content structures and the learning techniques implemented in lecture and homework based on multiple representations. Traditionally this course has been taught in a manner similar to the equivalent course for physics majors, focusing on mathematical solutions of abstract concept, including photoelectric concept, Bohr Atom model, and Schrodinger equation. Based on the trialogue style using IF-SO frame work in instructional design (figure 3.4), it was necessary determine that students in a reform-style quantum physics concept course are learning a broader set of representational performance than those in a more traditional course (Figure 3.5)
Figure 3.5 The characteristic of the instructional environmental design of a multiple representation based on IF-SO framework
IF-SO Frame work base on teaching Photoelectric effect, Bohr Atom Model, and
Schrodinger Equation Identify Key Concept
Focus on Characteristic of knowledge structures
Provide multiple representations Present applications
(sciences and technology)
Focus on form and function
Verbal Representation : Oral and Text vbooks
vpapers vmagazine vweb page
Visual Static Representation vTables
vGraphics vPictorial
Hands on Representation (Experiments) vvirtual
Visual Dynamic Representation vPhysics Simulations (Phet) Mathematic Representation
vGenerate own representation on equation of photoelectric effect from text book and web page
Analogy
vGenerate own representation on photoelectric effect using analogy (web page searching and create the similar analogy)
Sequence
Based on :
In order to provide precise sequences this instructional environment design, we associated the idea of conceptual change, which assumes that learning is a substitution of a scientific concept for a misconception or previous ideas that the student already possessed. For this reason, we included this set of sequence of learning design and learning processes:
1) Evaluating of previous concepts
2) Determining goals of the learning and objectives in each level for knowing student’s conceptual capture (diagnostic, formative and summative)
3) Selection of resources to help to the learner (texts, images, experiment, simulation, analogy etc)
4) Producing activities (virtual task, quizzes, essays, projects, and tests) 5) Developing interaction (collaborative work, peer works, with lecturers,
web page and web blog)
6) Integral evaluation: diagnostic, formative and summative.
The second factor will contribute in learning design and learning process is the change of representation or multiple representations format in learning process; this factor is associated with the abstraction levels, like the figure 3.6. The student will passes through of an abstraction level to another one. Thus, with the multiple representation approach, we can create a constructivist-learning environment:
2 max 0
max max
2 1
,
mv eV
E
E h
E B
= =
−
= υ
2) Work on the complexity of this microscopic phenomenon (investigation of interaction between electrons and photons using simulation and analogy) 3) Contextualize activities (experiment using virtual laboratory)
4) Provide technological applications for photoelectric effect concept (weblog and web page activity)
5) Support collaborative work and interaction with peers and lecturer (including homework activity)
(a) (b)
(c) (d)
[image:47.595.106.556.213.674.2]For details of how the students were engaged in during the treatment in this study: the experimental group was primarily given activities based on multiple representations. This approach presents and develops concepts through verbal (oral and writing), symbolic and equation, graphical, pictorial, tabular/bar , analogy and simulation. To illustrate, for understanding the concept of Einstein’s equation for photoelectric effect was first introduced from a numerically intuitive approach in which tables were used to collect the data and refine them on activity sheet from virtual laboratory. Then a verbal representation was used to verbally complement what was the relationship among the numbers in the other modes of representation. Finally, a transition and generate own representation was made to the quantum physics concept using graph, analogy and simulation.
The usage of multiple representations varied for each activity presented in this treatment. For instance, for the topic of photoelectric effect, first the pictorial representation then the verbal representations were constructed. Student was given chance to generate their own representation modes, such as developing symbolic and equation from graph or data observation from virtual laboratory experiment through simulation physics. However, for conceptualizing the concept of Planck’s constant from a graph, first, the mathematical and symbolic representation, and then the other representations including verbal and simulation were used.
modes as well. For example, students were not only required to translate graphical representation to mathematical/equation but also vice versa. It was aimed to make students to understand that the final achieving point is not the mathematical/equation form; the translation from an algebraic type of representation to a graphical one was also appreciated. Activities were given to the students and they were responsible to deal with them.
Table 3.6 The construct of the lesson plan of experimental group Learning
Structure and outcomes
Student Activity Lecturer Activity Goal of Activity
Introduction : 15 minutes
• Become aware that lesson will begin to start • Know what
lesson will cover and what will happen during the lesson
Listen to
explanation of lesson
• Open lesson • Distribute
today’s activity sheet
• Explain the main idea of today’s activity and promote some guide questions for understanding a topics
• Defining the problem
• Observing
• Forming the question
• Articulating the expectation
Body (Main
activities) : 125 Minutes
• Understand the main concept of the lesson
• Make all
necessary translations among
representations mode
• Do the
exercise physics problem solving
•Work in each group
•Take notes •Fill activity
sheet
•Discuss the
ideas to
translate among
representations mode with the other students •Group
presentation : present the results
representations
mode is
created
• Guide students when necessary
• Investigating the known • Carrying out the
study
• Communicating with others
• Examining the result
Conclusion : 10 minutes
• Recall and consolidates experiences
•Recall and share the main concept of the topic
• Review main points of lesson
However, treatment in control group was given a conventional quantum physics based on direct instruction can be characterized by its emphasis on procedural skills and manipulating only symbolic/mathematical expressions. In control groups the teacher usually begin by providing the rules for operations for manipulating mathematical concepts. After providing students with this rule, the teacher demonstrated several examples that incorporated the rule. The same process was then repeated for the other rules and procedures. Throughout the lesson presentation the teacher asked for questions from the students and asked them to help for solving the equation. The students in control groups were responsible for listening to the teacher, taking notes from the whiteboard, and solving the questions that the teacher asked to them.
3.6 Data Analysis Procedure
In order to uncover the role of multiple representations-based instruction on pre-service physics teacher students’ quantum physics performance, critical thinking disposition, and science generic skills, both quantitative and qualitative analyses of data proposed by the research questions will used. Onwuegbuzie and Teddlie (Johnson & Onwuegbuzie,2004) proposes seven-stage conceptualization of the mixed methods data analysis process. According to these authors, the seven data analysis stages are as follows: (a) data reduction, (b) data display, (c) data transformation, (d) data correlation, (e) data consolidation, (f) data comparison, and (g) data integration.
Figure 3.7 Sequential mixed method data analyses procedures Focus Group
Interview
Qualitative data analyzed
Inferences drawn from
qualitative data
Treatment Quasi-Experiment
Quantitative data analyzed
Inferences drawn from quantitative
data
Interview Conducted Additional
interview questions developed Semi-structured
Interview Task Protocol
Interview Conducted
Inferences drawn from
qualitative data
3.6.1 Quantitative Data Analyses
Quantitative data analyses will be classified as descriptive and inferential statistics. All the statistical analyses were carried out by using both Spread Sheet Excel and SPSS version 16. Data is initially examined to obtain descriptive statistics of the mean, median, mode, standard deviation, skewness, kurtosis, maximum and minimum values, and the describing graphs were presented in this part of statistics for experimental and controls groups involved in this study. To test the null hypothesis, the statistical technique of Mann-Whitney U Test (Minium, King, & Bear, 1993) will used for comparing the mean scores of control and experimental groups separately on the Quantum Physics Survey (QPS) and Re-representations Skills Inventory (RSI).
All quantitative data will used in term N-gain normalized score which could be gained from formula:
pre pre post
S S
S S
− − = −
max
gain
N (Meltzer, 2002)
3.6.2 Qualitative Data Analysis
All interviews were videotaped and then transcribed. When it finished transcribing the interviews, it will be used EZ-TEXT 3.06 to help analyze the transcriptions. I used EZ-TEXT 3.06 to create four categories to place students’ responses. Then the categories is constructed based upon expert-like problem solving strategies. The different categories show different ways students use representations to help solve problems. The categories are: (a) Participants used representations to understand the problem/concept; (b) Participants used representations to help solve the problem; (c) Participants used representations to evaluate their work and or answers; (d) Participants used representations to check for the consistency of other representations.
CHAPTER 5
CONCLUSION AND IMPLICATION
5.1 Conclusion
Based on the overall results of the study could be concluded that:
a) Student are more likely to use existing representation from a domain resource than to generate their own representation, use mathematical representation in learning and physics problem solving, and their representations (SR) are strongly dependent on teacher/lecturer’s representation (TR)
b) Students’ preconception in quantum physics is strongly influenced by classical physics conceptions and students’ misconceptions in several quantum physics concepts have been repaired through multiple representation-based instructions.
c) Multiple Representations-based instructions has been developed by using IF-SO framework approach appropriately with specific quantum physics concepts such as Photoelectric Effect, Bohr’s Atom Model, and Schrodinger Equations.
d) This research study has documented that multiple representations-based instruction versus the conventional instruction did make a significant influence on the quantum physics mastery, generic science skills, and critical thinking disposition of pre-service physics teacher students.
f) The result of semi-structured interviews indicated that the experimental group students used variety of representations in learning quantum physics and were capable of using the most appropriate one for the given quantum physics concept problems.
g) Most of the students mentioned that the multiple representations-based instructions were appropriate to enhance understanding and quantum physics concepts mastery. Therefore they had some inspirations how to create an innovative teaching and learning physics instructions.
5.2 Implication of Study
5.2.1 Implications for teaching practice
Effectiveness physics instruction needs more than lecturing. It requires active involvement of the students in physics learning process. Multiple representations-based instructions meets this need in physics classroom.
In interviews students agreed the idea that they like to be engaged in all kinds of representations for solving quantum physics problems. Therefore, teachers should emphasize applications of multiple representations. In a very simple way, establishing relationships between representational modes can be conducted in part of a daily lesson by making students to think about any situation that represents a physical object. Besides, allowing students to create their own representations, such as analogy makes them more creative and flexible in physics situation. However, students should be given an opportunity that they can use representations that they invent or create variety of modes representation in learning physics.
knowledge (CK), Pedagogical Content Knowledge (PCK), and Pedagogical Knowledge (PK).
One further implication can be suggested for the school physics textbooks and other teaching materials. The physics textbooks for elementary until high schools students are lacking of connections among representational modes of mathematical concepts. Almost of physics textbooks only served to include the symbolic and mathematical modes of representations. It will be beneficial to include other representational modes in addition to the symbolic and mathematical modes. Textbooks should not consider these representational modes as separated topics, but should give a clear attention to the translations and relationships among them.
The usage of multiple representations should also be valued in the new physics curriculum due to its various advantages. Multiple representations based instruction should be implemented in various topic in physics curriculum, such as mechanics, waves, energy, electricity, and heat and thermodynamics. The involvement of multiple representations in physics curriculum will accordingly make teachers or lecturers give more importance to multiple representations in instruction.
5.2.2 Theoretical Implications
modes of representations. Though it was not the intentional to look for evidence to support the theories considering multiple representations, it is consistent with the learning experiences in the current study.
The current study does not agree with the idea that students might be confused when they are provided with more than one representation. If translations among representation modes are established, they can develop deeper understanding and more likely to use different representation modes for solving one problem, instead of being lost in variety of representations. This view is supported by the statement in many previous studies. As noted by some researchers that a conceptual analysis of existing multiple representational learning environments suggests there are three main functions that multiple external representations (MERs) serve in learning situations - to complement, constrain and construct. The first function is to use representations that contain complementary information or support complementary cognitive processes. In the second, one representation is used to constrain possible (miss) interpretations in the use of another. Finally, MERs can be used to encourage learners to construct a deeper understanding of a situation.
5.3 Recommendations for Further Research
Generally, having known what students gathered from multiple representation-based instructions in this research study suggests some ideas for further research studies in physics classrooms. In this manner, future research can focus on teachers representation skills and teaching strategies in physics based on multiple representation and other science subject matter such as biology and chemistry courses. All of the data for this study was collected from students. Future research could combine data from students and their teachers/lecturers, because teachers/lecturers have also impact on shaping students’ representation preferences. What teaching strategies and representation types are used within physics classrooms by teachers and how those representations are conceptualized by the students seems to be worthwhile to study. Some students during the interviews claimed that they prefer to use mathematical mode of representation to solve quantum physics problems because it seems to them more mathematical and they were taught with more emphasis on this kind of representation during learning physics as wel
