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研究生: 鐘敏綺
Chung, Min-Chi
論文名稱: 以擴增實境表徵學習數學分數概念對學生學習理解之影響
The Effects of learning through Augmented Reality Representations on Students’ Understanding of Fraction
指導教授: 王健華
Wang, Chien-Hwa
學位類別: 碩士
Master
系所名稱: 圖文傳播學系
Department of Graphic Arts and Communications
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 71
中文關鍵詞: 數位學習表徵擴增實境分數學習
英文關鍵詞: e-learning, representations, augmented reality, fraction learning
DOI URL: http://doi.org/10.6345/THE.NTNU.DGAC.006.2019.F05
論文種類: 學術論文
相關次數: 點閱:207下載:32
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  • 表徵(Representations)常見於STEM教學當中,教師在教學中常以圖示、操作物等表徵,將學生難以理解的抽象概念予以具體化。然而,應用表徵進行學習,學生並非能自然而然習得其對應的抽象概念,甚至應用至真實情境當中。此外,大多數低先備知識學生,因無法掌握所學數學概念與生活間之關聯,導致缺乏學習數學的動機,甚至也傾向只注意表徵表層資訊,而無法更深入注意到關鍵資訊。本研究提出以擴增實境技術所創造的表徵 (AR Representations),將數學概念以不同於常見具體或抽象的方式呈現,導引學生從真實情境中出發注意關鍵表徵資訊,來解決以上之問題。為檢測此教具之教學效果,本研究採用準實驗法,並有來自北台灣共101位國小三年級學生參與本次實驗。學生的前後測試卷分數為學生理解之量化數據,高低先備知識則以前測分數進行區別,同時亦採集質性的訪談資料。研究結果顯示,實驗組學生在使用擴增實境表徵學習後,高低先備知識學生之後測成績並不顯著。總結而言,藉由擴增實境表徵學習,低先備知識學生之理解與高先備知識學生之間的差異呈現彌平的趨勢。此外,透過質化訪談討論,更發現這一群學生比起其他組別能將所學應用至更多元的例子中。本研究亦根據結論,提出教育意涵及未來研究建議。

    Representations are widely used in science, technology, engineering, mathematics (STEM) fields. Teachers often make use of representations, such as pictures, manipulatives, to demonstrate abstract concepts, which students find hard to understand, in more concrete and tangible ways. However, it is not automatically that students can pick up the target abstract concepts with those representations. Moreover, learning with pictures in textbooks, students have difficulty in translating from pictures to real-life situations. Nevertheless, most low prior knowledge students are lack of learning motivation in face with the mathematics concepts because they are not able to relate what they learned with their own real-life situations, and vice versa; also tend to pay attention to the task-irrelevant information. With the technique of augmented reality, the present study proposed “AR Representations” instructions, which are different from the well-used concrete or abstract concepts. By redirecting students’ attention to the most relevant information, the instructions aimed to solve the above problems. Thus, quasi-experiments were performed to verify the effectiveness of AR Representations instructions. 101 3rd-grade elementary students in northern Taiwan have participated. Pretest and posttest scores were collected as quantitative data of understanding. Levels of prior knowledge were also derived from pretest scores. Results of this study showed there was no significant difference on students’ understanding between high and low level of prior knowledge after learning with AR Representations. In conclusion, With the aid of AR representations, (1) low prior knowledge students’ understanding would equate with the higher ones’, and (2) low prior knowledge students could identify more novel examples other than textbooks provide. Pedagogical implications and future research are also discussed.

    Chinese Abstract 1 Abstract 2 Table of Content 3 List of Tables 6 List of Figures 7 CHAPTER ONE INTRODUCTION 8 1.1 Background 8 1.1.1 Representations in STEM education 8 1.1.2 Students’ learning difficulty in mathematics 9 1.1.3 The effectiveness of AR in mathematics education 9 1.2 Research purposes and questions 10 1.2.1 Assumption of solution to the problems 10 1.2.2 The process of validating the assumption 11 1.3 Limitations 13 1.4 Definition of terms 13 1.4.1 AR Representations 13 1.4.2 Prior Knowledge 13 1.4.3 Understanding 13 CHAPTER TWO LITERATURE REVIEW 14 2.1 Learning mediated with representations 14 2.1.1 The effectiveness of representations 14 2.1.2 The mechanism of linking representations 15 2.1.3 External and internal representations 17 2.2 Prior Knowledge 18 2.2.1 The impact of prior knowledge on students’ learning mediated with representations 18 2.2.2 The role of prior knowledge in multimedia intervention 19 2.3 Understanding 19 2.3.1 Procedural and conceptual understanding 19 2.3.2 The impacts of attention on understanding in learning 20 2.4 Learning with AR instruments 20 2.4.1 The benefits of mixed reality 20 2.4.2 AR applications in math 22 2.5 Learning Fractions 24 2.5.1 Common difficulties in learning fraction 24 2.5.2 Fraction teaching applications 24 2.5.3 Learning fractions mediated with representations 25 2.6 Summary 25 CHAPTER THREE RESEARCH METHOD 27 3.1 Research Framework 27 3.2 Participants 28 3.3 Instruments 29 3.3.1 Fraction Understanding Test 29 3.3.2 Interview Questions 31 3.4 Instructional Design for AR Representations 31 3.4.1 Design principles 31 3.4.2 Development of AR Representations 33 3.5 Procedure 37 3.6 Data analysis 39 CHAPTER FOUR RESULTS AND DISCUSSION 40 4.1 Results 40 4.1.1 RQ1: Overall, do instruction treatments (picture/ AR) affect students’ understanding? 40 4.1.2 RQ2: Is there a significant difference between learning with pictures and AR representations on students’ understanding? 41 4.1.3 RQ3: Is there a significant difference between high and low prior knowledge on students’ understanding? 43 4.1.4 RQ4: Whether the level of prior knowledge has an interaction effect with representations on students’ understanding? 43 4.1.5 RQ A1: Is there a significant difference between high and low prior knowledge on understanding in picture representation group? 43 4.1.6 RQ A2: Is there a significant difference between high and low prior knowledge on understanding in AR representation group? 45 4.1.7 Interview data 46 4.2 Discussion 47 4.2.1 Multiple representations facilitated by AR Representations 47 4.2.2 "Concrete-Pictorial-Abstract" sequences of AR Representations 48 4.2.3 High and low level of prior knowledge students’ perception to AR Representations 49 4.2.4 Enhancement of analogical thinking with personal experiences 51 CHAPTER FIVE CONCLUSION AND SUGGESTIONS 52 5.1 Conclusion 52 5.1.1 With the aid of AR Representations, low prior knowledge students’ understanding would equate with the higher ones’ 52 5.1.2 With the aid of AR representations, low prior knowledge students could identify more novel examples other than textbooks provide 53 5.2 Contributions of the study 53 5.2.1 Creation of real-life representations by integrating CPA transition and AR technique 53 5.2.2 Non-3D mathematics AR overlay 54 5.3 Limitations of the study 54 5.4 Suggestions for Future Research 55 5.4.1 The applicable scope of non-3D AR Representations 55 5.4.2 Discovery learning with AR Representations 55 5.4.3 Graphical analogical thinking 56 REFERENCES 57 APPENDICES 64 Appendix A: Understanding pretest 64 Appendix B: Understanding posttest 67 Appendix C: Pictures treatment instructions 70

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