化學是探討原子或分子等微觀粒子間關係的物質科學，但這些看不見的粒子對於學生而言是抽象而難以想像的。其中「分子形狀」的概念難以實際觀察，因此學生面對分子形狀等內容時，常有理論模型混淆、流於公式計算等狀況。擴增實境具有將二維材料三維化，將看不見的物體可視化與提供即時互動等特性，已有多個研究指出此技術能有效地提升學習成效。因此本研究設計以分子形狀為主題的擴增實境學習材料，探討此材料是否影響分子形狀概念的學習成效。過往的研究方法大多僅利用前後測的紙筆測驗探討學生的學習表現，較少討論其使用擴增實境學習材料的學習歷程，而且也有部分研究指出科技輔助學習材料會因學習者差異而有不同的影響情況。因此，本研究透過眼動儀對學習者視覺注意力落點與時間的紀錄來探討不同特性的學習者的理解情形。
　　本研究首先測試33位高一學生對分子形狀概念的先備知識，並以眼球追蹤技術記錄受試者於AR系統中的訊息處理模式，最後再以分子形狀測驗了解受試者對於分子形狀概念的理解情況，並以三份學習者特性量表瞭解學習者差異。在資料分析方面，研究者利用前後測t-test瞭解AR系統對於分子形狀概念理解的成效，以描述性統計說明受試者於AR系統的訊息處理模式，並以皮爾森相關性分析瞭解學習表現、訊息處理模式、學習者特性之間的相關性，再進一步透過回歸分析找出學習表現的預測因子。
　　研究結果顯示擴增實境學習材料能促進分子形狀概念之理解，且學習者特性可能為影響受試者於擴增實境環境時訊息處理模式的因素。擴增實境系統中3D圖像上的訊息統整以及其對擴增實境系統的注意力是影響學習表現的關鍵因素。於因此，研究者建議可將擴增實境材料應用於教學現場，且擴增實境系統的設計上，可能以3D靜態圖像的為主，動態及互動為輔。

In Chemistry, concepts related to microscopic particles such as"molecular shapes” are abstract and difficult for students to observe or imagine. When learning concepts of molecular shapes, students often feel confused about the theoretical models. In the study we developed an Augmented Reality activity for students to learn the concepts of “molecular shapes.” Augmented reality has the characteristics of changing 2D representations into 3D objects, visualizing invisible objects, and providing real-time interaction. Several studies have pointed out that it can effectively improve the learning achievement. Accordingly, one aim of this study is to explore whether the AR activity could improve the learning of molecular shapes. In most of previous studies, researchers used paper-and-pen tests to explore students' learning achievements. Students’ learning process was often negleted. In the study, the eye tracking method was employed to analyze the learning process. In addition, it has been mentioned in some studies that technology-assisted learning materials have different effects on learners with different characteristics. Therefore, this study will also explore the how learners characteristics may affect AR learning.
　　This study tested the prior knowledge of the molecular shape concept of 33 high school students, and used eye tracking technology to record the subject’s information processing mode in the AR system, and finally used the molecular shape test to understand the subject’s concept of molecular shape. Collecting learner characteristics through three scales. In terms of data analysis, the researchers used the pre- and post-test t-test to understand the effectiveness of the AR system in understanding the concept of molecular shapes, used descriptive statistics to illustrate the information processing of the subjects in the AR system, and used Pearson correlation analysis to understand learning performance , Information processing, learner characteristics, and then further through regression analysis to find predictors of learning performance.
　　The results showed that AR learning materials can promote the understanding of molecular shape concepts, and learner characteristics may be factors that affect the message processing patterns of subjects in AR. The integration effort on the information on the 3D images in the AR system and the motivational factor of attention to the AR App are the key factors that affected the learning performance. Accordingly, it was suggested that AR can be applied to the teaching, and the design of the AR may be mainly based on 3D static images, supplemented by dynamics and interaction.

中文文獻探討
行政院(2018)。107年個人家戶數位機會調查報告(未出版的統計數據)。取自https://www.ndc.gov.tw/Default.aspx
林樹聲、 黃柏鴻 (2009)。國小六年級學生在社會性科學議題教學中之論證能力研究-不同學業成就學生間之比較。科學教育學刊，17(2)，111-133。
邱美虹（2008）。模型與建模能力之理論架構。科學教育月刊，306，2-9。
邱美虹、唐尉天（2014）。行動科技、擴增實境與3D實驗影片教學：行動科技與擴增實境在科學教育上的應用。臺灣化學教育期刊，1(3)，257-263。
陳盈利(2015)。國小五年級新移民與非新移民學生的科學認識觀與科學態度之比較研究(未出版的碩士論文)。國立彰化師範大學科學教育研究所，彰化。
陳學志、賴惠德、邱發忠（2010）。眼球追蹤技術在學習與教育上的應用。教育科學研究期刊，55(4)，39-68。
劉香瑤、李麗菁、蔡今中（2007）。科學認識觀與社會性科學議題抉擇判斷之相關性探討。科學教育學刊，15(3)，335-356。

英文文獻探討
Alemdag, E., & Cagiltay, K. (2018). A systematic review of eye tracking research on multimedia learning. Computers & Education, 125, 413-428.
Alemdag, E., & Cagiltay, K. (2018). A systematic review of eye tracking research on multimedia learning. Computers & Education, 125, 413-428.
Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001). Recent advances in augmented reality. IEEE Computer Graphics and Applications, 21(6), 34-47.
Behmke, D., Kerven, D., Lutz, R., Paredes, J., Pennington, R., Brannock, E., ... & Stevens, K. (2018). Augmented reality chemistry: transforming 2-D molecular representations into interactive 3-D structures. In Proceedings of the Interdisciplinary STEM Teaching and Learning Conference (Vol. 2, No. 1, pp. 4-12).
Chen, S. C., Hsiao, M. S., & She, H. C. (2015). The effects of static versus dynamic 3D representations on 10th grade students’ atomic orbital mental model construction: Evidence from eye movement behaviors. Computers in Human Behavior, 53, 169-180.
Chen, Y. C. (2006, June). A study of comparing the use of augmented reality and physical models in chemistry education. In Proceedings of the 2006 ACM international conference on Virtual reality continuum and its applications (pp. 369-372).
Chen, Z. H., & Chen, S. Y. (2014). When educational agents meet surrogate competition: Impacts of competitive educational agents on students' motivation and performance. Computers & Education, 75, 274-281.
Cheng, K. H., & Tsai, C. C. (2013). Affordances of augmented reality in science learning: Suggestions for future research. Journal of science education and technology, 22(4), 449-462.
Conley, A. M., Pintrich, P. R., Vekiri, I., & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29, 186–204.
Conley, A. M., Pintrich, P. R., Vekiri, I., & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary educational psychology, 29(2), 186-204.
Davis. F. (1989). Perceived Usefulness, Perceived Ease of Use, and End User Acceptance of Information Technology. MIS Quarterly, 318-340.
Freitas, R., & Campos, P. (2008, September). SMART: a SysteM of Augmented Reality for Teaching 2 nd grade students. In Proceedings of the 22nd British HCI Group Annual Conference on People and Computers: Culture, Creativity, Interaction-Volume 2 (pp. 27-30). BCS Learning & Development Ltd..
Gilbert, J. K., Boulter, C. J., & Elmer, R.(2000). Positioning models inscience education and in design and technology education. In J. K.Gilbert & C. J. Boulter (Eds.),Developing Models in Science Education (pp. 3-17). Dordrecht,The Netherlands: Kluwer Academic Publisher.
Gilbert, S. W. (1991). Model building and definition of science. Journal of Research in Science Teaching, 28,73-79.
Hammer, D. (1994). Epistemological beliefs in introductory physics. Cognition and Instruction,12(2), 151-183.
Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88-140
Hudley, C., Daoud, A., Polanco, T., Wright-Castro, R., & Hershberg, R. (2003). Student Engagement, School Climate, and Future Expectations in High School.
Johnstone, A. H. (1993). The development of chemistry teaching: A changing　response to changing demand. Journal of chemical education, 70(9), 701.
Johnstone, A. H. (2000). Teaching of Chemistry - Logical or Psychological? Chem. Educ.
Just, M. A., & Carpenter, P. A. (1980). A theory of reading: from eye fixations to comprehension. Psychological review, 87(4), 329-354
Klopfer, E., & Sheldon, J. (2010). Augmenting your own reality: Student authoring of science‐based augmented reality games. New directions for youth development, 2010(128), 85-94.
Lai, M. L., Tsai, M. J., Yang*, F. Y., Hsu, C. Y., Liu, T. C., Lee, S. W. Y., Lee, M. H., Chiou, G. L., Liang, J. C., & Tsai, C. C. (2013). A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educational Research Review, 10, 90- 115.
Liversedge, S., Gilchrist, I., & Everling, S. (Eds.), (2011). The oxford handbook of eye　movements. NY: Oxford University Press.
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychology, 38(1), 43-52.
Milgram, P., Takemura, H., Utsumi, A., & Kishino, F. (1994). Augmented reality: a class of displays on the reality–virtuality continuum. Proceedings the SPIE: Telemanipulator and Telepresence Technologies, 2351, 282–292
O’Keefe, P. A., Letourneau, S. M., Homer, B. D., Schwartz, R. N., & Plass, J. L. (2014). Learning from multiple representations: An examination of fixation patterns in a science simulation. Computers in Human Behavior, 35, 234-242.
Pierce, R., Stacey, K., & Barkatsas, A. (2007). A scale for monitoring students’ attitudes to learning mathematics with technology. Computers & Education, 48(2), 285-300.
Prensky, M. (2001). Digital natives, digital immigrants. On the horizon, 9(5).
Radu, I. (2012, November). Why should my students use AR? A comparative review of the educational impacts of augmented-reality. In 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (pp. 313-314). IEEE.Res. Pract., 1(1), 9–15.
Ryder, J., Leach, J., & Driver, R. (1999). Undergraduate science students’ images of science. Journal of Research in Science Teaching, 36, 201-219.
Sweller, J. (2011). Cognitive load theory. In Psychology of learning and motivation (Vol. 55, pp. 37-76). Academic Press.
Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2002). Students’ understanding of the role of scientific models in learning science. International Journal of Science Education, 24(4), 357-368
Tsai, C. C. (1998). An analysis of scientific epistemological beliefs and learning orientations of Taiwanese eighth graders. Science Education, 82(4), 473-489.
Tsai, C. C., Ho, H. N. J., Liang, J. C., & Lin, H. M. (2011). Scientific epistemic beliefs, conceptions of learning science and self-efficacy of learning science among high school students. Learning and Instruction, 21(6), 757-769.
Wang, C. Y., & Barrow, L. H. (2011). Characteristics and levels of sophistication: An analysis of chemistry students’ ability to think with mental models. Research in Science Education, 41(4), 561-586.
Wu, H. K., Lee, S. W. Y., Chang, H. Y., & Liang, J. C. (2013). Current status, opportunities and challenges of augmented reality in education. Computers & education, 62, 41-49.
Yang, F. Y. (2017). Examining the reasoning of conflicting science information from the information processing perspective—an eye movement analysis. Journal of Research in Science Teaching, 54(10), 1347-1372.
Yang, F. Y., Tsai, M. L., Chiou, G. L., Lee, S. W. Y., Chang, C. C., & Chen, L. L. (2018). Instructional suggestions supporting science learning in digital environments based on a review of eye tracking studies. Educational Technology & Society, 21 (2), 28-45.