在這個科技進步迅速、3C產品蓬勃發展的時代，網路上充斥著各式各樣的資訊與文章，當人們遇到有待考證的科普文章、數據圖或統計數據時，是否有足夠的能力來理解數據圖及辨別其正確性是相當重要的。本研究探討34位非理工科系大學生在科普文章中的數據圖理解表現，以及了解有無修習統計相關課程、數據圖理解自我效能與數據圖理解表現之間的關聯性。研究工具的設計是根據Curcio（1987）的數據圖理解理論、洪振方（2015）團隊「數據建模能力」一系列相關研究中的「解釋、統整、應用數據模型能力」進行研究工具之設計，最後整合出四個層次的數據圖理解任務：讀取數據、數值比較、多層數值比較、預測趨勢，且根據任務彙整、設計出一份科普文章與測驗，以及選用Li等人（2018）的數據圖理解自我效能量表、潘怡如（2014）的科學自我效能量表這兩份量表，整合成一份自我效能量表。
研究結果顯示：(1)無論是整體表現、讀取數據、數值比較，受試者在「散佈圖」的理解任務表現是四種數據圖中最差的，而在多層數值比較中堆疊長條圖的表現是最差的。而從四種數據圖的「數值比較」進行錯誤分析，可以發現皆有一部份受試者是因在進行數值比較前讀取數據時發生錯誤，代表進行數值比較或是多層數值比較時，對受試者來說還是滿常讀取數據錯誤。此外，受試者在比值、相關程度、迴歸直線、斜率、截距等概念上較有困難。(2)大部分的題型有修習統計相關課程者與無修習統計相關課程者之間數據圖理解表現並無顯著差異，僅在「堆疊長條圖的讀取數據」此題型中有修習統計相關課程者的分數表現顯著低於無修習統計相關課程者。(3)有修習統計相關課程之學生數據圖理解自我效能顯著高於無修習統計相關課程之學生。受試者數據圖理解自我效能量表之得分，與在堆疊長條圖的總得分、堆疊長條圖的多層數值比較任務得分皆達顯著中度正相關。

In the era of rapid progress in science and technology, as well as vigorous development of 3C products, various information and articles can be found on the Internet. When people encounter popular science articles, graphs and statistical data that need to be verified, whether they are equipped to comprehend graphs and discern the correctness is quite important. This study aims to investigate the performance of graph comprehension in popular science articles of 34 non-science-major university students, and the relationship among graph comprehension performance, graph self-efficacy and whether students take statistics-related courses in university or not. The instruments were developed based on Curcio's (1987) theory of graph comprehension and Hung's (2015) "data modeling ability" including "interpreting, integrating and applying data modeling abilities." Finally, four levels of graph comprehension tasks were created: reading the data, comparing the data, multi-comparing the data, predicting the trends. A popular science article and a comprehension test were designed based on four levels of graph comprehension tasks. In addition, the graph self-efficacy scale of Li et al. (2018) and the scientific self-efficacy scale of Pan (2014) were combined as the graph self-efficacy scale in this study.
The results showed that: (1) Performance in overall, "reading the data", "comparing the data" tasks were worst for "scatterplots" among the four types of graphs. In addition, performance in the "multi-comparing the data" task was worst in "stacked bar chart". In the "comparing the data" task, some students' mistakes were found at the level of "reading the data". Furthermore, students had difficulties about ratio, correlation, regression lines, slopes and intercepts. (2) In most items, whether students take statistics-related courses in university did not make a difference. The difference was found in the "reading the data" task with "stacked bar chart", in which students who take statistics-related courses performed worse than those who do not. (3) Graph self-efficacy was significantly higher for students who take statistics-related courses. In addition, scores in graph self-efficacy scale developed by Li et al. (2018) moderately and positively correlated with overall scores of "stacked bar chart" and scores of the "multi-comparing the data" task with "stacked bar chart".

王意淳（2020）。中學生在熱量與比熱單元數據建模能力之分析。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
何仕仁、吳裕益、黃台珠（2007）。科學自我效能量表之發展。科學教育學刊，15(6)，613-626。
李宜穎（2016）。家長參與、自我概念與科學學習成就影響之探討－以TIMSS 2011臺灣八年級學生資料為例。未出版之碩士論文，國立彰化師範大學教育研究所，彰化縣。
李啟讓（2019）。運用虛擬實驗翻轉教學與虛擬實驗討論教學促進高中生對氣體定律的數據建模能力之研究。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
李德竹（2000）。資訊素養的意義、內涵與演變。圖書與資訊學刊，35，1-25。
林麗華、林清文（2003）。國中生數學科學習之目標導向、社會比較、自我效能與課業壓力關係研究。彰化師大輔導學報，(25)，87-132。
洪振方（2015）。嵌入虛擬實驗與後設認知的數據建模教學促進國中生高層次思考的能力。高雄市：國立高雄師範大學（科技部計畫編號：MOST104-2511-S-017-004-MY3）
洪瑞宏（2018）。嵌入電腦模擬的討論式教學對提升九年級學生電學數據建模能力之成效。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
翁郁凰（2017）。探討不同學習成就九年級學生熱量與比熱數據建模能力。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
張雅雯（2019）。探討不同密度概念理解程度八年級學生密度數據建模能力。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
教育部（2018）。十二年國民基本教育課程綱要－國民中小學暨普通型高級中等學校：自然科學領域。
傅彥閣（2019）。探討以科學建模為基礎的討論式教學對提升偏鄉國中學生直線運動數據建模能力的成效。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
楊育茱（2016）。家長參與、自我概念與數學學業成就影響之探討-以TIMSS 2011臺灣八年級學生資料為例。未出版之碩士論文，國立彰化師範大學教育研究所，彰化縣。
楊維明（2017）。虛擬實驗融入數據建模教學對國中生力與運動學習成效之影響。 未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
葉懿珍（2017）。融入虛擬實驗的討論式教學對國中生數據建模能力之影響─以熱量與比熱單元為例。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
潘怡如（2014）。以科學新聞提升中學生論證能力之探討。未出版之碩士論文，國立中山大學教育研究所在職專班，高雄市。
蔡宗哲（2017）。探討不同鷹架需求量之八年級學生的數據建模能力─以吹箭為例。未出版之碩士論文，國立高雄師範大學科學教育暨環境教育研究所，高雄市。
鄭立婷、魯盈讌、洪瑞兒、許文怡（2021）。情境式探究論證導向教學提升國中生 STEM 素養之成效。科學教育學刊，29(4)，299-323。
蕭建華（2013）。介入自我效能對高一學生地球科學學習成效之影響。未出版之博士論文，國立臺灣師範大學地球科學研究所，臺北市。
賴幸穗（2019）。自我效能、適應性完美主義、性別及教師自主支持對15歲學生科學學習興趣之影響：跨層次交互作用的檢驗。未出版之碩士論文，銘傳大學教育研究所碩士在職專班，新北市。
薛岳（2011）。新北市某國中八年級學生數學科學業自我概念、學習策略與學業成就之研究。未出版之碩士論文，銘傳大學教育研究所碩士在職專班，新北市。
藍鑫怡（2020）。新住民子女文化資本、數學自我概念與數學學習成就關係之研究—以TIMSS 2015 臺灣八年級學生資料為例。未出版之碩士論文，國立彰化師範大學教育研究所，彰化縣。
Ärlebäck, J. B., Blomberg, P., & Nilsson, P. (2014). An instructional design perspective on data modelling for learning statistics and modelling.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Advances in Behaviour Research and Therapy, 1(4), 139-161.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122.
Bandura, A., Freeman, W. H., & Lightsey, R. (1997). Self-efficacy: The exercise of control.
Bertin, J. (1983). Semiology of graphics (2nd ed., W. J. Berg, Trans.). Madison: University of Wisconsin Press. (Original work published 1967)
Binali, T., Chang, C. H., Chang, Y. J., & Chang, H. Y. (2022). High School and College Students’ Graph-Interpretation Competence in Scientific and Daily Contexts of Data Visualization. Science & Education, 1-23.
Brown, P. L., Concannon, J. P., Marx, D., Donaldson, C., & Black, A. (2016). An examination of middle school students’ STEM self-efficacy with relation to interest and perceptions of STEM. Journal of STEM Education, 17(3), 27-38.
Cooley, C. H. (1922). Human nature and social order. New York: Charles Scribner's Sons, 35-50.
Curcio, F. R. (1987). Comprehension of mathematical relationships expressed in graphs. Journal for Research in Mathematics Education, 18(5), 382-393.
Falco, L. D., & Summers, J. J. (2019). Improving career decision self-efficacy and STEM self-efficacy in high school girls: Evaluation of an intervention. Journal of Career Development, 46(1), 62-76.
Friel, S. N., Curcio, F. R., & Bright, G. W. (2001). Making sense of graphs: Critical factors influencing comprehension and instructional implications. Journal for Research in Mathematics Education, 32(2), 124-158.
Gott, R., & Duggan, S. (2003). Understanding and Using Scientific Evidence: How to Critically Evaluate Data. London: SAGE Publications.
Komarraju, M., & Nadler, D. (2013). Self-efficacy and academic achievement: Why do implicit beliefs, goals, and effort regulation matter. Learning and Individual Differences, 25, 67-72.
Lee, S., Kim, S. H., & Kwon, B. C. (2016). VLAT: Development of a visualization literacy assessment test. IEEE Transactions on Visualization and Computer Graphics, 23(1), 551-560.
Li, N. T., Brossard, D., Scheufele, D. A., Wilson, P. H., & Rose, K. M. (2018). Communicating data: interactive infographics, scientific data and credibility.
Margolis, H., & McCabe, P. P. (2006). Improving self-efficacy and motivation: What to do, what to say. Intervention in School and Clinic, 41(4), 218-227.
Mead, G. H. (1934). Mind, self, and society (Vol. 111). Chicago: University of Chicago press.
Mukuka, A., Mutarutinya, V., & Balimuttajjo, S. (2021). Mediating effect of self-efficacy on the relationship between instruction and students’ mathematical reasoning. Journal on Mathematics Education, 12(1), 73-92.
Rogers, C. R. (1951). Perceptual reorganization in client-centered therapy.
Saroughi, M., & Cheema, J. R. (2023). Examining the link between science self efficacy and science performance: evidence from a US assessment. SN Social Sciences, 3(12), 206.
Shavelson, R. J., Hubner, J. J., & Stanton, G. C. (1976). Self-concept: Validation of construct interpretations. Review of Educational Research, 46(3), 407-441.
Wood, R. (1968). Objectives in the teaching of mathematics. Educational Research, 10, 83-98.