本研究利用大學入學考試中心，96-100學年度指考化學考科的試題進行分析研究，主要的方向包括不同類別考生成績的表現、試題類型、試題難度、學生作答上較困難試題與非選擇題考生作答分析。
在不同類別考生成績的表現，是以全體參與96-100學年度的考生為比較的基礎；而試題類型、試題難度、學生作答上較困難試題與非選擇題考生作答分析，則採取一組9所學校的學生，分布區域在臺灣的北、中、南三個地區，並含有指考化學考科高、中、低三種成績組合。以100學年度而言，此組學校學生人數共計1,038位，對照全體考生，其成績分布卡方檢定值為17.03小於23.68，該組合學校的學生樣本，可以代表全體考生的分布。不同類別考生成績表現而言，採敘述統計方式；就試題類型，是採因素分析、階層性集群分析與專家判斷法；試題難度採多元迴歸分析；學生作答上較困難試題調查則採專家問卷調查方式；考生非選擇題作答則採類型分析方式。
本研究結果顯示，指考化學考科的成績表現，就不同類別考生而言，是男生優於女生、非應屆優於應屆、公立優於私立、學校規模愈大，考生成績愈好。其中，男女與畢業別的差異，效果量小於.2、學校別差異的效果量介於.2~.5、學校規模差異的效果量則是介於.5~.8。以試題類型而言，指考化學考科有三種主要的試題類型，其試題難度呈現階層性關係並具有顯著性差異；就影響試題難度的因素而言，本研究利用四種試題的屬性，對試題難度變異的解釋力可達64%；利用難度預估的迴歸方程式，計算化學考科5年113題所得的難度值與實測值之間比較，若以四種難度類別作區分，大部分是屬於同一類別或差別一個難度類別，僅1題差別兩個難度類別；關於學生作答上較困難的原因，與上述影響試題難度的變項相近，有些則是屬於學生的迷思概念；考生非選擇題的作答分析發現，不同年度的非選擇題，考生的作答表現，可以分類成不同的層級，並可找出考生實際作答的例子進行驗證。未來可嘗試不同科目或不同測驗的試題難度研究，以及教學上如何增進學生較高階認知能力等方向進行。

The purpose of this study was to investigate the items in chemistry of 2007-2011 Department Required Test (DRT) of College Entrance Examination Center (CEEC). The main purposes of this study are to compare the relationships of the student’s characteristics and chemistry test grade of DRT, to analyze the item formats, item difficulty, student’s poor performance items and response patterns of open-ended questions.
Except comparing the total students of 2007-2011 involving the DRT chemistry test, the researcher also sampled a group of 9 school students, which including the northern, middle, and southern areas of Taiwan, and with different DRT chemistry achievements. According to chi-square test, this sampling was an appropriate combination. By the methods of factor analysis, cluster analysis, multiple regression analysis, questionnaire analysis, and response patterns analysis, this study had following results.
Firstly, the performance of students varied with gender, retaken the test or not, and school type. The male students outperformed than the female ; the retaken students got better scores than the first-taken ones; the public school students performed better than those of private schools; the larger the schools were, the better performance were the students. But, the difference of gender and taking times did not have small effect size, and the difference of school type had small to medium, and the difference of school size had medium to large effect size. Secondly, there were three item formats in various years’ tests, and the passing rate also showed hierarchical relationships of these three item formats. Thirdly, the multiple regression analysis showed that there were four item attributes with great effect on item difficulty which accounted for 64% variance. Lastly, the reasons of student’s poor performance items were similar to those item attributes, besides that some student’s poor performance due to the misconceptions, and according to the response patterns of open-ended questions, the student’s performance has divided with different procedural and conceptual knowledge levels. Taken together, this study has provided methodology of item analysis and an example for other subjects. Furthermore, the item analysis also gives great help for school instruction and future item-writing.

大學入學考試中心（2011）。99課綱（102年開始實施）學科能力測驗暨指定科目考試各考科考試說明公告。2011年12月24日取自http://www.ceec.edu.tw/99課綱考試說明/1000930/99課綱考試說明.htm。
王文竹、方俊民、林志彪、施正雄、吳國良（1998）。指定科目考試規劃研究Ⅰ（化學科）。台北：大學入學考試中心。
王文竹、何國榮、林志彪、陸大榮、吳國良（1999）。指定科目考試規劃研究Ⅱ（化學科）。台北：大學入學考試中心。
朱惠文、區雅倫（2009）。 大學入學考試中心題庫實作與評鑑-以數學科為例。考試學刊，7，113-132。
余民寧、趙珮晴、許嘉家（2009）。影響國中小女學生學業成就與學習興趣因素-以臺灣國際數學與科學教育成就趨勢調查（TIMSS）資料為例。教育資料與研究，89，79-104。
吳皇慶、張俊彥（2011）。地球科學動畫試題的設計與應用。考試學刊，9，77-88。
吳國良（2010）。大考中心維持試題穩定與鑑別度的機制。選才電子報，第193期。2011年12月20日取自http://www.ceec.edu.tw/CeecMag/Articles/193/193-06.htm
吳國良（2011）。100學年度指定科目考試化學考科試題分析報告。台北：大學入學考試中心。
吳國良、邱美虹（2011）。高中化學成就測驗的試題類型與考生答題結果分析。科學教育月刊（投稿中）。
吳國良、陳泰然（2011）。99課綱與學科能力測驗自然考科相關議題之研究。考試學刊，9，49-76。
吳國良、程暐瀅（2007）。電腦螢幕閱卷的試辦與後續研究。考試學刊，2，133-156。
吳國良、蔡尚芳、邱美虹（2008）。學科能力測驗自然考科的發展歷史與未來展望。考試學刊，4，27-57。
李明燕（2011）。大學入學考試地理科試題結構之研究。考試學刊，9，1-24。
林大森（2002）。高中/高職的公立/私立分流對地位取得之影響。教育與心理研究，25，35-62。
林世華、葉嘉惠（1999）。數字系列完成測驗試題認知成份分析之研究。教育心理學報，31，139-165。
林如章、王忠茂、姚清發、郭崑圖、吳國良（2002）。90年度指定科目考試化學考科試題研發工作計畫。台北：大學入學考試中心。
林光賢（1990）。高中生的抽樣方法研究。台北：大學入學考試中心。
招聯會（2011）。大學多元入學方案流程圖。2012年6月2日取自http://www.jbcrc.edu.tw/left-32.htm#top
涂柏原、梁恩琪、翁大德、楊毅立（2004）。國中基本學力測驗自然科試題分析研究。論文發表於國立台南師範學院主辦「科技化測驗與能力指標評量國際研討會」。台南：國立台南師範學院。
洪碧霞、林素微、林娟如（2006）。認知複雜度分析架構對TASA-MAT六年級線上測驗試題難度的解釋力。教育研究發展期刊，2，69-86。
翁春和、蕭次融、林萬寅、謝明惠、羅左財、吳國良（2000）。指定科目考試規劃研究Ⅲ（化學科）。台北：大學入學考試中心。
區雅倫、朱惠文、王俐婷、徐發興、連秋華（2007）。 大學入學考試中心題庫之建置。考試學刊，2，109-132。
張芳全（2006）。影響數學成就因素探討：以臺灣在TIMSS 2003年的樣本為例。課程與教學季刊，9，151~168。
張銘秋、謝秀月、徐秋月（2009）。 PISA科學素養之試題認知成份分析。課程與教學季刊：基本能力評量之各國經驗比較，13，1-19。
教育部（2005）。普通高級中學課程暫行綱要。台北：教育部。
教育部（2008）。普通高級中學課程綱要。台北：教育部。
曹亮吉、朱惠文（2007）。數學科難易度主觀預估與客觀反應。考試學刊，3，59-80。
曹亮吉、程暐瀅（2003）。學科能力測驗與指定科目考試的命題理念與方向。文教新潮，2，12-18。
許擇基、吳家怡、李明燕、吳國良（2000）。用間接資訊來等化測驗。台北：大學入學考試中心。
陳竹亭（2010）。普通高級中學化學科99課綱制定理念、特色與教科書編審用考的教育功能。考試學刊，8，137-146。
陳竹亭、李遠鵬、陸天堯、鄭建鴻、吳國良（2001）。指定科目考試規劃研究Ⅳ（化學科）。台北：大學入學考試中心。
陳亮君（2006）。台灣地區高級中等學校之公私立別、地區、規模與教育資源對學業成就之影響。國立政治大學教育學系行政組碩士論文，未出版，臺北市。
程暐瀅（2009）。物理科通過率主觀預估方法的探究。考試學刊，7，81-112。
程暐瀅、區雅倫、朱惠文、林秀慧（2010）。100學年度大學入學考試選擇題新計分方式說明。選才電子報，第192期。2011年12月20日取自http://www.ceec.edu.tw/CeecMag/Articles/192/192-05.pdf。
監察院（2010）。人權調查報告第0990800662號。人權主題網。2011年12月24日取自http://humanrights.cy.gov.tw/AP_HOME/Op_Upload/eDoc/調查報告/99/0990005970990801644公布版.pdf。
駱明慶（2002）。誰是台大學生？性別、省籍和城鄉差異。經濟論文叢刊，1，113-147。
薛荷玉（2007）。國中數學要補才會好？ 2009年8月18日取自http://mag.und.com/mag/campus/storypage.jps?f_ART_D=79768
謝孟穎（2003）。家長社經背景與學生學業成就關聯性之研究。教育研究集刊，49，255-287。
羅珮華（2004）。從第三次國際科學與數學教育成就研究後續調查（TIMSS 1999）結果探討國中學生學習成就與學生特質的關係：七個國家之比較。國立臺灣師範大學科學教育研究所博士論文，未出版，臺北市。
Adadan, E., Irving, K.E., & Trundle, K. C. (2009). Impacts of multi-represen tational instruction on high school students’ conceptual understandings of the particulate nature of matter. International Journal of Science Education, 31, 1742-1775.
Adbo, K., & Taber, K. S. (2009). Learners’ mental models of the particle nature of matter: A study of 16-year-old Swedish science students. International Journal of Science Education, 31, 757-786.
Anderson, J. R. (1990). Cognitive psychology (3rd ed.). San Francisco: Freeman.
Anderson, J., Greeno, J., Reder, L., & Simon, H. (2000). Perspectives on learning, thinking, and activity. Educational Researcher, 29, 11-13.
Anderson, W., & Krathwohl, D. R. (Eds.) (2001). A taxonomy, for learning, teaching, and assessing: A revision of Blooms educational objectives. New York, NY: Longman.
Bailin, S. (2002). Critical thinking and science education. Science & Education, 11, 361-375.
Bloom, B. S. (1956). Taxonomy of educational objectives. New York: Longmans, Green & Co.
Bucat, R. (2004). Pedagogical content knowledge as away forward: Applied research in chemcitry education. Chemistry Education Research and Practice, 5,215-228.
Buck, P., Johnson, P., Fischler, H., Peuckert, J., & Seifert, S. (2001). The need for and the role of metacognition in teaching and learning the particle model. In H. Behrendt, Dahncke, H., Duit, R., Graeber, W., Komorek, M., Kross, A. (Ed.), Research in Science Education - Past, Present, and Future (pp. 225-234). Dordrecht,The Netherlands: Kluwer Academic Publishers.
Catell, R. B. (1965). The scientific analysis of personality. Baltimore, MD: Penguin.
Catell, R. B. & Vogelmann, S. (1977). A comprehensive trial of the scree and kg criteria for determining the number of factors. Multivariate Behavioral Research. 12, 289-325.
Chang, C. Y., & Cheng, W. Y. (2008) Science Achievement and Students’ Self-confidence and Interest in Science: A Taiwanese representative Sample study. International Journal of Science Education, 30, 1183-1200.
Chen, L. S. (2006). On varying the difficulty of test items. A paper presented at the 32nd Annual Conference of the International Association for Educational Assessment, Singapore, May 2006.
Chi, M. T. H. (1992). Conceptual change within and across ontological categories: Implications for learning and discovery in sciences. In R. Giere (Ed.), Cognitive models of science: Minnesota studies in the philosophy of science (pp.129-186). Minneapolis: University of Minnesota Press.
Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. The Journal of the Learning Sciences, 142, 161-199.
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981) Categorization and representation of physics problems by experts and novices. Cognitive Science. 5,121-52.
Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.) (1988). The nature of expertise. Hillsdale, NJ: Erlbaum.
Chi, M. T. H., Slotta, J. D., & deLeeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts, Learning and instruction, 4, 27-43.
Chittleborough, G. D., & Treagust, D. F. (2007). The modeling ability of non-major chemistry students and their understanding of the sub-microscopic level. Chemistry Education: Research and Practice, 8, 274-292.
Chiu, M. H. (2001). Algorithmic problem solving and conceptual understanding of chemistry by students at a local high school in Taiwan. Proc. Natl. Sci. Counc. ROC 11, 20-38.
Chiu, M. H. (2007). A national survey of students’ conceptions of chemistry in Taiwan. International Journal of Science Education, 29, 421-452.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. (2nd ed.). Hillsdale, NJ: Erlbaum.
Coleman, J. Hoffer, T., & Kilgore, S. (1982).Cognitive outcomes in public and private schools. Sociology of Education, 55, 65-76.
College Board (2009). Total Group Profile Report. Retrieved from http://professionals.collegeboard.com/profdownload/cbs-2009-national-TOTAL-GROUP.pdf6
Costu, B. (2007). Comparison of students’ performance on algorithmic, conceptual and graphical chemistry gas problems. Journal of Science Education and Technology, 16, 379-386.
Cromley, J. G. (2009). Reading achievement and science proficiency: International comparisons from the Programme on International Student Assessment. Reading psychology, 30, 89-118.
Dimitrov, D. M., & Raykav, T. (2003). Validation of cognitive structures: A structural equation modeling approach. Multivariate Behavioral Research, 38, 1-23.
Domin, D. S. (1999). A content analysis of general chemistry laboratory manuals for evidence of higher-order cognitive tasks. Journal of Chemical Education, 76, 109-112.
Duit, R. (2011). Bibliography – STCSE: Students' and Teachers' Conceptions and Science Education. Retrieved from http://www.ipn.uni-kiel.de/aktuell/ stcse/stcse.html. Retrieved 2011.12.24.
Dumais, S. A. (2002). Cultural capital, gender, and school success: The role of habitus. Sociology of Education, 75, 44-68.
Emmerich, W. (1989,). Appraising the cognitive features of subject tests (Educational Testing Service Report No. ETS-RR-89-53). Princeton, NJ: Educational Testing Service.
Enright, M. K., Allen, N., & Kim, M. (1993). A complexity analysis of items from a survey of academic achievement in the life sciences (Research report RR-93-18). Princeton, NJ：Educational Testing Service.
Facione, P. A. (1990). Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction, a report for the American Philosophical Association.
Fiorea, S.M., Cuevasa, H.M., & Oser, R.L. (2003). A picture is worth a thousand connections：The facilitative effects of diagrams on mental model development and task performance. Computers in Human Behavior, 19, 185-199.
Flum, H., & Kaplan, A. (2006). Exploratory orientation as an educational goal. Educational Psychologist, 41, 99-110.
Gabel, D. L. (1999). Improving teaching and learning through chemistry education research: A look to the future. Journal of Chemical Education, 76, 548-554.
Gagne, E. D., Walker Yekovich, C., & Yekovich, F. R. (1993). The cognitive psychology of school learning, 2nd edition. Harper Collins, New York, 59-113.
Garnett, P.J., Garnett, P.J., & Hackling, M.W. (1995). Refocusing the chemistry lab：A case for laboratory-based investigation. Australian Science Teachers Journal, 41, 26-32.
Glaser, E. M. (1941). An experiment in the development of critical thinking. Teacher’s College, Columbic University.
Gorin, J.S. (2005). Manipulating processing difficult of reading comprehension questions: The feasibility of verbal item generation. Journal of Educational Measurement, 42, 351-373.
Gorin, J. S., & Embretson, S. E. (2006). Item difficult modeling of paragraph comprehension items. Applied Psychological Measurement, 30, 394-411.
Gorodetsky, M., & Gussarsky, E. (1986). Misconceptualisation of the chemical equilibrium concept as revealed by different evaluation methods. European Journal of Science Education. 8, 427-441.
Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill.
Gussarsky, E., & Gorodetsky, M. (1990). On the chemical “equilibrium concept”: The associative framework.. Journal of Research in Science Teaching. 27, 197-204.
Hirvonnen P. E., & Virii, J. (2002). Physics student teachers’ ideas about the objectives of practical work. Science & Education, 11, 305-316.
Hodson, D. (1990). A critical look at practical work in school science. School Science Review, 70, 33-40.
Hofstein, A. (2004). The laboratory in chemistry education：Thirty years of experience with development, implementation and evaluation. Chemistry Education Research and Practice, 5, 247-264.
Hofstein, A., & Lunetta, V. N. (1982).The role of the laboratory in science teaching: Neglected aspects of research. Review of Educational Research, 52, 201-217.
Hofstein, A., & Lunetta, V. (2004). The laboratory in science education：Foundations for the twenty-first century. Science Education, 88, 25-54.
Hsu, T. C., Wu, K. L., Yu, J. Y Wu., & Lee, M. Y. (2002) Exploring the feasibility of collateral information test equating. International Journal of Testing, 2, 1-14.
Johnstone, A. H. J. (1993). The development of chemistry teaching. Journal of Chemical Education, 73, 701-705.
Johnstone, A. H. J. (2000). Teaching of chemistry logical or psychological? Chemistry education: research and practice in Europe, 1, 9-15.
Johnstone, A. H. J. (2006). Chemical education research in Glasgow in perspective. Chemistry Education Research and Practice, 7, 49-63.
Johnstone, A.H., & Al-shuaili, A. (2001). Learning in the laboratory：Some thoughts from the literature. University Chemistry Education, 5, 42-51.
Kaiser, H. F. (1958). The Varimax criterion for analytic rotation in factor analysis. Psychometrica, 23, 187-200.
Khattab, N. (2002). Social capital students’ perceptions and educational aspirations among palestinian students in Israel. Research in Education, 68, 77-88.
Kintsch, W. (1998). Comprehension: A paradigm for cognition. New York: Cambridge University Press.
Kozma, R.B., & Russell, J. (2005). Students becoming chemists：Developing representational competence. In J.K. Gilbert (Ed.), Visualization in Science Education (pp.121-146). Dordrecht, the Netherlands：Springer.
Krajcik, J.S. (1991). Developing students’ understanding of chemical concepts. In S.M. Glynn, R.H. Yeang, & B.K. Britton (Eds.), The psychology of learning science (pp.117-147). Hillsdale, NJ：Lawrence Erlbaum Associates.
Kuhn, D. (2005). Education for thinking. Cambridge, MA：Harvard University Press.
Kuhn, D. (2007). Is direct instruction and answer to the right question？Educational Psychologist, 42, 109-113.
Lai, K, & Griffin, P. (2001). Linking cognitive psychology and item response models. Paper presented at the annual conference of the Australian Association for Research in Education, Perth.
Landgraf, Kurt M. (2003). Using Assessments and Accountability to Raise Student Achievement. Educational Testing Service. ED 482 280.
Lareau, A. (2002). Invisible inequality: Social class and child reading in black families and white families. American Sociological Review, 67, 747-776.
Lee, K. W. L., Tang, W., Goh, N., & Chia, L. (2001). The predicting role of cognitive variables in problem solving in mole concept. Chemistry Education: Research and Practice in Europe, 2, 285-301.
Liang, J. C., Chou, C. C., & Chiu, M. H. (2011). Student test performances on behavior of gas particles and mismatch of teacher predictions. Chemistry Education Research and Practice, 12, 238–250.
Lin, Q., Kirsch, P., & Turner, R. (1996). Numeric and conceptual understanding of general chemistry at a minority institution. Journal of Chemical Education, 73, 1003-1005.
Lindquist, E. F. (1958). The nature of the problem of improving scholarship and college entrance examinations. In Invitational conference on testing problems (pp. 104-113). Princeton, NJ: Educational Testing Service.
Lohman, D. F. (1988). Spatial abilities as traits, processes, and knowledge. In R. J. Sternberg (Ed.), Advances in the Psychology of Human Intelligence, 4, 181-248. Hillsdale, NJ: Erlbaum.
Martin, M. O., Gregory, K. D., & Stemler, S. E. (2000). TIMSS 1999 Technical Report: IEA’s Repeat of the Third International Mathematics and Science Study at the Eighth Grade. Chestnut Hill, MA: Boston College.
Maskill, R., & Cachapuz, A, F. C. (1989). Learning about the chemistry topic of equilibrium: the use of word association tests to detect developing conceptualizations. International Journal of Science Education. 11, 57-69.
Mason, S. D., Shell, D. F., & Crawley, F. E. (1997). Differences in problem solving by nonscience majors in introductory chemistry on paired algorithmic-conceptual problems. Journal of Research in Science Teaching, 34, 905-923.
Mayer, R. (2002). Cognitive theory and the design of multimedia instruction. New Directions for Teaching and Learning, 89, 55-71.
Mayer, R. (2003). The promise of multimedia learning：Using the same instructional design methods across different media. Learning and Instruction, 13, 125-139.
Moje, E. B. (2007). Developing socially just subject-matter instruction: A review of the literature on disciplinary literacy. In L. Parker (Ed.), Review of research in education, (pp. 1-44). Washington, DC: American Educational Research Association.
Monteyne, K., Mark S., & Cracolice, M. S. (2004). What’s wrong with cookbooks (reply to Ault). Journal of Chemical Education, 81, 1559-1560.
Nakhleh, M. B.(1993). Are our students conceptual thinkers or algorithmic problem solvers? Journal of Chemical Education, 70, 52-55.
Nakhleh, M. B., & Mitchell, R. C. (1993). Concept learning versus problem solving: there is a difference. Journal of Chemical Education, 70, 190-192.
National Research Council (1995). National Science Education Standards. Washington, DC: National Academy Press.
Niaz, M. (1995). Relationship between student performance on conceptual and computational problems of chemical equilibrium. International Journal of Science Education, 17, 343-355.
Niaz, M., & Robinson, W. R. (1993). Teaching algorithmic problem solving or conceptual understanding: role of development level, mental capacity, and cognitive style. Journal of Science Education and Technology, 2, 407-416
Noddings, N. (2006). Critical lessons：What our schools should teach. New York：Cambridge University Press.
Novick, S., Nussbaum, J. (1978). Junior High School pupils' understanding of the particulate nature of matter: An interview study. Science Education, 62, 273-281.
Novick, S., Nussbaum, J. (1981). Pupils' understanding of the particulate nature of matter: A cross-age study. Science Education, 65, 187-196.
Nurrenbern, S., & Pickering, M. (1987). Concept learning versus problem solving. Is there a difference? Journal of Chemical Education, 64, 508-510.
Olson, D. (2003). Psychological theory and educational reform：How school remarks mind and society. New York：Cambridge University Press.
Pearson, P. D., Moje, E. B.,& Greenleaf, C. (2010). Literacy and science-Each in the service of the other. Science, 328, 459-463.
Pellegrino, J. W., Chudowsky, N., & Glaser, R. (Eds.) (2001). Knowing what students know: The science and design of educational assessment. Center for Education, National Research Council.
Peterson, R. F., Treagust, D. F., & Garnett, P. J. (1989). Development and application of a diagnostic instrument to evaluate grade-11 and grade-12 students' concepts of covalent bonding and structure following a course of instruction. Journal of Research in Science Teaching, 26, 301-314.
Pickering, M. (1990). Further studies on concept learning versus problem solving. Journal of Chemical Education, 67, 254-255.
Pintrich, P. R., Marx, R. W., & Boyle, R. A. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of educational research, 63, 167-199.
Pushkin, D. (2007). Critical thinking and problem solving-the theory behind flexible thinking and skills development. Journal of Science Education, 8, 13-17.
Quine, W. V., & Ullian, J. S. (1978). The Web of Beief (2nd edition). McGraw-Hill Education.
Resnick, L. B., & Glaser, R. (1975). Problem solving and intelligence. Retrieved from http://eric.ed.gov./PDFS/ED111727.pdf
Rosca, R. J. (2004). What makes a science item difficulty-A study of TIMSS-R items using regression and the Linear Logistic Test Model. Lynch Graduate School of Education, Boston College.
Rutherford, F. J., & Ahlgren, A. (1990). Science for All Americans. New York : Oxford University Press.
Sanger, M.J., & Phelps, A.J. (2007). What are students thinking when they pick their answer？ A content analysis of students’ explanations of gas properties. Journal of Chemical Education, 84, 870-874.
Sawrey, B. A. (1990). Concept learning versus problem solving: Revisited. Journal of Chemical Education, 67, 253-254.
Scheumeman, J., Gerritz, K., & Embretson, S. E. (1991). Effect of prose complexity achievement test item difficulty (Educational Testing Service Report No. ETS-RR-91-43). Princeton, NJ: Educational Testing Service.
Schmeiser, C. B., & Welch, C. J. (2006). Test development. In R.L. Brennan (Ed.) Educational Measurement (4th ed). New York: American Council on Education.
Schmidt, H. J. (1992). Conceptual difficulties with isomerism. Journal of Research in Science Teaching, 29, 995-1003.
Schoenfeld, A. H. (1978). Can heuristics be taught? In Lochhead, J, & Clement, J. J. (Eds). Cognitive Process instruction, Franklin Institute Press, Philadelphia, 315-338.
Stamovlasis, D., Tsaparlis, G., Kamilatos, C., Papaoikonomou, D., & Zarotiadou, E. (2004). Conceptual understanding versus algorithmic problem solving: A principal component analysis of a national examination. The Chemical Educator, 9, 398-405.
Stamovlasis, D., Tsaparlis, G., Kamilatos, C., Papaoikonomou, D. & Zarotiadou, E. (2005). Conceptual understanding versus algorithmic problem solving : Further evidence from a national chemistry examination. Chemistry Education Research and Practice, 6, 104-118.
Taber, K. S. (1994). Misunderstanding the ionic bond. Education in Chemistry, 7, 100-102.
Talanquer, V. (2009). On cognitive constrains and learning progressions: The case of “structure of matter”. International Journal of Science Education, 31, 2123-2136.
Treagust, D. F.,& Chittleborough, G. D. (2001). Chemistry: A matter of understanding repre-sentations. In J. Brophy (Ed.), Subject-specific instructional methods and activities (Vol. 8, pp. 239-267). Oxford: Elsevier Science Ltd.
van de Werfhorst, H. G.,& Kraaykamp, G. (2001). Four field-related educational resources and their impact on labor, consumption, and sociopolitical orientation. Sociology of Education, 74, 296-317.
Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and instruction, 4, 45-69.
Vosniadou, S., & Brewer, W. F. (1992). Mental models of the earth: A study of conceptual change in children. Cognitive psychology, 24, 535-585.
Webb, P. (2010). Science Education and Literacy: Imperatives for the Developed and Developing World. Science, 328, 448-450.
Wu, K. L., & Chiu, M. H. ( in prep.). A traditional experiment with a new perspective for inspiring student’s learning in chemistry. Chemistry Education Research and Practice.
Yepes-Barays, M. (1996). A cognitive study based on the NAEP science assessment. Office of Educational Research and Improvement, Washington, DC.
Yepes-Barays, M. (1997). Lessons learned from the coding of item attributes for the 1996 NAEP science assessment G4. Paper presented at the Annual meeting of the National Council in Measurement in Education, Chicago.
Yilmaz, A., Tuncer, G., & Alp, E. (2007). An old subject with recent evidence from Turkey: students’ performance on algorithmic and conceptual questions of chemistry. World Applied Sciences Journal, 2, 420-426.
Zoller, U. (1993). Lecture and learning: are they compatible? Maybe for LOCS; unlikely for HOCS. Journal of Chemical Education, 70, 195-197.
Zoller, U., Dori, Y., & Lubezky, A. (2002). Algorithmic, LOCS and HOCS (chemistry) exam question: performance and attitudes of college students. International Journal of Science Education, 24, 185-203.
Zoller, U., Lubezky, A., Nakhleh, M. B., Tessier, B., & Dori, Y. J. (1995). Success on algorithmic and LOCS vs. conceptual chemistry exam questions. Journal of Chemical Education, 72, 987-989.
Zoller, U., & Pushkin, D. (2007). Matching higher-order cognitive skills (HOCS) promotion goals with problem-based laboratory practice in a freshman organic chemistry course. Chemistry Education Research and Practice, 8, 153-171.
Zoller, U., & Tsaparlis, G. (1997). Higher- and lower-order cognitive skills: the case of chemistry. Research in Science Education, 27, 177-130.