無中文摘要

The ability to understand statistical information written in English is prominent given the global status of English and the importance of statistics to understand data, variation and chance which are omnipresent in modern life. Furthermore, college students might need to read and understand statistical results of research in their field of study, while English continues to be the preferred language of scientific communication in most published articles. The main purpose of this research was to investigate the issue concerning the opportunities of learning through reading statistics texts written in English as a second language for Indonesian pre-service English as a Foreign Language (EFL) teachers by taking two components of reading, i.e., reader and text, and the interaction between the two. Accordingly, three studies were compiled to reach the purpose. Initially, Indonesian pre-service EFL teachers’ views on statistics were explored in study one, which involved their values on the learning and conceptions of statistics. Study two concerned on statistics text, in which a framework for analyzing the accessibility of statistics text was developed and subsequently utilized to analyze two versions of college statistics textbooks. By taking the components under one of the accessibility attributes proposed in study two, i.e., the integration of verbal and visual information, six versions of statistics reading materials were designed. Subsequently, study three explored the relationships between different versions of statistics reading materials and students’ reading comprehension. Findings from study one revealed that almost all Indonesian pre-service EFL teachers in this study acknowledged the utility of statistics, yet only 60% of them had a positive intrinsic value in learning the course. Conflicting beliefs expressed by both positive and negative intrinsic value were also found on some students. Meanwhile, three types of conceptions of meanings of data were found underlying the six categories and the three factors of conceptions of statistics: data as numerical numbers, data as numbers in problem contexts; data as information for investigation. Additionally, an instrument for measuring conceptions of statistics was developed and validated in this study. Findings from study two proposed five accessibility attributes of statistics texts, which might reveal not only the strengths and weakness of statistics texts for particular readers, but also to what extent the content knowledge of statistics is presented in the textbooks. The textbooks analysis conducted using the framework revealed several different characteristics between English and Indonesian version textbooks. Indonesian textbook more likely emphasizes on a knowledge-based view of statistics, in which statistical basic knowledge and data as numerical numbers with or without contexts are presented dominantly. English version presents both knowledge based and problem solving views of statistics and more dominantly addresses data as numbers in problem contexts or data as information for investigation. Findings from study three revealed that the verbal information in form of data scales provided on boxplot hinder students reading comprehension. Moreover, providing not scaled-labeled boxplots by sequencing the boxplot before the corresponding verbal information was more favorable for reading comprehension. The implications of the findings and further research were discussed.

Abdelbasit, K. M. (2011). Learning Statistics in a foreign language. In International Encyclopedia of Statistical Science (pp. 729–730). Springer.
Abd-El-Fattah, S. M. (2005). The Effect of Prior Experience with Computers, Statistical Self-Efficacy, and Computer Anxiety on Students’ Achievement in an Introductory Statistics Course: A Partial Least Squares Path Analysis. International Education Journal, 5(5), 71–79.
Acee, T. W., & Weinstein, C. E. (2010). Effects of a value-reappraisal intervention on statistics students’ motivation and performance. The Journal of Experimental Education, 78(4), 487–512.
Aguinis, H., & Branstetter, S. A. (2007). Teaching the concept of the sampling distribution of the mean. Journal of Management Education.
Albrecht, J. E., & O’Brien, E. J. (1993). Updating a mental model: Maintaining both local and global coherence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19(5), 1061.
Aliaga, M., Cobb, G., Cuff, C., Garfield, J. B., Gould, R., Lock, R., … Utts, J. (2005). Guidelines for assessment and instruction in statistics education: College report (Vol. 30). California: American Statistical Association. Retrieved from http://www.amstat.org/education/gaise/
Alloy, L. B., & Tabachnik, N. (1984). Assessment of covariation by humans and animals: The joint influence of prior expectations and current situational information. Psychological Review, 91(1), 112.
Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261–271.
Armbruster, B. B. (1983). The Role of Metacognition in Reading to Learn: A Developmental Perspective. Reading Education Report No. 40.
Atkinson, J. W. (1964). An introduction to motivation. Oxford, England: Van Nostrand.
Badan Standar Nasional Pendidikan. (2006). Standar isi untuk satuan pendidikan dasar dan menengah. Jakarta: Badan Standar Nasional Pendidikan.
Bakker, A. (2004). Design research in statistics education: On symbolizing and computer tools.
Bakker, A., Biehler, R., & Konold, C. (2004). Should young students learn about box plots. Curricular Development in Statistics Education: International Association for Statistical Education, 163–173.
Bakker, A., & Gravemeijer, K. (2004). Learning to reason about distribution. In D. Ben-Zvi & J. B. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp. 147–168). Dordrecht, The Netherlands: Kluwer Academic Publishers.
Bandura, A. (1989). Social cognitive theory. In R. Vasta (Ed.), Annals of child development: Vol. 6. Six theories of child development: Revised formulation and current issues (Vol. 6, pp. 1–60). Greenwich: JAI Press.
Barron, K. E., & Hulleman, C. S. (2015). Expectancy-value-cost model of motivation. In J. Wright (Ed.), International Encyclopedia of the Social & Behavioral Sciences (2nd ed., Vol. 84, pp. 261–271). Oxford: Elsevier Ltd.
Barton, M. L., Heidema, C., & Jordan, D. (2002). Teaching Reading in Mathematics and Science. Educational Leadership, 60(3), 24.
Barwell, R. (2005). Integrating language and content: Issues from the mathematics classroom. Linguistics and Education, 16(2), 205–218. https://doi.org/10.1016/j.linged.2006.01.002
Basturk, R. (2005). The Effectiveness of Computer-Assisted Instruction in Teaching Introductory Statistics. Educational Technology & Society, 8(2), 170–178.
Berenson, S. B. (1997). Language, Diversity, and Assessment in Mathematics Learning. Focus on Learning Problems in Mathematics, 19(4), 1–10.
Biggs, J. B. (1985). The role of metalearning in study processes. British Journal of Educational Psychology, 55(3), 185–212. https://doi.org/10.1111/j.2044-8279.1985.tb02625.x
Biggs, J., & Tang, C. (2011). Teaching for Quality Learning at University: What the Student Does. McGraw-Hill Education (UK).
Bishop, A., FitzSimons, G., Seah, W. T., & Clarkson, P. (1999). Values in Mathematics Education: Making Values Teaching Explicit in the Mathematics Classroom. Presented at the Australian Association for Research in Education Annual Conference. Retrieved from http://files.eric.ed.gov/fulltext/ED453075.pdf
Bliss, T. J., Hilton III, J., Wiley, D., & Thanos, K. (2013). The cost and quality of online open textbooks: Perceptions of community college faculty and students. First Monday, 18(1).
Borasi, R., & Siegel, M. (2000). Reading Counts: Expanding the Role of Reading in Mathematics Classrooms. ERIC.
Braeken, J., & Blömeke, S. (2016). Comparing future teachers’ beliefs across countries: approximate measurement invariance with Bayesian elastic constraints for local item dependence and differential item functioning. Assessment & Evaluation in Higher Education, 41(5), 1–17. https://doi.org/http://dx.doi.org/10.1080/02602938.2016.1161005
Budé, L., Van De Wiel, M. W., Imbos, T., Candel, M., Broers, N. J., & Berger, M. P. (2007). Students’ achievements in a statistics course in relation to motivational aspects and study behaviour. Statistics Education Research Journal, 6(1), 5–21.
Burrill, G., & Biehler, R. (2011). Fundamental statistical ideas in the school curriculum and in training teachers. In Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education (pp. 57–69). Springer.
Carlson, K. A., & Winquist, J. R. (2011). Evaluating an active learning approach to teaching introductory statistics: A classroom workbook approach. Journal of Statistics Education, 19(1), 1–23.
Carnell, L. J. (2008). The effect of a student-designed data collection project on attitudes toward statistics. Journal of Statistics Education, 16(1), 1–15.
Chakrani, B., & Huang, J. L. (2014). The work of ideology: examining class, language use, and attitudes among Moroccan university students. International Journal of Bilingual Education and Bilingualism, 17(1), 1–14.
Chan, S. W., Ismail, Z., & Sumintono, B. (2015). Assessing statistical reasoning in descriptive statistics: A qualitative meta-analysis. Jurnal Teknologi, 72(2), 1–6.
Chance, B., del Mas, R., & Garfield, J. (2004). Reasoning about sampling distribitions. In The challenge of developing statistical literacy, reasoning and thinking (pp. 295–323). Springer.
Charalambous, C. Y., Delaney, S., Hsu, H.-Y., & Mesa, V. (2010). A comparative analysis of the addition and subtraction of fractions in textbooks from three countries. Mathematical Thinking and Learning, 12(2), 117–151.
Cheng, L., Li, M., Kirby, J. R., Qiang, H., & Wade-Woolley, L. (2010). English language immersion and students’ academic achievement in English, Chinese and mathematics. Evaluation & Research in Education, 23(3), 151–169.
Chervany Jr, N. L., Collier, R. O., Fienberg, S. E., Johnson, P. E., & Neter, J. (1977). A framework for the development of measurement instruments for evaluating the introductory statistics course. The American Statistician, 31(1), 17–23.
Clark, R. C., & Mayer, R. E. (2008). Learning by viewing versus learning by doing: Evidence‐based guidelines for principled learning environments. Performance Improvement, 47(9), 5–13.
Cobb, G. (1992). Teaching statistics. Heeding the Call for Change: Suggestions for Curricular Action, 3–43.
Cobb, G. W. (1987). Introductory textbooks: a framework for evaluation: a comparison of 16 books. Journal of the American Statistical Association, 82(397), 321–339.
Collins, K. M., & Onwuegbuzie, A. J. (2002). Reading ability and the performance of African American graduate students in research methodology courses. Journal of College Literacy and Learning, 31, 39–53.
Collins, L. B., & Mittag, K. C. (2005). Effect of calculator technology on student achievement in an introductory statistics course. Statistics Education Research Journal, 4(1), 7–15.
Collins, N. D. (1994). Metacognition and Reading To Learn. ERIC Digest.
Coyle, D., Hood, P., & Marsh, D. (2010). CLIL: Content and language integrated learning. Ernst Klett Sprachen.
Crandall, J. (1987). ESL through Content-Area Instruction: Mathematics, Science, Social Studies. Language in Education: Theory and Practice, No. 69. NY: Prentice Hall, Inc.
Crawford, K., Gordon, S., Nicholas, J., & Prosser, M. (1994). Conceptions of mathematics and how it is learned: The perspectives of students entering university. Learning and Instruction, 4(4), 331–345. https://doi.org/10.1016/0959-4752(94)90005-1
Crawford, K., Gordon, S., Nicholas, J., & Prosser, M. (1998). Qualitatively different experiences of learning mathematics at university. Learning and Instruction, 8(5), 455–468. https://doi.org/10.1016/S0959-4752(98)00005-X
Crawford, K., Gordon, S., Nicholas, J., & Prosser, M. (1998). University mathematics students’ conceptions of mathematics. Studies in Higher Education, 23(1), 87–94.
Cross, R. (2011). Troubling literacy: monolingual assumptions, multilingual contexts, and language teacher expertise. Teachers and Teaching, 17(4), 467–478. https://doi.org/10.1080/13540602.2011.580522
Daniel, F., & Braasch, J. L. (2013a). Application Exercises Improve Transfer of Statistical Knowledge in Real-World Situations. Teaching of Psychology, 0098628313487462.
Daniel, F., & Braasch, J. L. G. (2013b). Application exercises improve transfer of statistical knowledge in real-world situations. Teaching of Psychology, 40(3), 200–207. https://doi.org/10.1177/0098628313487462
Dauphinee, T. L., Schau, C., & Stevens, J. J. (1997). Survey of Attitudes Toward Statistics: Factor structure and factorial invariance for women and men. Structural Equation Modeling: A Multidisciplinary Journal, 4(2), 129–141.
Davis, N. T., & Blanchard, M. R. (2004). Collaborative teams in a university statistics course: A case study of how differing value structures inhibit change. School Science and Mathematics, 104(6), 279–287.
Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and education: The self-determination perspective. Educational Psychologist, 26(3–4), 325–346.
Delcham, H., & Sezer, R. (2010). Write-Skewed: Writing in an Introductory Statistics Course. Education, 130(4), 603–615.
delMas, R. (2002). Statistical literacy, reasoning, and thinking: A commentary. Journal of Statistics Education, 10(3).
delMas, R., Garfield, J. B., & Ooms, A. (2005). Using assessment items to study students’ difficulty reading and interpreting graphical representations of distributions. In Proceedings of the Fourth International Research Forum on Statistical Reasoning, Thinking and Literacy. Auckland, New Zealand: University of Auckland.
Dempster, M., & McCorry, N. K. (2009). The role of previous experience and attitudes toward statistics in statistics assessment outcomes among undergraduate psychology students. Journal of Statistics Education, 17(2), 1–7.
Dixon, L. Q. (2005). Bilingual education policy in Singapore: An analysis of its sociohistorical roots and current academic outcomes. International Journal of Bilingual Education and Bilingualism, 8(1), 25–47.
Draper, R. J., & Siebert, D. (2004). Different Goals, Similar Practices: Making Sense of the Mathematics and Literacy Instruction in aStandards-Based Mathematics Classroom. American Educational Research Journal, 41(4), 927–962.
Dunn, K. (2014). Why Wait? The Influence of Academic Self-Regulation, Intrinsic Motivation, and Statistics Anxiety on Procrastination in Online Statistics. Innovative Higher Education, 39(1), 33–44.
Duranti, A., & Goodwin, C. (1992). Rethinking context: Language as an interactive phenomenon (Vol. 11). Cambridge University Press.
Eccles, J., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., & Midgley, C. (1985). Self-perceptions, task perceptions, socializing influences, and the decision to enroll in mathematics. Women and Mathematics: Balancing the Equation, 95–121.
Eccles, J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., & Midgley, C. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motives: Psychological and sociological approaches (pp. 75–146). California: W.H. Freeman.
Eccles, J. S., & Wigfield, A. (1995). In the Mind of the Actor: The Structure of Adolescents’ Achievement Task Values and Expectancy-Related Beliefs. Personality and Social Psychology Bulletin, 21(3), 215–225. https://doi.org/10.1177/0146167295213003
Eccles, J. S., & Wigfield, A. (2002). Motivational Beliefs, Values, and Goals. Annual Review of Psychology, 53(1), 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153
Ehren, B. J., Murza, K. A., & Malani, M. D. (2012). Disciplinary literacy from a speech–language pathologist’s perspective. Topics in Language Disorders, 32(1), 85–98.
Eitel, A., Scheiter, K., Schüler, A., Nyström, M., & Holmqvist, K. (2013). How a picture facilitates the process of learning from text: Evidence for scaffolding. Learning and Instruction, 28, 48–63.
English, L. D. (2002). Priority themes and issues in international research on mathematics education. In L. D. English (Ed.), Handbook of international research in mathematics education (pp. 3–15). Mahwah, NJ: Lawrence Erlbaum/National Council of Teachers of Mathematics.
Evans, B. (2007). Student attitudes, conceptions, and achievement in introductory undergraduate college statistics. The Mathematics Educator, 17(2), 24–30.
Evnitskaya, N., & Morton, T. (2011). Knowledge construction, meaning-making and interaction in CLIL science classroom communities of practice. Language and Education, 25(2), 109–127.
Falk-Ross, F., & Evans, B. (2014). Word Games: Content Area Teachers’ Use of Vocabulary Strategies to Build Diverse Students’ Reading Competencies. Language and Literacy Spectrum, 24, 84–100.
Fang, Z. (1996). A review of research on teacher beliefs and practices. Educational Research, 38(1), 47–65.
Fang, Z. (2012). Approaches to developing content area literacies: A synthesis and a critique. Journal of Adolescent & Adult Literacy, 56(2), 103–108.
Fang, Z., & Schleppegrell, M. J. (2010). Disciplinary literacies across content areas: Supporting secondary reading through functional language analysis. Journal of Adolescent & Adult Literacy, 53(7), 587–597.
Flake, J. K., Barron, K. E., Hulleman, C., McCoach, B. D., & Welsh, M. E. (2015). Measuring cost: The forgotten component of expectancy-value theory. Contemporary Educational Psychology, 41, 232–244.
Franklin, C. A., & Garfield, J. B. (2006). The GAISE project: Developing statistics education guidelines for grades pre-K-12 and college courses. In G. F. Burrill & P. C. Elliott (Eds.), Thinking and reasoning with data and chance: 2006 NCTM yearbook (pp. 345–376). Reston, VA: National Council of Teachers of Mathematics.
Freedman, E. G., & Shah, P. (2002). Toward a model of knowledge-based graph comprehension. In Diagrammatic representation and inference (pp. 18–30). Springer.
Freitag, M. (1997). Reading and writing in the mathematics classroom. The Mathematics Educator, 8(1), 16–21.
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.
Gal, I. (2002). Adults’ statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1), 1–25.
Gal, I. (2004). Statistical literacy. In The challenge of developing statistical literacy, reasoning and thinking (pp. 47–78). Springer.
Gal, I., Ginsburg, L., & Schau, C. (1997). Monitoring attitudes and beliefs in statistics education. In I. Gal & J. B. Garfield (Eds.), The assessment challenge in statistics education (pp. 37–51). Amsterdam, Netherlands: International Statistical Institute/IOS Press.
Garfield, J. B. (1995). How students learn statistics. International Statistical Review/Revue Internationale de Statistique, 25–34.
Garfield, J. B., & Ben-Zvi, D. (2004). Research on Statistical Literacy, Reasoning, and Thinking: Issues, Challenges, and Implications. In D. Ben-Zvi & J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking (pp. 397–409). Springer Netherlands. Retrieved from http://link.springer.com/chapter/10.1007/1-4020-2278-6_17
Garfield, J. B., & Ben‐Zvi, D. (2007). How students learn statistics revisited: A current review of research on teaching and learning statistics. International Statistical Review, 75(3), 372–396.
Garfield, J. B., & Ben-Zvi, D. (2008a). Developing students’ statistical reasoning. The Netherlands: Springer.
Garfield, J. B., & Ben-Zvi, D. (2008b). Developing students’ statistical reasoning: Connecting research and teaching practice. Springer Science & Business Media.
Garfield, J. B., delMas, R., & Zieffler, A. (2010). Assessing important learning outcomes in introductory tertiary statistics courses. In Assessment Methods in Statistical Education: an International Perspective (pp. 75–86). West Sussex, UK: John Wiley & Sons Ltd.
Garfield, J. B., & Franklin, C. (2011). Assessment of learning, for learning, and as learning in statistics education. In Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education (pp. 133–145). Springer.
Garfield, J. B., & Gal, I. (1999). Assessment and statistics education: Current challenges and directions. International Statistical Review, 67(1), 1–12.
Gernsbacher, M. A. (1990). Language comprehension as structure building. Mahwah, NJ: Erlbaum.
Ghadessy, M., & Nicol, M. (2002). Attitude change in bilingual education: the case of Brunei Darussalam. International Journal of Bilingual Education and Bilingualism, 5(2), 113–128.
Giesbrecht, N. (1996). Strategies for Developing and Delivering Effective Introductory-Level Statistics and Methodology Courses. Retrieved from http://eric.ed.gov/?id=ED393668
Gnaldi, M. (2006). The relationship between poor numerical abilities and subsequent difficulty in accumulating statistical knowledge. Teaching Statistics, 28(2), 49–53.
Goll, P. S. (2009). Gift of Tongues: Passing the Ohio Mathematics Graduation Test. Education, 129(3), 547–555.
Gordon, S. (1995). What Counts for Students Studying Statistics? Higher Education Research and Development, 14(2), 167–184. https://doi.org/10.1080/0729436950140203
Gordon, S. (2004). Understanding students’ experiences of statistics in a service course. Statistics Education Research Journal, 3(1), 40–59.
Gorvine, B. J., & Smith, H. D. (2015). Predicting Student Success in a Psychological Statistics Course Emphasizing Collaborative Learning. Teaching of Psychology, 42(1), 56–59.
Graesser, A. C., Singer, M., & Trabasso, T. (1994). Constructing inferences during narrative text comprehension. Psychological Review, 101(3), 371–395.
Graham, A. (1987). Statistical investigation in the secondary school. New York: Cambridge University Press.
Gunderson, L. (2008). The state of the art of secondary ESL teaching and learning. Journal of Adolescent & Adult Literacy, 52(3), 184–188.
Gunning, T. G. (2003). The role of readability in today’s classrooms. Topics in Language Disorders, 23(3), 175–189.
Gunzel, M., & Binterova, H. (2016). Evaluation of Nonverbal Elements in Mathematics Textbooks. Universal Journal of Educational Research, 4(1), 122–130.
Guthrie, J. T. (1982a). Aims and features of text. In W. Otto & S. White (Eds.), Reading Expository Material (pp. 185--188). New York: Academic.
Guthrie, J. T. (1982b). Aims and features of text.
Hadi-Tabassum, S. (1999). Assessing students’ attitudes & achievements in a multicultural & multilingual science classroom. Multicultural Education, 7(2), 15.
Hall, L. A. (2005). Teachers and content area reading: Attitudes, beliefs and change. Teaching and Teacher Education, 21(4), 403–414.
Hannigan, A., Gill, O., & Leavy, A. M. (2013). An investigation of prospective secondary mathematics teachers’ conceptual knowledge of and attitudes towards statistics. Journal of Mathematics Teacher Education, 16(6), 427–449.
Harmon, L. L., & Pegg, J. (2012). Literacy strategies build connections between introductory biology laboratories and lecture concepts. Journal of College Science Teaching, 41(3), 92.
Harris, L. R., & Brown, G. T. L. (2010). Mixing interview and questionnaire methods: Practical problems in aligning data.
Harwell, M. R., Herrick, M. L., Curtis, D., Mundfrom, D., & Gold, K. (1996). Evaluating statistics texts used in education. Journal of Educational and Behavioral Statistics, 21(1), 3–34.
Heaton, R. M., & Mickelson, W. T. (2002). The learning and teaching of statistical investigation in teaching and teacher education. Journal of Mathematics Teacher Education, 5(1), 35–59.
Hegarty, M., & Just, M.-A. (1993). Constructing mental models of machines from text and diagrams. Journal of Memory and Language, 32(6), 717–742.
Hiebert, J., Gallimore, R., Garnier, H., Givvin, K. B., Hollingsworth, H., & Jacobs, J. (2003). Teaching mathematics in seven countries : results from the TIMSS 1999 video study. DIANE Publishing.
Hiedemann, B., & Jones, S. M. (2010a). Learning statistics at the farmers market? A comparison of academic service learning and case studies in an introductory statistics course. Journal of Statistics Education, 18(3). Retrieved from www.amstat.org/publications/jse/v18n3/hiedemann.pdf
Hiedemann, B., & Jones, S. M. (2010b). Learning statistics at the farmers market? A comparison of academic service learning and case studies in an introductory statistics course. Journal of Statistics Education, 18(3), n3.
Hofstede, G. H. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations (2nd ed.). California: Sage Publications Ltd.
Hogg, R. V. (1990). Statisticians gather to discuss statistical education. Amstat News, 169, 19–20.
Howley, P. P. (2008). Keeping it real, keeping them interested and keeping it in their minds. Journal of Statistics Education, 16(1), 1–19.
Huberty, C. J., & Barton, R. M. (1990). A Review of" Applied Multivariate Statistics Textbooks". Applied Psychological Measurement, 14(1), 95–101.
Hyden, P. (2005). Teaching statistics by taking advantage of the laptop’s ubiquity. New Directions for Teaching and Learning, 2005(101), 37–42.
Idris, K., & Yang, K.-L. (2017). Development and Validation of an Instrument to Measure Indonesian Pre-service Teachers’ Conceptions of Statistics. The Asia-Pacific Education Researcher, 26(5), 281–290. https://doi.org/https://doi.org/10.1007/s40299-017-0348-z
Jäppinen, A. K. (2005). Thinking and content learning of mathematics and science as cognitional development in CLIL. Teaching through a foreign language in Finland. Language and Education, 19, 148–169.
Jian, Y.-C., & Wu, C.-J. (2015). Using eye tracking to investigate semantic and spatial representations of scientific diagrams during text-diagram integration. Journal of Science Education and Technology, 24(1), 43–55.
Jordan, J. (2004). The use of orally recorded exam feedback as a supplement to written comments. Journal of Statistics Education [Online], 12(1). Retrieved from http://www.amstat.org/publications/jse/v12n1/jordan.html
Kaplan, J., Fisher, D., & Rogness, N. (2010). Lexical ambiguity in statistics: how students use and define the words: association, average, confidence, random and spread. Journal of Statistics Education, 18(2), 1–22.
Kaplan, J. J., Fisher, D. G., & Rogness, N. T. (2009). Lexical ambiguity in statistics: What do students know about the words association, average, confidence, random and spread. Journal of Statistics Education, 17(3), 1–19.
Kaplan, J. J., Fisher, D. G., & Rogness, N. T. (2009). Lexical ambiguity in statistics: What do students know about the words association, average, confidence, random and spread. Journal of Statistics Education, 17(3), 1–19.
Kaplan, J. J., Fisher, D. G., & Rogness, N. T. (2010). Lexical ambiguity in statistics: how students use and define the words: association, average, confidence, random and spread. Journal of Statistics Education, 18(2), 1–22.
Kaplan, J. J., Gabrosek, J. G., Curtiss, P., & Malone, C. (2014). Investigating student understanding of histograms. Journal of Statistics Education [Online], 22(2). Retrieved from www.amstat.org/publications /jse/v22n2/kaplan.pdf
Kaplan, J. J., Rogness, N. T., & Fisher, D. G. (2012). Lexical ambiguity: making a case against spread. Teaching Statistics, 34(2), 56–60.
Khazanov, L., & Prado, L. (2010). Correcting students’ misconceptions about probability in an introductory college statistics course. Adults Learning Mathematics, 5(1), 23–35.
Kintsch, W. (1988). The role of knowledge in discourse comprehension: a construction-integration model. Psychological Review, 95(2), 163–182. https://doi.org/10.1037/0033-295X.95.2.163
Kintsch, W. (1998). Comprehension: A paradigm for cognition. Cambridge university press.
Kintsch, W. (2013). Revisiting the construction-integration model of text comprehension and its implication for instruction. In D. E. Alvermann, N. J. Unrau, & R. B. Ruddell (Eds.), Theoretical Models and Processes of Reading (6th ed.). Newark, DE: International Reading Association.
Knox, A. B. (1980). Proficiency theory of adult learning. Contemporary Educational Psychology, 5(4), 378–404.
Knypstra, S. (2009). Teaching statistics in an activity encouraging format. Journal of Statistics Education [Online], 17(2). Retrieved from www.amstat.org/publications/jse/v17n2/knypstra.html
Kolawole, E. B. (2008). Effects of competitive and cooperative learning strategies on academic performance of Nigerian students in mathematics. Educational Research and Reviews, 3(1), 033–037.
Konold, C., Higgins, T., Russell, S. J., & Khalil, K. (2015). Data seen through different lenses. Educational Studies in Mathematics, 88(3), 305–325.
Konold, C., Pollatsek, A., Well, A., & Gagnon, A. (1997). Students analyzing data: research of critical barriers. Research on the Role of Technology in Teaching and Learning Statistics, 151.
Kuhlthau, C. C., Maniotes, L. K., & Caspari, A. K. (2015). Guided Inquiry: Learning in the 21st Century: Learning in the 21st Century. ABC-CLIO.
Lawson, T. J., Schwiers, M., Doellman, M., Grady, G., & Kelnhofer, R. (2003). Enhancing Students’ Ability to Use Statistical Reasoning with Everyday Problems. Teaching of Psychology, 30(2), 107–110. https://doi.org/10.1207/S15328023TOP3002_04
Lazaraton, A. (2005). Quantitative research methods. In Handbook of research in second language teaching and learning (pp. 209–224). Mahwah, NJ: Erlbaum.
Lee, M.-H., Johanson, R. E., & Tsai, C.-C. (2008). Exploring Taiwanese high school students’ conceptions of and approaches to learning science through a structural equation modeling analysis. Science Education, 92(2), 191–220. https://doi.org/10.1002/sce.20245
Lem, S., Kempen, G., Ceulemans, E., Onghena, P., Verschaffel, L., & Van Dooren, W. (2015). Combining multiple external representations and refutational text: an intervention on learning to interpret box plots. International Journal of Science and Mathematics Education, 13(4), 909–926.
Lem, S., Onghena, P., Verschaffel, L., & Van Dooren, W. (2013a). External representations for data distributions: In search of cognitive fit. Statistics Education Research Journal, 12(1), 4–19.
Lem, S., Onghena, P., Verschaffel, L., & Van Dooren, W. (2013b). The heuristic interpretation of box plots. Learning and Instruction, 26, 22–35.
Lemberger, N. (2002). Russian bilingual science learning: perspectives from secondary students. International Journal of Bilingual Education and Bilingualism, 5(1), 58–71.
Lesser, L. M., Wagler, A., Esquinca, A., & Valenzuela, M. G. (2013). Survey of native English speakers and Spanish-speaking English language learners in tertiary introductory statistics. Statistics Education Research Journal, 12(2), 6–31.
Lesser, L. M., & Winsor, M. S. (2009). English language learners in introductory statistics: Lessons learned from an exploratory case study of two pre-service teachers. Statistics Education Research Journal, 8(2), 5–32.
Levy, D., & Bookin, J. (2014). Cold calling and web postings: Do they improve students’ preparation and learning in statistics? Journal of the Scholarship of Teaching and Learning, 14(5), 92–109.
Liang, J.-C., Su, Y.-C., & Tsai, C.-C. (2014). The Assessment of Taiwanese College Students’ Conceptions of and Approaches to Learning Computer Science and Their Relationships. The Asia-Pacific Education Researcher, 24(4), 557–567. https://doi.org/10.1007/s40299-014-0201-6
Liem, A. D., Lau, S., & Nie, Y. (2008). The role of self-efficacy, task value, and achievement goals in predicting learning strategies, task disengagement, peer relationship, and achievement outcome. Contemporary Educational Psychology, 33(4), 486–512.
Liem, G. A. D., Martin, A. J., Nair, E., Bernardo, A. B. I., & Prasetya, P. H. (2009). Cultural Factors Relevant to Secondary School Students in Australia, Singapore, the Philippines and Indonesia: Relative Differences and Congruencies. Australian Journal of Guidance and Counselling, 19(02), 161–178. https://doi.org/10.1375/ajgc.19.2.161
Lo, Y. Y., & Lo, E. S. C. (2014). A meta-analysis of the effectiveness of English-medium education in Hong Kong. Review of Educational Research, 84(1), 47–73.
Lovett, M., Meyer, O., & Thille, C. (2008). JIME-The open learning initiative: Measuring the effectiveness of the OLI statistics course in accelerating student learning. Journal of Interactive Media in Education, 2008(1), Art. 13.
Lucas, A. R. (2012). Using WeBWorK, a Web-Based Homework Delivery and Grading System, to Help Prepare Students for Active Learning. PRIMUS, 22(2), 97–107.
Lucas, U. (2001). Deep and surface approaches to learning within introductory accounting: a phenomenographic study. Accounting Education, 10(2), 161–184.
Lunsford, M. L., & Poplin, P. (2011). From research to practice: basic mathematics skills and success in introductory statistics. Journal of Statistics Education, 19(1), 1–22.
Macher, D., Paechter, M., Papousek, I., & Ruggeri, K. (2012). Statistics anxiety, trait anxiety, learning behavior, and academic performance. European Journal of Psychology of Education, 27(4), 483–498.
Maclellan, E. (1997). Reading to learn. Studies in Higher Education, 22(3), 277–288.
Marton, F. (1981). Phenomenography—describing conceptions of the world around us. Instructional Science, 10(2), 177–200.
Marton, F. (1994). Phenomenography. In T. Husén & N. Postlethwaite (Eds.), International encyclopedia of education. Oxford, England: Pergamon.
Marton, F., & Pong, W. Y. (2005). On the unit of description in phenomenography. Higher Education Research & Development, 24(4), 335–348.
Marton, F., & Säljö, R. (1984). Approaches to learning. In F. Marton, D. J. Hounsell, & N. J. Entwistle (Eds.), The experience of learning (pp. 36–55). Edinburgh: Scottish Academic Press.
Mason, L., Pluchino, P., Tornatora, M. C., & Ariasi, N. (2013). An eye-tracking study of learning from science text with concrete and abstract illustrations. The Journal of Experimental Education, 81(3), 356–384.
Mayer, R. E. (1989). Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81(2), 240.
Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139.
Mayer, R. E. (2005). The Cambridge handbook of multimedia learning. Cambridge university press.
Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82(4), 715.
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52.
McAlevey, L., & Sullivan, C. (2010). Statistical literacy and sample survey results. International Journal of Mathematical Education in Science and Technology, 41(7), 911–920.
McGrath, A. L. (2014). Just checking in: the effect of an office hour meeting and learning reflection in an introductory statistics course. Teaching of Psychology, 41(1), 83–87.
McGraw, R., & Rubinstein-Ávila, E. (2009). Middle school immigrant students developing mathematical reasoning in Spanish and English. Bilingual Research Journal, 31(1–2), 147–173.
McNamara, D. S., & Magliano, J. (2009). Toward a comprehensive model of comprehension. Psychology of Learning and Motivation, 51, 297–384.
McTigue, E. M., & Slough, S. W. (2010). Student-accessible science texts: Elements of design. Reading Psychology, 31(3), 213–227.
Meletiou, M., & Lee, C. (2002). Student understanding of histograms: A stumbling stone to the development of intuitions about variation. In Proceedings of the Sixth International Conference on Teaching Statistics, Cape Town, South Africa.
Meletiou-Mavrotheris, M. (2003). Technological Tools in the Introductory Statistics Classroom: Effects on Student Understanding of Inferential Statistics. International Journal of Computers for Mathematical Learning, 8(3), 265–297. https://doi.org/10.1023/B:IJCO.0000021794.08422.65
Meletiou-Mavrotheris, M., & Lee, C. (2010). Investigating college-level introductory statistics students’ prior knowledge of graphing. Canadian Journal of Science, Mathematics and Technology Education, 10(4), 339–355.
Meyer, B. J. (2003). Text coherence and readability. Topics in Language Disorders, 23(3), 204–224.
Mills, J. D. (2004). Students’ attitudes toward statistics: Implications for the future. College Student Journal, 38(3), 349.
Mohan, B. A. (1986). Language and Content. Addison-Wesley.
Moje, E. B., Dillon, D. R., & O’Brien, D. (2000). Reexamining roles of learner, text, and context in secondary literacy. The Journal of Educational Research, 93(3), 165–180.
Molitor, S., Ballstaedt, S.-P., & Mandl, H. (1989). 1 Problems in Knowledge Acquisition from Text and Pictures. Advances in Psychology, 58, 3–35.
Moore, D. S. (1998). Statistics among the liberal arts. Journal of the American Statistical Association, 93(444), 1253–1259.
Moore, D. S., McCabe, G. P., & Craig, B. A. (2009). Introduction to the Practice of Statistics (fourth edition). New York, US: Freeman.
Moyer, P. S., & Milewicz, E. (2002). Learning to question: Categories of questioning used by preservice teachers during diagnostic mathematics interviews. Journal of Mathematics Teacher Education, 5(4), 293–315.
Neumann, D. L., Hood, M., & Neumann, M. (2013). Using real-life data when teaching statistics: Student perceptions of this strategy in an introductory statistics course. Statistics Education Research Journal, 12(2).
Neumann, D. L., Hood, M., & Neumann, M. M. (2012). An Evaluation of Computer-Based Interactive Simulations in the Assessment of Statistical Concepts. International Journal for Technology in Mathematics Education, 19(1), 17–23.
Neumann, D., Neumann, M., & Hood, M. (2011). Evaluating computer-based simulations, multimedia and animations that help integrate blended learning with lectures in first year statistics. Australasian Journal of Educational Technology, 27(2), 274–289.
Nikula, T., & Marsh, D. (1998). Terminological Considerations Regarding Content and Language Integrated Learning. Bulletin Suisse de Linguistique Applique, 67, 13–18.
Nisbett, R. E. (2010). The geography of thought: How Asians and Westerns think differently...and why. New York: Free Press.
Noll, J., & Hancock, S. (2014). Proper and paradigmatic metonymy as a lens for characterizing student conceptions of distributions and sampling. Educational Studies in Mathematics, 88(3), 361–383.
Noonan, J. (1990). Readability problems presented by mathematics text. Early Child Development and Care, 54(1), 57–81.
Noser, T. C., Tanner, J. R., & Shah, S. (2011). Have Basic Mathematical Skills Grown Obsolete In The Computer Age: Assessing Basic Mathematical Skills And Forecasting Performance In A Business Statistics Course. Journal of College Teaching & Learning (TLC), 5(4).
Ó Muircheartaigh, J., & Hickey, T. (2008). Academic outcome, anxiety and attitudes in early and late immersion in Ireland. International Journal of Bilingual Education and Bilingualism, 11(5), 558–576.
OECD. (2014). PISA 2012 Results in Focus: What 15-year-olds Know What They Can Do with What They Know.
Paas, F. G. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84(4), 429.
Padilla, A. M., & Gonzalez, R. (2001). Academic performance of immigrant and US-born Mexican heritage students: Effects of schooling in Mexico and bilingual/English language instruction. American Educational Research Journal, 38(3), 727–742.
Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45(3), 255–287.
Parke, C. S. (2008). Reasoning and communicating in the language of statistics. Journal of Statistics Education [Online], 16(1). Retrieved from www.amstat.org/publicati ons/jse/v16n1/parke.html
Parsons, J. E., Adler, T., & Meece, J. L. (1984). Sex differences in achievement: A test of alternate theories. Journal of Personality and Social Psychology, 46(1), 26–43.
Paxton, P. (2006). Dollars and sense: Convincing students that they can learn and want to learn statistics. Teaching Sociology, 34(1), 65–70.
Perry, W., & Chickering, A. (1997). Cognitive and ethical growth: The making of meaning. College Student Development and Academic Life, 4, 48–116.
Petocz, P., & Reid, A. (2005). Something strange and useless: service students’ conceptions of statistics, learning statistics and using statistics in their future profession. International Journal of Mathematical Education in Science and Technology, 36(7), 789–800. https://doi.org/10.1080/00207390500271503
Pfaff, T. J., & Weinberg, A. (2009). Do hands-on activities increase student understanding?: A case study. Journal of Statistics Education, 17(3), 1–34.
Pfannkuch, M. (2006). Comparing box plot distributions: A teacher’s reasoning. Statistics Education Research Journal, 5(2), 27–45.
Pierce, R., & Chick, H. (2013). Workplace statistical literacy for teachers: Interpreting box plots. Mathematics Education Research Journal, 25(2), 189–205.
Pintrich, P. R., & Schrauben, B. (1992). Students’ motivational beliefs and their cognitive engagement in classroom academic tasks. In D. H. Schunk & J. L. Meece (Eds.), Student perceptions in the classroom (pp. 149–183). New York: Lawrence Erlbaum Associates Inc.
Popper, K. (2014). Conjectures and refutations: The growth of scientific knowledge. NY: Routledge.
Prosser, M., & Trigwell, K. (1999). Understanding Learning and Teaching (1 edition). Buckingham England ; Philadelphia, PA: Open University Press.
Rangecroft, M. (2002). The language of statistics. Teaching Statistics, 24(2), 34–37.
REABURN, R. (2014). INTRODUCTORY STATISTICS COURSE TERTIARY STUDENTS’UNDERSTANDING OF P-VALUES. Statistics Education Research Journal, 13(1).
Read, S. J. (2014). Connectionist models of social reasoning and social behavior. Psychology Press.
Reading, C., & Reid, J. (2006). An emerging hierarchy of reasoning about distribution: From a variation perspective. Statistics Education Research Journal, 5(2), 46–68.
Reid, A., & Petocz, P. (2002). Students’ conceptions of statistics: A phenomenographic study. Journal of Statistics Education, 10(2), 1–12.
Richardson, J. S., Morgan, R. F., & Fleener, C. (2006). Reading to Learn in the Content Areas (6th edition). Belmont, CA: Wadsworth.
Richardson, V., Anders, P., Tidwell, D., & Lloyd, C. (1991). The relationship between teachers’ beliefs and practices in reading comprehension instruction. American Educational Research Journal, 28(3), 559–586.
Rossman, A., Chance, B., & Medina, E. (2006). Some important comparisons between statistics and mathematics, and why teachers should care. Thinking and Reasoning with Data and Chance, 1, 323.
Rossman, A. J., & Chance, B. L. (2014). Using simulation‐based inference for learning introductory statistics. Wiley Interdisciplinary Reviews: Computational Statistics, 6(4), 211–221.
Rumsey, D. J. (2002). Statistical literacy as a goal for introductory statistics courses. Journal of Statistics Education, 10(3), 6–13.
Sadoski, M., & Paivio, A. (2004). A dual coding theoretical model of reading. Theoretical Models and Processes of Reading, 5, 1329–1362.
Sailah, I. (2014). Buku Panduan Kurikulum Pendidikan Tinggi. Jakarta: Direktorat Jenderal Pendidikan Tinggi.
Sami, F. (2011). Course format effects on learning outcomes in an introductory statistics course. MathAMATYC Educator, 2(2), 48–51.
Schau, C., Stevens, J., Dauphinee, T. L., & Vecchio, A. D. (1995). The development and validation of the survey of antitudes toward statistics. Educational and Psychological Measurement, 55(5), 868–875.
Scheaffer, R. L. (2006). Statistics and mathematics: On making a happy marriage. In G. Burrill (Ed.), Thinking and reasoning with data and chance, 68th NCTM Yearbook (2006) (pp. 309–322). Reston, VA: National Council of Teachers of Mathematics.
Scheaffer, R. L., & Stasny, E. A. (2004). The state of undergraduate education in statistics: A report from the CBMS 2000. The American Statistician, 58(4), 265–271.
Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representation. Learning and Instruction, 13(2), 141–156.
Schnotz, W., Ludewig, U., Ullrich, M., Horz, H., McElvany, N., & Baumert, J. (2014). Strategy shifts during learning from texts and pictures. Journal of Educational Psychology, 106(4), 974.
Schommer, M., Crouse, A., & Rhodes, N. (1992). Epistemological beliefs and mathematical text comprehension: Believing it is simple does not make it so. Journal of Educational Psychology, 84(4), 435–443. https://doi.org/10.1037/0022-0663.84.4.435
Schwonke, R., Berthold, K., & Renkl, A. (2009). How multiple external representations are used and how they can be made more useful. Applied Cognitive Psychology, 23(9), 1227–1243.
Shah, P., & Hoeffner, J. (2002). Review of graph comprehension research: Implications for instruction. Educational Psychology Review, 14(1), 47–69.
Shaughnessy, J. M. (1992). Research in probability and statistics: Reflections and directions.
Shaughnessy, J. M. (2007). Research on statistics learning. Second Handbook of Research on Mathematics Teaching and Learning, 957–1009.
Shor, I. (2012). Empowering education: Critical teaching for social change. University of Chicago Press.
Shuard, H., & Rothery, A. (1984). Children reading mathematics. London: John Murray.
Smith, G. (1998). Learning statistics by doing statistics. Journal of Statistics Education, 6(3), 1–10.
Stalder, D. R., & Olson, E. A. (2011). T for two: Using mnemonics to teach statistics. Teaching of Psychology, 38(4), 247–250.
Stansbury, J. A., Wheeler, E. A., & Buckingham, J. T. (2014). Can Wii engage college-level learners? use of commercial off-the-shelf gaming in an introductory statistics course. Computers in the Schools, 31(1–2), 103–115.
Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312.
Sweller, J., Van Merrienboer, J. J., & Paas, F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.
Symanzik, J., & Vukasinovic, N. (2006). Teaching an introductory statistics course with CyberStats, an electronic textbook. Journal of Statistics Education [Online], 14(1). Retrieved from http://www.amstat.org/publications/jse/v14n1/symanzik.html
Terrazas-Arellanes, F. E., Knox, C., & Rivas, C. (2013). Collaborative online projects for English language learners in science. Cultural Studies of Science Education, 8(4), 953–971.
Thompson, D. R., & Rubenstein, R. N. (2000). Learning mathematics vocabulary: Potential pitfalls and instructional strategies. The Mathematics Teacher, 93(7), 568–574.
Tisdell, M. (1999). German Language Production in Young Learners Taught Science and Social Studies through Partial Immersion German. Babel, 34(2), 26–36.
Tomasetto, C., Matteucci, M. C., Carugati, F., & Selleri, P. (2009). Effect of task presentation on students’ performances in introductory statistics courses. Social Psychology of Education, 12(2), 191–211. https://doi.org/10.1007/s11218-008-9081-z
Trabasso, T., & Sperry, L. L. (1985). Causal relatedness and importance of story events. Journal of Memory and Language, 24(5), 595–611.
Triandis, H. C. (1995). Individualism & collectivism. Westview Press.
Trigwell, K., & Prosser, M. (1991). Improving the quality of student learning: the influence of learning context and student approaches to learning on learning outcomes. Higher Education, 22(3), 251–266. https://doi.org/10.1007/BF00132290
Trumpower, D. L. (2013). Formative use of intuitive analysis of variance. Mathematical Thinking and Learning, 15(4), 291–313.
Tsai, C. (2004). Conceptions of learning science among high school students in Taiwan: a phenomenographic analysis. International Journal of Science Education, 26(14), 1733–1750. https://doi.org/10.1080/0950069042000230776
Turegun, M., & Reeder, S. (2011). Community College Students’ Conceptual Understanding of Statistical Measures of Spread. Community College Journal of Research and Practice, 35(5), 410–426.
Tversky, B. (1997). Cognitive principles of graphic displays. In AAAI 1997 Fall Symposium on Reasoning with Diagrammatic Representations (Vol. 14).
Utts, J. (2003). What educated citizens should know about statistics and probability. The American Statistician, 57(2), 74–79.
Utts, J., Sommer, B., Acredolo, C., Maher, M. W., & Matthews, H. R. (2003). A study comparing traditional and hybrid internet-based instruction in introductory statistics classes. Journal of Statistics Education, 11(3), 171–173.
Van den Broek, P., Young, M., Tzeng, Y., & Linderholm, T. (1999). The landscape model of reading: Inferences and the online construction of a memory representation. In H. van Oostendorp & S. R. Goldman (Eds.), The construction of mental representations during reading (pp. 71–98).
Van, G. K., Morton, B. A., Liu, H. Q., & Kline, J. (2006). Effects of web-based instruction on math anxiety, the sense of mastery, and global self-esteem: A quasi-experimental study of undergraduate statistics students. Teaching Sociology, 34(4), 370–388.
van Weijen, D. (2012, November). The Language of (Future) Scientific Communication. Research Trends, (31). Retrieved from http://www.researchtrends.com/issue-31-november-2012/the-language-of-future-scientific-communication/
Verzani, J. (2008). Using R in Introductory Statistics Courses with the pmg Graphical User Interface. Journal of Statistics Education, 16(1), 01-17.
Von Glasersfeld, E. (1987). Learning as a constructive activity. In In C. Janvier (Ed.), Problems of representation in the. Citeseer.
Wallman, K. K. (1993). Enhancing statistical literacy: Enriching our society. Journal of the American Statistical Association, 88(421), 1–8.
Wang, J.-T., Tu, S.-Y., & Shieh, Y.-Y. (2007). A Study on Student Performance in the College Introductory Statistics Course. AMATYC Review, 29(1), 54–62.
Wang, P.-Y., Vaughn, B. K., & Liu, M. (2011). The impact of animation interactivity on novices’ learning of introductory statistics. Computers & Education, 56(1), 300–311.
Ward, B. (2004). The best of both worlds: A hybrid statistics course. Journal of Statistics Education, 12(3), 74–79.
Weinberg, A., & Wiesner, E. (2011). Understanding mathematics textbooks through reader-oriented theory. Educational Studies in Mathematics, 76(1), 49–63.
Wells, G., & Ball, T. (2008). Exploratory talk and dialogic inquiry. Exploring Talk in School, 13(2), 167–184.
Wells, M. (2006). Teaching notes: Making statistics “real” for social work students. Journal of Social Work Education, 42(2), 397–404.
Whitin, D. J., & Whitin, P. E. (2010). Learning to Read the Numbers: Integrating Critical Literacy and Critical Numeracy in K-8 Classrooms A Co-Publication of The National Council of Teachers of English and Routledge. Routledge.
Wiberg, M. (2009). Teaching statistics in integration with psychology. Journal of Statistics Education, 17(1), 1–16.
Wigfield, A., & Eccles, J. S. (2000). Expectancy–Value Theory of Achievement Motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015
Wild, C. (2006). The concept of distribution. Statistics Education Research Journal, 5(2), 10–26.
Wild, C. J., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223–248.
Wilson, S. G. (2013). The Flipped Class A Method to Address the Challenges of an Undergraduate Statistics Course. Teaching of Psychology, 0098628313487461.
Winquist, J. R., & Carlson, K. A. (2014). Flipped statistics class results: better performance than lecture over one year later. Journal of Statistics Education [Online], 22(3). Retrieved from http://www.amstat.org/publications/jse/v22n3/winquist.pdf
Wise, S. L. (1985). The development and validation of a scale measuring attitudes toward statistics. Educational and Psychological Measurement, 45(2), 401–405.
Woodward, S., Lloyd, A., & Kimmons, R. (2017). Student Voice in Textbook Evaluation: Comparing OpStudent Voice in Textbook Evaluation: Comparing Open and Restricted Textbooksen and Restricted Textbooks. The International Review of Research in Open and Distributed Learning, 18(6).
Wright, J. C., & Murphy, G. L. (1984). The utility of theories in intuitive statistics: The robustness of theory-based judgments. Journal of Experimental Psychology: General, 113(2), 301.
Xu, Y. J., Meyer, K. A., & Morgan, D. D. (2009). A mixedmethods assessment of using an online commercial tutoring system to teach introductory statistics. Journal of Statistics Education, 17(2), 1–17.
Yang, K.-L. (2014). An exploratory study of Taiwanese mathematics teachers’ conceptions of school mathematics, school statistics, and their diffrences. International Journal of Science and Mathematics Education, 12(6), 1497–1518. https://doi.org/10.1007/s10763-014-9519-z
Yang, K.-L. (2016). Analyzing Mathematics Textbooks through a Constructive-Empirical Perspective on Abstraction: The Case of Pythagoras’ Theorem. Eurasia Journal of Mathematics, Science and Technology Education, 12(4), 913–930.
Yang, N.-D. (1999). The relationship between EFL learners’ beliefs and learning strategy use. System, 27(4), 515–535.
Yore, L. D., Pimm, D., & Tuan, H.-L. (2007). The literacy component of mathematical and scientific literacy. International Journal of Science and Mathematics Education, 5(4), 559–589.
Yushau, B. (2009). Mathematics and language: issues among bilingual Arabs in English medium universities. International Journal of Mathematical Education in Science and Technology, 40(7), 915–926.
Zieffler, A., Garfield, J. B., Alt, S., Dupuis, D., Holleque, K., & Chang, B. (2008). What does research suggest about the teaching and learning of introductory statistics at the college level? A review of the literature. Journal of Statistics Education, 16(2), 1–23.
Zwaan, R. A., Langston, M. C., & Graesser, A. C. (1995). The construction of situation models in narrative comprehension: An event-indexing model. Psychological Science, 6(5), 292–297.