The Mathematics Attitudes and Perceptions Survey: an instrument to assess expert-like views and dispositions among undergraduate mathematics students

References

• Schoenfeld AH. Learning to think mathematically: problem solving, metacognition, and sense making in mathematics. In: Grouws D, editor. Handbook for research on mathematics teaching and learning. New York (NY): Macmillan; 1992. p. 334–370.
   Google Scholar
• Schoenfeld AH. Explorations of students' mathematical beliefs and behavior. J Res Math Educ. 1989;20:338–355.
   Web of Science ®Google Scholar
• Petocz P, Reid A, Wood L, et al. 2007. Undergraduate students' conceptions of mathematics: an international study. Int J Sci Math Educ. 2007;5:439–459.
   Google Scholar
• Fennema E, Sherman JA. Fennema-Sherman Mathematics Attitudes Scales: instruments designed to measure attitudes toward the learning of mathematics by females and males. J Res Math Educ. 1976;7:324–326.
   Google Scholar
• Sandman R. The mathematics attitude inventory: instrument and user's manual. J Res Math Educ. 1980;11:148–149.
   Google Scholar
• Tapia M, Marsh GE. An instrument to measure mathematics attitudes. Acad Exchange Quart. 2004;8:16–21.
   Google Scholar
• Laursen SL, Hassi M, Kogan M, et al. Benefits for women and men of inquiry-based learning in college mathematics: a multi-institution study. J Res Math Educ. 2014;45:406–418.
   Web of Science ®Google Scholar
• Crawford K, Gordon S, Nicholas J, et al. Conceptions of mathematics and how it is learned: the perspective of students entering university. Learn Instr. 1994;4:331–345.
   Google Scholar
• Crawford K, Gordon S, Nicholas J, et al. University mathematics students' conceptions of mathematics. Stud High Educ. 1998;23:87–94.
   Web of Science ®Google Scholar
• Crawford K, Gordon S, Nicholas J, et al. Qualitatively different experiences of learning mathematics at university. Learn Instr. 1998;8:455–468.
   Web of Science ®Google Scholar
• Maciejewski W, Merchant S. Mathematical tasks, Study approaches, and course grades in undergraduate mathematics: a year-by-year analysis. Int J Math Educ Sci Technol. 2015; DOI:10.1080/0020739X.2015.1072881
   Web of Science ®Google Scholar
• Maciejewski W. Instructors' perceptions of their students' conceptions: the case in undergraduate mathematics. Int J Teach Learn High Educ. Accepted for Publication.
   Google Scholar
• Phillip R. Mathematics teachers' beliefs and affect. In: Lester F, editor. Second handbook of research on mathematics teaching and learning. Charlotte: NCTM; 2007. p. 257–315.
   Google Scholar
• Thompson AG. Teachers' beliefs and conceptions: a synthesis of the research. In: Grouws D, editor. Handbook for research on mathematics teaching and learning. New York (NY): MacMillan; 1992. p. 334–370.
   Google Scholar
• Ernest P. The impact of beliefs on the teaching of mathematics. In: Keitel C, Damerow P, Bishop A, Gerdes P, editors. Mathematics, education, and society. Paris: UNESCO; 1989. p. 99–101.
   Google Scholar
• Thompson AG. The relationship between teachers' conceptions of mathematics and mathematics teaching to instructional practice. Educ Stud Math. 1984;15:105–127.
   Google Scholar
• Yackel E, Rasmussen C. Beliefs and norms in the mathematics classroom. In: Leder GC, Pehkonen E, Törner G, editors. Beliefs: a hidden variable in mathematics education? Netherlands: Springer; 2003. p. 313–330.
   Google Scholar
• Polly D, Mcgee JR, Wang C, et al. The Association between Teachers' Beliefs, Enacted Practices, and Student Learning in Mathematics. Math Educator. 2013;22:11–30.
   Google Scholar
• Aguirre J, Speer NM. Examining the relationship between beliefs and goals in teacher practice. J Math Behav. 1999;18:327–356.
   Google Scholar
• Stipek DJ, Givvin KB, Salmon JM, et al. Teachers' beliefs and practices related to mathematics instruction. Teach Teach Educ. 2001;17:213–226.
   Web of Science ®Google Scholar
• Enochs LG, Smith PL, Huinker D. Establishing factorial validity of the mathematics teaching efficacy beliefs instrument. Sch Sci Math. 2000;100:194–102.
   Google Scholar
• Schoenfeld AH, Herrmann DJ. Problem perception and knowledge structure in expert and novice mathematical problem solvers. J Exp Psychol Learn. 1982;8:484–494.
   Web of Science ®Google Scholar
• Dowker A. Computational estimation strategies of professional mathematicians. J Res Math Educ. 1992;23:45–55.
   Web of Science ®Google Scholar
• Weber K. Student difficulty in constructing proofs: the need for strategic knowledge. Educ Stud Math. 2001;48:101–119.
   Google Scholar
• Dewar J. What is mathematics: student and faculty views. In: Brown S, Karakok G, Hah Roh K, Oehrtman M, editors. Proceedings for the Eleventh Special Interest Group of the Mathematical Association of America on Research in Undergraduate Mathematics Education. Denver: Mathematical Association of America; 2008.
   Google Scholar
• Yusof Y, Tall D. Changing attitudes to university mathematics through problem solving. Educ Stud Math. 1998;37:67–82.
   Google Scholar
• Szydlik S. Beliefs of liberal arts mathematics students regarding the nature of mathematics. Teach Math Appl. 2013;32:95–111.
   Google Scholar
• Adams WK, Perkins KK, Podolefsky NS, et al. New Instrument for Measuring Student Beliefs about Physics and Learning Physics: The Colorado Learning Attitudes About Science Survey. Phys Rev Spec Top – Phys Educ Res. 2006;2:010101.
   Web of Science ®Google Scholar
• Gray KE, Adams WK, Wieman CE, et al. Students know what physicists believe, but they don't agree: a study using the CLASS survey. Phys Rev Spec Top – Phys Educ Res. 2008;4:020106.
   Google Scholar
• Semsar K, Knight JK, Birol G, et al. The Colorado Learning Attitudes About Science Survey (CLASS) for use in biology. CBE – Life Sci Educ. 2011;10:268–278.
   PubMed Web of Science ®Google Scholar
• Barbera J, Adams WK, Wieman CE, et al. Modifying and validating the Colorado Learning Attitudes About Science Survey for use in chemistry. Chem Educ Res. 2008;85:1435–1439.
   Web of Science ®Google Scholar
• Jolley A, Lane E, Kennedy B, et al. SPESS: a new instrument for measuring student perceptions in earth and ocean science. J Geosci Educ. 2012;60:83–91.
   Google Scholar
• Dorn B, Elliott Tew A. Becoming experts: measuring attitude development in introductory computer science. In: Camp T, Tymann P, Dougherty JD, Nagel K, editors. Proceeding of the 44th ACM Technical Symposium on Computer Science Education. Denver: ACM; 2013. p. 183–188.
   Google Scholar
• Adams WK, Wieman CE. Development and validation of instruments to measure learning of expert-like thinking. Int J Sci Educ. 2011;33:1289–1312.
   Web of Science ®Google Scholar
• Bates S, Galloway R, Loptson C, et al. How attitudes and beliefs about physics change from high school to faculty. Phys Rev Spec Top – Phys Educ Res. 2011;7:020114.
   Google Scholar
• Perkins KK, Gratny M. Who becomes a physics major? A long‐term longitudinal study examining the roles of pre‐college beliefs about physics and learning physics, interest, and academic achievement. In: Singh C, Sabella M, Rebello S, editors. American Institutes of Physics Conference Proceedings, 1289. Portland: AIP Publishing; 2010. p. 253–256.
   Google Scholar
• Perkins KK, Gratny MM, Adams WK, et al. Towards characterizing the relationship between students' interest in and their beliefs about physics. In: Heron P, McCullough L, Marx J, editors. American Institutes of Physics Conference Proceedings, 818. Salt Lake City: AIP Publishing; 2005. p. 137–140.
   Google Scholar
• Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol Rev. 1977;84:191–215.
   PubMed Web of Science ®Google Scholar
• Hasan S, Bagayoko D, Kelley E. Misconceptions and the Certainty of Response Index (CRI). Phys Educ. 1999;34:294–299.
   Google Scholar
• Potgieter M, Malatje E, Gaigher E, et al. Confidence versus performance as an indicator of the presence of alternative conceptions and inadequate problem-solving skills in mechanics. Int J Sci Educ. 2010;32:1407–1429.
   Web of Science ®Google Scholar
• Engelbrecht J, Harding A, Potgieter M. Undergraduate students' performance and confidence in procedural and conceptual mathematics. Int J Math Educ Sci Technol. 2005;36:701–712.
   Google Scholar
• Parsons S, Croft T, Harrison M. Does students' confidence in their ability in mathematics matter? Teach Math Appl. 2009;28:53–68.
   Google Scholar
• Hackett G, Betz N. An exploration of the mathematics self-efficacy/mathematics performance correspondence. J Res Math Educ. 1989;20:261–273.
   Web of Science ®Google Scholar
• Chi MTH, Feltovich PJ, Glasser R. Categorization and representation of physics problems by experts and novices. Cogn Sci. 1981;5:121–152.
   Web of Science ®Google Scholar
• Ericsson KA, Charness N, Feltovich PJ, et al., editors. The Cambridge handbook of expertise and expert performance. New York (NY): Cambridge University Press; 2006.
   Google Scholar
• Dweck C. Self-theories: their role in motivation, personality, and development. Philadelphia (PA): Taylor and Francis/Psychology Press; 1999.
   Google Scholar
• Dweck C. Mindset: the new psychology of success. New York (NY): Ballantine Books; 2006.
   Google Scholar
• Boaler J. The elephant in the classroom: helping children learn and love maths. London: Souvenir Press; 2010.
   Google Scholar
• Boaler J. When even the winners are losers: evaluating the experiences of top set' students. J Curric. Stud. 1997;29:165–182.
   Web of Science ®Google Scholar
• Boaler J, Wiliam D, Brown M. Students' Experiences of Ability Grouping - disaffection, polarization and the construction of failure. Br Educ Res J. 2000;26:631–648.
   Web of Science ®Google Scholar
• Boaler J. Ability grouping in mathematics classrooms. In: Lerman S, editor. Encyclopedia of mathematics education. Heidelberg: Springer; 2014.
   Google Scholar
• Dweck C. Mindset and math/science achievement. New York (NY): Carnegie Corporation of New York-Institute for Advanced Study Commission on Mathematics and Science Education; 2008.
   Google Scholar
• Boaler J. Ability and mathematics: the mindset revolution that is reshaping education. Forum. 2013;55:143–152.
   Google Scholar
• Silvia P. Exploring the psychology of interest. Oxford: Oxford University Press; 2006.
   Google Scholar
• Köller O, Baumert J. Does interest matter? The relationship between academic interest and achievement in mathematics. J Res Math Educ. 2001;32:448–470.
   Web of Science ®Google Scholar
• Marton F, Säljö R. On qualitative differences in learning: I – outcome and process. Br J Educ Psychol. 1976;46:4–11.
   Web of Science ®Google Scholar
• Prosser M, Trigwell K. Understanding learning and teaching: the experience in higher education. Berkshire: Open University Press; 1999.
   Google Scholar
• Biggs J, Tang C. Teaching for quality learning at university, 4th Ed. Berkshire: Open University Press; 2011.
   Google Scholar
• Choy JLF, O'Grady G, Rotgans JI. Is the Study Process Questionnaire (SPQ) a good predictor of academic achievement? Examining the mediating role of achievement-related classroom behaviours. Instr Sci. 2012;40:159–172.
   Web of Science ®Google Scholar
• Campbell C, Cabrera A. Making the mark: Are grades and deep learning related? Res High Educ. 2014;55:494–507.
   Web of Science ®Google Scholar
• Watkins D. Correlates of approaches to learning: a cross-cultural meta-analysis. In: Sternberg R, Zhang L, editors. Perspectives on thinking, learning, and cognitive styles. Mahwah (NJ): Erlbaum; 2001. p. 165–195.
   Google Scholar
• Rattan A, Good C, Dweck CS. ‘It's ok – not everyone can be good at math’: instructors with an entity theory comfort (and demotivate) students. J Exp Soc Psychol. 2012;48:731–737.
   Web of Science ®Google Scholar
• Everitt, B., Hothorn, T. An introduction to applied multivariate analysis with R. New York (NY): Springer New York; 2011.
   Google Scholar
• Costello A, Osborne J. Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Pract Assess Res Eval. 2005;10:1–9.
   Google Scholar
• Rosseel Y. lavaan: An R Package for structural equation modeling. J Stat Softw. 2012;48:1–36.
   Web of Science ®Google Scholar
• Tallman M, Carlson MP. A characterization of calculus I final exams in U.S. colleges and universities. In: Brown S, Larsen S, Marrongelle K, Oehrtman M, editors. Proceedings of the 15th Annual Conference on Research in Undergraduate Mathematics Education. Portland: Mathematical Association of America; 2012. p. 217–226.
   Google Scholar
• Maciejewski W. Flipping the calculus classroom: an evaluative study. To appear in Teach Math Appl.
   Google Scholar
• Cahill MJ, Hynes M, Trousil R, et al. Multiyear, mult-instructor evaluation of a large-class interactive-engagement curriculum. Phys Rev Spe Top – Phys Educ Res. 2014;10:020101.
   Google Scholar
• Hansen M, Birol G. Longitudinal study of student attitudes in a biology program. CBE – Life Sci Educ. 2014;13:331–337.
   PubMed Web of Science ®Google Scholar
• Madsen A, McKagan S, Sayre E. How physics instruction impacts students' beliefs about learning physics. Phys Rev Spec Top – Phys Educ Res. 2015;11:010115.
   Google Scholar
• Seymour E, Hewitt NM. Talking about leaving: why undergraduates leave the sciences. Boulder (CO): Westview Press; 1997.
   Google Scholar