Abstract
We describe the development of the Measure of Affect in Science and Technology (MAST), and study its usefulness for measuring science affect in middle school students via both classical and Rasch measurement perspectives. We then proceed to utilize the measurement structure of the MAST to understand how middle school students at varying levels of affect express their interest and attitudes toward science and technology and gender differences in how students express their affect. We found that affect in science and technology comprises a main dimension, science interest, and four peripheral dimensions: interest in careers in science and technology, attitudes toward science, and interest in attending science class. Of these, careers in science and technology carry the highest affective demand. While males showed higher levels of personal and situational interest in science, a greater interest in careers in science and technology was the biggest contributor to males’ higher affect toward science and technology. We argue that whether the MAST is used as a measure of a single construct or multiple subconstructs depends upon specific research or evaluation goals; however, both uses of the MAST yield measures which produce valid inferences for student affect.
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References
Alexander PA, Jetton TL (1996) The role of importance and interest in the processing of text. Educ Psychol Rev 8:89–121
Alexander PA, Murphy PK (1998) Profiling the differences in students’ knowledge, interest, and strategic processing. J Educ Psychol 90:435–447
Altmann TK (2008) Attitude: a concept analysis. Nurs Forum 43:144–150
Aydeniz M, & Kotowski M R (2014). Conceptual and methodological issues in the measurement of attitudes towards science. Electronic Journal of Science Education, 18(3).
Baram-Tsabari A, Yarden A (2011) Quantifying the gender gap in science interests. Int J Sci Math Educ 9(3):523–550
Bransford JD, Brown AL, Cocking RR (1999) How people learn: brain, mind, and school. National Academy Press, Washington
Brotman JS, Moore FM (2008) Girls and science: a review of four themes in the science education literature. J Res Sci Teach 45(9):971–1002
Cattell RB (1966) The scree test for the number of factors. Multivar Behav Res 1(2):245–276
Fraser BL (1978) Development of a test of science-related attitudes. Sci Educ 62:509–515
George R (2006) A cross-domain analysis of change in students’ attitudes toward science and attitudes about the utility of science. Int J Sci Educ 28(6):571–589
Hassan G (2008) Attitudes toward science among Australian tertiary and secondary school students. Research in Science and Technological Education 26:129–147
Hidi S (1995) A re-examination of the role of attention in learning from text. Educ Psychol Rev 7:323–350
Hidi S, Renninger KA (2006) The four-phase model of interest development. Educ Psychol 41(2):111–127
Hidi S, Renninger KA, Krapp A (2004) Interest, a motivational variable that combines affecting and cognitive functioning. In: Dai DY, Sternberg RJ (eds) Motivation, emotion, and cognition: integrative perspectives on intellectual functioning and development. Erlbaum, Mahwah, pp 89–115
Hulleman CS, Harackiewicz JM (2009) Promoting interest and performance in high school science classes. Science 326(5958):1410–1412
Jenkins EW, Pell RG (2006) The relevance of science education project (ROSE) in England: a summary of findings. Centre for Studies in Science and Mathematics Education, University of Leeds, Leeds
Kahle JB, Lakes MK (1983) The myth of equality in science classrooms. J Res Sci Teach 20(2):131–140
Kimmel LG, Miller JD, Eccles JS (2012) Do the paths to STEMM professions differ by gender? Peabody Journal of Education 87(1):92–113
Koballa T, Glynn S (2007) Attitudinal and motivational constructs in science learning. In: Abell SK, Lederman NG (eds) Handbook of research on science education. Routledge, Mahwah, pp 75–102
Koehler MJ, Mishra P (2009) What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education 9(1):60–70
Lamb RL, Annetta L, Meldrum J, Vallett D (2012) Measuring science interest: Rasch validation of the science interest survey. Int J Sci Math Educ 10:643–668
Linacre JM, Tennant A (2009) More about critical eigenvalue sizes in standardized-residual principal components analysis (PCA). Rasch Meas Trans 23(3):1228
Lipstein R, Renninger KA (2006) “Putting things into words”: 12–15-year-old students’ interest for writing. In: Boscolo P, Hidi S (eds) Motivation and writing: research and school practice. Kluwer Academic/Plenum, New York
Maltese AV, Tai RH (2011) Pipeline persistence: examining the association of educational experiences with earned degrees in STEM among U.S. students. Sci Educ 95:877–907
McDaniel MA, Waddill PJ, Finstad K, Bourg T (2000) The effects of text-based interest on attention and recall. J Educ Psychol 92:492–502
Miller PH, Slawinski Blessing J, Schwartz S (2006) Gender differences in high-school students’ views about science. Int J Sci Educ 28(4):363–381
Mitchell M (1993) Situational interest: its multifaceted structure in the secondary school mathematics classroom. J Educ Psychol 85:424–436
Moore RW, Foy RL (1997) The scientific attitude inventory: a revision (SAI II). J Res Sci Teach 34:327–336
NGSS Lead States (2013) Next generation science standards: for states, by states. Achieve, Inc. on behalf of the twenty-six states and partners that collaborated on the NGSS. National Academy Press, Washington
Nieswandt M (2007) Student affective and conceptual understanding in learning chemistry. J Res Sci Teach 44:908–937
Pintrich PR, Zusho A (2002) The development of academic self-regulation: the role of cognitive and motivational factors. In: Wigfield A, Eccles JS (eds) Development of achievement motivation. Academic, New York, pp 249–284
President’s Council of Advisors on Science and Technology (PCAST) (2010) Prepare and inspire: K-12 education in science, technology, engineering, and Math (STEM) for America's future. White House Office of Science and Technology Policy (OSTP), Washington
Romine WL, Sadler TD (2016) Measuring changes in interest in science and technology at the college level in response to two instructional interventions. Res Sci Educ 46(3):309–327
Romine W, Sadler T, Presley M, Klosterman M (2014) Student interest in technology and science (SITS) survey: development, validation, and use of a new instrument. International Journal of Science & Mathematics Education 12(2):261–283
Romine WL, Miller ME, Knese SA, Folk WR (2016) Multilevel assessment of middle school students’ interest in the health sciences: development and validation of a new measurement tool. CBE-Life Sciences Education 15(2):ar21
Sadler PM, Sonnert G, Hazari Z, Tai R (2012) Stability and volatility of STEM career interest in high school: a gender study. Sci Educ 96(3):411–427
Scantlebury K, Baker D (2007) Gender issues in science education research: remembering where the difference lies. In: Abell S, Lederman N (eds) Handbook of research on science education. Lawrence Erlbaum, Mahwah, pp 257–286
Shrigley RL, Koballa TR, Simpson RD (1988) Defining attitude for science educators. J Res Sci Teach 25(8):659–678
Siegel MA, Ranney MA (2003) Developing the changes in attitude about the relevance of science (CARS) questionnaire and assessing two high school science classes. J Res Sci Teach 40:757–775
Silvia P (2006) Exploring the psychology of interest. Oxford University Press, Oxford
Sjøberg S, Schreiner C (2005) How do learners in different cultures relate to science and technology? Results and perspectives from the project ROSE. Asia-Pacific Forum on Science Learning and Teaching 6(2):1–17
Swaminathan H, Rogers HJ (1990) Detecting differential item functioning using logistic regression procedures. J Educ Meas 27(4):361–370
Treagust DF, Duit R (2008) Conceptual change: a discussion of theoretical, methodological and practical challenges for science education. Cultural Studies of Science Education 3(2):297–328
Vispoel WP, Austin JR (1995) Success and failure in junior high school: a critical incident approach to understanding students’ attributional beliefs. Am Educ Res J 32:377–412
Wade SE (2001) Research on importance and interest: implications for curriculum development and future research. Educ Psychol Rev 13:243–261
What Works Clearinghouse (2014) WWC procedures and standards handbook (version 3.0). US Department of Education, Institute of Education Sciences, Princeton
Wright BD, Linacre JM (1996) Reasonable mean-square fit values. In: Linacre JM (ed) Rasch measurement transactions, part 2. MESA, Chicago
Zeidler DL (1984) Thirty studies involving the “scientific attitude inventory”: what confidence can we have in this instrument? J Res Sci Teach 21:341–342
Acknowledgements
The research reported here was supported by the US Department of Education through grants from the Institute of Education Sciences (IES; R305A150364) and the Investing in Innovation program (I3; U411C140081) to University of Missouri. The opinions expressed are those of the authors and do not represent views of IES, I3, or the Department of Education.
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Romine, W.L., Sadler, T.D. & Wulff, E.P. Conceptualizing Student Affect for Science and Technology at the Middle School Level: Development and Implementation of a Measure of Affect in Science and Technology (MAST). J Sci Educ Technol 26, 534–545 (2017). https://doi.org/10.1007/s10956-017-9697-x
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DOI: https://doi.org/10.1007/s10956-017-9697-x