Top

Journal of Science Teacher Education

Published in:

01-11-2011

The Psychometric Evaluation of a Three-Dimension Elementary Science Attitude Survey

Authors: Danhui Zhang, Todd Campbell

Published in: Journal of Science Teacher Education | Issue 7/2011

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

This study describes the development of an instrument to investigate elementary students attitudes toward science. As a result of the instrument development process employed, the finalized instrument consisted of 28-items separated into three dimensions. The instrument was found to exhibit acceptable ranges of internal consistency. Confirmatory Factor Analysis showed three factors that clustered into the three dimensions of attitude identified and concurrent validity was evidenced as correlations were found when comparing attitude measures with the instrument to students’ perceptions of their science classrooms. Based on the analyses completed, the instrument appears to be useful for assessing student attitude toward science.

previous article Observed Implementation of a Science Professional Development Program for K-8 Classrooms

next article Elementary Teachers’ Use of Graphical Representations in Science Teaching

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Available only for authorised users

Aldridge, J. M., & Fraser, B. J. (2000). A cross-cultural study of classroom learning environments in Australia and Taiwan. Learning Environment Research: An International Journal, 3, 101–134.CrossRef

Alsop, S., & Watts, M. (2003). Science education and affect. International Journal of Science Education, 25(9),1043–1047.

Baram-Tsabari, A., Sethi, R., Bry, L., & Yarden, A. (2006). Using questions sent to an Ask-A-Scientist site to identify children’s interests in science. Science Education, 90(6), 1050–1072.CrossRef

Baram-Tsabari, A., & Yarden, A. (2009). Identifying meta-clusters of students’ interest in science and their change with age. Journal of Research in Science Teaching, 46(9), 999–1022.CrossRef

Bentler, P. M. (1990). Comparative fit indexes in structural equation models. Psychological Bulletin, 107, 238–246.CrossRef

Blalock, C. L., Lichtenstein, M. J., & Owen, S. (2008). In Pursuit of validity: A comprehensive review of science attitude instruments 1935–2005. International Journal of Science Education, 30(7), 961–977.CrossRef

Bland, J. M., & Altman, D. G. (1997). Cronbach’s alpha. British Medical Journal, 314, 572.

Breckler, S. J. (1984). Empirical validation of affect, behaviour and cognition as distinct components of attitude. Journal of Personality and Social Psychology, 47, 1191–1205.CrossRef

Bronowski, J. (1973). The ascent of man. London: Warner Books.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 445–455). Newbury Park, CA: Sage.

Carey, N., & Shavelson, R. (1988). Outcomes, achievement, participation, and attitudes. In R. J. Shavelson, L. M. McDonnell, & J. Oakes (Eds.), Indicators for monitoring mathematics and science education (pp. 147–191). Los Angeles, CA: Rand Corporation.

Chen, S. (2002, June). The implementation of the IELC in elementary schools. Paper presented at the meeting of “The curriculum reformation in elementary and middle schools in China”, Beijing.

Chen, M., & Bargh, J. A. (1999). Consequences of automatic evaluation: Immediate behavioral predispositions to approach or avoid stimulus. Personality and Social Psychology Bulletin, 25(2), 215–224.CrossRef

Damasio, A. (1994). Descartes’ error: Emotion, reason, and the human brain. New York: Avon Books.

Eagly, A., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth, TX: Harcourt Brace Jovanovich.

Fraser, B. J. (1978a). Development of a test of science-related attitudes. Science Education, 62(4), 509–515.CrossRef

Fraser, B. J. (1978b). Some attitude Scales for ninth grade science preview. School Science and Mathematics, 78(5), 379–384.CrossRef

Fraser, B. J. (1998). Classroom environment instruments: Development, validity and applications. Learning Environment Research: An International Journal, 1, 7–33.CrossRef

Fraser, B. J., & Chionnh, Y. H. (2000). Classroom environment, self-esteem, achievement, and attitudes in geography and mathematics in Singapore. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.

Germann, P. (1988). Development of the attitude towards science in school assessment and its use to investigate the relationship between science achievement and attitude towards science in school. Journal of Research in Science Teaching, 25(8), 689–703.CrossRef

Haladyna, T., Olsen, R., & Shaughnessy, J. (1982). Relationships of student, teacher, and learning environment variables to attitudes toward science. Journal of Research in Science Teaching, 20(4), 311–324.CrossRef

Hazari, Z., Tai, R. H., & Sadler, P. M. (2007). Gender differences in introductory university physics performance: The influence of high school physics preparation and affective factors. Science Education, 91, 847–876.CrossRef

Hoyle, R. H., & Panter, A. T. (1995). Writing about structural equation models. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues and applications (pp. 158–176). Thousand Oaks, CA: Sage.

Hu, L., & Bender, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.CrossRef

Katz, D., & Stotland, E. (1959). A preliminary statement to a theory of attitude structure and change. In S. Koch (Ed.), Psychology: A study of a science (Vol. 3, pp. 423–475). New York: McGraw-Hill.

Keeves, J. P. (1975). The home, the school and achievement in mathematics and science. Science Education, 59(4), 439–460.CrossRef

Kline, R. B. (1998). Principles and practices of structural equation modeling. New York, NY: Guilford.

Klop, T., & Severiens, S. (2007). An exploration of attitudes towards modern biotechnology: A study among Dutch secondary school students. International Journal of Science Education, 29(5), 663–679.CrossRef

Koballa, T., & Crawley, F. (1985). The influence of attitude on science teaching and learning. School Science and Mathematics, 85, 222–232.CrossRef

Leong, F., & Austin, J. (2006). The psychology research handbook: A guide for graduate students and research assistants (2nd ed.). Thousand Oaks, CA: Sage Publications.

Lichtenstein, M. J., Owen, S. V., Blalock, C. L., Liu, Y., Ramirez, K. A., Pruski, L. A., et al. (2008). Psychometric reevaluation of the scientific attitude inventory-revised (SAI-II). Journal of Research in Science Teaching, 45(5), 600–616.CrossRef

Margianti, E. S., Fraser, B. J., & Aldridge, J. M. (2001, March). Learning environment, mathematical ability and students’ outcomes in university computing courses in Indonesia. Paper presented at the annual meeting of the American Educational Research Association, Seattle, WA.

Moss, C. H. (2001, March). Using environment assessments in improving teaching and learning in high school biology classrooms. Paper presented at the annual meeting of the American Educational Research Association, Seattle, WA.

Mueller, D. J. (1986). Measuring social attitudes. New York: Teachers College Press.

Mukoma, W., Flisher, A. J., Helleve, A., Aaro, L. E., Mathews, C., Kaaya, S., et al. (2009). Development and test–retest reliability of a research instrument designed to evaluate school-based HIV/AIDS interventions in South Africa and Tanzania. Scandinavian Journal of Public Health, 37, 7–15.CrossRef

Munby, H. (1983). Thirty studies involving the “scientific attitude inventory”: What confidence can we have in this instrument? Journal of Research in Science Teaching, 20(2), 141–162.CrossRef

Muthen, L. K., & Muthen, B. O. (1998–2006). Mplus user’s guide (4th ed.). Los Angeles, CA: Muthen & Muthen.

Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards Science: A review of the literature and its implications. International Journal of Science Education, 25(9), 1049–1079.CrossRef

Palmer, D. (2009). Student interest generated during an inquiry skills lesson. Journal of Research in Science Teaching, 46(2), 147–165.CrossRef

Patrick, H., Mantzicopoulos, P., & Samarapungavan, A. (2009). Motivation for learning science in kindergarten: Is there a gender gap and does integrated inquiry and literacy instruction make a difference. Journal of Research in Science Teaching, 46(2), 166–191.CrossRef

Popham, W. J. (2009). Assessing student affect. Teaching Social Responsibility, 66(8), 85–86.

Rosenberg, M. J., & Hovland, C. I. (1960). Cognitive, affective and behavioural components of attitudes. In C. I. Hovland & M. J. Rosenberg (Eds.), Attitude organisation and change: An analysis of consistency among attitude components (pp. 1–14). New Haven, CT: Yale University Press.

Schaverien, L., & Cosgrove, M. (2000). A biological basis for generative learning in technology-and-science part II: Implications for technology-and-science education. International Journal of Science Education, 22(1), 13–35.CrossRef

Scherz, Z., & Oren, M. (2006). How to change students’ images of science and technology. Science Education, 90(6), 965–985.CrossRef

Schibeci, R. A. (1982). Measuring student attitudes: Semantic differential or Likert instruments. Science Education, 66(4), 565–570.CrossRef

Schibeci, R. A., & McGaw, B. (1981). Empirical validation of the conceptual structure of a test of science-related attitudes. Educational and Psychological Measurement, 41(4), 1195–1201.

Shevlin, M., & Miles, J. N. V. (1998). Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personality and Individual Differences, 25(1), 85–90.CrossRef

Shrigley, R. L. (1988). Defining attitude for science educators. Journal of Research in Science Teaching, 25(8), 659–678.CrossRef

Simpson, R. D., Koballa, T. R., Oliver, J. S., & Crawley, F. E. (1994). Research on the affective dimension of science learning. In D. Gabel (Ed.), Handbook of research on science teaching and learning (pp. 211–234). New York: Macmillan Publishing Co.

Simpson, R. D., & Oliver, J. S. (1990). A summary of major influences on attitude toward and achievement in science among adolescent students. Science Education, 74(1), 1–18.CrossRef

Sjoberg, L., Derbaix, C., & Jansson, B. (1987). Preference and similarity: Affective and cognitive judgement? Scandinavian Journal of Psychology, 28(1), 56–68.CrossRef

Talton, E. L., & Simpson, R. D. (1987). Relationships of attitude toward classroom environment with attitude toward and achievement in science among tenth grade biology students. Journal of Research in Science Teaching, 24(6), 507–525.CrossRef

Taraban, R., Box, C., Myers, R., Pollard, R., & Bowen, C. W. (2007). Effects of active-learning experiences on achievement, attitudes, and behaviors in high school biology. Journal of Research in Science Teaching, 44(7), 960–979.CrossRef

Teixeira Dos Santos, F. M., & Mortimer, E. F. (2003). How emotions shape the relationship between a chemistry teacher and her high school students. International Journal of Science Education, 25(9), 1095–1110.CrossRef

Zandvliet, D., & Fraser, B. J. (1999). A model of educational productivity for high school internet classrooms. Paper presented at the annual meeting of the American Educational Research Association, Montreal, Canada.

Title: The Psychometric Evaluation of a Three-Dimension Elementary Science Attitude Survey
Authors: Danhui Zhang
Todd Campbell
Publication date: 01-11-2011
Publisher: Springer Netherlands
Published in: Journal of Science Teacher Education / Issue 7/2011
Print ISSN: 1046-560X
Electronic ISSN: 1573-1847
DOI: https://doi.org/10.1007/s10972-010-9202-3

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 7/2011

Elementary Teachers’ Use of Graphical Representations in Science Teaching

Erratum to: Using Socioscientific Issues in Primary Classrooms

Epistemological Predictors of “Self Efficacy on Learning Biology” and “Test Anxiety Related to Evaluation of Learning on Biology” for Pre-service Elementary Teachers

Observed Implementation of a Science Professional Development Program for K-8 Classrooms

Cognitive and Attitudinal Predictors Related to Line Graphing Achievement among Elementary Pre-service Teachers

Exploring a Science Teacher’s Uncertainty with Integrating Engineering Design: An Action Research Study

Premium Partner