Email this article A Brief Scale on Attitude Toward Learning of Scientific Subjects (ATLoSS) for Middle School Students
Abstract
This paper aims at developing and validating a brief scale specifically assessing Attitude Toward Learning of Scientific Subjects (ATLoSS) and at testing its measurement invariance across genders. The scale was validated on a sample of 18,436 Italian students (51% males) attending middle schools at 7th grade by using both exploratory factor analysis and confirmatory factor analysis. The four item scale had good internal consistency with a Cronbach’s alpha of .864 and a one-factor solution characterized by measurement invariance across genders. Associations with other measures – in particular with math academic self-concept and interest/enjoyment in math – supported convergent and divergent validity of the scale; besides, good criterion validity based on student achievement and prospective choice of higher education was confirmed. The scale represents a brief and easy instrument which can be used in large scale student assessment and can provide teachers and educators with preliminary information on their students’ attitudes which are relevant for academic achievement.
Keywords
Full Text:
PDFReferences
Akman, B., İzgi, Ü., Bağçe, H., & Akıllı, H. İ. (2007). The effect of elementary students’ attitude toward science on their levels of test anxiety. Education and Science, 32(146), 3-11.
Argentin, G., Pennisi, A., Vidoni, D., Abbiati, G., & Caputo, A. (2014). Trying to raise (low) math achievement and to promote (rigorous) policy evaluation in Italy: Evidence from a large scale randomized trial. Evaluation Review, 38(2), 99-132. doi: 10.1177/0193841X14529125
Blalock, C. L., Lichtenstein, M. J., Owen, S., Pruski, L., Marshall, C., & Toepperwein, M. (2008). In pursuit of validity: A comprehensive review of science attitude instruments 1935-2005. International Journal of Science Education, 30(7), 961-977.
Britton, E. D., & Schneider, S. A. (2007). Large-scale assessments in science education. In S. K. Abell & N. G. Lederman (Eds.), Handbook of Research on Science Education (pp. 1007-1040). Mahwah, NJ: LEA.
Caputo, A. (2013). Students’ perception of school violence and math achievement in middle schools of Southern Italy. Educational Assessment, 18(4), 269-284. doi: 10.1080/10627197.2013.846679
Caputo, A. (2015). Le dimensioni motivazionali dell’apprendimento scolastico: uno studio correlazionale sul concetto di sé e gli stili di attribuzione [The motivational patterns of school learning: A correlational study on self-concept and attributions]. Educational, Cultural and Psychological Studies (ECPS), 12, 143-167. doi: 10.7358/ecps-2015-012-capu
Caputo, A., & Langher, V. (2015). Validation of the Collaboration and Support for Inclusive Teaching (CSIT) scale in special education teachers. Journal of Psychoeducational Assessment, 33(3), 210-222. doi: 10.1177/0734282914548335
Caputo, A., & Rastelli, V. (2014). School improvement plans and student achievement: Preliminary evidence from the Quality and Merit Project in Italy. Improving Schools, 17(1), 72-98. doi:10.1177/1365480213515800
Cheung, D. (2009). Developing a scale to measure students’ attitudes toward chemistry lessons. International Journal of Science Education, 31(16), 2185-2203.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233-255.
Chiapetta, E. L., & Koballa, T. R. (2002). Science instruction in the middle and secondary schools (5th ed.). Upper Saddle River, NJ: Merrill Prentice Hall.
Else-Quest, N. M., Mineo, C. C., & Higgins, A. (2013). Math and science attitudes and achievement at the intersection of gender and ethnicity. Psychology of Women Quarterly, 37(2), 293-309. doi: 10.1177/0361684313480694
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exp-loratory factor analysis in psychological research. Psychological Methods, 4, 272-299. doi: 10.1037/1082-989X.4.3.272
Field, A. (2013). Discovering statistics using SPSS. London: Sage.
Fraser, J. B. (1981). Test of Science-Related Attitudes (TOSRA). Melbourne: Australian Council for Educational Research.
French, B. F., & Finch, W. H. (2006). Confirmatory factor analytic procedures for the determination of measurement invariance. Structural Equation Modeling, 13(3), 378-402.
Gardner, K. J., & Qualter, P. (2011). Factor structure, measurement invariance and structural invariance of the MSCEIT V2.0. Personality and Individual Differences, 51(4), 492-496.
Gardner, P. L. (1975). Attitude to science: A review. Studies in Science Education, 2, 1-41.
Gasiewski, J. A., Eagan, M. A., Garcia, G. A., Hurtado, S., & Chang, M. J. (2012). From gatekeeping to engagement: A multicontextual, mixed method study of student academic engagement in introductory STEM courses. Research in Higher Education, 53(2), 229-261.
George, R. (2000). Measuring change in students’ attitudes toward science over time: an application of Latent Variable. Journal of Science Education an d Technology, 9(3), 213-225.
Hawkins, J., & Pea, R. D. (1987). Tools for bridging the cultures of everyday and scientific thinking. Journal of Research in Science Teaching, 24(4), 291-307.
Hu, L. T., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 76-99). Thousand Oaks, CA: Sage.
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. doi: 10.1080/10705519909540118
Hutcheson, G. D., & Sofroniou, N. (1999). The multivariate social scientist: Introductory statistics using generalized linear models. Thousand Oaks, CA: Sage.
INVALSI (2010). Rapporto tecnico. Validazione del Questionario Studente per il Servizio Nazionale di Valutazione [Technical Report: Validation of the Student Questionnaire for the National Evaluation Service]. Roma: INVALSI.
Irwing, P. (2012). Sex differences in g: An analysis of the US standardization sample of the WAIS-III. Personality and Individual Differences, 53(2), 126-131.
Kline, R. B. (2010). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.
Klopfer, L. E. (1971). Evaluation of learning in science. In B. S. Bloom, J. T. Hastings, & G. F. Madaus (Eds.), Handbook of formative and summative evaluation of student learning (pp. 559-642). London: McGraw-Hill.
Koballa, T. R., & Warden, M. A. (1992). Changing and measuring attitudes in the science classroom. In F. Lawrenz, K. Cochran, & J. Krajcik (Eds.), Research matters to the science teacher (pp. 75-83). Manhattan, KS: National Association for Research in Science Teaching.
Koballa, T. R. (1988). Attitude and related concepts in science education. Science Education, 72, 115-126.
Lakshmi, G. B., & Rao, D. B. (2003). Attitude toward science. New Delhi: Discovery Publishing House.
Langher, V., Caputo, A., & Ricci, M. E. (2017). The potential role of perceived support for reduction of special education teachers’ burnout. International Journal of Educational Psychology, 6(2), 120-147. doi: 10.17583/ijep.2017.2126
Langher, V., Ricci, M. E., Propersi, F., Glumbic, N., & Caputo, A. (2016). Inclusion in Mozambique: A case study on a cooperative learning intervention. Cultura Y Educaciòn: Culture and Education, 28(1), 47-71. doi: 10.1080/11356405.2015.1120447
Lavonen, J., Gedrovics, J., Byman, R., Meisalo, V., Jutti, K., & Uitto, A. (2008). Students’ motivational orientations and career choice in science and technology: a comparative investigation in finland and Latvia. Journal of Baltic Science Education, 7(2), 86-102.
Lee, J. (2009). Universals and specifics of math self-concept, math self-efficacy, and math anxiety across 41 PISA 2003 participating countries. Learning and Individual Differences, 19, 355-365.
Lepper, M. R. (1988). Motivational considerations in the study of instruction. Cognition and Instruction, 5(4), 289-309. doi: 10.1207/s1532690xci0504_3
Liebert, R. M., & Morris, L. W. (1967). Cognitive and emotional components of test anxiety: A distinction and some initial data. Psychological Reports, 20, 975-978. doi: 10.2466/pr0.1967.20.3.975
Marsh, H. W., & Shavelson, R. J. (1985). Self-concept: Its multifaceted, hierarchical structure. Educational Psychologist, 20, 107-125. doi: 10.1207/s15326985ep2003_1
Martuza, V. R. (1977). Applying norm-referenced and criterion-referenced measurement in education. Boston, MA: Allyn & Bacon.
Mullis, I. V. S., Martin, M. O., Olson, J. F., Berger, D. R., Milne, D., & Stanco, G. M. (Eds.). (2008). TIMSS 2007 Encyclopedia: A guide to mathematics and science education around the world. Chestnut Hill, MA: Boston College.
Narmadha, U., & Chamundeswari, S. (2013). Attitude toward learning of science and academic achievement in science among students at the secondary level. Journal of Sociological Research, 4(2), 114-124.
Nasir, M., & Kono, Y. (2004). Development and validation of constructivist learner scale (CLS) for elementary school science students. Educational Technology Research, 27(1-2), 1-7.
Olsson, U. H., Foss, T., Troye, S. V., & Howell, R. D. (2000). The performance of ML, GLS, and WLS estimation in structural equation modeling under conditions of misspecification and nonnormality. Structural Equation Modeling, 7, 557-595. doi: 10.1207/S15328007SEM0704_3
Osborne, J., Simon, S., & Collins, S. (2003). Attitudes toward science: A review of the literature and its implications. International Journal of Science Education, 25, 1049-1079. doi: 10.1080/0950069032000032199
Parkinson, J., Hendley, D., Tanner, H., & Stables, A. (1998). Pupil’s attitudes to science in Key stage 3 of the national curriculum: a study of pupils in South Wales. Research in Science and Technological Education, 16(2), 165-176.
Peat, J., & Barton, B. (2008). Medical statistics: A guide to data analysis and critical appraisal. London: BMJ Books.
Pekrun, R., & Linnenbrink-Garcia, L. (2014). International handbook of emotions in education. New York: Routledge.
Pell, T., & Jarvis, T. (2001). Developing attitude to science scales for use with children of ages from five to eleven years. International Journal of Science Education, 23(8), 847-862.
Pintrich, P. R., & De Groot, E. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-50. doi: 10.1037/0022-0663.82
Pirchio, S., Passiatore, Y., Carrus, G., Maricchiolo, F., Taeschner, T., & Arcidiacono, F. (2017). Teachers and parents involvement for a good school experience of native and immigrant children. Journal of Educational, Cultural And Psychological Studies, 15, 73-94. doi: 10.7358/Ecps-2017-015-Pirc
Pirchio, S., Taeschner, T., Colibaba, A. C., Gheorghiu & Zacharová, Z. J.
(2015). Family involvement in second language learning: The Bilfam
project. In S. Mourão & M. Lourenço (Eds.), Early years second language
education (pp. 204-217). Oxon: Routledge-Taylor and Francis. doi:
4324/9781315889948
Poliandri, D., Cardone, M., Muzzioli, P., & Romiti, S. (2011). A rating scale
model for a scale of test anxiety in Italy. Working Paper 11. Retrieved from National Institute for the Educational Evaluation of Instruction and Training (INVALSI) website: http://www.invalsi.it/download/wp/wp11Poliandri.pdf
Prediger, S. (2001). Mathematics learning is also intercultural learning. Intercultural Education, 12(2), 163-171. doi: 10.1080/14675980120064809
Reiss, M. J. (2004). Students’ attitudes toward science: A long term perspective. Canadian Journal of Science, Mathematics and Technology Education, 4, 97-109.
Renmin, Y., Raymonds, W. R., Susan, T., & Hanxia, R. (1998). Student attitudes toward science learning: A cross-national study of American and Chinese secondary school students. Paper presented at the Annual Meeting of the National Science Teachers Association, Las Vegas, NV, April 16-19.
Schumacker, R. E., & Lomax, R. G. (2010). A beginner’s guide to structural equation modeling. Mahwah, NJ: Lawrence Erlbaum.
Shah, Z. A., & Mahmood, N. (2011). Developing a scale to measure attitude towardscience learning among school students. Bulletin of Education and Research, 33(1), 71-81.
Tanaka, J. S. (1993). Multifaceted conceptions of fit in structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 10-39). Newbury Park, CA: Sage.
TIMSS (1999). Trends in mathematics and science achievement around the world. http://timss.bc.edu/timss1999.htm
Weinburgh, M. H. (2000). Gender, ethnicity, and grade level as predictors of middle school students’ attitudes toward science. ERIC, ED442662.
DOI: https://doi.org/10.7358/ecps-2017-016-capu
Copyright (©) 2017 Journal of Educational, Cultural and Psychological Studies (ECPS Journal) – Editorial format and Graphical layout: copyright (©) LED Edizioni Universitarie
Journal of Educational, Cultural and Psychological Studies (ECPS)
Registered by Tribunale di Milano (19/05/2010 n. 278)
Online ISSN 2037-7924 - Print ISSN 2037-7932
Research Laboratory on Didactics and Evaluation - Department of Education - "Roma Tre" University
Executive Editor: Gaetano Domenici - Associate Executive Editor & Managing Editor: Valeria Biasci
Editorial Board: Eleftheria Argyropoulou - Massimo Baldacci - Joao Barroso - Richard Bates - Christofer Bezzina - Paolo Bonaiuto - Lucia Boncori - Pietro Boscolo - Sara Bubb - Carlo Felice Casula - Jean-Émile Charlier - Lucia Chiappetta Cajola - Carmela Covato - Jean-Louis Derouet - Peter Early - Franco Frabboni - Constance Katz - James Levin - Pietro Lucisano - Roberto Maragliano - Romuald Normand - Michael Osborne - Donatella Palomba - Michele Pellerey - Clotilde Pontecorvo - Vitaly V. Rubtzov - Jaap Scheerens - Noah W. Sobe - Francesco Susi - Giuseppe Spadafora - Pat Thomson
Editorial Staff: Fabio Alivernini - Guido Benvenuto - Anna Maria Ciraci - Massimiliano Fiorucci - Luca Mallia - Massimo Margottini - Giovanni Moretti - Carla Roverselli
Editorial Secretary:Nazarena Patrizi
© 2001 LED Edizioni Universitarie di Lettere Economia Diritto