Psychometric Properties of the Willingness to Read Questionnaire in an EFL Context
Subject Areas :
saeed mojaradi
1
,
Masoud Zoghi
2
*
,
nader assadi
3
1 - Department of ELT, Ahar Branch, Islamic Azad University, Ahar, Iran
2 - Department of English Language Teaching, Islamic Azad University, Ahar Branch, Ahar, Iran
3 - Department of English Language Teaching, Ahar Branch, Islamic Azad University, Ahar, Iran
Keywords: EFL reading, psychometric properties, willingness to communicate, willingness to read,
Abstract :
Willingness to read (WTR) is often assumed to be part of a blanket term known as willingness to communicate (WTC). Although the linguistic bases underlying WTR might be similar to WTC, the theoretical explanations of WTR are most likely to be different from WTC. Given the importance of this construct, the design of an independent, valid, and reliable instrument for WTR measurement seems to be a major requirement in the literature. Using a correlational study, we developed a willingness to read questionnaire (WTRQ) and checked its psychometric properties to ensure the WTRQ’s accuracy and appropriateness in an EFL context. In this correlational study, we utilized convenience sampling to recruit our research sample, which comprised 269 participants consisting of EFL learners with varying levels of proficiency. Results obtained from exploratory and confirmatory factor analysis revealed a 5-factor WTRQ with 40 items. Findings also showed that the WTRQ enjoys acceptable psychometric properties in terms of reliability and validity. The study concludes that the WTRQ has the potential to be employed in EFL reading research as a validated instrument for measuring WTR.
Atef-Vahid, S., & Fard Kashani, A. (2011). The Effect of English learning anxiety on Iranian high-school students’ English language achievement. Broad Research in Artificial Intelligence and Neuroscience, 2(3)29-44. https://lumenpublishing.com/journals/index.php/brain/article/view/1888
Chin, W.W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.). Modern Methods for Business Research (pp. 295–336). Erlbaum.
Cox, K. E., Guthrie, J. T., Metsala, J. L., & Wigfield, A. (2004). Motivational and cognitive predictors of text comprehension and reading amount. Scientific Studies of Reading, 3(3), 231-256.
de Vaus, D. (2004). Surveys in social research (5th ed.). Routledge.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Gambrell, L. B. (2011). Seven rules of engagement: What’s most important to know about motivation to read? The Reading Teacher, 65(3), 172-178.
Gotz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In V. E. Vinzi, W.W. Chin, J. Henseler, & H. Wang (Eds.). Handbook of Partial Least Squares (pp. 691–711). Springer. https://doi.org/10.1007/978-3-540-32827-8_30
Grabe, W., & Stoller, F.L. (2019). Teaching and researching reading (3rd ed.). Routledge. https://doi.org/10.4324/9781315726274
Guthrie, J. (2004). Teaching for literacy engagement. Journal of Literacy Research, 36(1), 1 – 28.
Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd Ed.). Sage.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Kirchner, E. & Mostert, M. L. (2017). Aspects of the reading motivation and reading activity of Namibian primary school readers. Cogent Education, 4(1). https://doi.org/ 10.1080/2331186X.2017.1411036
Khajavy, G.H., & Ghonsooly, B. (2017). Predictors of willingness to read in English: Testing a model based on possible selves and self-confidence. Journal of Multilingual and Multicultural Development, 1(2), 1-15. https://doi.org/10.1080/01434632.2017.1284853
Kline, R. B. (2016). Principles and practise of structural equation modeling (4th ed.). Guilford.
Kuppens, P., Oravecz, Z., & Tuerlinckx, F. (2010). Feelings change: Accounting for individual differences in the temporal dynamics of affect. Journal of Personality and Social Psychology, 99(6), 1042–1060. https://doi.org/10.1037/a0020962
Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563-575.
MacIntyre, P. D., Baker, S. C., Clément, R., & Conrod, S. (2001). Willingness to communicate, social support, and language-learning orientations of immersion students. Studies In Second Language Acquisition, 23(3), 369-388. https://doi.org/10.1017/S0272263101003035
Mojarradi, S., Zoghi, M., & Assadi, N. (in press).
Moomaw, J. (2013). Factors that foster or hinder student reading motivation in a suburban primary school (M.S. Thesis). http://hdl.handle.net/20.500.12648/5374
Mundfrom, D. J., Shaw, D. G., Lu Ke, T. (2005). Minimum sample size recommendations for conducting factor analysis, International Journal of Testing, 5(2), 159-168.
Norris, J., & Ortega, L. (2003). Defining and measuring SLA. In C. J. Doughty & M. H. Long (Eds.), The handbook of second language acquisition (pp. 717–761). Blackwell. https://doi.org/10.1002/9780470756492
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
Rae, G. (2007). A note on using stratified alpha to estimate the composite reliability of a test composed of interrelated nonhomogeneous items. Psychological Methods, 12(2), 177–184. https://doi.org/10.1037/1082-989X.12.2.177
Richards, J. C. (2022). Exploring emotions in language teaching. RELC Journal, 53(1), 225–239. https://doi.org/10.1177/0033688220927531
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research, 8(2), 23–74.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159–205.
Tilden, V. P., Nelson, C. A., & May, B. A. (1990). Use of qualitative methods to enhance content validity. Nursing Research, 39(3), 172-175.
Weir, C. J. (2005). Language testing and validation: An evidence-based approach. Palgrave-Macmillan.
Wigfield, A., Guthrie, J. T., Tonks, S., & Perencevich, K. C. (2004). Children’s motivation for reading: Domain specificity and instructional influences. The Journal of Educational Research, 97(6), 299-309.
Yong, A. G., & Pearce, S. (2013). A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79–94.