This chapter explains how exploratory factor analysis (EFA) is used to explore common factors that account for participants’ responses to research instruments, such as Likert-type scale questionnaires and tests. It provides an overview of important aspects, considerations and practical guidelines for conducting EFA. This chapter compares and contrasts some differences and similarities among EFA, confirmatory factor analysis and principal component analysis. Key steps for EFA are presented through the use of IBM SPSS (Statistical Package for Social Sciences).


Exploratory factor analysis (EFA) Principal component analysis (PCA) Factor loading Factor extraction Factor rotation Parallel analysis Questionnaires Tests Statistical Package for Social Sciences (SPSS) 


  1. Asención-Delaney, Y., & Collentine, J. (2011). A multidimensional analysis of a written L2 Spanish corpus. Applied Linguistics, 32(3), 299–322.CrossRefGoogle Scholar
  2. Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  3. Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York and London: Guilford Press.Google Scholar
  4. Cheng, L., Andrews, S., & Yu, Y. (2010). Impact and consequences of school-based assessment (SBA): Students’ and parents’ views of SBA in Hong Kong. Language Testing, 28(2), 221–249.CrossRefGoogle Scholar
  5. Davis, J. M. (2016). Toward a capacity framework for useful student learning outcomes assessment in college foreign language programs. Modern Language Journal, 100(1), 377–399.CrossRefGoogle Scholar
  6. DiStefano, C., Zhu, M., & Mîndrilă, D. (2009). Understanding and using factor scores: Considerations for the applied researcher. Practical Assessment, Research & Evaluation, 14(20). Retrieved from
  7. Dörnyei, Z., & Chan, L. (2013). Motivation and vision: An analysis of future L2 self images, sensory styles, and imagery capacity across two target languages. Language Learning, 63(3), 437–462.CrossRefGoogle Scholar
  8. Fabrigar, L. R., & Wegener, D. T. (2012). Exploratory factor analysis. Oxford: Oxford University Press.Google Scholar
  9. Field, A. (2013). Discovering statistics using IBM SPSS statistics (3rd ed.). Los Angeles: SAGE.Google Scholar
  10. Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185.CrossRefGoogle Scholar
  11. Kozaki, Y., & Ross, S. J. (2011). Contextual dynamics in foreign language learning motivation. Language Learning, 61(4), 1328–1354.CrossRefGoogle Scholar
  12. Ledesma, R. D., & Valero-Mora, P. (2007). Determining the number of factors to retain in EFA: An easy-to-use computer program for carrying out Parallel Analysis. Practical Assessment Research & Evaluation, 12(2). Retrieved from
  13. Mizumoto, A., & Takeuchi, O. (2011). Adaptation and validation of self-regulating capacity in vocabulary learning scale. Applied Linguistics, 33(1), 83–91.CrossRefGoogle Scholar
  14. Murray, J. C., Riazi, A. M., & Cross, J. L. (2012). Test candidates’ attitudes and their relationship to demographic and experiential variables: The case of overseas trained teachers in NSW, Australia. Language Testing, 29(4), 577–595.CrossRefGoogle Scholar
  15. O’Brien, M. G. (2014). L2 learners’ assessments of accentedness, fluency, and comprehensibility of native and nonnative German speech. Language Learning, 64(3), 715–748.CrossRefGoogle Scholar
  16. O’Connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instrumentation, and Computers, 32(3), 396–402.CrossRefGoogle Scholar
  17. Osborne, J. W. (2014). Best practices in exploratory factor analysis. Lexington, KY: CreateSpace Independent Publishing Platform.Google Scholar
  18. Peng, J. E., & Woodrow, L. (2010). Willingness to communicate in English: A model in the Chinese EFL classroom context. Language Learning, 60(4), 834–876.CrossRefGoogle Scholar
  19. Phakiti, A. (2003a). A closer look at gender differences in strategy use in L2 reading. Language Learning, 53(4), 649–702.CrossRefGoogle Scholar
  20. Phakiti, A. (2003b). A closer look at the relationship of cognitive and metacognitive strategy use to EFL reading comprehension test performance. Language Testing, 20(1), 26–56.CrossRefGoogle Scholar
  21. Phakiti, A. (2006). Modeling cognitive and metacognitive strategies and their relationships to EFL reading test performance. Melbourne Papers in Language Testing, 11, 53–102.Google Scholar
  22. Plonsky, L., & Gonulal, T. (2015). Methodological synthesis in quantitative L2 research: A review of reviews and a case study of exploratory factor analysis. Language Learning, 65(S1), 9–36.CrossRefGoogle Scholar
  23. Roever, C., & Phakiti, A. (2018). Quantitative methods for second language research: A problem-solving approach. New York: Routledge.Google Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  1. 1.Sydney School of Education and Social WorkThe University of SydneySydneyAustralia

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