Diagnosing English learners’ writing skills: A cognitive diagnostic modeling study

References

• Alderson, J. C. (2005). Diagnosing foreign language proficiency: The interface between learning and assessment. London: Continuum.
   Google Scholar
• Alderson, J. C., Haapakangas, E. L., Huhta, A., Nieminen, L., & Ullakonoja, R. (2015). The diagnosis of reading in a second or foreign language. New York, NY: Routledge.
   Google Scholar
• Aryadoust, V. (2018). Using recursive partitioning Rasch trees to investigate differential item functioning in second language reading tests. Studies in Educational Evaluation, 56, 197–19. doi:10.1016/j.stueduc.2018.01.003
   Web of Science ®Google Scholar
• Aryadoust, V., & Shahsavar, Z. (2016). Investigating the validity of the Persian blog attitude questionnaire: An evidence-based approach. Journal of Modern Applied Statistical Methods, 15(1), 417–451. doi:10.22237/jmasm/1462076460
   Web of Science ®Google Scholar
• Bacha, N. (2001). Writing evaluation: What can analytic versus holistic essay scoring tell us? System, 29, 371–383. doi:10.1016/S0346-251X(01)00025-2
   Google Scholar
• Banerjee, J., & Wall, D. (2006). Assessing and reporting performances on pre-sessional EAP courses: Developinga final assessment checklist and investigating its validity. Journal of English for Academic Purposes, 5(1), 50–69. doi:10.1016/j.jeap.2005.11.003
   Google Scholar
• Bergström, K. (2008) Vocabulary and receptive knowledge of English collocations among Swedish upper secondary school students (Unpublished doctoral dissertation), Stockholm University, Sweden.
   Google Scholar
• Carroll, J. B. (1968). The psychology of language testing. In A. Davies (Ed.), Language Testing Symposium: A Psycholinguistic Approach (pp. 46–69). Oxford, UK: Oxford University Press.
   Google Scholar
• Crocker, L. M., & Algina, J. (1986). Introduction to classical and modern test theory. New York: Holt: Rinehart and Winston.
   Google Scholar
• Engelhard, G. (2013). Invariant measurement: Using Rasch models in the social, behavioral, and health sciences. New York: Routledge.
   Google Scholar
• Hartz, S., Roussos, L., & Stout, W. (2002). Skill Diagnosis: Theory and practice [Computer software user manual for Arpeggio software]. Princeton, NJ: Educational Testing Service.
   Google Scholar
• Henson, R., Templin, J., & Willse, J. (2009). Defining a family of cognitive diagnosis models using log linear models with latent variables. Psychometrika, 74(2), 191–210. doi:10.1007/s11336-008-9089-5
   Web of Science ®Google Scholar
• Imbos, T. (2007). Thoughts about the development of tools for cognitive diagnosis of students’ writings in an e-learning environment. IASE/ISI Satellite’ Retrieved from http://iase-web.org/documents/papers/sat2007/Imbos.pdf
   Google Scholar
• Jang, E. E. (2008). A framework for cognitive diagnostic assessment. In C. A. Chapelle, Y. R. Chung, & J. Xu (Eds.), Towards adaptive CALL: Natural Language Processing for Diagnostic Language Assessment (pp. 117‐131). Ames: Iowa State University.
   Google Scholar
• Kato, K. (2009) Improving efficiency of cognitive diagnosis by using diagnostic items and adaptive testing(Unpublished doctoral dissertation), Minnesota University, USA.
   Google Scholar
• Kim, A. Y. (2015). Exploring ways to provide diagnostic feedback with an ESL placement test: Cognitive diagnostic assessment of L2 reading ability. Language Testing, 32(2), 227–258. doi:10.1177/0265532214558457
   Web of Science ®Google Scholar
• Kim, Y. H. (2010). An argument-based validity inquiry into the empirically-derived descriptor-based diagnostic (EDD) assessment in ESL academic writing (Unpublished doctoral dissertation), University of Toronto, Canada.
   Google Scholar
• Kim, Y. H. (2011). Diagnosing EAP writing ability using the reduced reparameterized unified. Language Testing, 28(4), 509–541. doi:10.1177/0265532211400860
   Web of Science ®Google Scholar
• Knoch, U. (2011). Rating scales for diagnostic assessment of writing: What should they look like and where should the criteria come from? Assessing Writing, 16(2), 81–96. doi:10.1016/j.asw.2011.02.003
   Google Scholar
• Kobayashi, H., & Rinnert, C. (2013). L1/L2/L3 writing development: Longitudinal case study of a Japanese multicompetent writer. Journal of Second Language Writing, 22(1), 4–33. doi:10.1016/j.jslw.2012.11.001
   Web of Science ®Google Scholar
• Lado, R. (1961). Language testing. New York: McGraw-Hill.
   Google Scholar
• Lee, Y. S., Park, Y. S., & Taylan, D. (2011). A cognitive diagnostic modeling of attribute mastery in Massachusetts, Minnesota, and the U.S. national sample using the TIMSS 2007. International Journal of Testing, 11(2), 144–177. doi:10.1080/15305058.2010.534571
   Google Scholar
• Lee, Y. W., Gentile, C., & Kantor, R. (2010). Toward automated multi-trait scoring of essays: Investigating links among holistic, analytic, and text feature scores. Applied Linguistics, 31(3), 391–417. doi:10.1093/applin/amp040
   Web of Science ®Google Scholar
• Lee, Y. W., & Sawaki, Y. (2009). Cognitive diagnostic approaches to language assessment: An overview. Language Assessment Quarterly, 6(3), 72–189.
   Web of Science ®Google Scholar
• Li, H., & Suen, H. K. (2013). Constructing and validating a Q-matrix for cognitive diagnostic analyses of a reading test. Educational Assessment, 18(1), 1–25. doi:10.1080/10627197.2013.761522
   Google Scholar
• Linacre, J. M. (1994). Many-facet Rasch measurement. Chicago: MESA Press.
   Google Scholar
• Madsen, H. S. (1983). Techniques in Testing. Oxford, UK: Oxford University Press.
   Google Scholar
• Mak, P., & Lee, I. (2014). Implementing assessment for learning in L2 writing: An activity theory perspective. System, 47, 73–87. doi:10.1016/j.system.2014.09.018
   Web of Science ®Google Scholar
• Messick, S. (1989). Validity. In R. Linn (Ed.), Educational measurement (3rd ed., pp. 13–103). Washington, DC: American Council on Education/Macmillan.
   Google Scholar
• Milanovic, M., Saville, N., & Shuhong, S. (1996). A study of the decision making behavior of composition markers. In M. Milanovic & N. Saville (Eds.), Studies in language testing 3: Performance testing, cognition and assessment (pp. 92–111). Cambridge: Cambridge University Press.
   Google Scholar
• Montero, D. H., Monfils, L., Wang, J., Yen, W. M., & Julian, M. W. (2003, April). Investigation of the application of cognitive diagnostic testing to an end-of-course high school examination. Paper presented at the Annual Meeting of the National Council on Measurement in Education. Chicago, IL.
   Google Scholar
• Nacira, G. (2010). Identification and analysis of some factors behind students. Poor writing productions the case study of 3rd year students at the English department (Unpublished master thesis), Batna University, Algeria.
   Google Scholar
• North, B. (2003). Scales for rating language performance: Descriptive models, formulation styles, and presentation formats. TOEFL Monograph 24. Princeton NJ: Educational Testing Service.
   Google Scholar
• Ransdell, S., & Barbier, M. L. (2002). New directions for research in L2 writing. the Netherlands: Kluwer Academic Publishers.
   Google Scholar
• Roberts, M. R., & Gierl, M. (2010). Developing score reports for cognitive diagnostic assessments. Educational Measurement: Issues and Practice, 29(3), 25–38. doi:10.1111/emip.2010.29.issue-3
   Google Scholar
• Roussos, L., Xueli, X., & Stout, W. (2003). Equating with the Fusion model using item parameter invariance. Unpublished manuscript, University of Illinois, Urbana-Champaign.
   Google Scholar
• Roussos, L. A., DiBello, L. V., Henson, R. A., & Jang, E. E. (2010). Skills diagnosis for education and psychology with IRT-based parametric latent class models. In S. Embretson & J. Roberts (Eds.), New directions in psychological measurement with model-based approaches (pp. 35–69). Washington, DC, US: American Psychological Association.
   Google Scholar
• Sofi, W. (2013). The influence of students’ mastery on collocation toward their writing (Unpublished thesis), State Institute of Islamic Studies, Salatiga, Indonesia.
   Google Scholar
• Struthers, L., Lapadat, J. C., & MacMillan, P. D. (2013). Assessing cohesion in children‘s writing: Development of a checklist. Assessing Writing, 18(3), 187–201. doi:10.1016/j.asw.2013.05.001
   Web of Science ®Google Scholar
• Tatsuoka, K. K. (1983). Rule space: An approach for dealing with misconceptions based on item response theory. Journal of Educational Measurement, 20(4), 345–354. doi:10.1111/jedm.1983.20.issue-4
   Web of Science ®Google Scholar
• Vakili, S., & Ebadi, S. (2019). Investigating contextual effects on Iranian EFL learners` mediation and reciprocity in academic writing. Cogent Education, 6(1), 1571289. doi:10.1080/2331186X.2019.1571289
   Web of Science ®Google Scholar
• Weigle, S. C. (2002). Assessing writing. UK: Cambridge University Press.
   Google Scholar
• Xie, Q. (2017). Diagnosing university students’ academic writing in English: Is cognitive diagnostic modelling the way forward? Educational Psychology, 37(1), 26–47. doi:10.1080/01443410.2016.1202900
   Web of Science ®Google Scholar
• Zhang, Y., DiBello, L., Puhan, G., Henson, R., & Templin, J. (2006, April). Estimating skills classification reliability of student profiles scores for TOEFL Internet-based test. Paper presented at the annual meeting of the National Council on Measurement in Education. San Francisco, CA.
   Google Scholar