Diagnosing university students’ academic writing in English: Is cognitive diagnostic modelling the way forward?

References

• Alderson, J. C. (2005). Diagnosing foreign language proficiency: The interface between learning and assessment. London: Continuum.
   Google Scholar
• Alderson, J. C., Poehner, M., Jang, E. E., & Chapelle, C. A. (2013). Future of diagnostic language assessment: Moving beyond where we are. Paper presented at the 35th Language Testing Research Colloquium, Seoul, Korea.
   Google Scholar
• Aryadoust, V. (2011). Application of the fusion model to while-listening performance tests. Shiken: JALT Testing & Evaluation SIG Newsletter, 15, 2–9.
   Google Scholar
• Aryadoust, V. (2015). Self-and peer assessments of oral presentations by first-year university students. Educational Assessment, 20, 199–225.10.1080/10627197.2015.1061989
   Web of Science ®Google Scholar
• Bacha, N. (2001). Writing evaluation: What can analytic versus holistic essay scoring tell us? System, 29, 371–383.10.1016/S0346-251X(01)00025-2
   Google Scholar
• Banerjee, J., & Wall, D. (2006). Assessing and reporting performances on pre-sessional EAP courses: Developing a final assessment checklist and investigating its validity. Journal of English for Academic Purposes, 5, 50–69.10.1016/j.jeap.2005.11.003
   Google Scholar
• Bray, M., & Kwok, P. (2003). Demand for private supplementary tutoring: Conceptual considerations, and socio-economic patterns in Hong Kong. Economics of Education Review, 22, 611–620.10.1016/S0272-7757(03)00032-3
   Web of Science ®Google Scholar
• Buck, G., & Tatsuoka, K. (1998). Application of the rule-space procedure to language testing: Examining attributes of a free response listening test. Language Testing, 15, 119–157.
   Google Scholar
• Cooper, W. H. (1981). Ubiquitous halo. Psychological Bulletin, 90, 218–244.10.1037/0033-2909.90.2.218
   Web of Science ®Google Scholar
• de la Torre, J. (2011). The generalized DINA model framework. Psychometrika, 76, 179–199.10.1007/s11336-011-9207-7
   Web of Science ®Google Scholar
• de la Torre, J. (2014). Cognitive diagnostic modeling: A general framework approach. Unpublished course material for a 2-day workshop at the Hong Kong Institute of Education, Hong Kong
   Google Scholar
• Eckes, T. (2009). Many-facet Rasch measurement. In S. Takala (Ed.), Reference supplement to the manual for relating language examinations to the Common European Framework of Reference for Languages: Learning, teaching, assessment (Section H, pp. 1–52). Strasbourg: Council of Europe/Language Policy Division.
   Google Scholar
• Eckes, T. (2011). Introduction to many-facet Rasch measurement. Frankfurt: Peter Lang.
   Google Scholar
• Engelhard, G. (2013). Invariant measurement: Using Rasch models in the social, behavioral, and health sciences. New York, NY: Routledge.
   Google Scholar
• Haertel, E. H. (1989). Using restricted latent class models to map the skill structure of achievement items. Journal of Educational Measurement, 26, 301–321.10.1111/jedm.1989.26.issue-4
   Web of Science ®Google Scholar
• Hamp-Lyons, L. (1991). Scoring procedures for ESL contexts. In L. Hamp-Lyons (Ed.), Assessing second language writing in academic contexts (pp. 241–276). Norwood, NJ: Ablex.
   Google Scholar
• Hamp-Lyons, L. (1995). Rating nonnative writing: The trouble with holistic scoring. TESOL Quarterly, 29, 759–762.10.2307/3588173
   Web of Science ®Google Scholar
• Hartz, S., Roussos, L., & Stout, W. (2002). Skills diagnosis: Theory and practice [User manual for Arpeggio software]. Princeton, NJ: ETS.
   Google Scholar
• Henson, R., Templin, J., & Douglas, J. (2007). Using efficient model based sum-scores for conducting skills diagnoses. Journal of Educational Measurement, 44, 361–376.10.1111/jedm.2007.44.issue-4
   Web of Science ®Google Scholar
• Jacob, H. L., Zinkgraf, S. A., Wormuth, D. R., Hartfiel, V. F., & Hughey, J. B. (1981). Testing ESL composition: A practical approach. Rowley, MA: Newbury House.
   Google Scholar
• Jang, E. E. (2009). Cognitive diagnostic assessment of L2 reading comprehension ability: Validity arguments for Fusion Model application to LanguEdge assessment. Language Testing, 26, 31–73.10.1177/0265532208097336
   Web of Science ®Google Scholar
• Jarvis, S., Grant, L., Bikowski, D., & Ferris, D. (2003). Exploring multiple profiles of highly rated learner compositions. Journal of Second Language Writing, 12, 377–403.10.1016/j.jslw.2003.09.001
   Web of Science ®Google Scholar
• Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25, 258–272.10.1177/01466210122032064
   Web of Science ®Google Scholar
• Kim, Y. H. (2011). Diagnosing EAP writing ability using the reduced Reparameterized Unified Model. Language Testing, 28, 509–541.10.1177/0265532211400860
   Web of Science ®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, 227–258.10.1177/0265532214558457
   Web of Science ®Google Scholar
• Knoch, U. (2009). Diagnostic writing assessment: The development and validation of a rating scale. Frankfurt: Peter Lang.
   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, 81–96.10.1016/j.asw.2011.02.003
   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, 391–417.10.1093/applin/amp040
   Web of Science ®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, 144–177.10.1080/15305058.2010.534571
   Google Scholar
• Lee, Y. W., & Sawaki, Y. (2009a). Application of three cognitive diagnosis models to esl reading and listening assessments. Language Assessment Quarterly, 6, 239–263.10.1080/15434300903079562
   Web of Science ®Google Scholar
• Lee, Y. W., & Sawaki, Y. (2009b). Cognitive diagnosis approaches to language assessment: An overview. Language Assessment Quarterly, 6, 172–189.10.1080/15434300902985108
   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), 1–25.10.1080/10627197.2013.761522
   Google Scholar
• Linacre, J. M. (2012). Facets computer program for many-facet Rasch measurement, version 3.70.0. Beaverton, OR: Winsteps.com.
   Google Scholar
• Maris, E. (1999). Estimating multiple classification latent class models. Psychometrika, 64, 187–212.10.1007/BF02294535
   Web of Science ®Google Scholar
• McNamara, T. (1996). Measuring second language performance. London: Longman.
   Google Scholar
• McNamara, D. S., Louwerse, M. M., McCarthy, P. M., & Graesser, A. C. (2010). Coh-Metrix: Capturing linguistic features of cohesion. Discourse Processes, 47, 292–330.10.1080/01638530902959943
   Web of Science ®Google Scholar
• Roussos, L. A., DiBello, L. V., Stout, W., Hartz, S. M., Henson, R. A., & Templin, J. L. (2007). The fusion model skills diagnosis system. In J. Leighton & M. Gierl (Eds.), Cognitive diagnostic assessment for education (pp. 275–318). New York, NY: Cambridge University Press.10.1017/CBO9780511611186
   Google Scholar
• Rupp, A. A., & Templin, J. L. (2008). Unique characteristics of diagnostic classification models: A comprehensive review of the current state-of-the-art. Measurement, 6, 219–262.
   Google Scholar
• Rupp, A. A., Templin, J. L., & Henson, R. A. (2010). Diagnostic measurement: Theory, methods, and applications. New York, NY: Guilford Press.
   Google Scholar
• Sawaki, Y., Kim, H.-J., & Gentile, C. (2009). Q-matrix construction: Defining the link between constructs and test items in large-scale reading and listening comprehension assessments. Language Assessment Quarterly, 6, 190–209.10.1080/15434300902801917
   Web of Science ®Google Scholar
• Struthers, L., Lapadat, J. C., & MacMillan, P. D. (2013). Assessing cohesion in children’s writing: Development of a checklist. Assessing Writing, 18, 187–201.10.1016/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, 345–354.10.1111/jedm.1983.20.issue-4
   Web of Science ®Google Scholar
• Tatsuoka, K. K., Corter, J. E., & Tatsuoka, C. (2004). Patterns of diagnosed mathematical content and process skills in TIMSS-R across a sample of 20 countries. American Educational Research Journal, 41, 901–926.10.3102/00028312041004901
   Web of Science ®Google Scholar
• von Davier, M. (2006). Multidimensional latent trait modeling (MDLTM) [Software program]. Princeton, NJ: Educational Testing Service.
   Google Scholar
• Weigle, S. C. (2002). Assessing writing. Cambridge: Cambridge University Press.10.1017/CBO9780511732997
   Google Scholar
• Wiersma, W. (2000). Research methods in education (7th ed.). Boston, MA: Allyn and Bacon.
   Google Scholar
• Wright, B. D., & Linacre, J. M. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8, 370. Retrieved from https://mmm1406.sanjose14-verio.com/rascho/rmt/rmt83b.htm
   Google Scholar