Book review: K. Sadeghi (Ed.), Technology-Assisted Language Assessment in Diverse Contexts: Lessons from the Transition to Online Testing During Covid-19
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引用次数: 0
Abstract
Agresti, A. (2013). Categorical data analysis (3rd ed.). Wiley. Dixon, P. (2008). Models of accuracy in repeated-measures designs. Journal of Memory and Language, 59(4), 447–456. https://doi.org/10.1016/j.jml.2007.11.004 Doran, H., Bates, D., Bliese, P., & Dowling, M. (2007). Estimating the multilevel Rasch model: With the lme4 package. Journal of Statistical Software, 20(2), 1–18. https://doi.org/10.18637/ jss.v020.i02 Embretson, S., & Gorin, J. (2001). Improving construct validity with cognitive psychology principles. Journal of Educational Measurement, 38(4), 343–368. https://doi.org/10. 1111/j.1745-3984.2001.tb01131.x Jiang, Z. (2018). Using the linear mixed-effect model framework to estimate generalizability variance components in R. Methodology, 14(3), 133–142. https://doi.org/10.1027/1614-2241/ a000149 Kidd, E., Donnelly, S., & Christiansen, M. H. (2018). Individual differences in language acquisition and processing. Trends in Cognitive Sciences, 22(2), 154–169. https://doi.org/10.1016/j. tics.2017.11.006
期刊介绍:
Language Testing is a fully peer reviewed international journal that publishes original research and review articles on language testing and assessment. It provides a forum for the exchange of ideas and information between people working in the fields of first and second language testing and assessment. This includes researchers and practitioners in EFL and ESL testing, and assessment in child language acquisition and language pathology. In addition, special attention is focused on issues of testing theory, experimental investigations, and the following up of practical implications.