Thesis: Automaticity in L2 learning: Theories, findings, and implications.
Committee: Dr. Yasuko Ito
Maie, R. & DeKeyser, R. M. (2020). Conflicting evidence of explicit and implicit knowledge from objective and subjective measures. Studies in Second Language Acquisition, 42, 359-382. Download
Maie, R. & Salen, B. (2021). Blustery with an occasional downpour: An analysis of target discourse in media weather forecasts. In M. J. Ahmaidan & M. H. Long (Eds.), The Cambridge handbook of task-based language teaching. Cambridge: Cambridge University Press.
Maie, R. (2019). Interview with Nick C. Ellis. MSU Working Papers in SLS, 10, 1-6. Download
Maie, R. (2020, March). Eyeing acceptability judgment task: Automaticity moderates different L2 knowledge and processing. Paper accepted for the American Association for Applied Linguistics, Denver: CO. Download
Maie, R. (2019, September). Does automaticity moderate different types of L2 knowledge use in grammaticality judgments? An eye-tracking study. Paper presented at the Second Language Research Forum 2019, Michigan State University, East Lansing: MI. Download
Maie, R. (2019, March). Demystifying the complexity of individual differences under incidental conditions: A conceptual replication and extension. Paper presented at the American Association for Applied Linguistics 2019, Atlanta: GA. Download
Nominated as a candidate for Graduate Student Award.
Maie, R. & DeKeyser, R. M. (2018, October). Beyond boundaries: Combining methodological approaches to research on acquisition of explicit and implicit knowledge under an incidental condition. Paper presented at the Second Language Research Forum 2018, Université du Québec à Montréal, Montreal: QC, Canada. Download
Maie, R. & Salen, B. (2018, March). Task-based analysis of target discourse in media weather forecasts. Paper presented for the TESOL 2018 International Convention & English Language Expo, Chicago: IL. Download
Basic statistical inference, Generalized linear (mixed) models,Bayesian data analysis, Latent variable modeling, and Rasch models and Item Response Theory