Data and codebook for SSLA article: "A closer look at a marginalized test method: Self-assessment as a measure of speaking proficiency"

Second language (L2) teachers may shy away from self-assessments because of warnings that students are not accurate self-assessors. This information stems from meta-analyses (Ross, 1998, Li & Zhang, 2021) in which self-assessment scores on average did not correlate highly with proficiency test results. However, researchers mostly used Pearson correlations, when polyserial could be used. Furthermore, self-assessments today can be computer-adaptive. With them, nonlinear statistics are needed to investigate their relationship with other measurements. We wondered, if we explored the relationship between self-assessment and proficiency test scores using more robust measurements (polyserial correlation, continuation ration modeling), would we find different results? We had 807 L2-Spanish learners take a computer-adaptive, L2-speaking self-assessment and the ACTFL Oral Proficiency Interview – computer (OPIc). The scores correlated at .61 (polyserial). Using continuation ratio modeling, we found each unit of increase on the OPIc scale was associated with a 130% increase in the odds of passing the self-assessment thresholds. In other words, a student was more likely to move on to higher self-assessment subsections if they had a higher OPIc rating. We found computer-adaptive self-assessments appropriate for low-stakes L2-proficiency measurements, especially because they are cost effective, make intuitive sense to learners, and promote learner agency.