Diagnostic classification modeling of EFL learners’ online learning performances during COVID-19 pandemic: individual vs. interactive learning

Abstract

ABSTRACT In the era of Covid-19 and right after the announcement of it as a pandemic and threat to humanity by the World Health Organization, most educational activities were globally forced to shut down their traditional teaching/learning activities. This is one of the biggest and most vital changes of educational settings which have led to migration to online educational platforms. This paper can be considered as one of the few first studies that aimed to investigate the Iranian EFL online learners’ learning performances (individual vs. interactive classroom tasks through quizzes, presentations, assignments, feedback and discussion) during the 2020–2021 educational year. DCM package (Diagnostic Classification Modeling) using R was used to classify the learning performances of 397 Iranian EFL BA students based on their learning behavior in online classes, and to find out to what extent their learning profiles related to their achievement. The results showed that interactive learning, performed through interaction and collaborative activities among students, is more challenging for the learners though for the majority of them mastering both individual and interactive learning is required to successfully pass the course. These findings can have important significance for all the practitioners in the field of Education.