Online Japanese Language Resit Assessment: Academic Misconduct and Technology

Abstract

The relevance of this study lies in the growing scale of academic dishonesty in online assessment, which undermines the reliability of language test results and the overall quality of e-learning. This research aims to determine whether online Japanese language resit assessment is easier than primary (sit) assessment and whether its results can be considered reliable. The significance of the study lies in its focus on academic misconduct in online resits, particularly the use of Online Translators (OT) and Input Method Editors (IME), which remain underexplored in the existing literature. The methodology combined quantitative and qualitative approaches, primarily analysing students’ written submissions and oral recordings from resit exams. The study was conducted in August 2023 with 32 undergraduate participants enrolled in Ab Initio and Intermediate Japanese modules as elective subjects at a British university. The data included students’ resit submissions, 18 task briefs for both sit and resit assessments, and corresponding marking schemes, which served as the analytical framework for evaluating authenticity and academic integrity. The results revealed that most submissions were not students’ own work, with widespread reliance on OT and IME. While the online written resit was not easier than the sit exam, the online oral resit proved significantly easier than the in-class oral assessment. Consequently, the findings indicate that the results of online Japanese resit assessments cannot be considered reliable due to the prevalence of academic misconduct. This study makes a novel contribution by being among the first to empirically document the impact of OT and IME on the validity of online language resits. Beyond Japanese, the findings highlight broader challenges for online language education, stressing the need for robust safeguards to ensure academic integrity. Practical recommendations include streamlining the online resit process and adopting measures such as online proctoring, AI-based detection tools, and pedagogical interventions. These results provide language teaching professionals with indicators for detecting OT and IME usage, while also informing global debates on academic integrity in e-learning.