Lindsay Mack

Ritsumeikan Asia Pacific University

Associate Professor, interested in academic writing, self access learning and vocabulary


Evaluating online vocabulary systems for assurance of L2 learning

Zoom E

This paper reports the results of a program-level, evaluation of online applications for vocabulary learning and their likelihood of best contributing to our system of Assurance of Learning (AOL) (MEXT, 2014). The investigation followed an argument-based approach (Gruba, Cardenas-Claros, Suvarov, and Rick, 2016). A team of tenured faculty were appointed as the Assurance of Vocabulary Learning team. The team investigated various online flashcard systems such as Quizlet, Memrise, Word Learner, English Central, and Word Engine. Following a system of evidence gathering and member checks, themes emerged with arguments for how each system best supports the vocabulary learning of Japanese university EFL learners. Methods included interviews with CALL experts, reading extant research, and a micro-level quasi-experimental comparison between two Pre-Intermediate English classes. One group used English Central and the other used Word Engine for the semester. Additionally, individual students were videotaped and interviewed while using both systems. The two groups were tested using the Pearson Progress test at the beginning and end of the semester and matched t-tests were performed to determine whether either system had an effect on Progress test vocabulary sub-scores. The results we report will include the categories for comparing systems that emerged in the data collection and analyses along with how some of the alternative systems compare side-by-side as well as our reflections on the argument-based evaluation system.