A Determinant of Optimal and Inhibited Mobile Language Learning Activity Quiz Level Length

Learner analytic exploratory research, concerned with mobile app learner survivability, was conducted. An app was developed to indicate productivity of quiz app usage for global mobile assisted language learning (MALL). The research focused on inhibiting and optimising effects of level length on total questions answered. Specifically, it aimed to answer the question: how many questions per level leads to the highest total unique questions being answered? The research was conducted within nine-day cohort timeframes and included three phases: a small-scale pilot study to establish parameters, an exploratory stage undertaken within the parameters and finally the use of a quadratic regression predictive model. The data was collected using Google Analytics and Google Firebase. The null hypothesis (H0) was rejected. A one-way analysis of variance found a statistically significant difference in the mean productivity of the lengths. Results of a Tukey post hoc test (p <.05) suggests question sets with less than eight questions, or more than 15 questions, appear to inhibit MALL autonomous learning. Optimal level question sets appear to be between lengths 8-14. The results visually encapsulated by a quadratic regression model broadly support H1 and H2. Set 12 is the statistically most significant optimal load. Gains of 107% are reported for switching from suboptimal to optimal approaches. The major conclusion of the research is that quiz length strongly affects quantity of work completed. A preliminary time-based model of optimal length has been provided, to broaden measurement opportunity, as the findings could potentially cross-apply to professional environments and other activity types. © 2023,International Journal of Interactive Mobile Technologies. All Rights Reserved.