Determinant of Optimal and Inhibited Mobile Language Learning Activity

Abstract

Learner analytic driven research concerned with mobile app learner survivability. An app was developed to indicate productiveness of quiz app usage for global mobile assisted language learning (MALL). The research focused on inhibiting and optimizing effects of level length on total questions answered. How many questions per level leads to the highest total unique questions being answered? The research focused on 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 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 up to 107% are reported for switching from suboptimal to optimal approaches.

Matching Degree Between University Students' Digital Literacy and the Current Situation of Mobile Language Learning

“…Learning mode was the weakest among the four MALL elements, and perceived satisfaction was the strongest. This finding indicates that university students recognize and are satisfied with MALL for foreign language learning, as evidenced by their satisfaction with this learning mode in terms of accessing foreign language learning resources, promoting foreign language skill development, and enhancing the diversity and interactivity of foreign language learning activities; the lowest score for learning mode indicates that university students still have deficiencies in the variety and interactivity of MALL activities [14].…”

An Adaptive M-Learning Usability Model for Facilitating M-Learning for Slow Learners

“…The study by [37] demonstrates the significant positive impact of the SMART-P training program on parenting knowledge and children's cognitive development. The quiz length strongly affects the quantity of work completed in mobile-assisted language learning (MALL), with question sets between lengths 8 and14 being the most optimal [38].…”

Estimating Learning Task Duration

“…Fortuitously, they provide the parameters of a simple model of adjacent Byrne operation duration. The multiple-choice MALL app study [9] provides a two-adjacent operation task; the 6.7 million video view study [8] provides a three-adjacent operation task; and a second video with interaction study [33] provides both three and four adjacent operation tasks. This data affords the possibility to model task duration.…”

“…Estimating Learning Task Duration: Modelling Within an Intentional Activity Framework duration for app-based mobile-assisted language learning (MALL) multiple-choice quizzes [9]. The consensus from the literature [10], is that extracting meaningful data on the interplay of study intention, human attention and overall engagement is very difficult.…”

“…However, this paper asserts that Carrol's second variable, learner engagement (perseverance), and therefore productivity of learning time, can be optimised by focusing on the relationship between complexity and duration of intentional learning tasks. Over the years, many researchers, EdTech developers, and teachers have noticed that the actual time on task should be limited for optimal results [1] [2] [5] [9]. But it is challenging to identify precisely how to do this, as the optimal duration of tasks is hidden within larger units of activity.…”