Location-based mobile learning system facilitating English learning

ABSTRACT

The central aim of this study was to determine the potential of the GPS-based MCL system for English learning in terms of its relationship with learning achievements. For this, the research enrolled 51 students of Moscow Aviation Institute, National Research University (Moscow, Russian Federation) aged 20 to 22, 35% were males, and 65% were females. The paper defined the predictors of self-efficacy, self-regulation, and academic success. The main research tool was represented by 7-point Likert scale questionnaire surveys. The calculation of Cronbach’s alphas allowed concluding that they were sufficiently reliable insofar as the values obtained for the questionnaires on respondents’ self-regulation, self-efficacy, the use of GPS-based MCL system, and this system’s perceived usefulness and simplicity equaled 0.78, 0.89, 0.84, and 0.84, respectively. Overall, the experiment outcomes uncovered that student self-regulation and self-efficacy do influence learning outcomes and can even predict future academic performance. There was a significant difference in the results of pre- and post-testing conducted before and after the implementation of the GPS-based MCL system with the upward trend observed. Alongside this, the mean scores for the perceived usefulness and ease of use of the proposed MCL system constituted 4.96 and 5.28 (on a 7-point scale).

KEYWORDS:

• Foreign language learning
• GPS-based learning
• location-based learning apps
• mobile context-aware learning
• mobile learning

Acknowledgments

This paper was financially supported by the Ministry of Education and Science of the Russian Federation on the program to improve the competitiveness of Peoples’ Friendship University of Russia (PFUR University, RUDN University) among the world’s leading research and education centers.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be available on request.

Additional information

Funding

This work was supported by Ministry of Education and Science of the Russian Federation on the program to improve the competitiveness of Peoples’ Friendship University of Russia (PFUR University, RUDN University) among the world’s leading research and education centers.

Notes on contributors

Svetlana Zubanova

Svetlana Zubanova is a Doctor of History, Professor, Deputy Director for research issues of the Foreign Languages Department I-11 of Moscow Aviation Institute (National Research University) in Moscow, Russian Federation. Her research interests include higher education, development of linguistic education, aviation institute, aviation translation, active language learning environment etc.

Elvira Didenko

Elvira Didenko is a Master in Linguistics, Assistant Lecturer at the Department of Foreign Languages and Cross-Cultural Communication of the Financial University under the Government of the Russian Federation in Moscow, Russian Federation. She is interested in digital technologies, education and modern learning technologies.

Irina Karabulatova

Irina Karabulatova is a Doctor of Philology, Professor, Academician, Professor at the Department of Foreign Languages of Philological Faculty of the Рeoples’ Friendship University of Russia (RUDN University) in Moscow and Machine Intelligence Laboratory of Moscow Institute of Physics and Technology in Dolgoprudny, Russian Federation. She is an expert in modern technologies, advertising, learning methods etc.