Flipped Classroom: Promoting Active LSP Teaching and Learning

Keywords:
Flipped classroom, Active teaching, Active learning, LSP, Digital Tools

Abstract:
This study aims to draw attention to the flipped learning model, which can be beneficial for various teaching subjects, including the language for specific purposes (LSP). This paper, following the results of existing teaching practices, recent studies, and qualitative research conducted, aims to examine the advantages, limitations, and solutions for the effective implementation of flipped LSP learning in higher educational contexts. The main purpose is to determine the potential benefits of the flipped classroom in promoting more active language teaching and learning and to facilitate solutions for its effective implementation. Additionally, it presents digital tools for both, synchronous and asynchronous learning, that can be utilized with the institutional LMS platforms. The students' perception of the flipped model and LSP provides valuable data for this research. The findings reveal the positive impact on the learning experience and satisfaction at a higher education level, which can reflect on learning outcomes. However, challenges are observed in regard to asynchronous interaction, such as digital distraction, technological issues y non-relevant learning material. The study facilitates ideas on how to perform instructional stages: presentation, practice, assessment, and feedback using determined digital tools.

CITATION:

IEEE format

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M. Veljković Michos, M. Robles Gómez, “Flipped Classroom: Promoting Active LSP Teaching and Learning,” in Sinteza 2023 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2023, pp. 299-305. doi:10.15308/Sinteza-2023-299-305

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Veljković Michos, M., Robles Gómez, M. (2023). Flipped Classroom: Promoting Active LSP Teaching and Learning. Paper presented at Sinteza 2023 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2023-299-305

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