Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Integrating Multiple Intelligence and Artificial Intelligence in Language Learning: Enhancing Personalization and Engagement

Version 1 : Received: 15 July 2023 / Approved: 17 July 2023 / Online: 17 July 2023 (03:44:07 CEST)

How to cite: Eslit, E. Integrating Multiple Intelligence and Artificial Intelligence in Language Learning: Enhancing Personalization and Engagement. Preprints 2023, 2023071044. https://doi.org/10.20944/preprints202307.1044.v1 Eslit, E. Integrating Multiple Intelligence and Artificial Intelligence in Language Learning: Enhancing Personalization and Engagement. Preprints 2023, 2023071044. https://doi.org/10.20944/preprints202307.1044.v1

Abstract

This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research gaps, objectives, research questions, and the theoretical framework. A literature review provides an overview of multiple intelligences theory by Howard Gardner, the role of AI in language learning, and identifies gaps in the existing literature. The methodology section outlines the research design and approach, participant selection, data collection methods, validity and reliability measures, and ethical considerations. Findings and results are presented through the analysis of qualitative data, exploring emergent themes and patterns. The discussion section critically examines the identified research gaps, discusses the validity and reliability of the study, addresses the scope and limitations, and explores the implications of the findings for theory, practice, and future research. The conclusion summarizes the key findings and contributions of the study, reflects on the achievement of research objectives, offers recommendations for further research, and provides final remarks tying together the main points of the study. This paper contributes to the existing body of knowledge by providing insights into the integration of multiple intelligences and AI in language learning and its impact on personalization, engagement, and language learning outcomes.

Keywords

Artificial Intelligence; language learning, Multiple intelligences; personalization and engagement

Subject

Social Sciences, Education

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