AI-powered virtual assistant solution for supporting international students
David, Nadine (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024120934005
https://urn.fi/URN:NBN:fi:amk-2024120934005
Tiivistelmä
The purpose of this thesis was to propose an AI-powered virtual assistant solution to address the support needs of international students at Haaga-Helia University of Applied Sciences. International students face numerous challenges, including academic difficulties, linguistic barriers, and cultural and social adjustments, which existing support systems do not adequately address. This study aimed to identify these unmet needs and explore how an AI-powered virtual assistant could provide personalized, real-time, and culturally adaptive support. The scope of the study was limited to conceptualizing the virtual assistant without delving into its technical design or implementation.
The theoretical framework incorporated Tinto’s Model of Student Retention, Maslow’s Hierarchy of Needs, Berry’s Acculturation Model, and Vygotsky’s Zone of Proximal Development (ZPD). These frameworks provided insights into academic and social integration, the fulfilment of psychological needs, cultural adaptation strategies, and scaffolding support systems. A mixed-method approach was adopted, utilizing quantitative surveys and qualitative semi-structured and structured interviews with international students at Haaga-Helia. Data were analysed using descriptive statistics for quantitative findings and thematic analysis for qualitative insights.
The results revealed significant gaps in academic advising, language support, and social integration services. Students expressed a strong need for immediate, flexible, and culturally sensitive assistance. The conceptualized virtual assistant was designed to address these needs through features such as academic guidance, linguistic support, administrative task automation, and resources fostering social integration. The proof of conceptualization demonstrated how AI technologies, including natural language processing and machine learning, could function as a scalable and accessible solution to enhance student well-being and academic success. The findings suggest that implementing such a system could improve international students' experiences, ease their transition into the host institution, and contribute to better academic outcomes. Future research could focus on the practical development and testing of the proposed solution to assess its effectiveness in real-world contexts.
The theoretical framework incorporated Tinto’s Model of Student Retention, Maslow’s Hierarchy of Needs, Berry’s Acculturation Model, and Vygotsky’s Zone of Proximal Development (ZPD). These frameworks provided insights into academic and social integration, the fulfilment of psychological needs, cultural adaptation strategies, and scaffolding support systems. A mixed-method approach was adopted, utilizing quantitative surveys and qualitative semi-structured and structured interviews with international students at Haaga-Helia. Data were analysed using descriptive statistics for quantitative findings and thematic analysis for qualitative insights.
The results revealed significant gaps in academic advising, language support, and social integration services. Students expressed a strong need for immediate, flexible, and culturally sensitive assistance. The conceptualized virtual assistant was designed to address these needs through features such as academic guidance, linguistic support, administrative task automation, and resources fostering social integration. The proof of conceptualization demonstrated how AI technologies, including natural language processing and machine learning, could function as a scalable and accessible solution to enhance student well-being and academic success. The findings suggest that implementing such a system could improve international students' experiences, ease their transition into the host institution, and contribute to better academic outcomes. Future research could focus on the practical development and testing of the proposed solution to assess its effectiveness in real-world contexts.