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The purpose of this study is to investigate the effects of algorithmic assistance, facilitated by AI: Literature review Dissertation, TCD, Ireland

University Trinity College Dublin (TCD)
Subject Literature review Dissertation

Introduction:

The purpose of this study is to investigate the effects of algorithmic assistance, facilitated by AI, on the academic performance of college students. The aim is to comprehensively understand how AIdriven tools impact student assignment performance in higher education settings. Integrating AI in learning environments has garnered scholarly attention, focusing on personalised student support (Luckin et al., 2016). This research contributes to understanding the effectiveness and limitations of AI in education, guiding the development of tools aligned with pedagogical goals (Van Den Beemt et al., 2019).

The study’s significance lies in informing educational institutions about the potential benefits and challenges of AIbased interventions. Exploring how AI influences academic outcomes aims to provide insights into students’ experiences and perceptions, contributing to responsible and effective technology use in learning environments. Understanding the impact of algorithmic assistance is crucial for preparing students to navigate AI in the evolving landscape of education and work (Gao et al., 2020).

Literature Review and Research Question:
The growing integration of artificial intelligence (AI) in education, particularly its influence on college students’ assignment performance, is a focal point of current scholarly investigation. Recent trends show an increased adoption of AIpowered tools like chatbots, automated grading systems, and personalised tutoring platforms, presenting diverse
approaches to enhancing the educational experience. Scholarly discourse emphasises critical issues, including the efficacy of AI in providing personalised learning experiences and debates around ethical considerations, privacy concerns, and the need for a balanced integration with traditional pedagogical methods (Luckin et al., 2016; Van Den Beemt et al.,2019).

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