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AN ASSESSMENT INTO THE USE OF ARTIFICIAL INTELLIGENCE AND IT'S EFFECTS ON ACADEMIC PERFORMANCE OF UNDERGRADUATES: A STUDY OF GREGORY UNIVERSITY STUDENTS, IMO STATE

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AN ASSESSMENT INTO THE USE OF ARTIFICIAL INTELLIGENCE AND IT'S EFFECTS ON ACADEMIC PERFORMANCE OF UNDERGRADUATES: A STUDY OF GREGORY UNIVERSITY  STUDENTS, IMO STATE

CHAPTER ONE

INTRODUCTION

Background of the study

Artificial intelligence (AI) has become an essential component of many businesses, transforming conventional methods and providing advanced solutions to intricate challenges. Within the realm of education, artificial intelligence (AI) technologies are progressively being used to augment the processes of teaching and learning. The aforementioned technologies include intelligent tutoring systems, automated grading software, adaptive learning platforms, and virtual teaching assistants. These technologies are specifically developed to enhance educational results and provide individualised learning experiences (Chen et al., 2020). The use of artificial intelligence (AI) in education originated in the 1960s with first trials in computer-assisted teaching. Nevertheless, substantial progress has been made in the last twenty years as a result of the establishment of advanced algorithms and enhanced processing capabilities. Preliminary artificial intelligence (AI) applications, such as the PLATO system, established the foundation for more sophisticated technologies like as IBM's Watson Tutor and AI-powered platforms like Coursera and Khan Academy (Luckin et al., 2016). The uses of artificial intelligence in higher education are varied and constantly developing. Intelligent tutoring systems (ITS) such as Carnegie Learning's MATHia and Pearson's MyLab provide tailored feedback and adaptable learning routes according to the specific performance of each student (Pane et al., 2015). Automated grading solutions, like Gradescope, simplify the marking process and provide reliable and unbiased assessments, allowing teachers to allocate more time to other educational tasks (Jordan, 2019). Furthermore, artificial intelligence (AI)-powered technologies like chatbots and virtual teaching assistants improve student involvement and assistance. Specifically, Georgia State University used an artificial intelligence chatbot called Pounce to aid students in managing administrative duties and enquiries, leading to higher rates of student retention (Bailey et al., 2018). Empirical evidence suggests that artificial intelligence (AI) technologies have the potential to enhance academic achievement by offering customised educational experiences that accommodate the unique learning preferences and requirements of individuals. Research has shown that personalised learning platforms, which modify teaching material according on student interactions, enhance comprehension and memory of the subject (Chen et al., 2020). Moreover, sophisticated teaching systems have the capability to provide prompt feedback and assistance, therefore enabling pupils to better tackle their areas of weakness (VanLehn, 2017). However, the influence of artificial intelligence on academic achievement is not consistently beneficial. A number of research indicate that the efficacy of AI tools is contingent upon many elements, such as the calibre of the AI system, the topic matter, and the use environment (Luckin et al., 2016). Moreover, there are apprehensions about over dependence on AI, which might result in an erosion of critical thinking and problem-solving abilities among students (Holstein et al., 2019).  Notwithstanding the possible advantages, the use of artificial intelligence in education poses several obstacles and ethical deliberations. One major issue is the digital gap, which refers to the lack of access to AI technology among pupils from disadvantaged families, therefore worsening pre-existing educational disparities (Jones, 2021). Furthermore, the collection and analysis of extensive student data by AI systems to provide personalised learning experiences give rise to concerns pertaining to data privacy and security (Pardo & Siemens, 2014). Furthermore, there is the ethical quandary of substituting human instructors with artificial intelligence, which might possibly reduce the significance of educators in the process of learning. Although AI may provide useful assistance, it is unable to accurately reproduce the empathy, inventiveness, and critical thinking that human instructors contribute to the classroom (Holstein et al., 2019). The potential of AI in education is promising, but it need meticulous evaluation of its deployment and consequent effects. Continual research and development are crucial to improve the efficiency and availability of AI technologies. Effective collaboration between policymakers and educational institutions is crucial to tackle the digital gap and provide equitable access to AI progress for all students (Jones, 2021). Furthermore, it is essential to provide educators with training to proficiently incorporate artificial intelligence (AI) into their instructional methods, capitalising on the advantages of AI while preserving the fundamental human aspects of education. Collaboration among AI developers, educators, and researchers will be essential for the development of ethical, efficient, and fair AI systems. Therefore, the researcher sought to assess the use of artificial intelligence and it's effects on academic performance of undergraduates: A study of Gregory University  students, Imo State.

1.2 Statement of the problem

The exponential progress of artificial intelligence (AI) technology has had a profound impact on many industries, including education. In light of the growing integration of AI technologies into educational institutions' pedagogical practices, it becomes essential to comprehend their influence on students' academic achievement. This study aims to examine the impact of artificial intelligence (AI) on the scholastic achievement of undergraduate students. The use of AI technologies, such as intelligent tutoring systems, personalised learning platforms, and automated grading systems, has the potential to augment learning experiences via the provision of tailored feedback and assistance (Chen et al., 2020). However, empirical data is required to substantiate these assertions and to ascertain the degree to which these technologies enhance academic results (Smith & Anderson, 2019). Furthermore, it is essential to tackle concerns about the fair availability of AI technologies and their capacity to worsen current educational disparities. Research indicates that pupils from disadvantaged backgrounds may not use AI technology to the same extent because of restricted availability and differing degrees of digital literacy (Jones, 2021). Hence, the objective of this study is to investigate not only the general influence of artificial intelligence on academic achievement but also the varying consequences across various student demographics. Hence, the study assess the use of artificial intelligence and it's effects on academic performance of undergraduates: A study of Gregory University  students, Imo State.

1.3 Objective of the study

Generaly, the study assess the use of artificial intelligence and it's effects on academic performance of undergraduates: A study of Gregory University  students, Imo State. The specific objectives is as follows

Assess the impact of AI on the academic performance of undergraduate students in Gregory University.

Examine the effectiveness of AI personalized learning platforms in enhancing students' understanding and retention of course material.

Analyze the efficiency of AI in academic support of undergraduate students in Gregory University.

1.4 Research Questions

The following questions have been prepared for the study

What is the effct of AI on the academic performance of undergraduate students in Gregory University?

How effective is AI personalized learning platforms in enhancing students' understanding and retention of course material?

How efficient is AI in academic support of undergraduate students in Gregory University?

1.5 Significance of the study

Findings of the study will be significant as AI technologies have the potential to augment the capabilities of educators by automating routine tasks such as grading and providing real-time insights into student performance. This study will explore how these technologies can be leveraged to free up educators' time, allowing them to focus on more impactful teaching activities and provide targeted support to students who need it most.

Findings of the study will also be significant to academia as by identifying the key factors that influence the success of AI integration in educational settings, this research will guide future development and implementation of AI tools. Insights from this study will help developers create more effective and user-friendly AI applications that are tailored to the needs of students and educators

1.6 Scope of the study

The study focus on the use of artificial intelligence and it's effects on academic performance of undergraduates: A study of Gregory University  students, Imo State. Empirically, the study will assess the impact of AI on the academic performance of undergraduate students in Gregory University , examine the effectiveness of AI personalized learning platforms in enhancing students' understanding and retention of course material and analyze the efficiency of AI in in academic support of undergraduate students in Gregory University. 

Geographically, the study is delimited to Gregory University  students, Imo State

1.7 Limitation of the study

Like in every human endeavour, the researchers encountered slight constraints while carrying out the study. The significant constraint are: 

Time: The researcher encountered time constraint as the researcher had to carry out this research along side other academic activities such as attending lectures and other educational activities required of her.

Finance: The researcher incurred more financial expenses in carrying out this study such as typesetting, printing, sourcing for relevant materials, literature, or information and in the data collection process.

Availability of Materials: The researcher encountered challenges in sourcing for literature in this study. The scarcity of literature on the subject due to the nature of the discourse was a limitation to this study.

1.8 Definition of terms

Artificial Intelligence (AI): A branch of computer science that involves the creation of systems capable of performing tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding.

Intelligent Tutoring Systems (ITS): Computer systems designed to provide immediate and customized instruction or feedback to learners, without human intervention, using AI to adapt to the needs of individual students.

Automated Grading Systems: Software applications that use algorithms and AI techniques to evaluate and score student assessments automatically, ensuring consistency and objectivity in grading.

Personalized Learning Platforms: Educational technologies that use AI to tailor learning experiences to the individual needs, skills, and interests of each student, often by adapting the content and pace of instruction.

Virtual Teaching Assistants: AI-driven systems that assist educators and students by answering questions, providing instructional support, and managing administrative tasks, thereby enhancing the learning experience.

Digital Divide: The gap between individuals who have access to modern information and communication technology and those who do not, often influenced by socio-economic, geographical, and educational factors.

Adaptive Learning: A method of educational delivery that uses technology to dynamically adjust the learning material based on the learner's performance and engagement, thereby personalizing the learning experience.

Educational Inequality:  Disparities in educational access, resources, and outcomes among different groups of students, often influenced by socio-economic status, race, and other demographic factors.


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