Project – Artificial Intelligence Adoption and Students’ Academic Performance in Public Secondary Schools in Lagos State

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

Education is widely recognised as a fundamental instrument for human development, social transformation and national advancement. It provides individuals with knowledge, skills, attitudes and competencies necessary for effective participation in society. At the secondary-school level, education is particularly important because it prepares students for higher education, employment, entrepreneurship and responsible citizenship. Consequently, improving the quality of teaching and learning and enhancing students’ academic performance remain major concerns for governments, educational institutions, teachers, parents and other stakeholders.

The rapid development of digital technologies has significantly transformed the educational environment. Computers, smartphones, internet technologies, digital learning platforms and educational applications have expanded students’ access to information and created new possibilities for teaching and learning. More recently, Artificial Intelligence (AI) has emerged as one of the most influential technologies capable of transforming educational processes. AI refers broadly to computational systems designed to perform tasks associated with human intelligence, including learning, reasoning, problem-solving, language processing, prediction and decision-making (Russell & Norvig, 2021).

The development of AI has progressed from relatively simple rule-based systems to sophisticated machine-learning and deep-learning technologies capable of processing large volumes of data and recognising complex patterns. Goodfellow, Bengio and Courville (2016) explain that deep learning, a branch of machine learning based on multilayered neural networks, has contributed substantially to advances in language processing, image recognition and other intelligent applications. These technological developments have created opportunities for AI to be applied beyond commercial and industrial settings, including healthcare, finance, government and education.

The educational application of Artificial Intelligence is commonly referred to as Artificial Intelligence in Education (AIED). AI can be used in education through intelligent tutoring systems, adaptive learning platforms, automated assessment, learning analytics, recommendation systems, conversational agents and generative AI applications. Holmes, Bialik and Fadel (2019) argue that AI has the potential to transform educational practices by supporting personalised learning, providing intelligent feedback and assisting teachers with instructional activities. Such applications may be particularly useful in learning environments where teachers have large numbers of students and limited time for individualised instruction.

One of the major attractions of AI in education is its potential to personalise learning. Students differ in their levels of knowledge, learning speed, interests and academic needs. In a conventional classroom, a teacher may find it difficult to provide individualised instruction to every student. AI-supported systems can potentially analyse learners’ responses and provide explanations, exercises or feedback suited to their learning needs. Zawacki-Richter et al. (2019), in their systematic review of AI applications in education, identified adaptive systems and personalisation, assessment, prediction and intelligent tutoring among important applications of AI in educational environments.

The emergence of generative Artificial Intelligence has further increased the relevance of AI to education. Generative AI refers to AI systems capable of creating new content, including text, images, audio, computer code and other forms of digital material. Large language models have become particularly important because they can interact with users through natural language and generate responses to questions or instructions. Applications such as ChatGPT and similar systems can explain concepts, generate examples, summarise information, formulate questions, assist with writing and provide conversational learning support.

The educational possibilities of large language models have attracted considerable scholarly attention. Kasneci et al. (2023) note that large language models can support personalised learning, tutoring, feedback and idea generation. Students may use these systems to obtain additional explanations when they do not understand a lesson, generate practice questions for revision, receive assistance with writing or explore academic topics beyond classroom instruction. Such uses can potentially extend learning opportunities beyond the traditional teacher-centred classroom.

However, the educational adoption of AI is accompanied by important concerns. AI-generated information may be inaccurate, biased or misleading, while students may become excessively dependent on AI-generated responses. Kasneci et al. (2023) identify misinformation, overreliance, bias and academic integrity among the major challenges associated with large language models in education. Therefore, the mere availability of AI technologies does not guarantee improved learning. The way students use AI, the guidance provided by teachers and the educational environment in which AI is introduced are important factors that can determine its effectiveness.

UNESCO (2023) similarly argues that generative AI has considerable potential to support education but requires a human-centred and ethically responsible approach. Issues such as data privacy, inequality, academic integrity, age appropriateness, human agency and the reliability of AI-generated information require careful consideration. According to UNESCO (2023), educational institutions should establish appropriate safeguards and ensure that AI supports rather than undermines meaningful human learning.

The importance of responsible AI use is further reflected in UNESCO’s AI Competency Framework for Students. UNESCO (2024) identifies competencies that students need in order to use AI effectively and responsibly. These include understanding AI, applying AI technologies and developing the ability to evaluate and use AI critically. The framework emphasises that students should not merely become consumers of AI-generated content but should develop the ability to understand AI systems, recognise their limitations and use them ethically.

The issue of AI adoption is particularly relevant to students at the secondary-school level. Secondary-school students are at a critical stage of intellectual development. They are expected to develop independent learning abilities, critical thinking, problem-solving skills and academic competencies that will prepare them for higher education and employment. AI may provide valuable support during this process, but inappropriate use may also affect the development of these competencies. If students rely excessively on AI to complete assignments, answer examination questions or generate written work, they may have fewer opportunities to practise independent reasoning and problem-solving.

The concept of AI adoption therefore extends beyond simple awareness of AI. Adoption involves the extent to which students accept, access and use AI technologies for specific purposes. The Technology Acceptance Model developed by Davis (1989) proposes that perceived usefulness and perceived ease of use are important factors influencing technology acceptance. In the educational context, students are more likely to adopt AI when they believe that it is useful for understanding lessons, completing academic tasks or improving their academic performance.

Venkatesh et al. (2003) further explain technology acceptance through the Unified Theory of Acceptance and Use of Technology, which identifies performance expectancy, effort expectancy, social influence and facilitating conditions as important factors affecting technology use. These factors are relevant to AI adoption in public secondary schools because students’ use of AI may depend not only on their perceptions of its usefulness but also on access to devices, internet connectivity, electricity, school policies and teacher support.

The Nigerian educational environment presents a particularly important context for examining AI adoption. Nigeria has a large and youthful population and an expanding digital economy. The country’s National Artificial Intelligence Strategy recognises AI as an important technology for national development and identifies education as an important area for AI application and capacity development (National Information Technology Development Agency [NITDA], 2024). The strategy also recognises challenges relating to infrastructure, digital skills and access that may influence the effective deployment of AI technologies.

Nigeria’s educational system has long faced challenges involving inadequate educational resources, teacher workload, unequal access to technology and differences in learning opportunities. AI may potentially provide additional educational support by giving students access to explanations, learning resources and practice activities. However, unequal access to smartphones, computers, reliable electricity and internet services may prevent some students from benefiting from AI technologies.

This issue of digital inequality is important because technology can produce unequal outcomes when access and skills are unevenly distributed. Students from relatively advantaged households may have personal smartphones, computers, reliable internet connectivity and greater exposure to digital technologies, whereas students from disadvantaged backgrounds may have limited access. Consequently, AI adoption may potentially widen existing educational inequalities if technological resources are not equitably distributed.

Recent Nigerian evidence provides support for the potential educational benefits of AI. De Simone et al. (2025) conducted a randomised controlled study involving secondary-school students in Nigeria and evaluated a structured generative-AI intervention using Microsoft Copilot. The intervention was designed to support English-language learning and was implemented with teacher involvement. The researchers reported a statistically significant improvement of 0.31 standard deviations in an assessment covering English, AI knowledge and digital skills, while the effect on English performance alone was approximately 0.23 standard deviations (De Simone et al., 2025). This finding provides important evidence that appropriately structured AI-supported learning can improve educational outcomes among Nigerian secondary-school students.

The importance of this study lies in the fact that it demonstrates that AI can contribute to measurable learning outcomes when incorporated into a structured educational programme. The World Bank study did not simply provide students with unrestricted access to AI. Rather, AI was integrated into an organised intervention with educational objectives and teacher support (De Simone et al., 2025). This suggests that the educational effectiveness of AI may depend substantially on the manner in which it is adopted and integrated into learning.

Other recent Nigerian studies have also investigated AI and academic achievement. Oduma et al. (2025) examined the effect of Artificial Intelligence on secondary-school students’ academic performance in Ika South Local Government Area of Delta State. Similarly, Aghogho Perculiar, Oduselu-Hassan and Tsetimi (2025) examined the influence of AI on secondary-school students’ cognitive development and academic achievement in Delta State. These studies indicate growing academic interest in the relationship between AI and secondary-school learning in Nigeria.

Aliyu, Garba and Dape (2026) also investigated AI-assisted learning tools, academic performance and study habits among secondary-school students in Nigeria. Their work reflects the increasing need to understand not only whether students use AI but also how AI-assisted learning may affect academic achievement and students’ approaches to studying.

Despite these emerging studies, there remains a need for additional research focusing specifically on public secondary schools in Lagos State. Lagos is one of Nigeria’s major economic, commercial and technological centres and has a large population of secondary-school students. The state’s relatively developed digital environment creates opportunities for students to access AI tools. Nevertheless, the availability and use of technology may vary considerably between schools and students.

Recent evidence from Lagos State provides an indication of this problem. Adetuyi-Olu-Francis (2026) examined secondary-school teachers’ use and perception of AI tools for improving students’ performance in French in Lagos State. The study reported limited use of AI chatbots and identified inadequate access to computers and internet facilities as significant barriers to AI adoption. This finding suggests that although AI technologies may be increasingly available, their actual integration into teaching and learning within Lagos State public secondary schools may still face infrastructural and pedagogical challenges.

The issue of teacher preparedness is equally important. Teachers play a critical role in determining whether AI is used as an educational support tool or simply as a mechanism for obtaining answers. Teachers need to understand the capabilities and limitations of AI and guide students on how to formulate appropriate questions, evaluate AI-generated responses, verify information and maintain academic integrity. UNESCO (2024) emphasises the need for AI-related competencies among educators and learners to ensure that AI is used responsibly and effectively.

Students’ academic performance is another important consideration. Academic performance generally refers to measurable achievement in academic activities and may be reflected in test scores, continuous assessment, assignments, examinations and other educational assessments. It is influenced by several factors, including students’ motivation, intelligence, teaching quality, learning environment, parental support, availability of educational resources and socioeconomic conditions.

The adoption of AI may influence academic performance through several mechanisms. First, AI can provide students with immediate explanations and feedback. Second, it can provide opportunities for repeated practice. Third, AI may assist students in finding and organising learning information. Fourth, AI can potentially personalise learning according to students’ individual needs. These functions may improve learning when students use AI actively and critically.

However, AI adoption may also have negative implications for academic performance when used inappropriately. Students may copy AI-generated answers without understanding the subject matter, submit AI-generated assignments as their own work, accept inaccurate information or become dependent on technology. Such practices may create the appearance of academic achievement without corresponding improvements in actual knowledge.

Consequently, it is necessary to distinguish between AI access, AI adoption and effective AI-supported learning. A student may have access to an AI tool but use it primarily for entertainment or non-academic activities. Another student may use AI regularly but mainly to complete assignments without learning. A third student may use AI to obtain explanations, practise questions and test personal understanding. These different patterns of use may produce different academic outcomes.

This makes the relationship between AI adoption and students’ academic performance an empirical question rather than an assumption. While AI has significant educational potential, its actual contribution to student achievement depends on the manner, purpose and context of use.

The issue is particularly important in public secondary schools because these schools serve students from diverse socioeconomic and educational backgrounds. Public schools may also experience challenges involving large class sizes, teacher workload, access to digital infrastructure and availability of instructional materials. AI could potentially supplement existing educational resources, but its effectiveness will depend on whether students and teachers have adequate access and competence.

The rapid development of AI also means that educational institutions need empirical evidence to guide policy decisions. Schools cannot simply ignore AI because students are increasingly exposed to it through smartphones and internet services. At the same time, unrestricted adoption without appropriate guidance may create risks for academic integrity and independent learning. Evidence is therefore required to determine whether AI adoption is associated with measurable improvements in students’ academic performance.

The present study is therefore designed to examine Artificial Intelligence Adoption and Students’ Academic Performance in Public Secondary Schools in Lagos State. By investigating the extent and nature of AI adoption and its relationship with academic performance, the study seeks to provide evidence that can support responsible and effective integration of AI into secondary education in Lagos State.

1.2 Statement of the Problem

Students’ academic performance remains a major concern within the Nigerian educational system. Secondary education is expected to equip students with knowledge, critical thinking, problem-solving abilities and other competencies necessary for higher education and future employment. However, achieving satisfactory academic outcomes can be difficult where students have limited access to learning resources, teachers have large workloads and individual students receive insufficient academic support.

The emergence of Artificial Intelligence presents both an opportunity and a challenge in addressing this problem. AI applications can provide students with explanations, examples, practice questions, feedback and access to additional learning resources. Generative AI systems can also respond to students’ questions in real time and potentially provide personalised academic assistance (Kasneci et al., 2023). Evidence from Nigeria indicates that a structured generative-AI intervention can produce significant improvements in students’ learning outcomes (De Simone et al., 2025).

Despite these potential benefits, there is growing concern that students may adopt AI without adequate guidance. Rather than using AI to deepen understanding, some students may use it to generate complete answers to homework, essays and other academic tasks. Such practices may reduce students’ engagement with learning and weaken the development of independent thinking. Kasneci et al. (2023) identify overreliance and academic integrity as significant challenges associated with generative AI in education.

Another problem is the reliability of AI-generated information. Generative AI systems can produce responses that appear accurate and authoritative while containing factual errors or misleading information. Students with limited subject knowledge may be unable to identify such inaccuracies. UNESCO (2023) therefore emphasises the importance of critical evaluation, human oversight and responsible use of generative AI in educational settings.

A further problem concerns unequal access to AI technologies. Effective AI adoption often requires access to smartphones, computers, internet connectivity, electricity and digital skills. Not all students in public secondary schools possess these resources equally. Students from households with greater technological resources may be able to use AI more frequently and effectively than students with limited access. This creates the possibility that AI could contribute to existing digital and educational inequalities rather than reducing them.

The problem is also related to teacher preparedness. The educational value of AI depends partly on the ability of teachers to guide students in its appropriate use. Teachers need to understand how AI works, its limitations and its potential educational applications. They must also be able to teach students how to verify information, protect personal data and maintain academic integrity. Evidence from Lagos State suggests that limited access to computers and internet facilities can constrain teachers’ adoption of AI (Adetuyi-Olu-Francis, 2026).

Another important problem is the limited availability of empirical evidence specifically concerning public secondary schools in Lagos State. Although recent studies have examined AI and students’ academic performance in Nigeria, several have been conducted outside Lagos State, including studies in Delta State (Aghogho Perculiar et al., 2025; Oduma et al., 2025). Educational conditions differ across states, and findings obtained in one location cannot automatically be generalised to another.

The World Bank study by De Simone et al. (2025) provides valuable experimental evidence from Nigerian secondary schools, but its intervention was conducted in Edo State and focused specifically on English-language learning. While the findings demonstrate the potential of structured AI-supported learning, they do not establish whether general AI adoption among students in Lagos State public secondary schools is significantly associated with academic performance.

There is therefore a contextual gap concerning how students in Lagos State public secondary schools are actually adopting AI and whether such adoption is reflected in their academic achievement. It is important to determine whether students are using AI mainly for meaningful learning activities such as concept clarification, research, revision and practice, or whether they are primarily using it to complete academic tasks without adequate understanding.

There is also an outcome gap. Much of the discussion surrounding AI in education focuses on its potential benefits, challenges or users’ perceptions. However, positive perceptions of AI do not necessarily mean that AI improves actual academic achievement. Students may report that AI is useful while their academic performance remains unchanged or even declines because of inappropriate dependence on the technology.

The central problem, therefore, is the uncertainty concerning the relationship between Artificial Intelligence adoption and students’ actual academic performance in public secondary schools in Lagos State. On one hand, effective AI adoption could provide students with additional learning resources, personalised assistance, immediate feedback and opportunities for independent learning. On the other hand, inappropriate adoption could encourage dependency, misinformation, academic dishonesty and reduced cognitive engagement (UNESCO, 2023; Kasneci et al., 2023).

The absence of sufficient empirical evidence from Lagos State makes it difficult for educational administrators and policymakers to determine the extent to which AI should be incorporated into public secondary education. Without such evidence, decisions concerning AI-related infrastructure, teacher training, student AI literacy and school-level guidelines may be based primarily on assumptions rather than demonstrated educational outcomes.

It is against this background that the present study investigates Artificial Intelligence Adoption and Students’ Academic Performance in Public Secondary Schools in Lagos State. The study seeks to establish whether a significant relationship exists between students’ adoption of AI and their academic performance and, consequently, provide evidence that can inform responsible AI integration in Lagos State’s public secondary-school system.

1.3 Aim of the Study

The main aim of this study is to examine the relationship between Artificial Intelligence adoption and students’ academic performance in public secondary schools in Lagos State.

Specifically, the study seeks to:

1. examine the extent to which students adopt Artificial Intelligence tools for academic purposes in public secondary schools in Lagos State;
2. identify the major Artificial Intelligence tools used by students for academic activities;
3. examine the purposes for which students use Artificial Intelligence in their learning activities;
4. assess the level of students’ academic performance in public secondary schools in Lagos State; and

1.4 Research Questions

The following research questions will guide the study:

1. To what extent do students adopt Artificial Intelligence tools for academic purposes in public secondary schools in Lagos State?
2. What Artificial Intelligence tools are commonly used by students for academic activities?
3. For what purposes do students use Artificial Intelligence in their learning activities?
4. What is the level of students’ academic performance in public secondary schools in Lagos State?

1.5 Research Hypothesis

The following null hypothesis will be tested at 0.05 level of significance:

H₀: There is no significant relationship between Artificial Intelligence adoption and students’ academic performance in public secondary schools in Lagos State.

1.6 Significance of the Study

The study will be beneficial to students, teachers, school administrators, parents, educational policymakers, curriculum planners and researchers.

Students

The findings will help students understand the potential educational benefits and limitations of Artificial Intelligence. The study may encourage students to use AI as a learning-support tool rather than as a replacement for independent academic effort. It may also promote responsible practices such as verifying AI-generated information and avoiding academic dishonesty.

Teachers

The findings will provide teachers with information concerning the extent to which students use AI and its relationship with academic performance. This may assist teachers in developing appropriate strategies for incorporating AI into teaching, revision, research and other academic activities.

School Administrators

School administrators may use the findings to make informed decisions concerning digital infrastructure, internet facilities, teacher training and institutional guidelines for AI use. The study may help administrators determine whether greater investment in AI-related educational resources is justified.

Parents

The findings may help parents understand the ways in which students use AI for academic purposes. This may enable parents to provide more effective supervision and encourage responsible use of AI at home.

Educational Policymakers

The study may provide empirical evidence useful to the Lagos State Ministry of Education and other educational authorities when developing policies concerning AI literacy, digital education, teacher professional development and responsible use of emerging technologies. This is particularly relevant given Nigeria’s National Artificial Intelligence Strategy, which identifies education as an important area for AI development and application (NITDA, 2024).

Curriculum Planners

Curriculum planners may use the findings to consider whether AI literacy, digital literacy, information evaluation and responsible AI use should receive greater attention in secondary-school education.

Researchers

The study will contribute to the growing body of literature on Artificial Intelligence and education in Nigeria. It may also provide a basis for further studies examining specific AI applications, subjects, student characteristics, teacher preparedness and learning outcomes.

1.7 Scope of the Study

The study focuses on Artificial Intelligence adoption and students’ academic performance in public secondary schools in Lagos State, Nigeria.

The conceptual scope covers students’ access to AI, frequency of AI use, purposes of AI use, commonly used AI tools and the educational use of AI for activities such as research, homework, revision, writing assistance, problem-solving and clarification of difficult concepts.

The dependent variable is students’ academic performance, while the independent variable is Artificial Intelligence adoption.

The geographical scope is limited to selected public secondary schools in Lagos State. Private secondary schools and tertiary institutions are excluded from the study.

The study focuses on AI as an educational technology and does not examine the technical development, programming or engineering of AI systems.

1.8 Operational Definition of Terms

Artificial Intelligence (AI): Computer-based systems designed to perform tasks that ordinarily require aspects of human intelligence, such as learning, reasoning, language processing, prediction and problem-solving.

Artificial Intelligence Adoption: The extent to which students accept, access and use Artificial Intelligence technologies for academic and learning-related activities.

AI-Assisted Learning: A learning process in which AI technologies provide students with support such as explanations, feedback, examples, practice questions or learning recommendations.

Generative Artificial Intelligence: AI technology capable of generating new content such as text, images, audio or computer code in response to user instructions.

AI Tools: Digital applications or platforms that use Artificial Intelligence to perform functions such as natural-language interaction, information generation, tutoring, feedback or automated learning support.

AI Literacy: The knowledge and skills required to understand, evaluate and use Artificial Intelligence effectively, critically, ethically and responsibly.

Students’ Academic Performance: The measurable level of students’ academic achievement as demonstrated through tests, continuous assessment, assignments, examinations or other approved academic measures.

Public Secondary Schools: Secondary schools established, funded and administered by government authorities for the education of students at the secondary-school level.

Responsible AI Use: The use of Artificial Intelligence in a manner that promotes academic integrity, critical thinking, information verification, privacy protection and responsible decision-making.

1.9 Organisation of the Study

The study will be organised into five chapters. Chapter One presents the introduction, including the background to the study, statement of the problem, aim and objectives, research questions, research hypothesis, significance, scope and operational definition of terms.

Chapter Two reviews related literature under conceptual review, theoretical review, empirical review and summary of the reviewed literature.

Chapter Three presents the research methodology, including research design, population of the study, sample size, sampling technique, research instrument, validity and reliability of the instrument, method of data collection and techniques for data analysis.

Chapter Four presents the results, analysis and interpretation of data collected from respondents.

Chapter Five presents the summary of findings, conclusion and recommendations, as well as suggestions for further studies.

Project – Artificial Intelligence Adoption and Students’ Academic Performance in Public Secondary Schools in Lagos State