Project – Impact of Artificial Intelligence-Based Learning Tools on Students’ Critical Thinking Skills in Selected Secondary Schools in Lagos State

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

Education has traditionally been regarded as a major instrument for intellectual development, social transformation and national development. However, the changing nature of contemporary society has expanded the expectations placed on educational institutions. Schools are no longer expected merely to provide learners with factual knowledge; they are increasingly expected to develop learners who can analyse information, evaluate evidence, solve problems, make informed decisions, communicate ideas effectively and adapt to rapidly changing technological environments. These competencies are particularly important in the twenty-first century because students are confronted with large quantities of information from conventional and digital sources. Consequently, the ability to think critically has become an essential component of effective learning.

Critical thinking involves the purposeful and reflective use of reasoning to understand, analyse and evaluate information before arriving at a conclusion. Facione (1990), based on the Delphi consensus of experts, identifies interpretation, analysis, evaluation, inference, explanation and self-regulation as major cognitive skills associated with critical thinking. Critical thinking therefore goes beyond remembering facts. It requires learners to question information, examine assumptions, identify relationships, assess the credibility of evidence and reach conclusions that can be logically defended. For secondary school students, these abilities are particularly important because the secondary-school period represents a stage at which learners increasingly encounter complex academic concepts and are expected to demonstrate greater intellectual independence.

The importance of critical thinking has become even more pronounced in the digital age. The internet and digital technologies have transformed the quantity, speed and accessibility of information available to students. Students can obtain information on virtually any academic topic within seconds through search engines, digital libraries, social media platforms, educational websites and mobile applications. However, the availability of information does not necessarily mean that students possess the ability to determine whether the information is accurate, relevant or credible. Students therefore require critical-thinking skills to distinguish evidence-based information from inaccurate, biased or misleading information. This challenge is particularly important in an environment where technological systems increasingly generate and recommend information to learners.

One of the most significant technological developments currently influencing education is Artificial Intelligence (AI). Artificial Intelligence broadly refers to computational systems designed to perform functions associated with aspects of human intelligence, including learning, prediction, reasoning, language processing, pattern recognition and decision-making. According to Miao et al. (2021), AI has the potential to transform education by supporting personalised learning, improving educational processes and expanding access to learning opportunities. At the same time, the authors emphasise that AI presents risks and challenges that education systems must carefully address.

The application of Artificial Intelligence to education is not entirely new. For several decades, educational researchers have explored intelligent tutoring systems, adaptive learning environments and automated assessment systems. Zawacki-Richter et al. (2019), in a systematic review of 146 studies, identified four major areas of AI application in education: profiling and prediction, assessment and evaluation, adaptive systems and personalisation, and intelligent tutoring systems. Their findings demonstrated that AI has gradually developed from a specialised technological innovation into a significant area of educational research. However, they also noted the relatively limited involvement of educators in AI research and the need for greater attention to pedagogical considerations.

AI-based learning tools can therefore be understood as digital technologies that employ AI techniques to support students’ learning processes. These tools include intelligent tutoring systems, adaptive learning platforms, automated feedback applications, AI-powered educational software, personalised learning systems, automated assessment technologies and generative AI applications. Such technologies can provide students with explanations, feedback, examples, questions, summaries and alternative approaches to learning tasks. The potential educational value of these tools lies partly in their ability to provide immediate and personalised responses that may be difficult for a teacher to provide individually to every student in a large classroom.

The development of generative Artificial Intelligence has substantially expanded the possibilities associated with AI-based learning. Generative AI systems can produce text, explanations, questions, examples, summaries and solutions in response to natural-language prompts. Students can interact with such systems conversationally, asking follow-up questions and requesting alternative explanations. This represents a major change from conventional digital learning resources because the learner is no longer simply retrieving information from a fixed database but interacting with a system that dynamically generates responses.

The educational implications of this development are considerable. When appropriately used, AI may support students in exploring concepts from different perspectives, identifying relationships among ideas, receiving immediate feedback and engaging in self-directed learning. Liu, Sihes and Lu (2025), in a systematic review of 15 studies, found that generative AI tools and large language models demonstrated potential to support critical thinking through analytical thinking, reasoning, evaluation, decision-making and problem-solving. They also found that generative AI could improve engagement, confidence and self-directed learning.

The potential of AI to support higher-order thinking is further demonstrated by Tian and Zheng (2025). Their meta-analysis examined 39 experimental and quasi-experimental studies involving 2,975 participants and found a moderate positive overall effect of AI on students’ four major competencies commonly referred to as the 4Cs: critical thinking, communication, collaboration and creativity. The study reported an overall Hedges’ g of 0.624 and found that AI-based learning was particularly effective when applied through adaptive and personalised learning systems.

However, the relationship between AI-based learning tools and critical thinking is not necessarily positive in all circumstances. AI can potentially become a substitute for students’ own intellectual effort. Instead of using AI to understand a difficult concept or examine different perspectives, students may use it simply to obtain answers to assignments. Such behaviour may reduce the cognitive effort involved in analysing information, developing arguments and solving problems independently. Liu et al. (2025) found that approximately one-third of the studies included in their systematic review reported negative effects associated with generative AI. The identified concerns included over-reliance on AI, passive thinking, declining analytical depth and impediments to autonomous skill development.

This dual nature of AI is central to the debate about its educational value. AI may act as a cognitive support when it encourages students to ask questions, compare perspectives, test assumptions and evaluate evidence. Conversely, it may act as a cognitive substitute when students simply accept AI-generated responses without independent examination. Therefore, the educational impact of AI depends substantially on how students interact with the technology and how teachers structure learning activities around it.

The reliability of AI-generated information is another important consideration. AI systems can generate responses that appear authoritative but contain factual inaccuracies, incomplete explanations, inappropriate generalisations or biased information. Students with strong critical-thinking abilities may be better positioned to identify such weaknesses, whereas students who automatically trust AI outputs may reproduce inaccurate information in their academic work. Liu et al. (2025) identified the reliability of generative AI as one of the important challenges requiring attention and emphasised that learners must critically evaluate AI-generated content rather than accept it without verification.

This issue has significant implications for secondary education. Secondary school students are still developing the intellectual habits that influence how they acquire, interpret and apply knowledge. If students repeatedly use AI to generate answers without engaging in independent reasoning, they may develop habits of intellectual dependence. Conversely, if AI is deliberately incorporated into learning tasks that require students to verify information, identify errors, compare arguments and defend conclusions, it may provide valuable opportunities for developing higher-order cognitive skills.

The role of the teacher is therefore crucial in determining how AI-based learning tools affect critical thinking. AI cannot independently determine whether a learning activity develops higher-order thinking. Teachers design the questions, tasks, assessments and discussions through which students interact with educational technologies. Zawacki-Richter et al. (2019) highlighted the need for greater attention to educators and pedagogical considerations in AI research and implementation. Similarly, Miao et al. (2021) emphasise that AI in education should be implemented in ways that maximise educational benefits while addressing risks, equity and human-centred concerns.

For example, a teacher can ask students to generate an answer to a problem using an AI tool and then independently determine whether the answer is correct. Students can be required to compare AI-generated information with their textbooks, identify unsupported claims, locate factual errors and explain why a particular conclusion is stronger than another. Such activities can turn AI from a simple answer-generating mechanism into a stimulus for critical inquiry.

The nature of assessment is also relevant. Traditional assessment practices that primarily reward the reproduction of information may encourage students to use AI for obtaining ready-made answers. In contrast, assessment tasks that require explanation, justification, comparison, reflection and application may encourage more meaningful engagement with AI. Therefore, the introduction of AI into schools may require educators to reconsider not only instructional methods but also the ways in which students’ learning is assessed.

Another concern is the possibility of unequal access to AI-based learning tools. Although smartphones and internet-enabled devices have become increasingly common, students do not necessarily have equal access to reliable internet connections, computers, smartphones, paid AI services and digital learning resources. Differences in access can influence how frequently students interact with AI-based educational technologies. Moreover, access to technology does not automatically translate into effective use. Students require digital literacy and AI literacy to understand how AI systems work, recognise their limitations and use them responsibly.

The Nigerian educational environment provides an important context for examining these issues. Nigeria has experienced significant growth in digital learning and technology-supported education. The increasing use of smartphones, internet services, online educational resources and digital platforms has created new opportunities for students to access learning materials beyond the physical classroom. AI is consequently becoming part of the broader technological environment within which Nigerian students learn.

Lagos State provides a particularly relevant context for investigating the relationship between AI-based learning tools and critical thinking. As one of Nigeria’s most populous and economically active states, Lagos has a large number of secondary schools and a substantial concentration of technological and educational activities. Students in Lagos are increasingly exposed to digital technologies both inside and outside the classroom. This makes Lagos an important setting for examining how emerging AI technologies are influencing students’ learning experiences.

The increasing exposure of students to AI also raises questions concerning the difference between technology use and meaningful learning. A student who uses an AI system to produce an answer may complete a task quickly, but task completion does not necessarily demonstrate learning. Genuine learning requires students to understand concepts, apply knowledge, evaluate evidence and develop independent reasoning. Thus, the central issue is not simply whether students use AI but whether their use of AI promotes deeper cognitive engagement.

Recent empirical literature provides evidence for both possibilities. Tian and Zheng (2025) found an overall positive effect of AI on students’ 4C skills, while Liu et al. (2025) demonstrated that generative AI can both nurture and hinder critical thinking depending on how it is used. This apparent contradiction suggests that AI should not be viewed as inherently beneficial or harmful. Rather, its educational effect depends on the interaction among technology, learners, teachers, learning tasks and educational context.

The distinction between AI-assisted learning and AI-dependent learning is therefore important. AI-assisted learning occurs when students use AI to obtain explanations, feedback, examples or alternative perspectives while retaining responsibility for their own reasoning and decisions. AI-dependent learning occurs when students delegate substantial portions of their intellectual work to AI and accept its outputs without sufficient evaluation. The former may support critical thinking, whereas the latter may weaken it.

Critical thinking itself involves several interrelated abilities. Students must be able to interpret information accurately, analyse relationships among ideas, evaluate evidence and arguments, draw logical inferences, explain their reasoning and regulate their own thinking (Facione, 1990). AI-based learning tools may potentially contribute to each of these dimensions. For instance, students may ask AI to provide different explanations of a concept, compare competing arguments, generate alternative solutions or identify weaknesses in an argument. However, the educational benefit occurs only when students actively evaluate and reason through the information provided.

The growing body of research also reveals an important research gap. Zawacki-Richter et al. (2019) observed that much early AI-in-education research concentrated on higher education and technical applications. More recent research has expanded toward generative AI and critical thinking, but Liu et al. (2025) noted limitations involving research scope, user dependency, reliability of AI outputs and pedagogical integration. Tian and Zheng (2025) similarly observed variations in AI effects according to educational level, technology type and application approach.

This suggests that evidence obtained from university students or foreign educational settings cannot automatically be generalised to Nigerian secondary school students. Secondary school students differ from university students in terms of age, learning autonomy, digital experience, academic maturity and teacher supervision. The school environment in Lagos also has its own technological, socioeconomic and pedagogical characteristics. There is therefore a need for empirical research that specifically investigates AI-based learning tools and critical thinking among secondary school students in Lagos State.

The issue is particularly timely because AI technologies are developing faster than many educational systems can establish appropriate guidelines for their use. Schools must determine how AI should be integrated into teaching without weakening students’ independent intellectual development. Teachers must also understand whether AI should be used primarily for explanation, feedback, practice, research, assessment or other educational functions. Without empirical evidence, decisions concerning AI adoption may be based largely on assumptions rather than evidence.

Therefore, the present study is concerned with determining the impact of Artificial Intelligence-Based Learning Tools on students’ critical thinking skills in selected secondary schools in Lagos State. The study focuses particularly on whether exposure to and use of AI-based learning tools is associated with students’ ability to analyse information, evaluate evidence, make inferences, reason logically and solve problems. By examining this relationship, the study seeks to contribute empirical evidence to the ongoing discussion about the appropriate role of AI in secondary education.

1.2 Statement of the Problem

The primary problem addressed by this study is the uncertainty surrounding the effect of the increasing use of Artificial Intelligence-Based Learning Tools on the development of critical-thinking skills among secondary school students. Critical thinking is expected to be an important outcome of contemporary education because students need to analyse information, evaluate evidence, identify assumptions, solve problems and make informed decisions. However, the rapid growth of AI technologies has created a learning environment in which students can obtain explanations, answers, summaries and complete academic responses with minimal cognitive effort.

The emergence of generative AI has made the problem more pronounced. Students can now enter a question into an AI system and receive an apparently comprehensive answer almost immediately. While this can make learning more convenient, it creates the possibility that students may become dependent on AI rather than develop their own reasoning abilities. Liu et al. (2025) found evidence that excessive dependence on generative AI may lead to passive thinking, reduced analytical depth and impaired autonomous skill development.

A second dimension of the problem concerns the accuracy and credibility of AI-generated information. AI systems do not always provide correct information, and their responses may contain factual errors, unsupported claims or biased interpretations. Students who lack adequate critical-thinking skills may accept these responses as accurate simply because they are presented fluently and confidently. Liu et al. (2025) identified AI reliability as one of the major challenges associated with its educational use and emphasised the need for learners to critically evaluate AI-generated information.

A third problem is that AI may encourage cognitive offloading. Instead of engaging in the processes of reading, analysing, comparing, reasoning and writing, students may delegate these activities to AI. The immediate consequence may be faster completion of assignments, but the long-term consequence could be inadequate development of independent intellectual abilities. This concern is particularly important at the secondary-school level because students are still developing the cognitive habits and learning strategies that they will carry into higher education and professional life.

At the same time, completely rejecting AI would also be problematic. Research indicates that AI can support higher-order learning when appropriately integrated into educational activities. Tian and Zheng (2025), for example, found a moderate positive overall effect of AI on students’ 4C skills, including critical thinking, and reported particularly positive effects where AI was used for adaptive and personalised learning. Liu et al. (2025) similarly found that most of the studies included in their review reported positive contributions of generative AI to critical thinking, although a substantial minority identified negative effects.

The problem, therefore, is not simply the presence of AI but the uncertainty regarding the conditions under which AI supports or undermines critical thinking. If AI is used to encourage students to compare information, test ideas, identify errors and justify conclusions, it may strengthen critical-thinking skills. If it is used primarily to provide ready-made answers, it may reduce students’ intellectual engagement. This makes the manner and extent of AI use an important issue for empirical investigation.

Another problem concerns teachers’ ability to integrate AI into classroom instruction. AI-based learning tools require pedagogically appropriate tasks and adequate supervision. Zawacki-Richter et al. (2019) identified a notable gap between AI research and educators’ involvement, suggesting that the pedagogical dimensions of AI require greater attention. If teachers are not adequately prepared to guide students’ interaction with AI, students may use these tools primarily for convenience rather than meaningful learning.

There is also a potential problem of unequal access. Students from different socioeconomic backgrounds may not have equal access to smartphones, computers, reliable internet connectivity or advanced AI applications. Such differences can affect students’ opportunities to benefit from AI-based learning. Furthermore, students who have access to AI may differ considerably in their digital literacy and ability to identify inaccurate or misleading AI-generated information.

Despite the rapid growth of AI in education, there remains limited empirical evidence specifically addressing the relationship between AI-based learning tools and critical-thinking skills among secondary school students in Lagos State. Existing international studies provide useful evidence, but their findings cannot automatically be transferred to Nigerian secondary schools because educational contexts, technological access, teacher preparation and students’ patterns of technology use differ across countries and educational levels.

The gap is evident in the existing literature. Zawacki-Richter et al. (2019) focused their systematic review primarily on higher education, while more recent research such as Tian and Zheng (2025) covers multiple educational levels and reports differences in AI effects according to learner characteristics and technological applications. Liu et al. (2025) also identified gaps concerning long-term effects, dependency, AI reliability and pedagogical integration. These gaps justify the need for context-specific research involving secondary school students.

The absence of adequate local evidence creates a practical problem for teachers, school administrators and education policymakers. Without empirical evidence, schools may either adopt AI technologies without sufficient safeguards or discourage their use without understanding their potential educational benefits. Both responses could be problematic. Unregulated use may encourage dependence and reduce independent thinking, while excessive restriction may prevent students from developing the AI literacy needed to function effectively in an increasingly technology-driven society.

The problem addressed by this study is therefore the lack of sufficient empirical evidence on whether and to what extent Artificial Intelligence-Based Learning Tools influence students’ critical thinking skills in selected secondary schools in Lagos State. Specifically, it is necessary to determine whether the use of these tools is associated with students’ abilities to analyse information, evaluate evidence, make logical inferences, solve problems and arrive at reasoned conclusions.

It is against this background that this study examines the Impact of Artificial Intelligence-Based Learning Tools on Students’ Critical Thinking Skills in Selected Secondary Schools in Lagos State. The findings are expected to provide evidence that can guide the responsible and pedagogically appropriate integration of AI into secondary-school education.

1.3 Aim of the Study

The main aim of this study is to examine the impact of Artificial Intelligence-Based Learning Tools on students’ critical thinking skills in selected secondary schools in Lagos State.

The specific objectives are to:

1. examine the extent to which students use Artificial Intelligence-Based Learning Tools for academic purposes in selected secondary schools in Lagos State;
2. determine the level of students’ critical thinking skills in selected secondary schools in Lagos State;
3. examine the influence of AI-based learning tools on students’ ability to analyse information;
4. determine the influence of AI-based learning tools on students’ ability to evaluate evidence and arguments.

1.4 Research Questions

The following research questions will guide the study:

1. To what extent do students use Artificial Intelligence-Based Learning Tools for academic purposes in selected secondary schools in Lagos State?
2. What is the level of students’ critical thinking skills in selected secondary schools in Lagos State?
3. To what extent do AI-based learning tools influence students’ ability to analyse information?
4. To what extent do AI-based learning tools influence students’ ability to evaluate evidence and arguments?

1.5 Research Hypothesis

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

H₀: There is no significant relationship between the use of Artificial Intelligence-Based Learning Tools and students’ critical thinking skills in selected secondary schools in Lagos State.

1.6 Significance of the Study

The study will be significant to students because it will increase awareness of the appropriate use of AI-based learning tools. The findings may encourage students to use AI as a learning aid while maintaining responsibility for their own reasoning, evaluation and decision-making. This may help reduce uncritical dependence on AI-generated responses.

The study will be useful to teachers because it will provide empirical evidence concerning the relationship between AI-based learning tools and critical thinking. Teachers may use the findings to design learning activities in which students interrogate AI-generated responses, compare information from different sources, identify errors, evaluate arguments and justify conclusions.

The study will also benefit school administrators. The findings may assist school management in developing appropriate guidelines for students’ use of AI technologies and in determining the type of teacher training, digital infrastructure and supervision required for effective AI integration.

The study will be relevant to education policymakers in Lagos State and Nigeria. Evidence from the study may contribute to policies concerning AI literacy, digital learning, curriculum development, teacher professional development and responsible technology use in secondary schools. Miao et al. (2021) emphasise that education policy must maximise the opportunities presented by AI while addressing risks, inclusion and equity.

The study will also benefit parents and guardians by providing greater understanding of how AI can influence students’ learning habits. Such knowledge may help parents encourage productive and responsible technology use.

Finally, the study will contribute to the existing body of academic literature on Artificial Intelligence in Education. It may serve as a useful reference for researchers investigating AI, critical thinking, digital literacy, academic achievement, creativity, problem-solving and other educational outcomes among Nigerian students.

1.7 Scope of the Study

The study focuses on the impact of Artificial Intelligence-Based Learning Tools on students’ critical thinking skills in selected secondary schools in Lagos State.

The independent variable is Artificial Intelligence-Based Learning Tools, while the dependent variable is students’ critical thinking skills. AI-based learning tools covered by the study include intelligent tutoring systems, adaptive learning applications, AI-powered educational applications, automated feedback systems and generative AI tools used for academic learning.

Students’ critical thinking skills will be examined in relation to major cognitive dimensions such as analysis, evaluation, inference, reasoning and problem-solving, consistent with the conceptualisation of critical thinking provided by Facione (1990).

Geographically, the study is restricted to selected secondary schools in Lagos State, Nigeria. The study does not seek to generalise its findings automatically to all secondary schools in Nigeria.

1.8 Operational Definition of Terms

Artificial Intelligence (AI): A field of computing concerned with developing systems capable of performing tasks associated with human intelligence, including learning, reasoning, prediction, language processing and problem-solving.

AI-Based Learning Tools: Digital educational technologies that use Artificial Intelligence to support students’ learning through functions such as personalised instruction, intelligent tutoring, automated feedback, content generation, assessment and adaptive learning.

Critical Thinking: A purposeful and self-regulated cognitive process involving interpretation, analysis, evaluation, inference, explanation and self-regulation (Facione, 1990).

Students: Learners enrolled in the selected secondary schools covered by this study.

Analysis: The ability to identify, examine and understand relationships among ideas, information, evidence and arguments.

Evaluation: The ability to judge the credibility, relevance, accuracy and strength of information, evidence or arguments.

Inference: The ability to draw reasonable conclusions from available evidence and information.

Problem-Solving: The ability to identify problems, consider alternatives and develop logical solutions using relevant knowledge and evidence.

Generative Artificial Intelligence: AI technology capable of generating new content such as text, explanations, questions, summaries and solutions in response to user instructions.

AI-Assisted Learning: A learning process in which students use AI technologies to support their understanding and learning while retaining responsibility for independent reasoning and judgement.

AI Dependency: Excessive reliance on AI systems to perform intellectual tasks that students would otherwise be expected to undertake independently.

Project – Impact of Artificial Intelligence-Based Learning Tools on Students’ Critical Thinking Skills in Selected Secondary Schools in Lagos State