Statistical Analysis of ChatGPT Adoption Among University Students
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Abstract
About This Research Topic
Artificial intelligence has rapidly moved into everyday academic life, and ChatGPT, launched by OpenAI in November 2022, became the fastest-growing consumer application in history — one million users in days, over 100 million in two months. Built on transformer-based generative architecture, it produces coherent text for essay writing, code generation, problem solving, translation and tutoring, positioning itself as always-available academic assistant while raising concerns about academic dishonesty, accuracy and critical thinking erosion.
Technology Acceptance Model (TAM) by Davis posits perceived usefulness and perceived ease of use as primary determinants of intention to use new technology, extended in TAM2 and UTAUT to include social influence, facilitating conditions and experience. In Nigeria, internet penetration reached 55.4% in 2023 per Nigerian Communications Commission, with campuses as high digital activity clusters. Yet patterns, motivations and consequences of ChatGPT adoption among Nigerian undergraduates remain underexplored, leaving policy formation in empirical vacuum risking overly restrictive or insufficiently firm responses.
This study conducts comprehensive statistical analysis among 200 undergraduates at University of Lagos using structured 25-item Likert questionnaire. Methods include descriptive statistics, Pearson correlation, multiple linear regression, one-way ANOVA and chi-square tests. Findings show 96.5% ever used ChatGPT, 66.5% weekly or more frequent, with perceived usefulness beta 0.287, ease of use 0.214, frequency 0.172 as strongest predictors of adoption intention, model explaining 68.3% variance. Significant differences across academic levels F=8.74 p<0.001 but no gender difference chi-square 0.184 p=0.912. The analysis demonstrates multivariate pipeline applicable to emerging AI phenomena in resource-constrained contexts. For methodological foundation, see our guides to technology adoption models and survey analysis using SPSS.
Main Abstract
This study undertook statistical analysis of ChatGPT adoption among university students focusing on drivers and perceived academic impact. Cross-sectional survey design with 200 undergraduate students at University of Lagos using structured 25-item Likert questionnaire. Data analysed via descriptive statistics, Pearson correlation, multiple linear regression, one-way ANOVA and chi-square tests. Majority 96.5% had used ChatGPT at least once, 66.5% reporting multiple times per week or more. Perceived usefulness (beta=0.287, p<0.001), ease of use (beta=0.214, p<0.001) and frequency of use (beta=0.172, p=0.006) emerged as strongest predictors of adoption intention. Significant difference in adoption levels across academic levels (F=8.74, p<0.001), while no significant gender difference (chi-square=0.184, p=0.912). Overall regression model accounted for 68.3% variance (R2=0.683, F=52.47, p<0.001). Study concludes ChatGPT adoption widespread principally driven by perceived utility and accessibility. Recommendations for universities to develop clear AI policies, integrate AI literacy into curricula and promote ethical use.
Chapter One Preview
Background to the Study
Emergence of AI in everyday life has catalysed transformations across domains, education no exception. ChatGPT, large language model developed by OpenAI, publicly launched November 2022, garnered over one million users within days, exceeding 100 million in two months, fastest-growing consumer application in history. Phenomenal uptake raises pressing questions about how digitally engaged university students adopt and interact with technology.
ChatGPT belongs to generative AI systems built on transformer-based neural networks capable of producing coherent contextually relevant text. Capabilities span essay writing, code generation, mathematical problem solving, translation, tutoring, summarisation. For students, opportunities as academic assistant explaining complex concepts, providing research summaries, writing assistance, alongside risks misuse in dishonesty, accuracy issues, erosion of critical thinking. Theoretical foundation well established: Technology Acceptance Model (TAM) Davis 1989 posits perceived usefulness and ease of use as primary determinants of intention, extended in TAM2 and UTAUT incorporating social influence, facilitating conditions, experience. In context of ChatGPT, these frameworks provide robust foundation examining multifaceted drivers.
In Nigeria and sub-Saharan Africa, adoption of AI tools among students relatively underexplored despite rapid growth of internet penetration and smartphone usage. Nigerian Communications Commission 2024 reported internet penetration approximately 55.4% in 2023, campuses clusters of high digital activity. As Nigerian universities grapple with inadequate physical and human resources, AI tools offer potential supplements to formal instruction. However patterns, motivations and consequences remain poorly understood, creating significant empirical gap. This study addresses gap employing rigorous statistical methods to examine adoption patterns at University of Lagos, measuring prevalence, predictors and perceived impact on academic performance.
Nigerian Communications Commission – Industry Statistics and Internet Penetration
Hu 2023 – ChatGPT Growth Analysis and Adoption Studies
Statement of the Problem
Despite rapid diffusion globally, systematic empirical data on adoption patterns and determinants within Nigerian universities remain scarce. Most existing studies qualitative or small convenience samples from Western institutions limiting generalizability to Nigerian context. Anecdotal evidence and institutional debates widespread in Nigeria, yet little quantitative data to inform policy by administrators and regulatory bodies. Key problem is university policies on AI use being formed in empirical vacuum. Without sound statistical data on how many students using ChatGPT, how frequently, for what purposes and with what outcomes, institutional responses risk being overly restrictive stifling legitimate benefits or insufficiently firm allowing academic integrity to deteriorate. Question of equity: do adoption rates differ across gender, academic level or faculty? Understanding differentials crucial for designing inclusive effective AI literacy programmes. This study addresses insufficient statistical evidence on nature, extent and determinants of ChatGPT adoption among Nigerian university students to support evidence-based policy and educational planning.
Aim and Objectives
Aim: To conduct comprehensive statistical analysis of ChatGPT adoption among undergraduate students at University of Lagos.
1. Determine prevalence and frequency of ChatGPT use among undergraduate students at University of Lagos.
2. Assess students' perceived usefulness, ease of use and trust in ChatGPT.
3. Identify key predictors of ChatGPT adoption intention among students using regression analysis.
4. Examine whether significant differences in ChatGPT adoption exist across academic levels using ANOVA.
5. Determine whether gender significantly influences ChatGPT adoption patterns using chi-square analysis.
6. Assess students' perceptions of impact of ChatGPT on their academic performance.
Research Questions
What is prevalence and frequency of ChatGPT use among undergraduate students at University of Lagos?
What are students' perceived levels of usefulness, ease of use and trust with respect to ChatGPT?
What are key predictors of ChatGPT adoption intention among undergraduate students?
Is there statistically significant difference in ChatGPT adoption levels across academic levels?
Is there statistically significant association between gender and ChatGPT adoption category?
How do students perceive impact of ChatGPT on their academic performance?
Significance of the Study
Academically contributes to emerging literature on AI adoption in higher education particularly developing economies where studies sparse. Employing range of statistical tools including descriptive, correlation, regression, ANOVA and chi-square demonstrates application of multivariate techniques to contemporary social phenomenon, contributing to methodological repertoire. Policy-wise findings provide university administrators, curriculum developers and regulatory authorities evidence-based insights to guide formulation of policies on AI use. Nigerian Universities Commission and senate bodies can draw on recommendations to develop balanced guidelines. For students and educators, highlights benefits and challenges serving as basis for developing AI literacy curricula and responsible use frameworks. Industry stakeholders and EdTech developers may find adoption determinants useful for designing AI tools better meeting needs of African student populations. For practical adoption, see our resources on academic integrity policies and AI literacy curriculum design for universities.
Scope of the Study
Geographically limited to University of Lagos, Akoka, Lagos State. Target population undergraduate students across all faculties and levels 100 to 400 level. Focuses on ChatGPT as primary AI tool although related generative AI tools may be referenced contextually. Time frame 2024/2025 academic session.
Operational Definition of Terms
ChatGPT: Large language model developed by OpenAI based on Generative Pre-trained Transformer architecture capable of generating human-like text in response to prompts.
Technology Adoption: Process by which individual or group comes to accept and regularly use new technology.
Perceived Usefulness: Degree to which user believes using technology will enhance performance, in this case academic performance.
Perceived Ease of Use: Degree to which user believes using technology will be free from effort.
Adoption Intention: Strength of individual's intention to continue using or adopt specific technology in future.
Frequency of Use: Regularity with which student engages with ChatGPT in context of academic work.
Academic Performance: Degree to which students accomplish educational goals typically measured by grades, understanding and completion of tasks.
OpenAI – GPT-4 Technical Report and Capabilities
EDUCAUSE – Higher Education Technology Adoption Research
Short Conclusion
Analysis of 200 University of Lagos undergraduates confirms ChatGPT adoption widespread at 96.5% ever used, 66.5% weekly or more, principally driven by perceived usefulness beta 0.287 and ease of use 0.214 per TAM, plus frequency 0.172, model accounting for 68.3% variance R2=0.683 F=52.47 p<0.001. Significant differences across academic levels F=8.74 p<0.001 suggest upper levels adopt more for research and projects, while gender shows no significant association chi-square 0.184 p=0.912 indicating equity in access. Findings suggest students view ChatGPT as utility enhancing rather than novelty. Recommendations include universities developing clear policies distinguishing legitimate assistance from academic dishonesty, integrating AI literacy into curricula covering prompt engineering, critical evaluation and ethics, providing equitable access and training across levels, and promoting ethical use via honor codes and assessment redesign emphasizing process over product. Limitations include self-report social desirability bias, cross-sectional design unable to track longitudinal change, single institution limiting generalizability, and rapidly evolving capabilities. Future research should be multi-institutional longitudinal incorporating UTAUT constructs like social influence and facilitating conditions. Explore our collection of EdTech adoption studies and responsible AI use guidelines for higher education.
Frequently Asked Questions
Q: How prevalent is ChatGPT use among University of Lagos students?
A: 96.5% had used ChatGPT at least once, 66.5% reported multiple times per week or more frequent, indicating near-universal awareness and widespread habitual use within sampled 200 undergraduates.
Q: What drives adoption intention according to TAM?
A: Perceived usefulness beta 0.287 p<0.001 strongest predictor, followed by ease of use beta 0.214 p<0.001 and frequency of use beta 0.172 p=0.006. Students adopt when they believe tool enhances academic performance and is free from effort.
Q: Does academic level affect adoption?
A: Yes. One-way ANOVA F=8.74 p<0.001 showed significant differences across 100L to 400L. Upper levels often use more for research, final year projects and complex assignments, while lower levels may use for basic explanations.
Q: Is there gender difference in adoption?
A: No. Chi-square test of independence chi-square 0.184 p=0.912 showed no significant association between gender and adoption category, suggesting equitable access and acceptance across male and female students.
Q: How much variance does model explain?
A: Overall regression model R2=0.683 F=52.47 p<0.001 accounting for 68.3% variance in adoption intention using usefulness, ease of use, frequency, awareness and trust, indicating strong explanatory power.
Q: What about impact on academic performance?
A: Students generally perceived positive impact on understanding, research efficiency and assignment completion, while concerns remain about over-reliance, accuracy of outputs and erosion of critical thinking, warranting balanced policy.
Q: What are limitations?
A: Self-reported questionnaire risking social desirability bias, cross-sectional single time point unable to track longitudinal change, findings specific to University of Lagos not fully generalizable, and rapidly evolving AI capabilities may affect relevance of items.
Q: What policies should universities adopt?
A: Develop clear guidelines distinguishing legitimate tutoring assistance from dishonesty, integrate AI literacy into curricula, provide equitable training, redesign assessments to emphasize critical thinking and process, and promote ethical use via awareness campaigns.
Q: How does this fit TAM and UTAUT?
A: Results support TAM core constructs usefulness and ease of use as primary determinants, aligning with extensions TAM2 and UTAUT which add social influence and facilitating conditions. Future studies can incorporate those constructs for fuller model.
Q: Can this method be replicated?
A: Yes. Cross-sectional survey with 25-item Likert questionnaire measuring TAM constructs, descriptive, correlation, multiple regression, ANOVA and chi-square forms reproducible template for other Nigerian universities and comparative studies across faculties.
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