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Impact of Data Analytics Education on the Decision-Making Skills of Accounting Education Students in Nigeria

Abstract

The increasing availability of large volumes of financial and non-financial data has transformed the accounting profession and created growing demand for accounting graduates who can analyse information and use evidence to support effective decisions. Modern accounting professionals are increasingly expected to apply data analytics to identify trends, detect anomalies, evaluate financial performance, assess risks, interpret business information, and support strategic and managerial decisions. Accounting education students in Nigeria therefore require adequate data analytics knowledge and practical skills to prepare for technology-driven accounting environments. However, limited exposure to structured data analytics education, inadequate access to analytical software, insufficient practical datasets, and gaps in lecturers' technological competencies may constrain students' ability to use accounting data effectively for decision-making. Data analytics education provides an opportunity to strengthen students' analytical capabilities and improve their ability to make informed decisions using accounting and business information. Against this background, this study investigates the impact of data analytics education on the decision-making skills of accounting education students in Nigeria. The study will be anchored on Human Capital Theory, Constructivist Learning Theory, and the Technology Acceptance Model (TAM). Human Capital Theory explains how investment in education and technical competencies can improve students' knowledge, productivity, professional capabilities, and employability. Constructivist Learning Theory emphasizes active participation, practical application, problem-solving, and knowledge construction through meaningful learning experiences, providing a basis for examining how data analytics education may develop students' decision-making abilities. The Technology Acceptance Model explains how students' perceived usefulness and perceived ease of use of data analytics technologies may influence their willingness to engage with analytical tools and apply them effectively. Collectively, these theoretical perspectives provide a suitable framework for explaining how data analytics education may influence the decision-making skills of accounting education students in Nigeria. The study will adopt a quantitative quasi-experimental or analytical cross-sectional research design. The study population will comprise undergraduate and postgraduate accounting education students enrolled in selected universities and institutions offering accounting education programmes in Nigeria. A multistage sampling technique will be used to select geopolitical zones, states, universities or institutions, faculties or departments, levels of study, and eligible accounting education students. Data analytics education will be assessed using indicators such as exposure to data analytics courses, frequency and duration of analytics training, spreadsheet-based analysis, statistical analysis, accounting data visualization, data cleaning, financial data analysis, audit analytics, dashboard development, use of accounting analytics software, data interpretation, trend analysis, anomaly detection, forecasting exercises, practical projects, case studies, business simulations, and lecturer-guided analytical activities. Decision-making skills will be assessed using indicators such as identification and definition of accounting problems, interpretation of financial information, evaluation of alternatives, evidence-based reasoning, risk assessment, financial decision-making, problem-solving, critical thinking, forecasting, evaluation of outcomes, logical reasoning, judgement, and ability to make appropriate decisions from accounting and business data. Data will be collected using structured questionnaires, standardized decision-making skills assessment tools, accounting data interpretation tests, practical analytics exercises, case-based decision-making tasks, business scenarios, and pre-test and post-test assessments where a quasi-experimental intervention is adopted. Descriptive statistics will be used to summarize students' demographic and academic characteristics, exposure to data analytics education, analytical tools used, practical experience, and decision-making skill levels. Inferential statistical techniques, including chi-square tests, paired and independent t-tests, correlation analysis, and multiple regression analysis where appropriate, will be used to determine the impact of data analytics education on decision-making skills. Where a quasi-experimental design is adopted, decision-making skill scores before and after the educational intervention may be compared with those of a comparison group to determine changes associated with the intervention. Diagnostic tests will also be conducted to assess the reliability, validity, and robustness of the findings. The study is expected to find that data analytics education has a significant positive impact on the decision-making skills of accounting education students in Nigeria. Students exposed to structured, practical, and accounting-focused data analytics education are expected to demonstrate stronger abilities to interpret financial information, identify accounting problems, evaluate alternatives, assess risks, recognize trends, detect anomalies, and make evidence-based decisions than students with limited exposure. Practical use of accounting datasets may help students connect theoretical accounting knowledge with realistic business situations and improve their ability to evaluate information before reaching conclusions. Data visualization, forecasting, dashboard analysis, and scenario-based exercises may further strengthen students' critical thinking, analytical reasoning, judgement, and confidence in making accounting-related decisions. However, inadequate access to computers and analytics software, unreliable internet connectivity and electricity, limited practical datasets, insufficiently trained lecturers, large class sizes, curriculum constraints, and limited institutional support may reduce the effectiveness of data analytics education. The study therefore expects practical, current, industry-relevant, and technology-supported data analytics education to contribute significantly to improved decision-making skills among accounting education students in Nigeria. The study is expected to contribute to the literature on data analytics education, decision-making skills, accounting education, accounting analytics, digital accounting, educational technology, data-driven decision-making, accounting information systems, analytical skills, and higher education in Nigeria. The findings will provide useful information to the National Universities Commission, universities, faculties of education and management sciences, accounting education departments, accounting educators, professional accounting bodies, employers, curriculum developers, educational technology providers, and policymakers regarding strategies for strengthening data-driven decision-making competencies among future accounting educators and professionals. The study will also provide evidence-based recommendations for integrating data analytics into accounting education curricula, improving access to analytics software and computer laboratories, strengthening lecturers' capacity in accounting analytics, incorporating practical datasets and case-based decision-making exercises into teaching, promoting university-industry collaboration, and ensuring that accounting education students possess the analytical and decision-making competencies required for effective participation in Nigeria's increasingly data-driven accounting environment.

Keywords: Data analytics education, decision-making skills, accounting education students, accounting education, accounting analytics, data-driven decision-making, analytical skills, digital accounting, educational technology, accounting information systems, Nigerian universities, Nigeria.