Datasets Comparison

Background This dataset was created to examine the impact of gamified learning environments on student retention, motivation, and engagement among undergraduate economics students in Nigeria. It integrates quantitative and qualitative data to provide robust evidence on digital pedagogy in higher education. Research Design A mixed methods design was adopted: • Quantitative quasi-experiments compared students exposed to gamification with those taught traditionally. • Qualitative interviews and focus groups explored perceptions, challenges, and best practices. Population and Sampling The population comprised undergraduate economics students from Nigerian universities with integrated digital learning. Stratified random sampling captured students from levels 100–400. Institutions were purposively selected for diversity and documented gamification initiatives. Five universities participated: Covenant University, Babcock University, Usmanu Danfodiyo University, University of Nigeria, Nsukka, and Benue State University. Data Collection Three instruments were used: • Structured questionnaire (adapted from validated scales such as the Intrinsic Motivation Inventory). • Classroom observations (participation and attentiveness). • Semi-structured interviews and focus groups (perceptions of gamification). Validity and Reliability Content validity was established through expert review, and pilot testing refined clarity; Cronbach’s alpha exceeded 0.70, confirming reliability. Triangulation of quantitative and qualitative strands enhanced credibility. Data Analysis • Quantitative: Descriptive statistics (means, frequencies, SDs) and inferential tests (t-tests, ANOVA, regression, chi-square). A chi-square test revealed a highly significant association between gamification exposure and retention, with Phi = 0.989 (near-perfect correlation) and a contingency coefficient of 0.703 (strong association). • Qualitative: Thematic analysis identified effectiveness, challenges, and best practices. Dataset Contents • Quantitative files: demographics, gamification exposure (binary), motivation, engagement, retention scores, cross-tabulations. • Qualitative transcripts: interviews and focus groups. • Metadata: institutional gamification practices, sampling framework, coding schemes. Ethics Ethical approval was obtained, informed consent secured, and confidentiality maintained through anonymization. Data are used solely for academic purposes. Significance This dataset provides empirical evidence linking gamification to improved retention in economics education. It offers both statistical rigor and contextual depth, supporting replication, meta-analysis, and policy development in digital pedagogy.

Data Collection and Protocols The dataset was generated through a mixed-methods design that combined quantitative quasi-experiments with qualitative interviews and focus groups. This approach ensured both statistical rigor and contextual depth. Population and Sampling • Target population: undergraduate economics students in Nigerian universities with digital learning integration. • Institutions were purposively selected for diversity and documented gamification initiatives. • Stratified random sampling captured students across study levels (100–400). • Sample size was determined using Cochran’s formula at 95% confidence to ensure representativeness. Instruments and Protocols 1. Structured Questionnaire o Items adapted from validated scales, including the Intrinsic Motivation Inventory. o Measured engagement, intrinsic motivation, and retention. 2. Classroom Observations o Recorded behavioural indicators such as attentiveness and participation. 3. Semi-Structured Interviews and Focus Groups o Explored perceptions, challenges, and best practices in gamified learning. Validity and Reliability • Content validity established through expert review. • Pilot testing refined clarity and usability. • Reliability confirmed with Cronbach’s alpha (>0.70 threshold). • Triangulation of quantitative and qualitative strands enhanced credibility. Data Analysis Workflow • Quantitative: Descriptive statistics (means, frequencies, SDs) and inferential tests (t-tests, ANOVA, regression, chi-square). A chi-square test revealed a highly significant association between gamification exposure and retention (Phi = 0.989; contingency coefficient = 0.703). Logit regression was also used for econometric tests. • Qualitative: Thematic analysis followed Braun & Clarke’s six-step process (familiarization, coding, theme development, review, definition, reporting). Software and Procedures • Statistical analyses conducted using standard packages (EViews). • Maximum-likelihood estimation applied in logistic regression. • Thematic coding performed manually and cross-validated by multiple researchers. Ethical Protocols • Institutional review board approval obtained. • Informed consent secured from all participants. • Responses anonymized to maintain confidentiality. This dataset was thus derived through a transparent, replicable workflow involving validated instruments, rigorous sampling, and established statistical and qualitative protocols. It can be reproduced by applying the same mixed-methods design, instruments, and analysis procedures in comparable educational contexts.

Economics, Education

Attribution-NonCommercial 3.0 Unported

Research Hypothesis The study hypothesizes that gamification as an intelligent pedagogical system significantly improves student motivation, participation, and knowledge retention in Nigerian undergraduate economics education. By embedding game mechanics (points, badges, leaderboards, interactive challenges), passive learning is transformed into active problem solving engagement, addressing disengagement and poor comprehension. Data Overview • Population: Undergraduate economics students across Nigerian universities (federal, state, private) with varying ICT infrastructure. • Sample: Stratified random sampling across study levels (100–400). • Instruments: Structured questionnaires, classroom observations, semi structured interviews/focus groups. • Validity & Reliability: Expert review, pilot testing, Cronbach’s alpha > 0.70, triangulation of quantitative and qualitative strands. • Analysis Methods: Descriptive statistics, ANOVA, t tests, logistic regression, chi square tests, thematic coding. What the Data Shows • Motivation & Engagement: Gamification significantly increased motivation and participation compared to traditional methods. • Retention: Chi square analysis confirmed a strong link between gamification and knowledge retention (Φ = 0.989; contingency = 0.703). • Demographics: Age and gender had no significant impact; ICT infrastructure influenced effectiveness. • Behavioural Outcomes: Students exposed to gamification showed higher attentiveness, collaboration, and willingness to apply concepts in real world scenarios. • Perceptions: Interviews revealed gamification made economics more relatable, reduced abstraction, and encouraged problem solving. Notable Findings • Gamification shifted learning from passive reception to active collaboration and problem solving. • Effectiveness varied by institutional readiness and ICT infrastructure, not by demographics. • Policy implications: need for educator training, curriculum alignment, and investment in educational technology. • Extends constructivist and self determination theories to a developing economy context, showing applicability beyond Western settings. Interpretation and Use • Researchers: Provides replicable evidence of gamification’s impact on cognitive and behavioural outcomes. • Educators: Practical guidance for integrating game mechanics into curricula. • Policymakers: Supports investment in ICT infrastructure and teacher training. • Curriculum Developers: Aligns gamification strategies with constructivist and motivational theories to improve learning outcomes. Conclusion The data demonstrates that gamification is a transformative pedagogical system that enhances motivation, participation, and retention in economics education. Properly implemented, it bridges the gap between abstract theory and practical application, preparing graduates with skills essential for national development.

Data Collection and Protocols The dataset was generated through a mixed-methods design that combined quantitative quasi-experiments with qualitative interviews and focus groups. This approach ensured both statistical rigor and contextual depth. Population and Sampling • Target population: undergraduate economics students in Nigerian universities with digital learning integration. • Institutions were purposively selected for diversity and documented gamification initiatives. • Stratified random sampling captured students across study levels (100–400). • Sample size was determined using Cochran’s formula at 95% confidence to ensure representativeness. Instruments and Protocols 1. Structured Questionnaire o Items adapted from validated scales, including the Intrinsic Motivation Inventory. o Measured engagement, intrinsic motivation, and retention. 2. Classroom Observations o Recorded behavioural indicators such as attentiveness and participation. 3. Semi-Structured Interviews and Focus Groups o Explored perceptions, challenges, and best practices in gamified learning. Validity and Reliability • Content validity established through expert review. • Pilot testing refined clarity and usability. • Reliability confirmed with Cronbach’s alpha (>0.70 threshold). • Triangulation of quantitative and qualitative strands enhanced credibility. Data Analysis Workflow • Quantitative: Descriptive statistics (means, frequencies, SDs) and inferential tests (t-tests, ANOVA, regression, chi-square). A chi-square test revealed a highly significant association between gamification exposure and retention (Phi = 0.989; contingency coefficient = 0.703). Logit regression was also used for econometric tests. • Qualitative: Thematic analysis followed Braun & Clarke’s six-step process (familiarization, coding, theme development, review, definition, reporting). Software and Procedures • Statistical analyses conducted using standard packages (EViews). • Maximum-likelihood estimation applied in logistic regression. • Thematic coding performed manually and cross-validated by multiple researchers. Ethical Protocols • Institutional review board approval obtained. • Informed consent secured from all participants. • Responses anonymized to maintain confidentiality. This dataset was thus derived through a transparent, replicable workflow involving validated instruments, rigorous sampling, and established statistical and qualitative protocols. It can be reproduced by applying the same mixed-methods design, instruments, and analysis procedures in comparable educational contexts.

Economics, Education, Gamification

Attribution-NonCommercial 3.0 Unported