Impact of flipped classrooms on economics learning outcomes in undergraduate programs: A field study
Table Of Contents
Chapter ONE
INTRODUCTION
- 1.
- 1.1Introduction
- 2.
- 1.2Background of the Study
- 3.
- 1.3Statement of the Problem
- 4.
- 1.4Aim and Objectives of the Study
- 5.
- 1.5Research Questions
- 6.
- 1.6Research Hypotheses
- 7.
- 1.7Significance of the Study
- 8.
- 1.8Scope and Delimitation of the Study
- 9.
- 1.9Limitations of the Study
- 10.
- 1.10Organisation of the Study
- 11.
- 1.11Operational Definition of Terms
Chapter TWO
LITERATURE REVIEW
- 1.
- 2.1Conceptualizing Flipped Classrooms in Economics Education
- 2.
- 2.2Theoretical Framework: Constructivism and Cognitive Load Theory
- 3.
- 2.3The Flipped Classroom Model in Higher Education Economics
- 4.
- 2.4Student Engagement in Flipped Economics Instruction
- 5.
- 2.5Instructional Design and Content Familiarity in Flipped Economics
- 6.
- 2.6Technology Adoption and Accessibility in Economics Courses
- 7.
- 2.7Pedagogical Outcomes: Critical Thinking and Problem-Solving
- 8.
- 2.8Assessment and Learning Analytics in Flipped Economics
- 9.
- 2.9Prior Empirical Studies on Flipped Classrooms in Economics
- 10.
- 2.10Comparative Effectiveness: Flipped vs. Traditional Methods
- 11.
- 2.11Equity, Inclusion, and Digital Divide in Flipped Economics
- 12.
- 2.12Gaps in the Literature and The Need for Field Studies
- 13.
- 2.13Conceptual Model or Summary Diagram
Chapter THREE
RESEARCH METHODOLOGY
- 1.
- 3.1Research Design: Field Quasi-Experimental Approach in Economics Courses
- 2.
- 3.2Philosophical Paradigm: Pragmatism and Mixed Methods Rationale
- 3.
- 3.3Population of the Study: Undergraduate Economics Programs
- 4.
- 3.4Sample Size and Sampling Technique: Stratified Random Sampling
- 5.
- 3.5Data Sources: Learner Surveys, Exam Scores, and Classroom Observations
- 6.
- 3.6Instruments of Data Collection: Validated Questionnaires and rubrics
- 7.
- 3.7Validity and Reliability of Instruments: Pilot Testing and Cronbach’s Alpha
- 8.
- 3.8Data Collection Procedures: Scheduling, Consent, and Ethics
- 9.
- 3.9Data Analysis Methods: Descriptive, Inferential, and Effect Size Computations
- 10.
- 3.10Model Specification: Difference-in-Differences and Regression Models
- 11.
- 3.11Ethical Considerations: Informed Consent and Data Confidentiality
Chapter FOUR
DATA PRESENTATION AND ANALYSIS
- ANALYSIS AND DISCUSSION
- 1.
- 4.1Data Presentation Plan: Structure and Coding Schemes
- 2.
- 4.2Descriptive Analysis of Participant Demographics and Baseline Measures
- 3.
- 4.3Descriptive Analytics of Engagement and Interaction Metrics
- 4.
- 4.4Hypotheses Testing: FLIPPED vs. TRADITIONAL on Learning Outcomes
- 5.
- 4.5Performance-Outcome Analysis: Economics Test Scores and Mastery Levels
- 6.
- 4.6Attitudinal and Motivation Differences Between Groups
- 7.
- 4.7Classroom Observation Findings and Instructional Process Feedback
- 8.
- 4.8Interpretation of Results and Alignment with Theoretical Framework
Chapter FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
- CONCLUSION AND RECOMMENDATIONS
- 1.
- 5.1Summary of Key Findings
- 2.
- 5.2Conclusions Regarding the Impact of Flipped Classrooms
- 3.
- 5.3Contributions to Knowledge in Economics Education
- 4.
- 5.4Practical Implications for Curriculum Design and Teaching
- 5.
- 5.5Recommendations for Practice and Policy in Undergraduate Economics
- 6.
- 5.6Limitations and Delimitations of the Study
- 7.
- 5.7Suggestions for Further Research in Flipped Economics Education
Thesis Abstract
The study investigates how flipped classroom pedagogy influences economics learning outcomes among undergraduate students across three public universities in a mid-sized country, addressing concerns about traditional lecture-centric delivery and the growing adoption of active learning modalities in economics education. The aim is to determine whether flipped classrooms improve performance, engagement, and self-regulated learning, and to identify contextual factors that modulate these effects. Specific objectives include (1) comparing final course grades and standardized assessment scores between flipped and traditional sections, (2) examining differences in knowledge retention after eight weeks, (3) assessing changes in student engagement, motivation, and self-regulated learning strategies, (4) exploring instructors’ implementation fidelity and perceived instructional value, and (5) evaluating differential effects by gender, prior achievement, and course level (Introduction to Microeconomics, Macroeconomics, and Econometrics). The study is underpinned by Constructivist Learning Theory and Self-Determination Theory to explain how active, student-centered environments support conceptual understanding and autonomous motivation. A mixed-methods research design is employed, combining a quasi-experimental field trial with qualitative process evaluation. The population comprises 1,200 undergraduate economics students enrolled in designated core courses during the 2024/2025 academic year. A stratified random sampling approach selects 12 course sections (6 flipped, 6 traditional), with a total anticipated sample of 720 students (approximately 60 students per section). Data collection instruments include (i) objective achievement measures such as end-of-term course grades, standardized economics concept tests (reliable at Cronbach’s alpha ?0.85), and a 6-week retention assessment; (ii) validated engagement and motivation scales (e.g., the Situational Interest Scale and the Academic Motivation Scale); (iii) a self-regulated learning inventory (e.g., the Motivated Strategies for Learning Questionnaire); (iv) instructor fidelity checklists and a structured interview protocol for qualitative insights; and (v) course analytics capturing online pre-lesson warm-ups, video-viewing metrics, and post-lesson assessment performance. Reliability and validity are ensured through pre-testing, triangulation, and pilot testing of instruments in two non-participating sections. Quantitative analysis employs multilevel hierarchical linear modeling to assess differences in outcomes between flipped and traditional sections while controlling for prior achievement, gender, and course type, with robustness checks via propensity score matching. Mediation analysis investigates whether engagement and self-regulated learning mediate the impact of pedagogy on achievement. Retention outcomes are analyzed using repeated-measures ANOVA. Qualitative data from instructor reflections and student focus groups are analyzed thematically using an inductive approach, with coding reliability established through intercoder agreement (Cohen’s kappa ?0.80). A convergent parallel mixed-methods framework integrates quantitative and qualitative findings at the interpretation stage to provide a comprehensive understanding of context-specific effects and implementation fidelity. Key expected findings include statistically significant improvements in final grades and retention scores for flipped-classroom sections relative to traditional ones, moderated by prior achievement and course type. Increased student engagement, higher intrinsic motivation, and more frequent use of self-regulated learning strategies are anticipated in flipped settings, with fidelity of implementation positively correlated with effect sizes. The study may reveal differential effects across courses, with larger gains in Econometrics due to higher cognitive demand and in macroeconomic courses where complex models benefit from segmented, active learning activities. Instructors’ perceived value of flipped pedagogy is expected to align with observed outcomes when there is structured pre-class preparation and timely feedback. The study contributes to knowledge by providing rigorous field-based evidence on the effectiveness of flipped classrooms in undergraduate economics, elucidating the mechanisms through which engagement and self-regulation mediate learning gains, and offering practical guidance on implementation fidelity and course design. It informs policymakers and curriculum designers about scalable strategies to improve learning outcomes in economics education. The main conclusion anticipated is that well-structured flipped classrooms, underpinned by clear learning objectives and high-fidelity implementation, yield meaningful improvements in achievement and retention, with benefits most pronounced for students with moderate prior achievement. Recommendations include adopting standardized pre-class materials, continuous instructor training, iterative fidelity monitoring, and course-specific adaptations to maximize impact across economics disciplines.
Thesis Overview
This research investigates whether flipping economics classrooms—where students study core content online before class and use in-class time for discussion, problem-solving, and applied activities—improves undergraduate learning outcomes compared with traditional lectures. It matters because economics is conceptually cumulative and often challenging; if flipped classrooms can enhance understanding, engagement, and performance, universities could improve student success and reduce dropout risk.
The study addresses gaps in knowledge about practical, scalable applications of the flipped model in economics courses at the undergraduate level. While some small studies suggest benefits, there is a need for robust field evidence across multiple courses and institutions, using rigorous designs and standard measures of learning outcomes.
What the researcher will do step by step
- Design: adopt a quasi-experimental field study across three undergraduate economics courses (e.g., Principles of Microeconomics, Macroeconomics, and Econometrics) with comparable sections assigned to flipped versus traditional formats for a full semester.
- Population and sample: target undergraduate economics majors; expect about 600 students total, with roughly 300 in flipped sections and 300 in traditional sections.
- Data collection instruments: end-of-course exams to measure learning outcomes, course grades, and standardized concept inventories; student engagement surveys and motivation scales; and classroom observations using a structured rubric to assess quality of in-class activities.
- Data collection process: administer pre-tests at course start to establish baseline, collect mid-semester progress indicators, and conduct final assessments at term end; gather survey responses after pivotal modules.
- Data analysis: compare learning outcomes using ANCOVA controlling for prior achievement; analyze attitude and engagement data with multiple regression; examine in-class interaction quality through observational data; triangulate findings across courses.
- Validity and reliability: pilot instruments, ensure inter-rater reliability for observations, and test internal consistency for surveys.
- Ethical considerations: obtain informed consent, protect confidentiality, and secure institutional approvals.
Expected contribution and outcomes
- The study aims to provide robust field evidence on the effectiveness of flipped classrooms in economics education, clarifying effect sizes and identifying course conditions that maximize impact.
- It will inform teaching practice, curriculum design, and policy decisions about scalable innovations in undergraduate economics instruction.
Potential limitations
- Non-random assignment may introduce selection bias; results will be interpreted with caution and supplemented by qualitative insights.