Research Methods & Statistics in Education
Edition: 1
Copyright: 2023
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This textbook can be used in an introductory-level undergraduate or masters course in research methods and data analysis. The textbook explains the basic building blocks of a research study in easy to understand language and shows the application of each concept through several examples. Chapter 1 is dedicated towards writing a research study problem statement, purpose statement, research questions, hypotheses (null & research) which are explained through examples. The common terms used in research design, sampling, data collection and data analysis are defined to help the reader familiarize with language utilized in a research study. Chapter 2 on review of literature provides steps to find relevant research articles related to the problem and purpose statement as well as examples to summarize a quantitative and qualitative research article. The book is mainly focused on research designs (Chapter 3-quantitative and qualitative), sampling and data collection (chapter 4) and data analysis (Chapter 5-data visualization, descriptive and inferential statistical models: t-tests, ANOVA, regression and non-parametric models [chi-square, Mann-Whitney, and Wilcoxon test]). The exercises at the end of each chapter contain practice questions that are designed to test the reader's knowledge, comprehension, and application of the concepts. Knowledge check questions are provided within each chapter to assess the reader's understanding of the topic covered in subsections.
SPECIAL FEATURES:
1. The book contains over 100 research scenarios from different academic disciplines within social sciences within the 12 exercises which are practical and real-world examples that the reader can practice to test their comprehension on various aspects of research (e.g., variables, constructs, research design, sampling, data collection and analysis).
2. There are 15 worksheets which the reader can use to apply the concepts of constructs, variables, research design, sampling, data collection, and data analysis.
3. The book contains around 50 SPSS data sets at the end of chapter 5 which can be used as practice questions and/or homework assignments.
4. Hand calculations of t-test, ANOVA and simple regression models would help the reader to gain a deep appraisal and a solid foundation of the mechanics involved within each statistical model.
5. A list of references at the end of chapter 3 (research designs), chapter 4 (sampling and data collection), and chapter 5 (data analysis) to locate additional information on a specific topic.
6. An objective-based, cumulative quiz at the end of book which tests reader's knowledge on all the topics covered in each chapter.
7. A resource section at the end of the book on dissertation and scholarly writing as well as quantitative and qualitative research.
Chapter 1 Building Blocks of a Research Study
Definition of Research
Objectives of Research
General Kinds of Research
Frameworks
Theoretical Framework
Conceptual Framework
Process of Aligning a Research Study to a Theoretical Framework
Problem Statement
Purpose Statement
Research Questions
Hypothesis
Common Terms Used in Research Design
Common Terms Used in Sampling and Data Collection
Common Terms Used in Data Analysis
References
Exercises
Chapter 2 Review of Research Literature
Purpose/Objectives
Scope of Research Problem
Seeking New Lines of Inquiry
Avoid Fruitless Approaches
Seeking Support for Developing and/or Grounding Theory
Sources for Literature Review
Primary Sources
Secondary Sources
Steps in Review of Literature
Identify the Past Research Literature Relevant to the Study
Review Past Research Literature to the Study
Evaluate Similar Empirical Investigations
Summarize the Relevant Research Literature
Organize and Synthesize the Research Literature
Edit, Revise, and Refine Literature Review
Process of Conducting a Systematic Literature Review
Common Structure of Reviewing a Research Study
Examples of Research Article Summaries
Quantitative Research Article (The colors denote the specific aspect of research article.)
Mixed-Methods Research Article with a Qualitative and Quantitative Component:
Qualitative Article Summary-Based on Themes
References
Exercises
Chapter 3 Research Designs
Quantitative Research Design
Causal-Comparative Research
Randomized Experimental Research
Quasi-Experimental Research
Single-Subject Experimental Research
Correlational Research
Example Research Scenarios
Research Scenario 1: RCT Posttest Only Design
Research Scenario 2: RCT with Pre-test, Post-test with Control Group
Research Scenario 3: RCT Factorial Design
Research Scenario 4: RCT Block Design
Research Scenario 5: RCT Crossover, Repeated Measures
Research Scenario 6: QED without Control Group
Research Scenario 7: QED with Control Group but no Pre-Test
Research Scenario 8: QED with Control Group and Pre-Test
Research Scenario 9: Non-Equivalent Comparison Group
Research Scenario 10: Interrupted Time Series Design
Research Scenario 11: Regression Discontinuity Design
Qualitative Research Design
Phenomenology
Ethnography
Symbolic Interactionism and Grounded Theory
References
Reading Resources Kit on Ethnography
Reading Resources Kit on Grounded Theory
Reading Resources Kit on Symbolic Interactionism
Reading Resources Kit on Phenomenology
Reading Resource Kit for Quantitative and Qualitative Research Design
Exercises
Chapter 4 Sampling and Data Collection
Sampling Designs
Probability-Based Sampling Designs
Non-Probability-Based Sampling Designs
Examples of Sampling Designs
Constructs
Variables
Types of Variables
Validity and Reliability
Data Collection Methods
References
Reading Resources Kit for Sampling and Data Collection
Exercises
Chapter 5 Data Analysis
Descriptive Statistics
Inferential Statistics
Parametric Statistical Models
T-Test Statistical Model
One-Sample T-test
Independent Sample T-test
Dependent Sample T-test
Analysis of Variance (ANOVA) Statistical Model
One-Way ANOVA Model
Factorial ANOVA Model
Repeated Measures ANOVA Model
Correlation Statistical Model
Pearson Product Moment Correlation Coefficient
Assumptions of a Correlation Model
Covariance
Covariance Hand Calculation
Correlation Analysis in SPSS
Linear Regression Statistical Model
Simple Linear Regression Model
Multiple Linear Regression Model
Hierarchical or Stepwise Linear Regression Model
Non-Parametric Statistical Models
Commonly used Non-Parametric Tests
Chi-Square Analysis
Mann-Whitney Test
Kruskal–Wallis Test
Data Visualization
Reference
Reading Resources Kit for Data Analysis
Exercises
Worksheets
Cumulative Quiz
Resources
Appendices
Appendix A: T-Test Table
Appendix B: F-Test Table
Appendix C: Chi-Square Table
Parul Acharya holds a Ph.D. in Educational Statistics with emphasis on research methods, psychometrics, data analysis, and program evaluation from the University of Central Florida. She has a multi-disciplinary academic background with degrees in Health Science, Kinesiology, Business Administration, Logistics/Supply Chain Management, Educational Statistics, and Instructional Technology. She is currently working as an Associate Professor at Columbus State University, Columbus, Georgia in the College of Education and Health Professions. She teaches graduate-level courses in research methods, statistics, psychometrics, and program evaluation. She has served as a Chairperson and/or Research Methodologist in 32 completed doctoral dissertations. She has published 30 peer-reviewed publications. Parul has worked as a Principal Evaluator on research projects for the National Science Foundation (NSF) and the US Department of Education (USDOE). She regularly works on NSF and USDOE review panels as a subject matter expert of assessment and program evaluation. Parul currently holds leadership positions within the special interest groups and Divisions of American Educational Research Association (AERA). Her research interests include: Technological issues with online teaching and student learning; STEM/STEAM-based intervention studies; Perceived Behavioral Interventions and Supports (PBIS); Individual and Contextual factors that influence productive (e.g., organizational citizenship behaviors) and counter-productive behaviors (e.g., aggression) at work, Pre-K assessment issues; Program Evaluation; Psychometrics (Scale Development and Validation); State-based assessment scores (e.g., Milestone scores, CCRPI scores, growth percentile scores). In the past, Parul has worked in the Accountability, Assessment and Research Department in large school districts within the state of Florida as a Data and Program Evaluation Analyst.