This course Advanced Educational Research & Statistics (Educ 302) is a graduate-level course designed to deepen learners' competencies in conceptualizing, designing, and managing educational research that meets high quality standards. The course provides a comprehensive exploration of advanced research paradigms, methodologies, and statistical applications relevant to education. Emphasis is placed on the development of research proposals aligned with institutional and national research agendas, the critical analysis of literature using AI-powered tools, and the application of quantitative, qualitative, and mixed-method approaches. Learners will also engage with sophisticated statistical techniques including Structural Equation Modeling (SEM), Partial Least Squares (PLS), and big data analytics for educational research. This course is practice-oriented, integrating real-world research challenges, ethical considerations, and publication strategies for high-impact dissemination. Through lectures, collaborative activities, and hands-on data analysis, students are expected to produce quality outputs such as research proposals, reviewed literature matrices, and statistical analysis reports suitable for publication and professional presentation.
Course Goals
1. To develop research projects aligned with institutional, regional, and national educational priorities.
2. To strengthen students’ competencies in designing methodologically rigorous and ethically sound educational research.
3. To apply advanced statistical and analytical techniques in investigating complex educational phenomena.
4. To integrate digital innovations and AI-powered tools throughout the research process for enhanced quality and efficiency.
5. To produce research outputs that inform educational policy, enhance practice, and contribute to scholarly discourse.
Course Learning Outcomes
1. Demonstrate an advanced understanding of research paradigms and theoretical foundations.
2. Build advanced knowledge and skills in educational research design and analytics.
3. Formulate researchable problems aligned with educational priorities.
4. Construct coherent conceptual and theoretical frameworks.
5. Conduct comprehensive literature reviews using AI and digital tools.
6. Apply appropriate quantitative, qualitative, and mixed methods research designs.
7. Utilize advanced statistical techniques in analyzing educational data.
8. Develop valid and reliable research instruments.
9. Prepare publishable research outputs for reputable academic journals.
10. Evaluate research proposals for funding and ethical compliance.
11. Translate research findings into actionable educational policies and practices.
Course Requirements
To successfully complete this course, students are expected to fulfill the following academic and performance-based requirements:
|
1. Full Attendance (100%) |
Active and consistent attendance in all sessions (face-to-face and online) is mandatory for full participation and performance monitoring. |
|
2. Timely Submission of Learning Tasks |
All worksheets, activity sheets, and academic outputs must be submitted on or before the prescribed deadlines. |
|
3. Active Class Participation |
Students are expected to participate in discussions, peer evaluations, collaborative tasks, and sharing of insights during synchronous and asynchronous sessions. |
|
4. Oral and Written Reports |
Assigned topics must be presented both orally and in writing, showcasing the student’s mastery, synthesis, and communication skills. |
|
5. Major Performance-Based Assessments |
Includes: • IMRaD-format Research Proposal • Oral Proposal Defense/Presentation • Written Exams and Comprehensive Assessments |
|
6. Use of Research Software Tools |
Required tools for data analysis and interpretation tasks. · SPSS v26 (https://www.ibm.com/support/pages/downloading-ibm-spss-statistics-26-end-support-30-sep-2025 ) § JASP (https://jasp-stats.org/ ) § JAMOVI (https://www.jamovi.org/ ) § Statistica (https://statistica.software.informer.com/ ) § |
Course Content and Structure
The course begins with an Orientation Session, which familiarizes students with the course overview, requirements, and expectations. Activities include output mapping, student socialization, and the submission of a Research Interest Survey. This is followed by Module 1 Foundations and Institutional Alignment of Research, where students explore the nature and scope of educational research, characteristics of effective researchers, ethical authorship, and institutional/national research priorities. Assessments in this module include reflective essays, ethical case reports, and alignment matrices. Module 2 Formulating Research Problems and Literature Gaps equips students with the skills to articulate problem statements, conduct gap analysis, and perform systematic literature reviews using the PRISMA framework. Learners are required to submit a comprehensive set of worksheets (1–11), a PRISMA table, and a draft of the literature review, all properly referenced using APA 7th edition. Module 3 Advanced Research Methodologies is delivered in both face-to-face and online modes. Students engage in philosophical and methodological discourses surrounding quantitative, qualitative, and mixed-method designs. Assignments include the submission of worksheets (12–16), a refined methods and materials section, and participation in a peer-reviewed write-up. A Midterm Exam is conducted to assess learning from Modules 1 to 3. In Module 4 Educational Statistics and Data Analytics, students are introduced to various statistical methods and modeling techniques including SEM, PLS, and factor analysis. The module emphasizes application through the use of SPSS, AMOS, or similar software, with analytical reports and interpretation papers as key outputs. Module 5 Proposal Writing and Scholarly Publication focuses on enhancing research outputs through bibliometric tools, academic phrase banks, and AI writing assistants. Students will draft their final research proposals, prepare for publication, and deliver a 3-Minute Thesis Challenge Video. The course culminates in the Final Examination and Output Submission, including oral and written evaluations of Modules 4 and 5, and submission of revised final proposals. Throughout the course, learning is assessed through a variety of strategies such as participation, essays, case reports, problem sets, methodology write-ups, software outputs, and oral presentations. The course ensures that students can independently design and implement rigorous educational research that aligns with institutional thrusts and global standards.
Learning Modalities, Instructional Strategies and Principle
This course employs a blended learning approach, integrating both online and face-to-face modalities to optimize learner engagement and flexibility. Online sessions are delivered through synchronous lectures, digital breakout activities, and guided self-paced tasks using learning management platforms. Face-to-face sessions emphasize interactive lectures, collaborative workshops, peer critiques, and hands-on application of research and statistical software tools. Instructional strategies include problem-based learning, guided research writing, peer assessment, case analysis, scaffolded worksheet completion, and the use of AI-enhanced tools for literature reviews and proposal development. Active learning is promoted through output-based assessments, formative feedback loops, and critical reflection activities that align with course objectives. These strategies ensure students not only gain theoretical knowledge but also develop practical research competencies anchored on institutional priorities and scholarly standards.
Anchored on the principles of adult learning and scholarly inquiry, this course is designed as a masterclass in advanced educational research, fostering deep engagement with theoretical, methodological, and analytical constructs. It follows the constructivist principle that learners build new knowledge upon prior academic and professional experiences, making learning contextual, purposeful, and transformative. The course embraces higher-order thinking, critical analysis, and research problem-solving as core tenets, emphasizing inquiry-based learning, self-directed exploration, and collaborative knowledge construction. Emphasis is placed on academic rigor, research ethics, and evidence-based reasoning, ensuring that students not only master complex research frameworks and statistical tools but also demonstrate scholarly independence and innovation in crafting proposals aligned with national and institutional agendas.