This module aims to prepare students to use the concepts and methods of quantitative social science research to conduct research on educational issues. Students learn core techniques and concepts for designing and evaluating quantitative research, sophisticated statistical analysis techniques (including the use of one or more software packages such as SPSS, R, SAS, Stata, Amos, MPlus, and relevant Artificial Intelligence-based options), and how to write up quantitative analysis results. Through this module, students become critical consumers as well as producers of quantitative research. Building on insights acquired in EDS442 (Engaging with Educational Literature) and EDS443 (Educational Research: Theory and Practice) in Year 1 of the EdD programme, this module enables students to gain a comprehensive and deeper understanding of how to critically analyse, design, conduct, and evaluate quantitative research. This module prepares students for further honing their skills and understandings in EDS446 (Advanced Educational Research Studies) in Year 3 of the EdD programme, developing and conducting their thesis in Year 4 of the programme, and evaluating how they will become contributors to research and scholarship in their area of educational focus.
A. Evaluate the logical and statistical integrity of quantitative evidence to interrogate the relationship between theory and practice within professional educational contexts. B. Architect and justify quantitative research designs that translate educational challenges into testable theoretical frameworks to generate actionable systematic intelligence. C. Critically select and implement statistical analyses and validate data-driven outputs through rigorous auditing of analytical procedures to ensure findings meet technical and ethical standards. D. Independently produce quantitative outputs that synthesize empirical results into professional narratives and strategic recommendations to support data-informed decision-making and systemic educational improvement.
The teaching and learning strategy of this module is designed to progressively enhance student competencies as independent researchers. This competency-based approach ensures a transparent, step-by-step enhancement of skills, moving students from foundational understanding to advanced research leadership. This methodology is realized through the following four themes: 1. Research-Led Pedagogy The curriculum is fundamentally research-led, integrating advanced quantitative methodologies with the students' ongoing doctoral inquiries. Lectures provide the theoretical foundation, while interactive sessions guide students to analyze published research and interrogate evidence. This approach builds the critical skills necessary for the EdD thesis, preparing students to contribute original scholarship to their fields and publish for practitioner, policymaker, and research audiences. Students are strongly encouraged to build on the ideas and proposals from EDS442 and EDS443, utilizing them to advance their EDS444 projects. This ensures a progressive development of their research and practice as they move toward EDS446 and EDS501. 2. Research-Led Project-Based Learning (RLPBL) Learning is anchored in Research-Led Project-Based Learning, where students address authentic educational challenges from their professional workplaces. By designing research—such as action, observational, or participatory research—that translates these real-world issues into testable frameworks, students generate actionable institutional insights. This practical focus ensures that module outputs have immediate professional utility and foster systemic improvement in education. Students are strongly encouraged to either identify real-world educational challenges or design research-driven solutions for Center for Excellence (CoE) partners/other partners and initiatives at the Academy of Future Education. 3. AI-Empowered Learning and Literacy The module integrates an AI-empowered learning environment, utilizing Generative AI and a specialized AI Assistant/Agent to facilitate inquiry and formative feedback. Students engage in iterative "reasoning loops" with AI to refine research designs and audit data-driven outputs. This integration is specifically designed to enhance AI literacy, moving students beyond basic usage to the high-level critical competence required to ethically integrate AI tools into professional research contexts. 4. Blended Onsite and Online Delivery Teaching is delivered through a flexible, blended format that combines intensive onsite residence learning with synchronous and asynchronous online sessions. • Onsite Residencies: Focuses on high-impact interpersonal interaction, including field trips, peer group work, and intensive case study analysis. • Online Learning: Utilizes a flipped classroom model composed of synchronous dialogues, consultations, and group work, alongside asynchronous discussions and independent research. This multimodal delivery ensures deeper reflective opportunities and provides the personalized support necessary for doctoral-level professional development.