Research Goals for the Department of Education
– Conduct rigorous and ethical studies that can contribute to ongoing discussions around the nature and mission of education
– Conduct rigorous and ethical studies that can have practical implications for policymakers, curriculum developers, and practitioners at a national and international level
– Disseminate the knowledge produced through peer-reviewed journals, conferences, and symposia.
The faculty of the Department of Education of the UCY employs a variety of methodological approaches, both quantitative and qualitative, to answer their research inquiries. With respect to quantitative methods, the faculty uses both basic approaches (e.g., exploratory factor analysis, ANOVA, regression analysis, etc), as well as more advanced statistical approaches and techniques, such as multilevel modeling, IRT models, structuring equation models, and the Generalizability-theory framework. With respect to qualitative research, the faculty employs different research strategies (e.g., ethnography, phenomenology, grounded theory, biographical research and action and applied research) and uses a variety of data collection methods (e.g., in-depth interviews, observations, and documentary analysis). In addition to these quantitative and qualitative approaches, faculty members are also using mixed method approaches both at the research design and the data collection and analysis levels. Finally, faculty members are using meta-analytic approaches to synthesize quantitative research findings and conduct secondary analyses of international comparative studies.
The Department of Education offers a compulsory research course for undergraduate students that covers issues including research design, and the use of basic quantitative and qualitative methods for addressing the research questions posed. At the graduate level, the Department offers a variety of courses for Master and Ph.D. students, such as discourse analysis (EDU 520), Qualitative Research in Education (EDU 682), the use of univariate and multivariate statistical techniques for analyzing quantitative data (EDU 683), multilevel modeling techniques (EDU 780), and structural equation modeling (EDU 788).