Module: Applying Quantitative Approaches to Educational Research

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Applying Quantitative Approaches to Educational Research
Module Code	EDU1060 (ITS: IE603)
Faculty	Policy & Professional Practice	School	DCU Institute of Education
NFQ level	9	Credit Rating	5

Description

This module focuses on the rationale for, and application of, quantitative methodology to research problems in education. It challenges students to interrogate the epistemological and ontological principles underpinning quantitative research and the implications of adopting a positivist world view for one's research. Popular designs, (randomised control trials, pre-experimental, experimental, quasi-experimental, correlational, cohort...) and strategies (surveys, interventions, repeated measures....), and the strengths, limitations and challenges of each, are addressed. Students are encouraged to examine the applicability of the various options to their research in the context of their existing knowledge and skills and personal/professional commitments, interests and ambitions.

Learning Outcomes

1. Evaluate one's philosophical stance/world view and the extent to which this 'fits with' the quantitative approach, in general, and the specific methodologies and strategies used in his/her research study
2. Explain and craft appropriate and informed responses to key issues in quantitative inquiry (Sample size; sampling frames, random assignment. Selection of appropriate statistical tests; interpretation - significant, power, inferences etc; error, internal and external threats to validity and the objective stance of the researcher)
3. Code and input quantitative data correctly and efficiently
4. Analyse, interpret and report accurately and appropriately the findings of quantitative inquiry
5. Craft a workable project plan for a potential quantitative methods research project
6. Consider and reflect on ethical issues in quantitative research

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	10	Active engagement in class and group-based discussion and critique of course content.
Laboratory	10	Sessions using SPSS
Online activity	25	Participation in synchronous and/or asynchronous online classes. Discussion and/or critical review of relevant research recommended by the tutor(s).
Independent Study	40	Reading and critical review of literature relevant to the module.
Assignment Completion	40	Quantitative Methods Research Plan. Oral presentation and defence of research plan
Total Workload: 125

Section Breakdown
CRN	10532	Part of Term	Semester 1
Coursework	0%	Examination Weight	0%
Grade Scale	PASS/FAIL	Pass Both Elements	Y
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Martin Brown	Module Teacher	Majella Mcsharry

Type	Description	% of total	Assessment Date
Assessment Breakdown
Assignment	Students are required to craft a workable Quantitative Methods Research plan for their research that maps the anticipated actions and decisions that will have to be made (or have already been made) at critical junctures on their research journey. The research plan will include the following items: 1. Title 2. Introduction 3. Problem Statement 4. Purpose 5. Hypotheses 6. Definition of key terms 7. Methodology 8. Research design 9. Population and sampling plan 10. Data collection procedures 11. Data analysis 12. Concluding statement (Significance and limitations) 13. References, Appendices	80%	n/a
Presentation	Oral Presentation and defence of research plan.	20%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

1
Identify, critique and interpret existing quantitative research studies in a potential research area - advanced literature searching including systematic reviews, meta-analysis

2
Quantitative data analysis: concepts and methods of relevance to practitioner research in education

3
Research Ethics: concepts, requirements and tools

4
Framing and operationalising a quantitative research question

5
Development of hypotheses (Null, research..., assumptions, predictions)

6
Study Variables: Independent, dependent and control; implications for data analysis

7
Develop (and critique existing) quantitative instruments (surveys, tests, scales, checklists)

8
Survey design, platforms and administration

9
Sampling (Probability and non-probability...)

10
Use SPSS (or equivalent) for data entry, preparation and analysis (Coding, entering, cleaning manually)

11
Use SPSS (or equivalent) for data analysis using parametric and non-parametric techniques (Selecting appropriate tests, describing trends, comparing groups, relating variables, correlations)

12
Interpreting and reporting results (significance levels, one/two tailed, effect sizes, magnitude)

13
Validity, reliability, generalisability, threats, error

14
Development of a quantitative methods research plan

Indicative Reading List

Books:

Cox, J. and Cox, K.B: 2008, Your opinion, please! How to build the best questionnaires in the field of education, Corwin Press, London,
Floyd, J. and Fowler, J.: 2008, Survey Research Methods. Applied Social Research Methods, Sage, London,
Hancock, G.R., Mueller, R.O. and Stapleton, L.M: 2010, The reviewer’s guide to quantitative methods in the social sciences, Sage, London,
Hoy, W.K. and Adams, C.M.: 2015, Quantitative research in education: A primer., Sage, London,
Mujis,D.: 2011, Doing Quantitative Research in Education with SPSS, 2nd, Sage, London,
Rubin, A.: 2012, Statistics for evidence-based practice and evaluation, Cengage Learning, MA,

Articles:

Campbell, C., & Levin, B.: 2009, Using data to support educational improvement. Educational Assessment, Accountability, and Evaluation, Educational Assessment, Accountability, and Evaluation, 21(1), 47–65, 27659
2008: Resolving the 50-year debate around using and misusing Likert scales, Medical Education, 42, 1150-1152, 27660, 1
Research on data use: A framework and analysis: Measurement, 9, 173-206, 27661, 1, Farrell, C.
Educational Administration Quarterly: 51(3), 438-471, 27662, 1, Schildkamp, K., Poortman, C., Luyten, H. and Ebbeler, J., 2017
28(2), 242-258: 27663, 1, Schildkamp, K., & Kuiper, W., 2010, Data informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education
27664: 1, Tavakol, M. and Dennick, R., 2011, Making sense of Cronbach's alpha, International journal of medical education, 2, 53,
1: Vaughan, T., Deeble, M. and Bush, J., 2017, Evidence-informed decision making, Australian Educational Leader, 39(4), 32,

Other Resources

Annotated Reading List: Reading list prepared for the EdD modules, Research Methods 1 and 2,