EDUC41320 Advanced Research Methods 2(Quantitative)

Academic Year 2023/2024

The aim of the module is to familiarise students with the key principles of quantitative research and enable them to gain a critical understanding of the assumptions, strengths and limitations of such research. Students will develop their quantitative analysis skills, applying multivariate analysis techniques including multiple regression within SPSS, and mediation and moderation analyses within the PROCESS macro.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should be able to:
1. describe, use and critically evaluate a range of approaches for collecting and analysing quantitative data;
2. demonstrate a thorough understanding of the issues involved in designing survey questionnaires and developing scales;
3. use SPSS to conduct statistical analyses and interpret results;
4. understand and apply the principles of univariate, bivariate and multivariate statistics for the purposes of quantitative analysis of data;
5. demonstrate a familiarity with advanced statistical techniques such as multiple linear and logistic regression, and mediation and moderation analysis;
6. show an awareness of the issues involved in conducting mixed-methods research in educational settings.

Student Effort Hours: 
Student Effort Type Hours


Seminar (or Webinar)


Specified Learning Activities


Autonomous Student Learning




Approaches to Teaching and Learning:
Online delivery through Brightspace. Students work independent through set activities each week. 
Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
EDUC41860 - Research Methods 2

Additional Information:
Students need to have completed Research Methods 2 or similar module which covers basic quantitative research design and analysis.

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Conduct and report on a multivariate analysis using either the module teaching dataset or another dataset of your choice Coursework (End of Trimester) n/a Graded No


Portfolio: Participation in class activities through discussion board posts Throughout the Trimester n/a Graded No


Carry forward of passed components
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Feedback on the assignment is provided at the end of the module. Feedback on set tasks is provided on an ongoing basis via discussion board

Name Role
Ms Aisling Davies Lecturer / Co-Lecturer
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.

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