MSc in Evidence-Based Social Intervention and Policy Evaluation

at University of Oxford

The MSc has five major components:
 

• core course on evaluation methods

• pathway course, either Social Intervention or Policy Evaluation

• specialist option, eg Children and Families, Social Policies and Health Inequalities, or Community Analysis and Large-Scale Interventions

• research methods training (Quantitative and Qualitative Methods, R-Programming, Systematic Reviews)

• MSc thesis.

During the first and second terms, the majority of learning is classroom-based, complemented by independent reading, tutorials, and formative and summative assessments. The third term involves largely self-directed study for remaining summative assessments, exam/assessment revision, and further development of the MSc thesis; additional lectures and question/answer are typically offered on an optional basis to support students in preparing for exams/assessments and using various methodologies for thesis projects.

Core course in evaluation methods

This course, taken over two terms, trains students to critically consume and produce evaluation research for policies and social interventions, focusing on multiple methods, including randomised controlled trials and quasi-randomised methods, qualitative evaluation and systematic review methods. The course has a strong focus on ‘open science’ and research transparency.

Pathway course

You will select one of two available pathways, to be taken over two terms. Whichever pathway you take, you will write a thesis on a topic agreed with your supervisor. The thesis is undertaken throughout the duration of the course. 

The two pathways are:
 

• Social Intervention, covering evidence-based methods to evaluate social interventions, theories underlying interventions, ethical issues, and applying research in practice and policy, including the challenges of implementing programmes in the real world; or

• Policy Evaluation, introducing you to social policy analysis, policy formation, and the relationship between evidence and policy, and to different research methods for evaluating policies, eg quasi- experimental designs, natural experiments.

You may be able to change your choice of pathway in the first week of the programme.

Specialist options

You will take a one-term specialist courses from a list of options which may include Children and Families, Social Policies and Health Inequalities, Community Analysis and Large-Scale Interventions.

MSc students may attend advanced methods classes, such as Intermediate Statistics, in their second term.

Research methods training

Students following the social intervention or policy evaluation pathway take a core evaluation methods course. In addition, all students in the MSc EBSIPE take the following methods courses:
 

• systematic reviews, quantitative, qualitative and mixed methods, ie to learn to synthesise the best available evidence (2 terms)

• quantitative methods, ie key statistical concepts and application in the leading software, R (1 term)

• qualitative research methods, ie design, data collection, analysis and qualitative meta-synthesis (1 term)

• field methods, ie managing, costing and running real-world evaluations.

Proven and potential academic excellence

Degree-level qualifications

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:
 

• a first-class or strong upper second-class undergraduate degree with honours.

For applicants with a degree from the USA, a bachelor’s degree with a minimum overall GPA of 3.5 out of 4.0, or 4.0 out of 5.0 is sought.

There is no requirement on subject area and students from a wide range of disciplinary backgrounds are considered.

GRE General Test scores

No Graduate Record Examination (GRE) or GMAT scores are sought.

Further guidance
 

• Quantitative methods and statistics: Prior training in statistics or quantitative research methods is not a requirement. However, a large component of the course is training in quantitative methods; this entails both statistics and statistical programming in R. All modules start at an introductory level; however, students benefit strongly from familiarising themselves with basic statistical concepts, e.g., correlation, least square regressions and statistical significance. It is essential that students familiarise themselves with the R programming language and RStudio software before starting the course. The summer pre-course reading list will make recommendations for open-source self-study materials.

• Publications: Publications are not expected.

English language proficiency

Minimum scores required to meet the University's higher level requirement

IELTS Academic

 7.5  

TOEFL iBT, including the 'Home Edition'

110

Home    
£19,950

Overseas    
£30,910

Recent graduates from the Master’s programme have gone on to study for doctorates in a range of high quality universities. Many graduates go on to pursue academic careers in world-leading research universities, while others hold influential positions in government, non-governmental and international organisations, such as the World Bank, J-PAL, World Health Organisation and UN agencies.