Introduction to Systematic Reviews - Online (join a waiting list)

Course Code


Organised by

NCRM, University of Southampton and Durham Research Methods Centre


Dr Nadia Siddiqui




Online run by University of Southampton and University of Durham


View in Google Maps  (SO17 1BJ)


Jacqui Thorp
Training and Capacity Building Co-Ordinator, National Centre for Research Methods, University of Southampton


A growing body of research evidence and readily available technology to tap a wide area of scientific research has given a lot of opportunities for researcher to conduct review-based inquiries adopting scientific principles and methods. This now demands all researchers to be able to search and synthesise research knowledge, adopting scientific principles of systematic, rigorous, and unbiased research. This one day course will introduce knowledge, understanding and skills that will enable students to overview the existing research knowledge in their own topic areas of interest. This introductory session will be a stage advanced from conducting ordinary literature review. Adopting a systematic approach of searching, synthesising, evaluating, and reporting existing research evidence will give students understanding of rigorous research designs and how this could be adopted for their own primary research projects.   

The course covers:

  • Research designs and its importance in research projects
  • Types of reviews in relation with research designs (e.g. mixed methods review, narrative review, scoping review etc.)
  • High quality research and principles of evaluating research
  • Bias in research studies
  • Criteria of judging research quality

By the end of the course participants will:

  • Methods for systematic search of existing studies
  • Establishing criteria for selecting and screening the studies
  • Controlling for bias
  • Assessment of different kinds of bias in SRs, e.g, publication bias
  • Data extraction of included studies
  •  Evaluating studies on criteria of rigorous research
  • Judging the quality of evidence
  • Synthesising and reporting the process and findings of review
  • Developing summaries of existing reviews

This course is open to all who want to acquire basic knowledge of systematic reviews in the area of social sciences, a basic knowledge of Microsoft Word and Excel packages is required. Participants will need a calculator to hand.

Preparatory Reading

Read resources available on this link : School of Education : Resources - Durham University

Conductingasystematicreview.pdf (

Torgerson, C., Hall, J. and Light, K., 2012. Systematic reviews. Research Methods and Methodologies in Education. London: Sage, pp.217-230.



Entry (no or almost no prior knowledge)


The fee per teaching day is: • £30 per day for students registered at UK/EU University. • £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions. • £100 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of its cancellation of a course, including but not limited to any travel or accommodation costs. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration


South East


Qualitative Data Handling and Data Analysis, Systematic reviews , , Searching scientific evidence , , Extracting data , , Data synthesis

Related publications and presentations

Qualitative Data Handling and Data Analysis

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