Systematic Literature Review & Meta-Analysis

About Course

This asynchronous learning experience is tailored for learners at all levels, from beginners to advanced researchers, who want to master systematic literature reviews (SLR) and meta-analysis. Designed by experienced scholars and authors of highly cited research articles, this course offers:

Cutting-edge methodologies to streamline your review and analysis process.
Hands-on training with tools and techniques for efficient, high-quality research output.
Comprehensive guidance to produce work suitable for publication in high-impact journals or inclusion in a PhD thesis.

The course features video lectures, live classes, interactive activities, and assessments. After each session, participants can submit their work for personalized feedback and guidance for improvement.

With eight interactive weekend live sessions, participants can connect with trainers in real-time, ensuring a collaborative and immersive learning experience. All lessons will be recorded and made available for flexible access.

Upon completion, participants will receive a Certificate of Completion from the Association of Professional Researchers and Academicians UK (APRA UK).

Course Content

Module 1: Fundamentals of Systematic Literature Review
• Understanding SLR concepts and methodologies. • PRISMA guidelines for systematic reviews. • Research question formulation and structuring. • Data search and extraction strategies using academic databases.

Introduction to The APRA Digital Learning Management System

03:46
Systematic literature review research article template Illustration

12:02
Systematic Literature Review & Meta-analysis Live session 1 Recording

01:14:07
Introduction to Systematic Literature Review & Meta-Analysis

11:06
Conceptualization Step1: Developing Research Question

13:20
Research Question Development using ChatGPT

13:12
Step 2: From Research Question to Keywords

09:14
Step 3: Search Strategy (PRISMA Framework)

17:53
How to use SCOPUS database for exporting records

17:07
Step 4: Microsoft Excel for Research Data Filtration & Descriptive Analysis

18:02

Module 3: Bibliometric Analysis
• Introduction to bibliometric analysis and its applications. • Using software like VOSviewer and Biblioshiny for citation analysis. • Network mapping and co-citation analysis. • Identifying trends, patterns, and research gaps.

Module 2: Literature Synthesis and Classification
• Thematic analysis of literature. • Categorizing and classifying research findings. • Developing conceptual frameworks from existing literature. • Tools for qualitative data analysis

Module 4: Introduction to Meta-Analysis
• Overview of meta-analysis: Purpose and significance. • Statistical methods for meta-analysis. • Data collection, coding, and preparation for meta-analysis. • Tools for meta-analysis • Interpreting and reporting results for publication.

About Course

What Will You Learn?

Course Content

Module 1: Fundamentals of Systematic Literature Review • Understanding SLR concepts and methodologies. • PRISMA guidelines for systematic reviews. • Research question formulation and structuring. • Data search and extraction strategies using academic databases.

Introduction to The APRA Digital Learning Management System

Systematic literature review research article template Illustration

Systematic Literature Review & Meta-analysis Live session 1 Recording

Introduction to Systematic Literature Review & Meta-Analysis

Conceptualization Step1: Developing Research Question

Research Question Development using ChatGPT

Step 2: From Research Question to Keywords

Step 3: Search Strategy (PRISMA Framework)

How to use SCOPUS database for exporting records

Step 4: Microsoft Excel for Research Data Filtration & Descriptive Analysis

Module 3: Bibliometric Analysis • Introduction to bibliometric analysis and its applications. • Using software like VOSviewer and Biblioshiny for citation analysis. • Network mapping and co-citation analysis. • Identifying trends, patterns, and research gaps.

Module 2: Literature Synthesis and Classification • Thematic analysis of literature. • Categorizing and classifying research findings. • Developing conceptual frameworks from existing literature. • Tools for qualitative data analysis

Module 4: Introduction to Meta-Analysis • Overview of meta-analysis: Purpose and significance. • Statistical methods for meta-analysis. • Data collection, coding, and preparation for meta-analysis. • Tools for meta-analysis • Interpreting and reporting results for publication.

Student Ratings & Reviews

Module 1: Fundamentals of Systematic Literature Review
• Understanding SLR concepts and methodologies. • PRISMA guidelines for systematic reviews. • Research question formulation and structuring. • Data search and extraction strategies using academic databases.

Module 3: Bibliometric Analysis
• Introduction to bibliometric analysis and its applications. • Using software like VOSviewer and Biblioshiny for citation analysis. • Network mapping and co-citation analysis. • Identifying trends, patterns, and research gaps.

Module 2: Literature Synthesis and Classification
• Thematic analysis of literature. • Categorizing and classifying research findings. • Developing conceptual frameworks from existing literature. • Tools for qualitative data analysis

Module 4: Introduction to Meta-Analysis
• Overview of meta-analysis: Purpose and significance. • Statistical methods for meta-analysis. • Data collection, coding, and preparation for meta-analysis. • Tools for meta-analysis • Interpreting and reporting results for publication.