Systematic Review on Educational Recommender Systems Based on Competency (2020–2025)
This repository contains the complete materials, search strategies, screening data, and extraction files associated with the systematic review entitled:
"Sistemas de Recomendação de Recursos Educacionais Baseados em Competências: Uma Revisão Sistemática (2020–2025)"
The review follows the PRISMA 2020 guidelines and investigates techniques, evaluation methods, challenges, and impacts of competency-based educational recommender systems.
📌 Objective
To analyze empirical studies published between 2020 and 2025 that propose, implement, or evaluate educational recommender systems grounded in competency modeling.
🔎 Research Questions
The review is structured around the following research questions:
- RQ1: Which recommendation techniques and algorithms are used?
- RQ2: What pedagogical objectives guide these systems?
- RQ3: What types of data and metrics are used?
- RQ4: How is system effectiveness evaluated?
- RQ5: What impacts on learning and engagement are reported?
- RQ6: What implementation challenges are identified?
📚 Data Sources
Searches were conducted on May 20, 2025, in the following databases:
- IEEE Xplore
- ACM Digital Library
- Scopus
- ScienceDirect
- SpringerLink
Only peer-reviewed articles published in English between 2020 and 2025 were included.
🔍 Search Strategy
Search date: May 20, 2025
Search fields: Title, Abstract, and Keywords (when supported).
Filters applied:
- Publication years: 2020–2025
- Language: English
- Document type: Peer-reviewed journal and conference papers
Core Boolean String
("recommen* system" OR "recommen* model" OR "digital content" OR "personalized feedback")
AND
("competenc*" OR "skill*" OR "adaptive learning")
AND
("Learning Analytics" OR "educational data mining")
Records Retrieved
- IEEE Xplore: 41
- ACM Digital Library: 50
- Scopus: 50
- ScienceDirect: 245
- SpringerLink: 249
Total records identified: 635
📂 Repository Structure
⚖️ Risk of Bias Assessment
A qualitative methodological assessment was conducted considering:
- Study design
- Presence of control group
- Sample size and characterization
- Evaluation transparency
- Reproducibility
🔓 Reproducibility and Transparency
This repository provides:
- Full search strings used in each database
- Raw export files from databases
- Screening decisions
- Full-text included in the review
- Risk of bias assessment
All materials are shared to ensure transparency and reproducibility in accordance with Open Science principles.
📄 Citation
If you use materials from this repository, please cite:
[Insert final citation after publication]
👥 Authors
Marcos Bião, Laercio Costa e Lais Salvador
📬 Contact
For questions or additional materials, please contact: