The role of micro-credentials in the future digitalized AI-driven education

TL;DR

This paper analyzes the rising role of micro-credentials in digitalized, AI-driven higher education, highlighting their growth, significance, and potential policy implications through bibliometric network analysis.

Contribution

It provides a comprehensive bibliometric analysis of micro-credentials research, revealing trends, clusters, and insights to inform future educational strategies and policies.

Findings

Significant increase in micro-credentials publications from 1992 to 2024

Identification of key research clusters using bibliometric network analysis

Insights into the role of micro-credentials in digital and AI-driven education

Abstract

This paper focuses on assessing the potential of micro-credentials in digitalized higher education in the era of artificial intelligence. Micro-credentials are commonly described as mini qualifications or digital badges that certify an individual competency in a specific skill or cluster of skills. Being different from traditional academic credentials in both their granularity and focus, micro-credentials represent a new and exciting topic that is rapidly gaining popularity all around the world both within higher educational institutions, such as public and private universities, as well as within other education providers, such as non-governmental organizations and SMEs. The popularity of micro-credentials has been further enhanced by the recent COVID-19 pandemic which caused digital surge in higher education leading to many rapid technological innovations and changes that were unthinkable before. The rising interest in micro-credentialing can be best demonstrated by the increase of the number of scientific publications on this topic from just 1 in 1992 to 165 in 2024. The paper employs a comprehensive bibliometric network analysis using the terms micro-credentials based on a sample of 608 selected publications indexed in the Scopus database. It carries out the network cluster analysis using both text data as well as bibliometric data with the help of VOSviewer software. The results and outcomes of this research might be helpful for researchers, stakeholders, and policymakers in devising effective strategies and policies for transforming the future digitalized AI-driven higher education.