A scoping review of 146 studies reveals that while GenAI tools show promise in engineering and computing education, there is a critical need for more evidence-based research on their pedagogical implications beyond just studying perceptions and affordances.

Objective: The study aimed to analyze the implications of integrating Generative AI in engineering and computing education from K-12 to tertiary levels, focusing on empirical studies and educational practices.

Methods:

• Conducted a scoping review based on PRISMA-ScR guidelines
• Analyzed 146 studies from SCOPUS, Web of Science (WoS), and ERIC databases
• Used bibliometric analysis to examine trends in citations, authors, and research topics
• Employed qualitative coding to analyze educational features and outcomes
• Utilized software tools (VOSViewer and MAXQDA) for data analysis

Key Findings:

• Most studies (24 approved after screening) focused on computing education at the tertiary level
• ChatGPT was the most commonly used GenAI tool in educational settings
• Student-centered proposals dominated the research, with limited teacher-centered studies
• The majority of learning outcomes focused on cognitive domain rather than affective or behavioral domains
• Teachers reported moderate confidence levels in AI integration
• Studies showed both positive and negative perceptions from students and teachers regarding GenAI use
• AI literacy and prompt engineering emerged as crucial skills, though their relationship needs further exploration

Implications:

• Highlights the need for better integration of GenAI tools in educational curricula
• Emphasizes the importance of teacher training and support in GenAI implementation
• Suggests the need for clearer frameworks for AI literacy in educational contexts
• Demonstrates the potential of GenAI to enhance learning experiences when properly implemented
• Points to the necessity of developing evidence-based methodologies for GenAI integration

Limitations:

• Limited to specific databases and search terms
• Potential bias in analysis due to researchers' contexts and formation
• Possible exclusion of relevant studies in gray literature or other languages
• Time-bound nature of the review might have missed newer publications
• Focus primarily on English-language publications

Future Directions:

• Need for more research on cognitive styles in student-AI interaction
• Investigation of long-term impacts of GenAI in diverse educational settings
• Development of better conceptualization of AI literacy competencies
• More studies on teacher formation and pedagogical implementation
• Research on sociocultural contexts and identity aspects in GenAI usage

Title and Authors: "Generative AI in Engineering and Computing Education: A Scoping Review of Empirical Studies and Educational Practices" by Jonathan Álvarez Ariza, Milena Benitez Restrepo, and Carola Hernández Hernández

Published On: February 17, 2025 (Current date mentioned in article)

Published By: IEEE Access

This comprehensive review contributes significantly to understanding the current state of GenAI in engineering and computing education, while highlighting crucial areas needing attention for effective implementation of these technologies in educational settings.