TY - JOUR
T1 - Transforming education with AI
T2 - A systematic review of ChatGPT's role in learning, academic practices, and institutional adoption
AU - Salih, Sayeed
AU - Husain, Omayma
AU - Hamdan, Mosab
AU - Abdelsalam, Samah
AU - Elshafie, Hashim
AU - Motwakel, Abdelwahed
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2025/3
Y1 - 2025/3
N2 - The integration of AI tools like ChatGPT into education has generated significant interest due to their potential to transform learning environments by providing personalized learning, automating tasks, and improving student engagement. However, gaps remain in the literature, particularly in comparing AI-supported education methods with traditional approaches and understanding ChatGPT's specific role in academic writing, literature reviews, and teacher development. This study addresses these gaps through a systematic literature review (SLR), evaluating the effectiveness of AI tools versus traditional teaching approaches. It focuses on ChatGPT's application in areas such as academic writing, lesson planning, student assessment, and the professional development of educators. Additionally, the study explores institutional strategies for balancing the benefits of AI with the need to maintain academic integrity and educational quality. The methodology involved a systematic search across academic databases with a structured analysis of key studies in AI-supported education. The main contributions include identifying the comparative advantages and limitations of AI in enhancing student learning, offering best practices for incorporating AI tools into teaching, and examining prompt engineering as a crucial factor in optimizing AI usage. The study reveals that ChatGPT and other AI tools significantly enhance educational efficiency and engagement, but they require careful management to prevent over-reliance. The study advocates for a balanced approach, integrating both AI and traditional methods to achieve optimal educational outcomes while maintaining academic integrity.
AB - The integration of AI tools like ChatGPT into education has generated significant interest due to their potential to transform learning environments by providing personalized learning, automating tasks, and improving student engagement. However, gaps remain in the literature, particularly in comparing AI-supported education methods with traditional approaches and understanding ChatGPT's specific role in academic writing, literature reviews, and teacher development. This study addresses these gaps through a systematic literature review (SLR), evaluating the effectiveness of AI tools versus traditional teaching approaches. It focuses on ChatGPT's application in areas such as academic writing, lesson planning, student assessment, and the professional development of educators. Additionally, the study explores institutional strategies for balancing the benefits of AI with the need to maintain academic integrity and educational quality. The methodology involved a systematic search across academic databases with a structured analysis of key studies in AI-supported education. The main contributions include identifying the comparative advantages and limitations of AI in enhancing student learning, offering best practices for incorporating AI tools into teaching, and examining prompt engineering as a crucial factor in optimizing AI usage. The study reveals that ChatGPT and other AI tools significantly enhance educational efficiency and engagement, but they require careful management to prevent over-reliance. The study advocates for a balanced approach, integrating both AI and traditional methods to achieve optimal educational outcomes while maintaining academic integrity.
KW - Academic writing
KW - Ai-supported education
KW - ChatGPT
KW - Generative AI
KW - Institutional policies
KW - Prompt engineering
KW - Teaching preparation
KW - Traditional teaching methods
UR - http://www.scopus.com/inward/record.url?scp=85213950375&partnerID=8YFLogxK
U2 - 10.1016/j.rineng.2024.103837
DO - 10.1016/j.rineng.2024.103837
M3 - Review article
AN - SCOPUS:85213950375
SN - 2590-1230
VL - 25
JO - Results in Engineering
JF - Results in Engineering
M1 - 103837
ER -