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AI-Enhanced Think-Pair-Share: A Learning Analytics Approach to Foster Linguistic Creative Thinking and Collaborative Learning

Title: AI-Enhanced Think-Pair-Share: A Learning Analytics Approach to Foster Linguistic Creative Thinking and Collaborative Learning
Language: English
Authors: René Lobo-Quintero (ORCID 0000-0003-2989-5357)
Source: Journal of Learning Analytics. 2025 12(2):19-34.
Availability: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
Peer Reviewed: Y
Page Count: 16
Publication Date: 2025
Document Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Descriptors: Artificial Intelligence; Cooperative Learning; Creative Thinking; Undergraduate Students; Science Instruction; Learning Analytics; Technology Uses in Education; Educational Technology; Creativity; Writing (Composition); Writing Skills; Collaborative Writing
ISSN: 1929-7750
Abstract: This study investigates the integration of artificial intelligence into the Think-Pair-Share (TPS) methodology through a learning analytics lens. Using a mixed-methods quasi-experimental design (N=140), we examined how an AI-enhanced collaborative platform influences creative thinking among computer science undergraduates. The experimental group (n=80) utilized a Google Gemini-powered chatbot for scaffolding, while the control group (n=60) used a standard platform. Through comprehensive learning analytics, we identified optimal AI integration in moderate similarity ranges (0.3-0.7), achieved by 70% of participants. The experimental group demonstrated 30-37% productivity gains and 99% increase in thematic diversity, with moderate lexical standardization effects. Our findings provide empirical evidence for designing educational technologies that balance structured support with creative freedom in AI-enhanced collaborative learning.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1483355
Database: ERIC