AI-Enhanced Think-Pair-Share: A Learning Analytics Approach to Foster Linguistic Creative Thinking and Collaborative Learning
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| 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 |
| 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 |
| 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. |
|---|---|
| ISSN: | 1929-7750 |
