| Title: |
Khanmigo in the Virtual Classroom: A Strategic Evaluation through SWOT and Acceptability Analysis |
| Language: |
English |
| Authors: |
Joel I. Alvarez (ORCID 0000-0002-2774-614X); Jermil R. Angeles (ORCID 0009-0008-4434-3220) |
| Source: |
Educational Process: International Journal. Article e2025272 2025 16. |
| Availability: |
UNIVERSITEPARK Limited. iTOWER Plaza (No61, 9th floor) Merkez Mh Akar Cd No3, Sisli, Istanbul, Turkey 34382. e-mail: editor@edupij.com; Web site: http://www.edupij.com/ |
| Peer Reviewed: |
Y |
| Page Count: |
27 |
| Publication Date: |
2025 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
Higher Education; Postsecondary Education |
| Descriptors: |
Artificial Intelligence; Technology Uses in Education; Feedback (Response); Personal Autonomy; Student Motivation; Access to Education; Ethics; Cultural Awareness; Foreign Countries; College Students; Student Attitudes |
| Geographic Terms: |
Philippines |
| ISSN: |
2147-0901; 2564-8020 |
| Abstract: |
Background/purpose: This study examines students' perspectives and acceptance of Khanmigo, an AI-driven educational platform, regarding personalized learning, diversity, and participation. As artificial intelligence becomes more integrated into educational settings, it is essential to comprehend students' perceptions and acceptance of these technologies. The main objective is to analyze how perceived strengths, shortcomings, and prospective opportunities affect students' readiness to embrace AI tools in educational environments. Materials/methods: A mixed-methods approach was utilized, including quantitative surveys and qualitative interviews to gather data from students. Quantitative data evaluated overall acceptance and particular attitudes towards AI-assisted learning, whilst qualitative data offered more profound insights into student experiences and apprehensions. Hierarchical regression analysis was employed to ascertain the predictive significance of students' attitudes regarding their acceptance of AI in education. Results: Quantitative results demonstrated a significant degree of acceptability for Khanmigo, with students valuing its capacity to improve comprehension, provide immediate feedback, and facilitate autonomous learning. Qualitative replies emphasized heightened motivation and access to varied educational materials while also expressing concerns over technical constraints, ethical dilemmas, and cultural sensitivity. Regression analysis demonstrated that perceived strengths, shortcomings, and opportunities strongly forecasted students' acceptance of AI in educational settings. Conclusion: The study indicates that successful integration of AI in education necessitates not just utilizing its technology benefits but also mitigating its limits through human monitoring and ethical principles. Future advancements must emphasize emotional intelligence, cultural sensitivity, and usability to enhance the educational advantages of AI while mitigating its disadvantages. |
| Abstractor: |
As Provided |
| Entry Date: |
2025 |
| Accession Number: |
EJ1483352 |
| Database: |
ERIC |