Teacher Readiness and Challenges in AI-Based Geometry Learning: A Phenomenological Study

Cheisar Ranggayanan; Evy Lalan Langi; Suri Toding Lembang

doi:10.35445/alishlah.v18i2.8987

Teacher Readiness and Challenges in AI-Based Geometry Learning: A Phenomenological Study

Cheisar Ranggayanan, Evy Lalan Langi, Suri Toding Lembang

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology in mathematics education by supporting adaptive learning, interactive visualization, and personalized instruction. Although numerous studies have examined the effectiveness of AI in improving students’ mathematical achievement, limited attention has been given to teachers’ readiness to integrate AI into geometry learning, particularly in semi-urban educational contexts. This study aimed to explore junior high school mathematics teachers’ perceptions, readiness, challenges, and expectations regarding the implementation of AI-based geometry learning.This study employed a qualitative phenomenological approach involving 15 junior high school mathematics teachers from Tana Toraja Regency, Indonesia, selected through purposive sampling. Data were collected using semi-structured interviews, non-participant observations, and document analysis. The data were analyzed thematically through open coding, axial coding, category development, and theme identification, supported by NVivo 15. Credibility was enhanced through source and method triangulation, member checking, and audit trails.Four major themes emerged: positive perceptions of AI integration, varying levels of teacher readiness, infrastructural and competency-related challenges, and expectations for institutional support and continuous professional development. Teachers recognized AI as a valuable tool for enhancing students’ spatial visualization, conceptual understanding, and engagement in geometry learning. However, inadequate digital infrastructure, limited AI literacy, insufficient professional training, and concerns regarding reduced human interaction and data privacy constrained effective implementation.The findings indicate that successful AI integration in geometry learning depends on the interaction between teachers’ pedagogical readiness, technological competence, institutional support, and educational policy. This study contributes to the discourse on AI in mathematics education by extending understanding of teacher readiness in semi-urban contexts and providing practical recommendations for sustainable professional development, infrastructure improvement, and context-sensitive AI integration in secondary education.

Keywords

artificial intelligence in education; geometry learning; teacher readiness; mathematics education

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DOI: https://doi.org/10.35445/alishlah.v18i2.8987