Game-Changer or Hype? A Longitudinal Study of GenAI Opportunities, Challenges, and Teaching–Learning Activities

Despite widespread claims that Generative Artificial Intelligence (GenAI) will transform education, longitudinal empirical evidence on its pedagogical integration remains limited. This study examines how GenAI use shapes teaching and learning practices over time. Using a mixed methods longitudinal design, the study draws on 34 semi structured interviews conducted at two time points, six to eight months apart, with 17 secondary school teachers who independently adopted GenAI tools. The analysis was triangulated with 212 GenAI-supported teaching and learning activities. A theory-driven classification based on the SAMR framework was combined with inductive thematic analysis and quantitative pre-post comparisons. The findings, based on a thematic analysis of teacher discourse, reveal differentiated trends in opportunities and challenges. Opportunities related to fostering creativity increased over time, whereas efficiency, workload reduction, and teacher empowerment remained stable. Concerns regarding content quality and inherent biases showed a marginal increase, while references to prohibited or improper use declined. Regarding teaching and learning activities, a significant increase was observed in teaching-related uses of GenAI over time. In addition, a significant increase was identified at the Modification level, indicating a shift toward more advanced forms of pedagogical redesign, particularly through the development of personalized materials, AI-supported instructional planning, and adaptive feedback practices, while learning activities at higher levels remained comparatively stable. Taken together, these findings position the SAMR as a dynamic framework for examining longitudinal patterns of GenAI integration and suggest that GenAI currently accelerates instructional innovation more than it fundamentally restructures student learning paradigms.

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Publication Details

Journal
Education Sciences
Published
2026-05-08
DOI
https://doi.org/10.3390/educsci16050744
Primary Topic
Teaching and Learning Programming
Type
article
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article

Game-Changer or Hype? A Longitudinal Study of GenAI Opportunities, Challenges, and Teaching–Learning Activities

Ina Blau, Tamar Shamir-Inbal, Liron Levy-Nadav
Education Sciences
Teaching and Learning Programming
article

Game-Changer or Hype? A Longitudinal Study of GenAI Opportunities, Challenges, and Teaching–Learning Activities

Ina Blau, Tamar Shamir-Inbal, Liron Levy-Nadav
article en

Abstract

Despite widespread claims that Generative Artificial Intelligence (GenAI) will transform education, longitudinal empirical evidence on its pedagogical integration remains limited. This study examines how GenAI use shapes teaching and learning practices over time. Using a mixed methods longitudinal design, the study draws on 34 semi structured interviews conducted at two time points, six to eight months apart, with 17 secondary school teachers who independently adopted GenAI tools. The analysis was triangulated with 212 GenAI-supported teaching and learning activities. A theory-driven classification based on the SAMR framework was combined with inductive thematic analysis and quantitative pre-post comparisons. The findings, based on a thematic analysis of teacher discourse, reveal differentiated trends in opportunities and challenges. Opportunities related to fostering creativity increased over time, whereas efficiency, workload reduction, and teacher empowerment remained stable. Concerns regarding content quality and inherent biases showed a marginal increase, while references to prohibited or improper use declined. Regarding teaching and learning activities, a significant increase was observed in teaching-related uses of GenAI over time. In addition, a significant increase was identified at the Modification level, indicating a shift toward more advanced forms of pedagogical redesign, particularly through the development of personalized materials, AI-supported instructional planning, and adaptive feedback practices, while learning activities at higher levels remained comparatively stable. Taken together, these findings position the SAMR as a dynamic framework for examining longitudinal patterns of GenAI integration and suggest that GenAI currently accelerates instructional innovation more than it fundamentally restructures student learning paradigms.

Education SciencesVol. 16(5)
Open University of Israel (IL)
Openalex Percentile: Top 4%
Teaching and Learning Programming
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