Maayan Shay Sayag, Ina Blau, Orit Avidov-Ungar E55 73.6% of Enactment with Students activities (39 of 53) achieved Modification or Redefinition levels, compared to only 18.4% of Design of Learning Materials activities (16 of 87). Table 3 presents this distribution. Table 3. Distribution of Activities by Integration Level and SAMR Level Implementation Level Substitution Augmentation Modification Redefinition Total Future Planning 0 15 18 8 41 Design of Learning Materials 15 56 12 4 87 Enactment with Students 2 12 32 7 53 Total 17 83 62 19 181 The pattern is striking: 73.6% of Enactment with Students activities (39 out of 53) achieved Modification or Redefinition levels, compared to only 18.4% of Design of Learning Materials activities (16 out of 87). Conversely, 81.6% of Design activities remained at Substitution or Augmentation levels. This dramatic difference suggests that direct student engagement serves as the mechanism enabling progression to transformative integration levels. The finding extends research showing that most GenAI activities concentrate at Augmentation levels (Shamir Inbal et al., 2024; Jiménez-García et al., 2024) by identifying the specific factor - student-facing integration that enables movement beyond enhancement. The difficulty teachers face in translating AI capabilities into pedagogically sound integration (Ding et al., 2024; Kong & Yang, 2024) may stem not from insufficient technical knowledge but from inadequate transition from teacher-centered design to student-centered enactment. The transformative potential of GenAI manifests most fully when students directly interact with AI tools in authentic learning contexts. While the aggregate analysis identified integration level as the key factor driving transformative integration, this pattern masks considerable individual variance. The 73.6% success rate for studentfacing activities represents an average that obscures different trajectories among teachers. Understanding what enables some teachers to successfully transition to integration with students while others face persistent barriers, warrants further investigation. Conclusions This study examined GenAI integration patterns among high-school teachers following formal TPD, analyzing how integration levels manifest across pedagogical domains and what factors are associated with different SAMR levels. Analysis of 181 documented activities across two interview rounds revealed two key findings. First, GenAI integration varied substantially across pedagogical domains, with Teaching activities concentrating at Augmentation levels while Learning activities, where students directly engaged with AI tools, concentrated at Modification levels. Second, while temporal progression alone did not significantly impact integration levels, the level of integration emerged as the critical differentiating factor. Activities involving direct student engagement achieved transformative integration levels at substantially higher rates than teacher-centered design activities. Theoretically, this study extends the SAMR framework by identifying implementation approach as a critical factor in technology integration. The findings suggest that transformative integration depends not merely on tool capabilities or temporal familiarity, but on the pedagogical approach to integration, specifically, the degree of direct student engagement with AI tools. This challenges
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