State and local education leaders are grappling with the challenge of meeting the professional learning needs of educators amid a rapidly evolving technological landscape and uncertain funding. As new tools powered by artificial intelligence (AI) continue to emerge, the pressure to adapt has intensified. A recent fictional case study highlights this struggle: an enthusiastic educator named Sasha, who found herself overwhelmed by the constant influx of AI tools after attending a webinar titled “Using Generative AI to Save Time on Lesson Planning.” Despite her initial excitement, she was unable to translate the insights from the workshop into her classroom practices due to a lack of ongoing support.
This fictional account reflects a broader national issue addressed in a new guide from the State Educational Technology Directors Association (SETDA), titled Improving Professional Learning Systems to Better Support Today’s Educators: How Title II, Part A Offers a Model for State and Local Leadership. Published in collaboration with FullScale, ISTE+ASCD, and Learning Forward, the guide outlines evidence-based strategies aimed at enhancing professional learning systems, especially in light of increasing expectations around AI integration in education.
To assess the current landscape, SETDA conducted a national survey and organized focus groups with education leaders. The findings revealed four systemic issues that hinder effective professional development. First, there is a lack of shared definitions for tech-integrated instruction across states and districts, leading to inconsistent training that often prioritizes vendor availability over meaningful instructional goals. Second, funding is frequently directed towards short-term training, focusing on specific platforms without fostering long-term educator capacity. Third, states and districts tend to monitor participation rather than improvement, failing to collect data that reflect real instructional change. Finally, while pockets of excellence exist, there is a deficiency in the structures needed to scale successful models.
These challenges are magnified by the rapid proliferation of AI tools, as educators increasingly seek clarity and support in integrating these technologies into their teaching. Without systemic changes to support professional learning, many educators risk falling into a cycle of brief workshops leading to uncertainty, ultimately hindering their effectiveness in the classroom.
To combat these issues, the SETDA guide proposes six actionable steps for education agencies. First, leaders should publish and communicate a shared statewide vision for high-quality, tech-integrated instruction that aligns with established frameworks. This vision can help standardize expectations and provide a common instructional anchor for funded activities. Second, agencies should align funding around these priorities, utilizing braided budgets to support multiyear professional learning pathways rather than individual workshops.
Third, monitoring and compliance should be reframed as opportunities for improvement. For example, the Wyoming Innovator Network encourages districts to submit artifacts like lesson plans and student work to provide insights into implementation, focusing on strengthening practices rather than punitive compliance. Fourth, education leaders must prioritize durable professional learning models that emphasize coaching and collaborative learning over one-off sessions.
Moreover, elevating ed-tech leadership and fostering cross-functional decision-making can help ensure that technology purchases and professional learning plans align with instructional priorities. The experience of Claremont Unified in California illustrates the benefits of such collaboration. Lastly, documenting and scaling what works is essential; by sharing successful practices, state leaders can foster collaboration and ensure high-quality resources are accessible to all educators.
As educational institutions grapple with the implications of AI, recent survey data from Education Week indicates that while exposure to AI training is on the rise, it largely consists of isolated sessions rather than sustained, job-embedded professional learning. Education leaders are thus confronted with a critical question: How can they transform the current interest in AI and emerging educational technologies into meaningful, equitable improvements in teaching and learning? The SETDA guide serves as a resource for building modern professional learning systems that meet the demands of today’s classrooms and effectively integrate AI into educational practices.
For further insights, the full guide is available for download.
See also
AI Research in STEM Education Overlooks Student Development, New Study Reveals
AI Use in UK Law Education Surges 88% for Assessments, Raising Competence Concerns
K-12 Leaders Must Make 5 Key Moves to Effectively Integrate AI in Schools
