AI in inclusive education: teachers’ visions of future-oriented practices

Synthesis: Daniusevičiūtė-Brazaitė, Gaižiūnienė, and Pučėtaitė (2026) analyze fifty essays in which Lithuanian high school teachers imagined their own classroom in 2040, in a learning environment where AI tools are widely used. Rather than measuring technology acceptance or readiness, the study reads the essays as evidence of teachers' Learner Agency and futures thinking, asking how educators build probable futures from present conditions and preferable futures from professional values. Teachers expected personalized, adaptive support to strengthen inclusion, and rated that promise highly across personal efficiency, care for learners' needs, and contribution to a progressive society. At the same time, many worried that over-reliance on AI could fragment learning and weaken the critical skills they are responsible for building. The authors argue that these visions belong inside teacher competence, since teachers interpret, adapt, and negotiate what AI-driven inclusion will mean. The findings describe imagined futures and reported beliefs, not observed effects of AI on inclusive classrooms.

Key Findings

• Fifty Lithuanian high school teachers wrote essays imagining themselves teaching in 2040 in a learning environment where AI tools are widely used.
• Teachers expected AI to provide personalized assistants, adaptive tasks, and immersive simulations that respond to each learner's abilities, pace, and learning style.
• They rated AI's importance similarly highly for personal efficiency, for caring for learners' needs, and for contributing to a progressive and creative society (medians 10, 10, and 9).
• Concerns centered on over-reliance: AI could fragment learning and let students avoid thinking, hunting for answers instead of solving problems themselves.
• Ethical and governance issues such as algorithmic bias, transparency, data privacy, accountability, and human oversight were less salient than immediate classroom applications.
• Personal experience (median 9) shaped the envisioned future more than organizational culture (median 8), and business representatives and experts were rated as the most influential actors in driving change.

What the teachers imagined

Across the essays, the dominant image of 2040 was a classroom of personalized assistance: AI assistants and immersive simulation tools that adapt to each student's abilities, pace, and learning style, differentiating materials, offering alternative explanations, and adjusting tasks to a learner's level. Language teaching recurred as an example, with lessons that adjust immediately to the learner. One teacher imagined AI reading an online book aloud, explaining complex ideas, and then generating questions that push critical thinking, leaving the humanities and sciences accessible to anyone with an internet connection.

The same essays carried a counter-current. Teachers worried that dependence on AI tools could fragment learning, letting students gain information while losing the critical life skills that subjects are meant to build. One answer was blunt: the only thing learned through AI is AI. Others insisted that students should learn to use AI critically and verify its output, and that AI should support teachers' organizing work rather than take over instruction.

Futures thinking as teacher agency

The study reads the essays through markers of futures thinking rather than technology acceptance. Broadening markers were most often a wider range of actions, strategies, and solutions for addressing the future (24%), enhanced understanding of futures thinking (20%), and a broader range of approaches (18%). Under the approaching markers, 30% treated the future as more imaginable and less distant and 28% tied it to present realities and actions.

Structural skills, which align with probable futures extrapolated from current trends, were most often identifying causal relationships (22%) and differentiating problems, objectives, and solutions to organize plans (20%). Leading dynamical skills were moving between present realities and future possibilities (22%) and envisioning new possibilities with practical actions (18%), alongside a shift from single necessities to multiple options (18%), which connect to preferable futures grounded in values. Ethical and governance issues were less prominent than pedagogical ones, which the authors attribute to the data collection method.

What shaped the visions

Personal experience received the highest rating (median 9), followed by societal factors (median 9, wider spread), while organizational culture was rated significantly lower (median 8). Business representatives and experts were seen as the most influential actors in driving change (median 9), ahead of politicians (median 8) and students and parents (median 7).

Teachers' sense of their own role was more measured than their vision. They reported a moderate sense of Learner Agency to contribute to bringing the envisioned future about (M = 4.90, SD = 1.39) while agreeing that change would require active effort rather than arriving on its own (M = 5.88, SD = 1.58), and expressed high concern about the future of education (M = 6.00, SD = 1.15) while associating AI with progress rather than regression (M = 5.41, SD = 1.97).

What this means for practice

• The practitioner value of this study lies in what teachers' imagined futures reveal about their assumptions, not in evidence about what AI will do in inclusive classrooms.
• Because the essays describe desired 2040 scenarios rather than tested practice, they are best read as a prompt for reflection.
• Read against a school's own context, the visions suggest questions worth asking.
• Where would adaptive support actually reduce barriers for learners who currently receive only part of the support they need, and where would it widen the gap for students without reliable access?
• The essays also show that teachers want AI to carry organizing work while instruction and professional judgment stay with them, and that over-reliance is their central worry. That concern argues for teaching critical evaluation of AI output within subjects, rather than assuming learners will acquire it on their own. The futures-thinking markers matter for professional learning too: teachers who can already imagine several possible futures are better placed to treat AI as a choice to be negotiated with collective voice than as a change to be absorbed.

Limitations

• The study is interpretive rather than representative: fifty teachers completed the questionnaire out of 125 who agreed, and recruitment combined purposive and convenience sampling, so teachers already interested in AI or inclusion may be overrepresented.
• Written narratives allowed reflection but blocked follow-up questions, and responses of not sure were excluded as missing, leaving valid numbers of 43 to 47 in places.
• The Lithuanian setting gives these visions their shape.
• Since September 2024 the country has required general schools and kindergartens to admit children with special educational needs, yet a national audit reported that although 94% of pupils with special educational needs attended general schools in 2024 to 2025, 56% did not receive all the educational support required. That gap between formal inclusion and individualized support is the background against which teachers imagine AI helping, and against which the authors warn that existing inequalities in access and support could be reproduced rather than resolved.

Connected Concepts

• Learner Agency
• Inclusive Learning
• Personalized Learning
• Teaching
• Equity
• Adaptive Learning

Connected Articles

• Pre-service teachers' agency during their interactions with generative AI while designing for learning - a process view — Pre-service teachers' agency with generative AI
• Where Artificial Intelligence Enters Teacher Work — Where Artificial Intelligence Enters Teacher Work
• Assistive Generative AI for Visually Impaired Learners: Personalization and Inclusion in Higher Education — Assistive Generative AI for Visually Impaired Learners

Citation

Daniusevičiūtė-Brazaitė, L., Gaižiūnienė, L., & Pučėtaitė, R. (2026). AI in inclusive education: teachers’ visions of future-oriented practices.