September 23, 2026

Technology has become an established part of education, influencing how students access academic content and support. What began with digital classrooms and online access to information has expanded into technologies that can respond to students, generate content, provide feedback, and support instruction. AI has added a new dimension to this landscape.

The Digital Education Council’s 2026 global survey found that 88% of surveyed higher education students used AI in their learning. The study included 27,284 students across 35 countries, indicating that AI use has become widespread across different higher education systems.

The scale of this adoption raises a more practical issue for educational institutions, how technology can be integrated in ways that support educational objectives and appropriate academic standards. Education Technology Day, observed on September 23, offers an opportunity to examine how its use has evolved and what this means for the future of education.

The Evolution of Education Technology

Education technology has developed alongside changes in digital infrastructure and access. Early adoption focused largely on bringing devices, connectivity, and digital resources into learning environments. Online platforms then expanded access to course materials and enabled learning beyond the physical classroom.

AI introduces a different set of capabilities. Digital systems can now respond to student inputs, generate learning materials, provide feedback, and support aspects of instructional planning. UNESCO identifies AI as having potential applications across teaching and learning, while emphasizing the importance of equitable and human-centered approaches to its use.

This evolution can be seen in the capabilities that have emerged over time:

• Digital access: Devices, connectivity, and online resources expanded access to educational content.
• Online learning: Digital platforms supported remote instruction and flexible access to coursework.
• Interactive learning: Multimedia tools and simulations introduced new ways to engage with academic content.
• AI-enabled learning: AI has introduced systems that can respond to questions, generate content, and adapt certain activities based on user input.

Together, these developments have expanded the role of technology across learning and teaching

AI Is Becoming Part of Everyday Education

For students, one of AI’s most visible applications is on-demand academic support. Conversational tools can explain unfamiliar concepts, work through problems, and generate practice materials, extending access to assistance beyond scheduled classroom instruction. The 2026 Student Generative AI Survey found that 95% of surveyed students used AI in at least one way, while 94% reported using generative AI to support assessed work.

Educators also use these systems to prepare quizzes or assessments, develop classroom activities, and organize instructional content.

According to a 2025 Gallup study, six in 10 teachers reported using an AI tool for their work. Teaching professionals can use AI to develop initial materials and refine them for specific instructional needs, while reviewing the content for accuracy and alignment with course requirements.

Education technology can help educators:

• Create practice questions at different difficulty levels.
• Develop examples for explaining complex concepts.
• Prepare lesson outlines and classroom activities.
• Summarize lengthy instructional materials.
• Suggest feedback for student assignments.
• Generate ideas for projects and collaborative activities.

These applications are extending how students and educators access academic support.

Advancing Personalized Learning Through Adaptive Technologies

Education technology is also redefining how students receive instruction. Traditional lessons often follow the same sequence for an entire class, even when learners have different levels of preparation. Adaptive technologies can use student performance data to adjust learning activities. A student struggling with algebra, for example, may receive additional practice on foundational concepts, while a student who has demonstrated proficiency can progress to more advanced material.

Where personalized technology helps

• Learning gaps: Digital systems can identify recurring mistakes and suggest targeted practice.
• Flexible progress: Students may work through selected activities at a suitable pace.
• Immediate feedback: Learners can receive guidance without waiting for every task to be reviewed manually.
• Teacher support: Teachers can use performance patterns to plan reviews and additional instructions.

The value of these technologies depends on the quality of the underlying content and how educators interpret the data. Performance data cannot fully explain why a student is struggling. Language barriers, confidence, or circumstances outside the classroom may influence academic performance. Teachers remain important in interpreting these patterns and determining the appropriate response.

AI Is Extending the Capabilities of Learning Platforms

Traditional learning platforms largely organize content, assignments, assessments, and student records. AI adds the ability to use interactions within those systems to inform what happens next. A platform can analyze responses to practice questions, identify recurring errors, and recommend material that corresponds with the areas where a student needs further work.

This creates several practical applications:

• Targeted practice: Question sets can be adjusted using previous responses or demonstrated proficiency.
• Contextual support: Students can request explanations while working through course material instead of leaving the learning environment to find additional help.
• Progress signals: Patterns across assessments and activities can help identify concepts that may require further attention.
• Skill-based practice: Interactive exercises can provide repeated practice in areas such as language learning, coding, and professional training.

AI changes how learning platforms can use student activity. Beyond distributing and managing content, AI-enabled platforms can use student activity to inform subsequent exercises, feedback, and support.

This capability is also opening the way for more interactive forms of technology-enabled learning.

Enhancing Experiential Learning Through Immersive Technologies

Virtual reality, augmented reality, and extended reality can support experiential learning through simulated environments. Instead of simply reading about scientific concepts or professional procedures, students can explore them through immersive experiences. Healthcare students have the opportunity to practice procedures in simulated environments before working with real patients, while engineering and vocational learners can explore virtual equipment and rehearse workplace scenarios. These technologies are especially useful when practical training is expensive, difficult to arrange, or potentially dangerous.

Education technology can make these experiences even more useful by adapting simulations to students’ performance and providing feedback as they practice. However, immersive learning requires suitable equipment, technical support, and thoughtful planning. Their use should support practical learning while complementing real-world training and teacher guidance.

As these technologies become part of learning environments, students also need the skills to evaluate how AI works, recognize its limitations, and use it responsibly. This makes AI literacy an important part of technology-enabled education

Developing AI Literacy for Responsible and Effective Learning

As AI becomes more common in education and employment, students need to understand more than how to operate an AI application. They must learn how to evaluate its responses, recognize its limitations, and use it responsibly.

AI literacy is shifting toward an important part of modern education as students may encounter generated information in assignments, research, examinations, and future workplaces.

Important AI literacy skills

• Questioning AI output: Students should examine whether generated information is accurate and complete.
• Verifying sources: AI responses should be checked against reliable evidence.
• Writing effective prompts: Clear instructions can help students obtain more useful responses.
• Protecting privacy: Learners should avoid sharing sensitive personal or institutional information.
• Recognizing bias: AI-generated content may reflect limitations in its training data or design.
• Maintaining independent thinking: Students must continue developing their own reasoning and problem-solving abilities.

AI literacy should be introduced through practical activities that allow students to compare AI-generated explanations with textbooks, identify errors in generated answers, and discuss the ethical use of automated assistance.

This growing emphasis on responsible AI use also raises important questions about how student knowledge and skills should be evaluated.

Rethinking Assessment Through Artificial Intelligence

Generative AI has created new challenges for traditional assignments and examinations. Students frequently use AI to produce essays, solve problems, summarize readings, and generate project materials. This has made it more difficult for educators to determine whether submitted work accurately reflects a student’s understanding.

Educational institutions are responding by reconsidering how learning is assessed. The University of Sydney, for example, has introduced a two-lane approach that distinguishes between secure assessments used to demonstrate learning outcomes and open assessments where generative AI can be incorporated into the learning process. Secure formats can include in-person oral, practical, and written assessments, while open assessments allow AI use where it is appropriate to the task.

Approaches such as this place greater emphasis on defining where AI use is appropriate within academic work. They also bring wider institutional considerations into focus, including whether students have equitable access to technology and how its use is governed across the learning environment.

Ensuring Equity and Accountable Technology Adoption in Education

The rapid adoption of AI and digital learning tools also raises concerns about fairness and accessibility. Students do not necessarily have equal access to reliable internet connections, suitable devices, paid AI services, or supportive learning environments.

If institutions introduce advanced technology without addressing these differences, existing educational inequalities may widen.

Technology adoption also introduces questions about data privacy. Learning platforms can collect information about student performance, behavior, and participation. Institutions must establish clear rules for collecting, storing, and using such information.

AI systems can also produce inaccurate or biased outputs, requiring institutions to establish appropriate review and oversight. Broader technology use should also account for screen time and opportunities for direct interaction, discussion, and collaborative learning.

Responsible technology adoption requires several priorities:

• Providing equitable access to digital learning resources.
• Training teachers to use AI effectively.
• Protecting student information.
• Evaluating tools before introducing them widely.
• Maintaining opportunities for discussion, collaboration, and practical learning.
• Establishing clear rules for academic integrity.

Technology should improve educational opportunities without compromising student rights or learning quality.

Conclusion

The next phase of education technology will be defined by the choices institutions make around its use. As AI capabilities advance, the priority is to ensure that technology serves a clear educational purpose and contributes meaningfully to learning. Education Technology Day offers a timely moment to keep that purpose at the center of the conversation.