AI in Instruction and Pedagogy

This section covers terms that concern how AI impacts teaching, learning, and curriculum design.

Computer programs that automatically adjust their behavior based on data and feedback, learning from patterns to improve performance over time. In education, these algorithms power personalized learning platforms that adjust difficulty, pacing, and content based on how each student performs, creating customized learning paths for every learner.

User interfaces that automatically adjust their layout, features, or presentation based on user needs, preferences, or abilities. In educational settings, this means learning platforms that can change font sizes for struggling readers, simplify navigation for younger students, or provide alternative controls for students with disabilities.

Educational technology that adjusts content difficulty, pacing, and teaching methods in real-time based on individual student performance and learning patterns. This approach ensures each student gets appropriately challenging material—neither too easy nor too frustrating—maximizing engagement and learning outcomes.

The design and implementation of AI systems to be usable by people with disabilities or diverse needs. In schools, this means AI tools that work with screen readers, offer text-to-speech, provide visual alternatives, and ensure every student can participate fully regardless of their abilities.

Teaching that incorporates AI tools to enhance delivery and personalization of content. Teachers use AI to differentiate lessons, provide instant feedback, identify struggling students, and create customized learning materials while maintaining human oversight.

Combining traditional face-to-face instruction with AI-enhanced digital learning. AI personalizes the online components, tracks progress across both formats, and helps teachers coordinate in-person activities with digital practice.

Artificial intelligence specifically designed for educational technology applications. EdTech AI focuses on learning outcomes, pedagogical principles, and the unique needs of students and teachers rather than general-purpose AI applications.

Software applications using artificial intelligence to support teaching and learning. These include intelligent tutoring systems, automated graders, learning analytics platforms, content generators, and adaptive learning systems.

Computer programs providing personalized instruction without human intervention, adapting to individual student needs. These systems offer consistent, patient, always-available support that complements human teaching by providing practice and reinforcement.

Material created by artificial intelligence systems, including text, images, videos, or audio. In education, this includes practice problems, lesson plans, study guides, and creative writing, and requires careful review for accuracy and appropriateness.

Using AI to create adaptive game-like learning experiences that adjust to student performance. These systems personalize challenges, rewards, and progression paths to maintain optimal engagement and learning for each student.

Technology that evaluates and scores student work without human intervention. Automated grading now includes essay evaluation and complex problem-solving, giving teachers more time for instruction while students get faster feedback. Modern systems often include batch grading capabilities, allowing teachers to evaluate entire class sets simultaneously while maintaining consistency across all submissions.

The creation of educational materials using AI systems. This includes generating lesson plans, practice problems, reading passages, quiz questions, and explanations, though all AI-generated content requires human review for accuracy and appropriateness.

Teaching methods and practices that effectively integrate digital technologies into education. AI requires evolving digital pedagogy to include new approaches like AI-assisted differentiation, automated feedback loops, and data-driven instruction.

Technology providing immediate responses to student work or questions. AI-powered instant feedback helps students correct mistakes right away, understand concepts before moving on, and stay engaged through timely reinforcement.

Real-time questioning systems that collect and display student responses instantly. AI enhances polling by analyzing responses to identify misconceptions, adjust follow-up questions, and provide immediate clarification where needed.

Digital environments where students can experiment and learn through manipulation of variables. AI-powered simulations adapt scenarios based on student actions, provide guided exploration, and create personalized learning experiences. For example, a chemistry simulation might let students mix virtual chemicals safely, with AI adjusting difficulty and providing hints based on their understanding.

The effective incorporation of technology tools into teaching and learning processes. Successful AI integration doesn't just involve using tools, but fundamentally enhances pedagogy, improves outcomes, and prepares students for a technology-rich future.

Technology converting written text into spoken words, often paired with speech recognition for two-way communication. In education, text-to-speech helps struggling readers, supports language learners, assists students with visual impairments, and provides alternative ways to access content, while speech recognition allows students to respond verbally, creating fully accessible learning experiences.