Teaching and Learning with AI
OpenBook is built around the belief that most effective learning happens when the right content reaches the right learner at the right moment. This page explains the educational philosophy behind OpenBook, the recurring challenges it was designed to address, and how its built-in AI assistant ELISA creates a genuinely adaptive learning experience.
AI and Modern Education
The widespread availability of large language model (LLM) based AI assistants has sparked a global debate about modern teaching and learning practices. But the core question, whether our established educational approaches remain valid in the age of AI — is not entirely new. Anyone with long enough experience in education will recognize that educators have long questioned whether each successive generation learns as deeply as the last. At the same time, many teaching and learning methods have been proposed to enhance student-centeredness and improve the teaching and learning experience. What is truly new is the pace of change.
Many teaching and assessment practices, though didactically sound, are struggling to keep up with rapid AI advancement. The temptation for students is real: why write an essay when AI can produce one in seconds? Yet learning is an active process that requires effort, involvement, and engagement. A shortcut does not build understanding, and learners who take it ultimately betray themselves, as educators and students agree alike.
Banning AI, however, is neither enforceable nor sensible. Technological change was never the problem. The problem has ever been how humans respond to the change. It is safe to assume that AI will continue to permeate professional and personal life, and used thoughtfully — with good prompts, human oversight, and critical evaluation — it offers genuine value for educators and learners alike. The better question is therefore not which traditional practices still make sense, but how we can combine the strengths of human-guided learning with the capabilities of AI to support learners most effectively.
Challenges in Teaching and Learning
OpenBook was designed to solve three recurring problems in everyday teaching and learning:
Traditional, linear learning material does not fit all learners equally well.
Educators lack transparent feedback about student learning progress.
Students lose orientation about priorities, timelines, and prerequisites.
Inflexible Learning Materials — Traditional learning materials like slide decks, transcripts, scripts, and textbooks, embed assumptions about the students who will use them. They assume a certain level of prior knowledge, a particular motivation, and specific learning goals. Even carefully crafted material will fit some learners well while containing too much detail for some and too little for others. The result is that content created with great effort is frequently ignored. This problem has been intensified over the years by increasingly goal-oriented and economised approaches to studying, long before AI entered the picture.
Limited Progress Visibility — Learning Management Systems (LMS) such as Moodle or ILIAS offer powerful didactical tools, but many educators cannot or do not use them effectively — whether through lack of awareness, limited technical skills, or local institutional restrictions. These platforms have also accumulated decades of features, which makes it hard for them to quickly respond to emerging technology and trends. As a result, though invaluable teaching tools, they can feel dated. Educators who turn to external tools, however, often lose the structured learning model and progress tracking that a full LMS provides. The result is that educators, especially in self-directed learning contexts such as the Inverted Classroom model (ICM), lack meaningful feedback on how students are actually progressing.
Disorientation and Loss of Structure — The more material students receive, and the more scattered it is across documents and platforms, the harder it becomes to maintain a clear sense of direction. Students routinely report in course evaluations that a lecture lacked a coherent thread – even when the educator provided one explicitly. The problem is rarely an absence of structure; it is an absence of structure that is visible and navigable to the learner.
How OpenBook Responds
Interactive Textbooks
OpenBook is an LMS in its own right, built around a textbook metaphor that draws on the long and proven history of structured learning materials. Unlike systems that are mainly used to distribute static PDF lecture notes, OpenBook organises content into textbook pages that students actively engage with. PDFs remain available for cases where they are the most practical option, but students learn through textbook pages – and those pages are interactive from the ground up.
Interactive activities are woven throughout: comprehension checks, quizzes, programming assignments, and more. They are not add-ons; they are central to how material is presented. Informed by the history of Computer-Aided Teaching (CAT), OpenBook also provides a strong learner model covering learning targets, competencies, goals, and achievements: giving both students and educators a shared vocabulary for progress.
Adaptive Guidance with ELISA
The built-in AI, called ELISA (named in homage to Joseph Weizenbaum’s ELIZA), addresses the second and third challenges together. While textbooks follow a linear structure, reflecting the sequential nature of most courses, ELISA continuously assesses each learner’s progress and adjusts the experience accordingly. It selects relevant content from the available textbooks, adds supplementary explanations or activities on demand, and guides the learner along a path that is visible and navigable at all times. Students never lose orientation, because the system makes the learning path, past achievements, and remaining work consistently visible.
ELISA is fundamentally different from AI chatbots or assistants that respond to prompts and fall silent otherwise. It acts proactively, not by pursuing autonomous background goals, but by remaining in constant interaction with the human learner. The human is always in the loop. ELISA’s purpose is to maximise learning outcomes: it assesses prior knowledge and understanding, finds and selects the most relevant materials and activities, and suggests or creates additional exercises like quizzes, programming tasks, assessment simulations, and more, tailored to individual needs.
Lecturers benefit equally. Learning dashboards summarise progress across a group, highlight where understanding broke down, and help educators direct their attention where it is most needed. The system also supports students in preparing questions for class and engaging with lecturers and fellow learners. Throughout, OpenBook balances academic rigour with playfulness and a measured use of gamification, because effective learning must be engaging to be lasting.