Redesigning Teaching and Learning

Artificial intelligence did not create the weaknesses of traditional teaching. It made them impossible to ignore. When students can generate explanations, summaries, arguments, and solutions in seconds, teaching can no longer be organized primarily around the transmission of information. A correct answer is no longer sufficient evidence of understanding, and a polished final product may conceal a weak or entirely externalized intellectual process. Redesigning Teaching and Learning examines what must change when inherited teaching practices no longer provide reliable evidence of learning. The book argues that the central challenge is not deciding whether AI should be allowed in education. AI is already part of the environment in which students study, write, solve problems, and prepare assessments. The real question is how to redesign teaching so that understanding, judgment, problem formulation, and intellectual responsibility remain at the center. Readers will learn how to: distinguish genuine learning from simulated learning; move beyond the lecture-centered transmission model; reorganize class time around discussion, interpretation, decision making, and feedback; design learning activities with a nondelegable intellectual core; teach students to formulate problems rather than merely solve them; integrate AI without allowing it to replace the student's cognitive work; make reasoning, revision, and intellectual process visible; redesign assignments that currently reward plausible output; strengthen tutoring and instructor guidance; introduce immediate changes without redesigning an entire course at once. The book combines conceptual analysis with practical examples from engineering, health sciences, social sciences, humanities, and professional education. It also includes a quick guide, concrete redesign criteria, and fifteen prompts for instructors who want to improve classes, activities, feedback, and assessment. Written for university instructors, secondary-school teachers, academic coordinators, and educational leaders, this volume offers a rigorous framework for reconstructing teaching in an environment where information is abundant but understanding still requires deliberate intellectual work. AI does not eliminate the need for teaching. It makes thoughtful teaching more necessary.