Focusing on the teaching of computer science in the generative A.I. (GenAI) era, the 4th edition of this Guide to Teaching Computer Science aims to contribute to the urgent effort to rethink and redesign computer science education.

This Guide to Teaching Computer Science is intended for all computer science educators, from elementary, middle and high school to academia. It is organized in a way that enables an immediate application of its main ideas. This goal is achieved by presenting the rationale for addressing a variety of computer science education topics, as well as their detailed actual teaching process (including activities, worksheets, topics for discussions, and more). The rise of GenAI necessitates immediate changes in computer science education, even as we recognize that predictions about the future of the discipline of computer science--and of educational systems more broadly--must be made with caution.

• The guide focuses on computer science education - teaching and learning.
• The guide is organized in three parts: Overview of Contemporary Computer Science Education; Computer Science Education Pedagogy: Research and Implementation; and Teacher Preparation Frameworks.
• Each chapter presents a pedagogical topic along with its meaning, importance and relevance in the context of computer science education, its basic pedagogical principles, and how it can be applied in computer science education in general--and in the Methods of Teaching Computer Science (MTCS) course in particular.
• Topics addressed in this guide include the following in the context of computer science education: research in computer science education; learners' alternative conceptions; types of questions; assessment; teaching methods and learning spaces; lab-based teaching; teaching planning; teacher preparation programs; and prospective teachers practicum.

The 4th edition of this highly useful guide includes 232 activities. This unique resource can be used by many people involved in computer science education: in particular, instructors of an MTCS course, instructors of in-service teachers' professional development programs, and teachers across all levels and students.

This concise yet thorough textbook presents an active-learning model for the teaching of computer science. Offering both a conceptual framework and detailed implementation guidelines, the work is designed to support a Methods of Teaching Computer Science (MTCS) course, but may be applied to the teaching of any area of computer science at any level, from elementary school to university. This text is not limited to any specific curriculum or programming language, but instead suggests various options for lesson and syllabus organization.

Fully updated and revised, the third edition features more than 40 new activities, bringing the total to more than 150, together with new chapters on computational thinking, data science, and soft concepts and soft skills. This edition also introduces new conceptual frameworks for teaching such as the MERge model, and new formats for the professional development of computer science educators.

Topics and features: includes an extensive set of activities, to further support the pedagogical principles outlined in each chapter; discusses educational approaches to computational thinking, how to address soft concepts and skills in a MTCS course, and the pedagogy of data science (NEW); focuses on teaching methods, lab-based teaching, and research in computer science education, as well as on problem-solving strategies; examines how to recognize and address learners' misconceptions, and the different types of questions teachers can use to vary their teaching methods; provides coverage of assessment, teaching planning, and designing a MTCS course; reviews high school teacher preparation programs, and how prospective teachers can gain experience in teaching computer science.