Computer Science Logo Style: Symbolic Computing

Computer Science Logo Style: Symbolic Computing teaches fundamental programming concepts through the Logo programming language. The book serves as volume 2 in Brian Harvey's series on Logo and computer science education. The text covers topics including recursion, list processing, and symbolic manipulation through hands-on programming examples. Students learn to write programs that process words and sentences, manipulate mathematical expressions, and handle complex data structures. Technical concepts build progressively from basic to advanced, with each chapter containing exercises and projects for practice. The material focuses on developing problem-solving skills and computational thinking rather than simply teaching Logo syntax. The book represents an approach to computer science education that emphasizes the connections between programming, mathematics, and language processing. Through its focus on symbolic computing, it demonstrates how computers can work with abstract concepts and non-numerical data.

Limited reviews exist online for this technical text from 1997. What readers liked: - Clear explanations of symbolic computing concepts - Progressive difficulty that builds understanding - Practical examples using Logo programming - Focus on computer science fundamentals rather than just coding - Integration of recursion and data structure concepts What readers disliked: - Some found Logo outdated compared to modern languages - Examples can feel simplistic for experienced programmers - Reference sections could be more comprehensive Available ratings: Goodreads: Only 2 ratings, average 4.5/5 Amazon: No ratings found Other review sources show few ratings From a computer science educator on an archived mailing list: "Harvey's Logo series remains valuable for teaching core CS concepts, even as languages change. The symbolic computing volume especially demonstrates how to build complex abstractions from simple parts." The limited review data makes it difficult to draw broad conclusions about reader reception.

Structure and Interpretation of Computer Programs by Harold Abelson, Gerald Jay Sussman. This text explores programming through functional concepts and Scheme language, building from basic procedures to complex systems with similar pedagogical progression to Logo Style.

Mindstorms: Children, Computers, and Powerful Ideas by Seymour Papert. The book presents the philosophy behind Logo programming and constructionist learning that formed the foundation for Harvey's approach to teaching computer science.

The Little Schemer by Daniel P. Friedman. This book teaches recursive thinking and functional programming through a series of questions and answers that mirror the incremental learning style of Logo Style.

How to Design Programs by Matthias Felleisen, Robert Bruce Findler, Matthew Flatt, Shriram Krishnamurthi. The text introduces systematic program design using Racket language with emphasis on fundamental concepts that align with Harvey's focus on thinking through problems.

Simply Scheme: Introducing Computer Science by Brian Harvey. This companion text approaches computer science concepts through Scheme programming with the same educational philosophy as the Logo Style series.

🔹 Brian Harvey developed this book while teaching Logo programming at UC Berkeley, where he emphasized how Logo could be used to explore advanced computer science concepts beyond its reputation as just a children's language. 🔹 The book is part of a three-volume series that progressively takes readers from basic Logo programming to advanced topics like artificial intelligence and language processing. 🔹 Logo, the programming language featured in this book, was created by Seymour Papert and others at MIT in 1967, drawing inspiration from the constructivist learning theories of Jean Piaget. 🔹 Despite focusing on Logo, the book teaches universal programming concepts like recursion, functional programming, and symbolic computation that are relevant to modern languages like Python and JavaScript. 🔹 The "Symbolic Computing" volume explores how computers can manipulate symbols and language rather than just numbers, laying groundwork for understanding artificial intelligence and natural language processing.