Books › Knowledge-based tutoring
Knowledge-based tutoring
377 pages
A deep, methodical dive into the foundational logic of teaching machines how to teach humans.
What it feels like
Reading this foundational text feels like stepping into the meticulous, pioneering laboratory of early artificial intelligence. The pace is steady and deliberate, demanding the reader's full intellectual engagement as it unpacks the complex architecture of expert systems. There is a distinctively academic, analytical mood that permeates the pages, reflecting its origins as a rigorous doctoral thesis. The prose is dense and precise, prioritizing clarity and structural integrity over stylistic flourish. It offers a fascinating, structured journey from abstract cognitive theories to concrete computational models. This is a book that will deeply satisfy cognitive scientists, ed-tech historians, and AI researchers who want to understand the bedrock logic of how machines were first programmed to understand and guide human learning.
- Mood
- intellectual
- focused
- structured
- Tone
- academic
- analytical
- methodical
- objective
- Pace
- steady
- Themes
- human-computer interaction · cognitive modeling · artificial intelligence history · pedagogical logic
- The writing
- Dense, precise, and highly structured, characteristic of rigorous computer science literature.
- The arc
- Moves from a foundational curiosity about machine capabilities to a satisfying, structured understanding of cognitive modeling.
- Who it's for
- AI researchers, ed-tech developers, and cognitive scientists fascinated by the historical roots of intelligent tutoring systems.
About the book
Bibliography: p. [362]-372. Revision of the author's thesis. Includes index.
Description from Open Library.
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