- What legal punishment did Turing face in 1952 for his relationship with a man, and how did it relate to his death two years later?
Artificial Intelligence
The science and engineering of intelligent machines.
- Why did the ACM name its new computing prize after Alan Turing, who had died twelve years earlier without such recognition?
- What did Minsky and Papert's book Perceptrons prove about single-layer neural networks?
- Why did Perceptrons cool enthusiasm for connectionist AI approaches for a decade?
- What role did Minsky play in founding the MIT Artificial Intelligence Laboratory?
- How did John McCarthy come to coin the term 'artificial intelligence' at the 1955 Dartmouth workshop proposal?
- What made LISP's design unusual, and why did treating code as data matter for symbolic AI?
- Why did early AI researchers like McCarthy believe human-level machine intelligence was close at hand?
- What is the physical symbol system hypothesis, and what does it claim about intelligence?
- How did Newell and Simon's General Problem Solver extend the ideas behind Logic Theorist?
- In what sense did Newell and Simon argue human problem-solving and computation are the same activity?
- Why did Simon argue that the classical model of a fully rational economic actor was unrealistic?
- How did Simon's work span economics, psychology, and cognitive science at once?
- Why did Isaac Asimov originally write the Three Laws of Robotics?
- How did Edward Feigenbaum's expert systems like DENDRAL and MYCIN differ from earlier AI research aimed at universal reasoning engines?
- How accurate was MYCIN at diagnosing blood infections compared to human clinicians?
- What made real-time continuous speech recognition, which Raj Reddy pioneered at Carnegie Mellon, so difficult in the 1970s and 1980s?
- What technologies did Douglas Engelbart demonstrate in the 1968 'Mother of All Demos'?
- What did Engelbart consider the true goal behind his inventions, beyond the mouse itself?
- What upgrades did IBM make to Deep Blue between the 1996 loss and the 1997 rematch?
- Why did Kasparov suspect human intervention in Deep Blue's second game, and how did IBM respond?
- What was the final score of the 1997 rematch between Deep Blue and Kasparov?
- What does the slime mould experiment suggest about how simple organisms solve optimisation problems?
- If the underlying model wasn't new, what made ChatGPT's interface feel different to ordinary users?
- Which other major AI labs released competing language models in the months after GPT-4?
- How did the population of people debating AI systems change in 2023?
- How do systems like AlphaGo and superhuman game-playing agents trace their lineage back to Barto and Sutton's framework?
- Which modern AI systems trace their lineage back to Barto and Sutton's foundational reinforcement learning work?
- What distinct categories of tutoring systems emerge from a Latent Class Analysis of 86 studies on Intelligent Tutoring Systems and Robot Tutoring Systems?
- How do Intelligent Tutoring Systems and Robot Tutoring Systems complement each other in delivering personalized, adaptive instruction versus social-emotional engagement?
- What AI techniques, such as Bayesian Knowledge Tracing and Large Language Models, are driving improvements in adaptability and learning outcomes within tutoring systems?
- What ethical, scalability, and cognitive-adaptability gaps remain unresolved in current tutoring system research, and how might hybrid ITS-RTS solutions address them?
- How does this chapter distinguish between instructional intelligence and adaptivity in AI-enabled serious games?
- What historical trajectory connects early computer-assisted instruction and intelligent tutoring systems to today's AI-enabled adaptive learning architectures?
- In what ways might large language models, reinforcement learning, and agent-based architectures enable more integrated instructional adaptation within serious games?
- What practical and research challenges, such as explainability, validation, and computational cost, limit the deployment of AI-enabled serious games despite their promise?
- How does Physics-STAR use step-by-step guidance and reflective prompts instead of direct answers to support deeper learning in high school physics?
- What gains in accuracy and efficiency did students show on conceptual, computational, and informational physics questions after using Physics-STAR?
- Why did complex information problems see a 100% score improvement while overall efficiency gains were more modest at 5.95%?
- Which sensor combination and model architecture performed best under 10-fold cross-validation versus leave-one-subject-out (LOSO) evaluation, and what does that difference imply about generalizing cognitive load classifiers to new individuals?
- What design components define a next-generation intelligent tutoring system that adapts to individual learners?
- What limitations do conditional-statement-driven dialogue agents have compared to neural network based approaches for tutoring?
- In what extended reality contexts, such as rehabilitation and trauma healing, have computer-based tutoring agents already been deployed?
- How does a deep reinforcement learning agent that adapts to a student's changing metacognitive level compare to a static classifier-based approach for teaching strategy-switching in intelligent tutoring systems?
- Why do static, classifier-based metacognitive interventions only benefit students who already know how to use the target strategy, while adaptive DRL-based interventions close the skills gap across the whole class?
- What evidence shows that DRL-based metacognitive interventions in one tutoring domain (a logic tutor) transfer to prepare students for future learning in an unrelated domain (a probability tutor)?
- How does elaborated feedback across verbal, graphical, and mathematical representations relate to post-test performance in high school physics?
- Why does using a diverse set of representations benefit students with lower representational competence more than those with higher competence?
- What do these findings imply for designing adaptive, multimodal feedback in intelligent tutoring systems that use large language models?
- How can intrinsic and extraneous cognitive load be estimated from transcripts of real-world AI-assisted knowledge work?
- Why does extraneous cognitive load have a much larger negative association with task performance than intrinsic load in AI-assisted work?
- How does AI-generated content usage compensate for cognitive load, and why is this compensation only partial?
- How does professional expertise moderate the relationship between cognitive load and performance benefits from AI assistance?
- How do model-tracing cognitive tutors represent a student's problem-solving strategies and misconceptions?
- Why are Bayesian Networks well suited for decision-making in intelligent tutoring systems?
- In what ways do intelligent tutoring systems adapt instruction to a learner's individual progress?
- How have spaced repetition systems evolved from the Leitner box method through the SM-2 algorithm to modern machine-learning approaches like SSP-MMC and LSTM-HLR?
- In what ways do deep learning models like LSTM-HLR and natural language processing enable AI systems to predict optimal review timing and assess partial knowledge?
- How do removal and clustering, as two distinct abstraction operations over irrelevant details in symbolic explanations, differ in their effects on human understanding versus cognitive effort?
- How can Answer Set Programming be used to formally define which details in a logical trace are 'irrelevant' and thus eligible for abstraction in an explanation?
- What does the finding that clustering improves understanding while removal reduces cognitive effort imply for designing human-centered explanations from symbolic AI systems?
- Why do traditional machine learning bias metrics fail to transfer to LLM-generated educational content?
- At which stages of the LLM life cycle, from development to deployment, can algorithmic bias enter educational applications?
- How might personalized LLM tutoring affect cognitive load management for different student populations?
- Why can tailoring an LLM's responses to individual learners be pedagogically desirable rather than a form of unfair bias?
- How can large language models be used to evaluate the quality of a tutor's response to a student's math error?
- What role does automated LLM-based assessment play in scaling effective tutoring practices?
- How can large language models be used to classify whether a human tutor's praise response is effective or effort-based, rather than person-based?
- In what ways can automated explanatory feedback help train human tutors to give higher-quality corrective feedback in real time?