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Related Concept Videos

Language Development01:22

Language Development

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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SPROUT: An Interactive Authoring Tool for Generating Programming Tutorials With the Visualization of Large Language

Yihan Liu, Zhen Wen, Luoxuan Weng

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    Summary
    This summary is machine-generated.

    This study introduces SPROUT, a tool using tree-of-thought large language models (LLMs) to improve programming tutorial creation. SPROUT enhances user control and understanding, leading to more reliable and customizable tutorials.

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    Area of Science:

    • Artificial Intelligence
    • Human-Computer Interaction
    • Software Engineering Education

    Background:

    • Large language models (LLMs) like ChatGPT accelerate programming tutorial generation.
    • Current LLM approaches lack transparency, limiting user control and understanding of tutorial creation.
    • Existing methods hinder the ability to customize and ensure the reliability of generated content.

    Purpose of the Study:

    • To develop a novel approach for transparent and controllable programming tutorial generation using LLMs.
    • To introduce SPROUT, an authoring tool designed to enhance user interaction and oversight in the tutorial creation process.
    • To improve the quality, reliability, and customizability of AI-generated programming tutorials.

    Main Methods:

    • Decomposition of the programming tutorial creation task into distinct, manageable steps.
    • Application of the tree-of-thought method to encourage exploratory and diverse LLM outputs.
    • Development of SPROUT, featuring interactive visualizations for user control and understanding.

    Main Results:

    • SPROUT facilitates active user participation in the programming tutorial creation workflow.
    • The approach leads to demonstrably more reliable and customizable programming tutorials.
    • User studies confirm enhanced understanding and control over the generation process.

    Conclusions:

    • SPROUT effectively addresses the transparency and control limitations in LLM-based tutorial generation.
    • The tool empowers users, improving the overall quality and user experience of programming tutorials.
    • This work advances the development of more interactive and user-centric AI authoring systems.