computer science

STUDENT

STUDENT is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand STUDENT rather than just read about it. In short: STUDENT is an early artificial intelligence program that solves algebra word problems. It is written in Lisp by Daniel G.

Key takeaways

STUDENT belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect STUDENT to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of STUDENT from memory before moving on to harder problems.

Reference excerpt

STUDENT is an early artificial intelligence program that solves algebra word problems. It is written in Lisp by Daniel G. Bobrow as his PhD thesis in 1964 (Bobrow 1964). It was designed to read and solve the kind of word problems found in high school algebra books. The program is often cited as an early accomplishment of AI in natural language processing.

Technical description Within Project MAC at MIT, the STUDENT system was an early example of a question answering software, which uniquely involved natural language processing and symbolic programming. Other early attempts for solving algebra story problems were realized with 1960s hardware and software as well: for example, the Philips, Baseball and Synthex systems. STUDENT accepts an algebra story written in the English language as input, and generates a number as output. This is realized with a layered pipeline that consists of heuristics for pattern transformation. At first, sentences in English are converted into kernel sentences, which each contain a single piece of information. Next, the kernel sentences are converted into mathematical expressions. The knowledge base that supports the transformation contains 52 facts. STUDENT uses a rule-based system with logic inference. The rules are pre-programmed by the software developer and are able to parse natural language. More powerful techniques for natural language processing, such as machine learning, came into use later as hardware grew more capable, and gained popularity over simpler rule-based systems.

References

Natural Language Input for a Computer Problem Solving System, Bobrow's PhD thesis. Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2, p. 19 Crevier, Daniel (1993). AI: The Tumultuous Search for Artificial Intelligence. New York, NY: BasicBooks. ISBN 0-465-02997-3., pp. 76–79

Worked examples

Example 1 — a first encounter with STUDENT

Start with the simplest possible case. Write down what STUDENT claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to STUDENT before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about STUDENT ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of STUDENT

In research: STUDENT appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses STUDENT in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: STUDENT is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1960s in artificial intelligence, 1964 software, Computer programming stubs, so understanding it makes those chapters shorter.
In everyday life: Look for STUDENT outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study STUDENT in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what STUDENT means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain STUDENT out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is STUDENT in simple terms?

STUDENT is an early artificial intelligence program that solves algebra word problems. It is written in Lisp by Daniel G.

Why does STUDENT matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study STUDENT?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on STUDENT.