Human and machine learning when related to language

HL content: Modeling & Simulation

From the IB

Using knowledge, such as the syntax of a language, leads to an appreciation of the difficulties involved in machine language learning. Students should be familiar with the concept of cognitive learning and the use of heuristics and probabilities in machine learning.

Language

Linguists distinguish between language acquisition and language learning. Children acquire language through a subconscious process during which they are unaware of grammatical rules. This happens especially when they acquire their first language. They repeat what is said to them and get a feel for what is and what is not correct. In order to acquire a language, they need a source of natural communication, which is usually the mother, the father, or the caregiver.

Language learning, on the other hand, is the result of direct instruction in the rules of language. Language learning is not an age-appropriate activity for very young children as learning presupposes that learners have a conscious knowledge of the new language and can talk about that knowledge. They usually have a basic knowledge of the grammar.

Heuristic

In computer science, artificial intelligence, and mathematical optimization, a heuristic is a technique designed for solving a problem more quickly when classic methods are too slow, or for finding an approximate solution when classic methods fail to find any exact solution. This is achieved by trading optimality, completeness, accuracy, or precision for speed. In a way, it can be considered a shortcut.

Standards

• Discuss the differences between human and machine learning when related to language.

Make clear the differences between two or more concepts or items.

Offer a considered and balanced review that includes a range of arguments, factors or hypotheses. Opinions or conclusions should be presented clearly and supported by appropriate evidence.