generelisering

Generelisering refers to the process of extending observations, rules, or conclusions drawn from specific cases to broader classes or general principles. The term is used across disciplines to describe how individuals or systems move from particular instances to broader applicability, and how empirical findings are applied beyond the original data set.

In psychology and education, generalization describes how a response learned in one situation transfers to other, similar situations. Stimulus generalization occurs when a reaction to a conditioned stimulus extends to stimuli that resemble it. Generalization is influenced by similarity, reinforcement history, and cognitive expectations, and it can lead to adaptive behavior or erroneous beliefs (for example, overgeneralization).

In research and statistics, generalization (external validity) refers to the extent to which findings from a sample apply to a larger population. Threats include sampling bias, measurement error, and contextual factors. Techniques to improve generalization include random sampling, replication, and pre-registration.

In machine learning, generalization is the ability of a model to perform well on unseen data. Overfitting leads to poor generalization, while underfitting indicates the model fails to capture structure. Methods such as cross-validation, regularization, and model simplification aim to improve generalization.

In linguistics, generalization describes the tendency to extend grammatical or phonological rules beyond observed instances, a key aspect of language acquisition and rule learning. This can result in productive but imperfect forms, such as applying a rule to irregular words (overgeneralization).

Notes: the spelling generelisering is uncommon in standard Dutch; the more common term is generalisering with ij. Generelisering is therefore typically seen as a nonstandard or less common variant.