Information Processing Ability and its Implications for Teaching and Learning

Yıl 2022, Cilt: 6 Sayı: 12, 110 - 123, 11.11.2022

Mariette Fourie Gawie Schlebusch

https://doi.org/10.31458/iejes.1130846

Cited By: 2

Öz

The aim of this paper is to explore how the brain processes information, and which factors affect the information processing ability of learners in the classroom. From the hierarchical linear modelling (HLM) analysis, it is evident that the independent variables age, home language, language of learning and teaching (LOLT), and average class size affect the information processing ability of learners in the classroom. The process by which the brain acquires, use, and think about knowledge is known as cognition. Cognition are those intellectual or perceptual processes occurring within us that the typical individual would describe as thinking, rational processing, or the mind. Through learning, an individual’s cognition develops long-term changes in mental representations or associations because of environmental learning and experiences. A quantitative design was followed to gather data from Grade 11 learners by means of a questionnaire. The results revealed that information processing ability of learners as a dependent variable was significantly influenced by the following independent variables: age, home language, language of learning and teaching, and average class size. Recommendations to teachers on how to facilitate efficient information processing are made, which could result in meaningful learning and understanding by the learners. It is hoped by the researchers that, employing these tactics, will render valid results that are consistent with the need to enhance learners’ depth and breadth of processing information, and thereby become sophisticated and complex producers of knowledge.

Anahtar Kelimeler

Cognition, hierarchical linear modelling, human memory model, information processing ability.

Destekleyen Kurum

Research Fund of the Central University of Technology

Teşekkür

The article stems from a doctoral study financed by the Research Fund of the Central University of Technology, South Africa from 2017-2019.

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