Adaptive learning in computing for non-native speakers.

Rimbaud, Yann; McEwan, Tom; Lawson, Alistair; Cairncross, Sandra

Abstract

A significant proportion of e-Learning resources for engineering and computing education appear to be exclusively in English, requiring many learners to adapt themselves to learning within an English language context. Adaptive learning has a role to play in minimizing this adjustment and strengthening the learning. This research plans to understand learning needs, and take a Content and Language Integrated Learning (CLIL) approach to create algorithms to supply online learning experiences and content to meet these needs, adding novel mechanisms to help learners cope, develop their language capabilities, and enhance their ability to learn in another language. This work-in-progress describes the early stages of the research and we welcome insights into taxonomies of adaptive learning techniques, and mixed methods approaches to evaluating learning effectiveness, for those learning in an additional language.

Citation

Rimbaud, Y., McEwan, T., Lawson, A., & Cairncross, S. (2014, October). Adaptive learning in computing for non-native speakers

• Start Date: Oct 22, 2014
• End Date: Oct 25, 2014
• Publication Date: 2014
• Deposit Date: Dec 3, 2014
• Peer Reviewed: Peer Reviewed
• Pages: 1-4
• Book Title: 2014 IEEE Frontiers in Education Conference Proceedings
• ISBN: 978-1-4799-3921-3
• DOI: https://doi.org/10.1109/FIE.2014.7044142
• Keywords: Adaptive learning
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/7335