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The Influence of Learners’ Attitudes to and Perceptions of Call

A Methodological Approach

Bibliographic Data

ID22299552
AuthorsMieke Vandewaetere (0000-0002-0708-8741, K.U.Leuven), Pieter Desmet (0000-0002-9849-0874, KU Leuven), Piet Desmet (K.U.Leuven)
Year2010
Volume160
Pages1-23
Publication date2010-01-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueITL - International Journal of Applied Linguistics (JOURNAL)
Journal identifiersISSN: 0019-0829 • E-ISSN: 1783-1490
PublisherJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/itl.160.01van
OpenAlexW2241149922
LanguageEN
References cited33

In recent years, the field of Computer-Assisted Language Learning – CALL – has grown tremendously and has seen a number of major developments: CALL has become accessible to a larger and more diverse audience and has developed didactic practices that can be implemented in education. In addition, there has been a growing amount of research that focuses on learners’ attitudes towards CALL and, more generally, towards computer-based language learning environments. These, however, seem to be fraught with methodological problems, often leading to inconsistent results. Rather than corroborating separate unidirectional relations between variables (e.g., the effect of instructional intervention on learning outcomes or motivation), researchers need to develop structural and integrative models that integrate multiple relations between several latent constructs. It is our aim in this pilot study to present a methodological framework for CALL-related theory construction. To reach this goal, we psychometrically validated the multifaceted construct of ‘attitude to CALL’. We demonstrate the development and validation of a preliminary integrative model on the concept of ‘attitude to CALL’. Structural equation modelling was used for the validation of our model

Construct (python library) · Field (mathematics) · Intervention (counseling) · Language acquisition · Latent variable · Mathematics education · Perception · Structural equation modeling · Artificial Intelligence · Computer Science · Education and Technology Integration · EFL/ESL Teaching and Learning · Gender and Technology in Education · Psychology

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Highly citedNo

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