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Direct linkNix, John-Michael L. – International Journal of Listening, 2021
The relationship between second language (L2) listening presage and process variables was examined in a large cross-sectional study. A formal model of learning beliefs was adapted to create a structural equation model testing the interrelationships of individual difference (gender, practice, experience with native teachers) and trait variables…
Descriptors: Correlation, Listening Comprehension, Case Studies, Individual Differences
Gurzynski-Weiss, Laura, Ed. – Language Learning & Language Teaching, 2020
This book examines the role of interlocutors and their individual differences (IDs) in second language (L2) development from four theoretical lenses: the cognitive-interactionist approach, sociocultural theory, the variationist approach, and complex dynamic systems theory. A theoretical overview to each approach is written by a preeminent scholar…
Descriptors: Individual Differences, Second Language Learning, Second Language Instruction, Sociocultural Patterns
Odendaal, Albi – Research Studies in Music Education, 2019
Perceptual Learning Style theory (PLS) claims that the presentation of information in either a visual, auditory or kinaesthetic format will improve the learning of selected individuals due to the dominance of one or more modality in their information gathering. The modality dominance of six Western classical pianists in higher music education was…
Descriptors: Cognitive Style, Music, Music Education, Musical Instruments
Download full textStamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
