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Hitoshi Nishizawa – Language Testing, 2024
Corpus-based studies have offered the domain definition inference for test developers. Yet, corpus-based studies on temporal fluency measures (e.g., speech rate) have been limited, especially in the context of academic lecture settings. This made it difficult for test developers to sample representative fluency features to create authentic…
Descriptors: High Stakes Tests, Language Tests, Second Language Learning, Computer Assisted Testing
Hsieh, Ching-Ni; Wang, Yuan – Language Testing, 2019
This study investigated a range of fluency, grammar, vocabulary, and content features of young language students' speaking performances, using a discourse-analytic approach. In total, 179 test takers' responses to the speaking section of the "TOEFL Junior"® Comprehensive test were selected for analysis. Mixed-design ANOVAs were used to…
Descriptors: Oral Language, Second Language Learning, Language Fluency, Grammar
Plakans, Lia; Gebril, Atta; Bilki, Zeynep – Language Testing, 2019
The present study investigates integrated writing assessment performances with regard to the linguistic features of complexity, accuracy, and fluency (CAF). Given the increasing presence of integrated tasks in large-scale and classroom assessments, validity evidence is needed for the claim that their scores reflect targeted language abilities.…
Descriptors: Accuracy, Language Tests, Scores, Writing Evaluation
Ockey, Gary J.; Koyama, Dennis; Setoguchi, Eric; Sun, Angela – Language Testing, 2015
The purpose of this study was to determine the extent to which performance on the TOEFL iBT speaking section is associated with other indicators of Japanese university students' abilities to communicate orally in an academic English environment and to determine which components of oral ability for these tasks are best assessed by TOEFL iBT. To…
Descriptors: Language Tests, English (Second Language), Second Language Learning, Correlation
Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David – Language Testing, 2012
This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…
Descriptors: Scoring, Classification, Weighted Scores, Comparative Analysis