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Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
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Ali, Shurooq A. – Arab World English Journal, 2021
This study shows impoliteness as a form of face-threatening that can be intentionally caused by verbal threats in a particular setting. It investigates: what strategies and mitigators do IraqiKurdish English as a foreign language (EFL) learners use in situations of threat responses? The present investigation paper aims to examine impoliteness…
Descriptors: Pragmatics, Second Language Learning, Second Language Instruction, Foreign Countries
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DiCerbo, Kristen E. – Measurement: Interdisciplinary Research and Perspectives, 2014
The Task Model is a description of each task in a workflow. It defines attributes associated with that task. The creation of task models becomes increasingly important as the assessment tasks become more complex. Explicitly delineating the impact of task variables on the ability to collect evidence and make inferences demands thoughtfulness from…
Descriptors: Task Analysis, Models, Taxonomy, Design
Edward Paul Getman – Online Submission, 2020
Despite calls for engaging assessments targeting young language learners (YLLs) between 8 and 13 years old, what makes assessment tasks engaging and how such task characteristics affect measurement quality have not been well studied empirically. Furthermore, there has been a dearth of validity research about technology-enhanced speaking tests for…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Learner Engagement