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Li, Haiying; Graesser, Arthur C. – Journal of Research on Technology in Education, 2021
This study investigated how computer agents' language style affects summary writing in an Intelligent Tutoring System, called CSAL AutoTutor. Participants interacted with two computer agents in one of three language styles: (1) a "formal" language style, (2) an "informal" language style, and (3) a "mixed" language…
Descriptors: Intelligent Tutoring Systems, Language Styles, Writing (Composition), Writing Improvement
Li, Haiying; Graesser, Art C. – Grantee Submission, 2020
This study investigated how computer agents' language style affects summary writing in an Intelligent Tutoring System, called CSAL AutoTutor. Participants interacted with two computer agents in one of three language styles: (1) a "formal" language style; (2) an "informal" language style; and (3) a "mixed" language…
Descriptors: Intelligent Tutoring Systems, Language Styles, Writing (Composition), Writing Improvement
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Arévalo, María-José; Cantera, María Asun; García-Marina, Vanessa; Alves-Castro, Marian – Education Sciences, 2021
Although Error Analysis (EA) has been broadly used in Foreign Language and Mother Tongue learning contexts, it has not been applied in the field of engineering and by STEM (Science, Technology, Engineering, and Mathematics) students in a systematic way. In this interdisciplinary pilot study, we applied the EA methodology to a wide corpus of…
Descriptors: STEM Education, Instructional Design, Essays, Computational Linguistics
Laurinen, Leena I. – 1988
Sentences are understood by outlining associative relations between the concepts representing the meanings of the words. When the words are received the activation spreads from their conceptual counterparts to the other concepts in memory, so that some implicit thoughts are often added to the mental representation of a sentence. As sentences are…
Descriptors: Adolescents, Associative Learning, Cognitive Processes, Concept Formation