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A Comparison of Spoken and Written Language Use in Traditional and Technology-Mediated Learning Environments. TOEFL® Research Report. RR-94. ETS RR-21-16

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Title: A Comparison of Spoken and Written Language Use in Traditional and Technology-Mediated Learning Environments. TOEFL® Research Report. RR-94. ETS RR-21-16
Language: English
Authors: Kyle, Kristopher, Choe, Ann Tai, Eguchi, Masaki, LaFlair, Geoff, Ziegler, Nicole
Source: ETS Research Report Series. Dec 2021.
Availability: Educational Testing Service. Rosedale Road, MS19-R Princeton, NJ 08541. Tel: 609-921-9000; Fax: 609-734-5410; e-mail: RDweb@ets.org; Web site: https://www.ets.org/research/policy_research_reports/ets
Peer Reviewed: Y
Page Count: 29
Publication Date: 2021
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Comparative Analysis, Second Language Learning, English (Second Language), Language Tests, Computer Assisted Testing, Academic Language, Speech Communication, Writing Tests, Computational Linguistics, Integrated Learning Systems, Language Usage, Test Validity, Computer Assisted Instruction, Scores, Teaching Methods, Conventional Instruction, Higher Education, College Admission, Admission Criteria
Assessment and Survey Identifiers: Test of English as a Foreign Language
ISSN: 2330-8516
Abstract: A key piece of a validity argument for a language assessment tool is clear overlap between assessment tasks and the target language use (TLU) domain (i.e., the domain description inference). The TOEFL 2000 Spoken and Written Academic Language (T2K-SWAL) corpus, which represents a variety of academic registers and disciplines in traditional learning environments (e.g., lectures, office hours, textbooks, course packs), has served as an important foundation for the TOEFL iBT®test's domain description inference for more than 15 years. There are, however, signs that the characteristics of the registers that students encounter may be changing. Increasingly, typical university courses include technology-mediated learning environments (TMLEs), such as those represented by course management software and other online educational tools. To ensure that the characteristics of TOEFL iBT test tasks continue to align with the TLU domain, it is important to analyze the registers that are typically encountered in TMLEs. In this study, we address this issue by collecting a relatively large (4.5 million words) corpus of spoken and written TMLE registers across the six primary disciplines represented in T2KSWAL. This corpus was subsequently tagged for a wide variety of linguistic features, and a multidimensional analysis was conducted to compare and contrast written and spoken language in TMLE and T2K-SWAL. The results indicate that although some similarities exist across spoken and written texts in traditional learning environments and TMLEs, language use also differs across learning environments (and modes) with regard to key linguistic dimensions.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1340797
Database: ERIC
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  Data: A key piece of a validity argument for a language assessment tool is clear overlap between assessment tasks and the target language use (TLU) domain (i.e., the domain description inference). The TOEFL 2000 Spoken and Written Academic Language (T2K-SWAL) corpus, which represents a variety of academic registers and disciplines in traditional learning environments (e.g., lectures, office hours, textbooks, course packs), has served as an important foundation for the TOEFL iBT®test's domain description inference for more than 15 years. There are, however, signs that the characteristics of the registers that students encounter may be changing. Increasingly, typical university courses include technology-mediated learning environments (TMLEs), such as those represented by course management software and other online educational tools. To ensure that the characteristics of TOEFL iBT test tasks continue to align with the TLU domain, it is important to analyze the registers that are typically encountered in TMLEs. In this study, we address this issue by collecting a relatively large (4.5 million words) corpus of spoken and written TMLE registers across the six primary disciplines represented in T2KSWAL. This corpus was subsequently tagged for a wide variety of linguistic features, and a multidimensional analysis was conducted to compare and contrast written and spoken language in TMLE and T2K-SWAL. The results indicate that although some similarities exist across spoken and written texts in traditional learning environments and TMLEs, language use also differs across learning environments (and modes) with regard to key linguistic dimensions.
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      – SubjectFull: Second Language Learning
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      – SubjectFull: English (Second Language)
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      – SubjectFull: Language Tests
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