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Autoethnographic Approach to Studying the Affective Information Behavior of a Deaf Student

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HCI International 2019 - Posters (HCII 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1032))

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Abstract

Deaf and hard of hearing students in higher education—a growing population—may acquire substantially less information in the classroom than their hearing peers. Although assistive technologies (AT) are designed to help hearing-impaired students close that information gap, negative experiences using technologies can impede users’ abilities to retrieve information and learn. The author of this study, who is a profoundly deaf Ph.D. student, has conducted an autoethnographic study of his affective experiences using AT in formal and informal educational settings. His experiences, which are documented in an AT Use Diary, have been analyzed using the framework of activity theory. Ultimately, the researcher plans to interview and survey fellow hearing-impaired students, hearing peers, and faculty and staff members, in order to recommend improvements to existing AT, and make higher education most inclusive for students with hearing loss.

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Author information

Authors and Affiliations

  1. University of Tennessee, Knoxville, USA

    Kevin J. Mallary

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  1. Kevin J. Mallary
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Correspondence to Kevin J. Mallary .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

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Mallary, K.J. (2019). Autoethnographic Approach to Studying the Affective Information Behavior of a Deaf Student. In: Stephanidis, C. (eds) HCI International 2019 - Posters. HCII 2019. Communications in Computer and Information Science, vol 1032. Springer, Cham. https://doi.org/10.1007/978-3-030-23522-2_34

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  • DOI: https://doi.org/10.1007/978-3-030-23522-2_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23521-5

  • Online ISBN: 978-3-030-23522-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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