Digital interaction literacy model – conceptualizing competencies for literate interactions with voice-based AI systems
Open accessAbstract
AI-based systems, and especially voice-based AI systems, are gaining popularity and set novel requirements for end users. Research has provided first approaches postulating and conceptualizing AI-related user competencies. However, voice-based technology utilizing spoken language for operation has been neglected so far. This study presents qualitative interviews of 12 experts in research, development, or design of voice-based AI and explores the skills and competencies which are needed to interact with VBAI in a self-determined and mindful manner. Analyses highlight that, contrary to existing assumptions and providers’ advertising promises, not only language skills but a wider variety of competencies is required. As a result, ten skills and competencies are derived and integrated into the model of “Digital Interaction Literacy - DIL”. The current paper contributes to a holistic model of AI Literacy using the example of voice-based AI technology. Wider implications for practice and science are discussed.
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The Meta AI Literacy Scale (MAILS) is a self-assessment instrument for measuring AI literacy and additional psychological competencies (problem-solving, learning, self-efficacy, persuasion literacy) that are assumed to support successful interaction with AI.
“The Meta AI Literacy Scale (MAILS; [10]) is a scale for measuring AI literacy and other psychological competencies (problem-solving, learning, self-efficacy, persuasion literacy) that are assumed to support successful interaction with AI [[17], [18], [19]].”
From Meta AI literacy scale: Further validation and development of a short version (2024) · cites this paper as [17]
So far, there is some conceptual thinking to include such aspects, but no measurement tool yet.
“So far, there is some conceptual thinking to include such aspects [8-10, 13, 47], but no measurement tool yet.”
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Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2023.100014 · Cited by 488 · see citing works
Self-citationExamining artificial intelligence literacy among pre-service teachers for future classrooms
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Ma, S., & Chen, Z. (2024) · IEEE Access · doi:10.1109/access.2024.3468378 · Cited by 55 · see citing works
Meta AI literacy scale: Further validation and development of a short version
Koch, M. J., Carolus, A., Wienrich, C., & Latoschik, M. E. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e39686 · Cited by 44 · see citing works
Self-citation
- Authors
- Carolus, A., Augustin, Y., Markus, A., & Wienrich, C.
- Affiliations
- University of Würzburg (DE)
- Corresponding author
- Carolus, Astrid
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2023
- Volume
- 4
- Pages
- 100114
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4312084956
- Cited by
- 128
- References
- 13
- Citations by year
- 2026: 32 · 2025: 44 · 2024: 43 · 2023: 8 · 2022: 1
- FWCI
- 20.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Bayerische Akademie der Wissenschaften
- Topics
- Physical Sciences › Computer Science › Information Systems › Digital literacy in education
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Literacy, Media, and Education
- Keywords
- AI literacy, user competence, voice assistants, expert interviews, self-determination
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