André Markus, M.Sc.

André Markus M. Sc.

Wissenschaftlicher Mitarbeiter

Research Assistant / PhD Student

Psychologie Intelligenter Interaktiver Systeme
Julius-Maximilians-Universität Würzburg
Institut für Mensch-Computer-Medien
Universität Würzburg
Emil-Fischer-Straße 50
97074 Würzburg
Deutschland

Mini-CV

Since 2021 research assistant in the MOTIV project as part of the AI Psychology research group.
Studied Psychology (B.Sc. and M.Sc.) specializing in Digital Game Studies, Virtual Reality and Media at the Technical University of Darmstadt.
Studied Media and Instructional Psychology (M.Sc.) at the Technical University of Chemnitz.
Worked as a student assistant for the Chair of Educational Psychology at TU Darmstadt (2015-2017).
Worked as a student assistant for Forschungsinstitut für Betriebliche Bildung (2019-2020).
Freelancer for Video Production, Instructional Design and Science Communication.

Research Interests

User Experience
Virtual Environments
Voice Control Systems
Gaming-Psychology and Player Experience
Social Media and Streaming (YouTube, Twitch)

Media (Extracts)

GameStar (2020). Welcher Spieler-Typ bist du? [Video]

GameStar (2019). Warum SPOILER nicht immer schlecht sind! [Video]

Psychologie-lernen.de (2020). Ist das Gähnen virtueller Agenten ansteckend? [Video]

GIGA (2021). Mit ganz simplen Tricks: So manipulieren uns God of War, Zelda und Harry Potter. [Artikel]

Psychologie-lernen.de (2020). Videospiele in der Psychotherapie - Depression und Angst loswerden. [Video]

Publications

Wienrich, Carolin, Astrid Carolus, André Markus, Yannik Augustin, Jan Pfister, and Andreas Hotho. “Long-Term Effects of Perceived Friendship With Intelligent Voice Assistants on Usage Behavior, User Experience, and Social Perceptions”. Computers 12, no. 4 (2023): 77. https://doi.org/https://doi.org/10.3390/computers12040077.
- [ Abstract ]
- [ BibTeX ]
- [ URL ]
- [ DOI ]
Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.

@article{noauthororeditor2023longterm, abstract = {Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.}, author = {Wienrich, Carolin and Carolus, Astrid and Markus, André and Augustin, Yannik and Pfister, Jan and Hotho, Andreas}, journal = {Computers}, keywords = {a.carolus}, number = 4, pages = 77, title = {Long-Term Effects of Perceived Friendship with Intelligent Voice Assistants on Usage Behavior, User Experience, and Social Perceptions}, volume = 12, year = 2023 }
Wienrich, Carolin, Astrid Carolus, André Markus, and Yannik Augustin. AI Literacy: Kompetenzdimensionen und Einflussfaktoren im Kontext von Arbeit, Pub. L. No. 1, 1 (2022).
- [ BibTeX ]
@standard{wienrich2022literacy, author = {Wienrich, Carolin and Carolus, Astrid and Markus, André and Augustin, Yannik}, howpublished = {Working Paper}, institution = {KI-Observatorium des Bundesministeriums für Arbeit und Soziales}, keywords = {AI_Literacy}, number = 1, pages = {1-24}, title = {AI Literacy: Kompetenzdimensionen und Einflussfaktoren im Kontext von Arbeit}, type = {Publication}, volume = 1, year = 2022 }
Carolus, Astrid, Yannik Augustin, André Markus, and Carolin Wienrich. “Digital Interaction Literacy Model. Conceptualizing Competencies for Literate Interactions With Voice-Based AI Systems”. Computers and Education: Artificial Intelligence, December 2022, 100114. https://doi.org/10.1016/j.caeai.2022.100114.
- [ BibTeX ]
- [ DOI ]
@article{Carolus_2022, author = {Carolus, Astrid and Augustin, Yannik and Markus, André and Wienrich, Carolin}, journal = {Computers and Education: Artificial Intelligence}, keywords = {yaugustin}, month = {dec}, pages = 100114, publisher = {Elsevier BV}, title = {Digital interaction literacy model. Conceptualizing competencies for literate interactions with voice-based AI systems}, year = 2022 }
Wienrich, Carolin, Astrid Carolus, Yannik Augustin, and André Markus. “AI Literacy: Kompetenzdimensionen Und Einflussfaktoren Im Kontext Von Arbeit.”.
- [ BibTeX ]
@preprint{wienrich2021literacy, author = {Wienrich, Carolin and Carolus, Astrid and Augustin, Yannik and Markus, André}, institution = {KI-Observatorium des Bundesministeriums für Arbeit und Soziales}, keywords = {a.carolus}, title = {AI Literacy: Kompetenzdimensionen und Einflussfaktoren im Kontext von Arbeit.}, type = {Publication}, year = 2021 }