Motivation

Nowadays, with the raise of sensor technology (e.g., smartwatches) and artificial intelligence (AI), more and more user-adaptive systems arise. Such systems collect user data (for example, biosignals like heart rate (ECG data) or gaze (eye-tracking data)), recognize a user state (e.g., stress, joy, negative emotions) and adapt the system (e.g., via changes in the user’s system, notification that aims to change a user’s behavior or simple notification on current stress level).
Specifically, in video meetings, leveraging biosignals can be helpful to detect unpleasant user states (e.g. stress negative emotions, fatigue, high cognitive effort, nervousness). By detecting such states and intervening (e.g. attention feedback, suggestion to take breaks, supporting in calming down when having negative emotions), the users can be supported in having better meetings.
User-adaptive video meeting systems (VMS) can provide feedback for individual users. Furthermore, adaptations can also be used in group settings, e.g., during virtual meetings. Currently, besides prescriptive design knowledge, also descriptive knowledge on the users’ perception regarding acceptance and use of adaptive VMS and the underlying processes is limited. However, to design and implement user- adaptive VMS, it is important to better understand factors that influence acceptance and use of such systems.
Critical elements for user-adaptation of VMS cover both, technical aspects (e.g. the timing of the adaptation, the performance of the underlying classification algorithm) and user-centric aspects (e.g. what information should be displayed, which type of information is perceived as helpful, what information can or cannot be shared with other participants in the call). Concerns and drivers for accepting and using user- -based adaptations in VMS could be related to privacy concerns, but also to the design of specific system features.
This thesis shall investigate potential challenges and drivers for acceptance and use of user-adaptive VMS. Therefore, the student should review existing work and develop a survey to assess the user’s opinion regarding user-adaptive VMS. Based on the findings, design suggestions for user-adaptive VMS shall be derived.

Goal of the thesis

• Review related work and existing survey/interview guides
• Create a survey
• Potentially conduct follow-up interviews
• Analyze results

Recommended Skills

• Strong time management and communication skills
• Interest in implications of technology
• Strong analytical and English skills
• Experience in surveys is recommended, but not needed

Contact

If you are interested in this topic and want to apply for this thesis, please contact Julia Seitz with your CV and current transcript of records. Feel free to reach out beforehand if you have any questions.