Designing and Evaluating a Conversational ELN Interaction Concept under Simulated AI Conditions: A Wizard-of-Oz Study in Scientific Research Contexts

Kurzfassung

Electronic Laboratory Notebooks (ELN) have become central infrastructures for scientific documentation, offering structured data storage, traceability, and regulatory compliance. However, their prevailing interaction paradigm remains predominantly form-based and keyboard-centered, which may conflict with laboratory realities such as sterility constraints, multitasking, and distributed collaboration. This thesis investigates how a conversational interaction concept for ELN can be designed and evaluated under simulated AI conditions, with a primary focus on interaction structure rather than algorithmic performance. Grounded in Human–Computer Interaction (HCI) theory and informed by Computer-Supported Collaborative Learning (CSCL), the work conceptualizes the ELN as a socio-technical artifact that mediates cognition, documentation practices, and collaborative continuity. Design foundations were derived from literature-informed considerations, insights from a DLR user requirements survey, and contextual observations from Kadi4Mat and POLiS laboratory environments. These inputs were synthesized into structural design drivers, including multimodal interaction, in-situ documentation support, human-in-the-loop control, and transparency in AI mediated workflows. A Wizard-of-Oz (WoZ) study was conducted to evaluate the conversational ELN prototype under simulated AI conditions. Voice-based documentation and chatbot-style retrieval were manually simulated to isolate interaction effects from technical AI limitations. A baseline condition using traditional documentation was compared with the prototype. Quantitative measures included the System Usability Scale (SUS), NASA-TLX workload assessment, and a Trust in Automation scale, complemented by qualitative interviews. Due to the exploratory design and limited sample size, quantitative results were analyzed descriptively. Findings suggest that conversational interaction structures appear promising for supporting perceived workflow fluidity and contextual retrieval when technical performance is assumed optimal. At the same time, issues of predictability, transparency, and epistemic responsibility emerged as critical design considerations. The thesis contributes to HCI research by empirically examining conversational interaction paradigms within high-stakes scientific documentation contexts using a methodologically controlled simulation approach.