Coding Guide and Qualitative Content Analysis of a Student-Designed AI-Supported Immersive Training System (Supplementary Material)

This dataset provides the supplementary material for the practice paper "Gestaltung eines KI-gestützten immersiven Trainingssystems durch nicht-informatiknahe Studierende", presented at the XR-Learning workshop (DELFI 2026). It documents the qualitative content analysis of an exploratory case study on a university seminar in which students from business and social science programmes (without a computer science background) conceived and prototyped an AI-supported immersive Virtual Reality training system for difficult counseling conversations in a job center. The data were collected at three points during the seminar (n = 8): short written reflections at the start, group interviews with the AI and VR subgroups, and a final questionnaire. The analysis follows Mayring's qualitative content analysis with deductive main categories derived from the guiding questions and inductively developed subcategories. The category system is fully operationalised, with a definition, anchor examples, and explicit coding rules including delimitation rules between related categories. The file contains two sheets: (1) the coding guide with 20 categories across the three areas "experiencing the design process", "challenges", and "enabling conditions", and (2) the documentation of the analysis with 184 coded text segments, each with source, quotation, paraphrase, category, and an optional comment. All personal names have been anonymised. The coded material is in German.