Data and Code underlying the PhD dissertation on Cognitive Assistants to Share Knowledge among Factory Operators

The data and code contained in this collection stem from the research conducted as part of Samuel Kernan Freire's PhD dissertation. The data was collected during empirical and ethnographic studies on conversational AI assistants to support knowledge sharing among factory operators. The research objective was to deepen our knowledge of the opportunities, challenges, impacts, and risks associated with deploying such systems, enabling us to create design guidelines. The data (in CSV format) includes quantitative data for user experience, usability, and workload using standardized surveys. It also contains qualitative data (in CSV format) in the form of comments from factory personnel collected through semi-structured interviews and surveys. We also included the code (python and yaml format) for one of the assistants. The READMEs in the folders contain additional information regarding the methods used. Ethical approval for the collection of data was given by TU Delft's Human Research Ethics Committee. Personally identifiable and confidential data has been removed from the dataset to enable open access.

本合集收录的数据与代码源自Samuel Kernan Freire的博士学位论文相关研究。该数据采集自针对对话式AI助手的实证与民族志研究，旨在支持工厂操作员间的知识共享。本研究的目标在于深化我们对部署此类系统所涉及的机遇、挑战、影响与风险的认知，以此制定相关设计准则。本数据集包含CSV格式的定量数据，涵盖基于标准化问卷采集的用户体验、易用性及工作负荷相关信息；同时还收录了通过半结构化访谈与问卷收集的工厂工作人员评论形式的定性数据，同样采用CSV格式。此外，本合集还包含其中一款助手的代码，格式为Python与YAML。各文件夹内的README文件提供了所用研究方法的补充说明。本数据集的采集已获得代尔夫特理工大学（TU Delft）人类研究伦理委员会的伦理批准。为实现开放获取，数据集已移除所有个人可识别信息与机密数据。