Working with others within an organization can have a variety of positive effects, and the benefits of collaboration have been discussed in various disciplines. In information science, interest in collaborative information seeking, including collaborative information seeking by students in an online learning environment is expanding. This study was aimed at understanding graduate students' collaborative information seeking behaviors through the process of a group project, including factors that affected students' perceptions of collaborative work and their difficulties during the collaborative process. The research was based on Yue and He's model, which describes information users' collaborative communication and information behaviors, and Kuhlthau's model, which describes users' individual information seeking behaviors. The participants were 43 students enrolled in a master's level course delivered primarily online. The students were required to work together in groups to complete a research project. Data were collected through a background survey, behavior survey, and online communication texts and analyzed using descriptive statistics, statistical tests, and content analyses. The results showed significant changes in collaborative and information seeking behaviors and perceptions across three stages of the project during the semester. Theoretical, practical, and methodological implications for future research are discussed.

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The purpose of this study was to collect design requirements from women engineers on artificial intelligence teammates such as Microsoft Teams, Slack, and Trello. A mixed methods research design was used for this study with an online survey and semi-structure interviews. The study results revealed design requirements from women engineers including solutions to sociotechnical issues that could arise from artificial intelligence teammates in the workplace. The results showed various ways women engineers collaborate in the workplace with and without artificial intelligence. Additionally, women engineers' attitude towards artificial intelligence was examined to identify if there was a correlation to self-efficacy. This research study fills a previous study gap that solicited design requirements from research scientists, by soliciting practitioners. Practitioners such as women engineers are underrepresented in the workplace, and they could benefit from an artificial intelligence teammate with their design requirements. Finally, this study contributes to the information science literature on collaborative information seeking, artificial intelligence design, and engineers' information seeking behaviors.