Characterizing and Predicting Tasks at Risk in Team Task Management
Collaborative project management involves interacting with various tasks in a shared planning space where members add, assign, complete, and edit project-related tasks to have a shared view of the project’s status. This process directly impacts how individual team members select, prioritize, and org...
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| Other Authors: | |
| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/143357 |
| _version_ | 1826209958061932544 |
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| author | Soliman, Nouran |
| author2 | Karger, David R. |
| author_facet | Karger, David R. Soliman, Nouran |
| author_sort | Soliman, Nouran |
| collection | MIT |
| description | Collaborative project management involves interacting with various tasks in a shared planning space where members add, assign, complete, and edit project-related tasks to have a shared view of the project’s status. This process directly impacts how individual team members select, prioritize, and organize tasks on which to focus on a daily basis. However, such coordination and task prioritization can become increasingly challenging for individuals working on multiple projects with big teams. Accordingly, tasks could become at risk and eventually not be completed on time, leading to personal or team losses in many situations. To support task-doers in completing their tasks, we conducted a mixed-methods study focusing on Microsoft Planner—a collaborative project management tool—to understand how users manage their tasks in a team setting, what challenges they encounter, and their preferred solutions. Based on the findings from a qualitative survey with 151 participants and our Planner log data analysis, we further developed a task at risk prediction model using various task characteristics and user actions. Our experimental results suggest that a task at risk can be classified with high effectiveness (accuracy of 89%). Our work provides novel insights on how users manage their tasks in team task management tools, what challenges they face, how they perceive a task at risk, and how tasks at risk can be modeled. Such an application can significantly improve the user experience in such tools by providing a personal assistant that helps users prioritize their tasks and pay attention to critical situations. |
| first_indexed | 2024-09-23T14:37:14Z |
| format | Thesis |
| id | mit-1721.1/143357 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T14:37:14Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1433572022-06-16T03:15:50Z Characterizing and Predicting Tasks at Risk in Team Task Management Soliman, Nouran Karger, David R. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Collaborative project management involves interacting with various tasks in a shared planning space where members add, assign, complete, and edit project-related tasks to have a shared view of the project’s status. This process directly impacts how individual team members select, prioritize, and organize tasks on which to focus on a daily basis. However, such coordination and task prioritization can become increasingly challenging for individuals working on multiple projects with big teams. Accordingly, tasks could become at risk and eventually not be completed on time, leading to personal or team losses in many situations. To support task-doers in completing their tasks, we conducted a mixed-methods study focusing on Microsoft Planner—a collaborative project management tool—to understand how users manage their tasks in a team setting, what challenges they encounter, and their preferred solutions. Based on the findings from a qualitative survey with 151 participants and our Planner log data analysis, we further developed a task at risk prediction model using various task characteristics and user actions. Our experimental results suggest that a task at risk can be classified with high effectiveness (accuracy of 89%). Our work provides novel insights on how users manage their tasks in team task management tools, what challenges they face, how they perceive a task at risk, and how tasks at risk can be modeled. Such an application can significantly improve the user experience in such tools by providing a personal assistant that helps users prioritize their tasks and pay attention to critical situations. S.M. 2022-06-15T13:14:58Z 2022-06-15T13:14:58Z 2022-02 2022-03-04T20:59:54.436Z Thesis https://hdl.handle.net/1721.1/143357 In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Soliman, Nouran Characterizing and Predicting Tasks at Risk in Team Task Management |
| title | Characterizing and Predicting Tasks at Risk in Team Task Management |
| title_full | Characterizing and Predicting Tasks at Risk in Team Task Management |
| title_fullStr | Characterizing and Predicting Tasks at Risk in Team Task Management |
| title_full_unstemmed | Characterizing and Predicting Tasks at Risk in Team Task Management |
| title_short | Characterizing and Predicting Tasks at Risk in Team Task Management |
| title_sort | characterizing and predicting tasks at risk in team task management |
| url | https://hdl.handle.net/1721.1/143357 |
| work_keys_str_mv | AT solimannouran characterizingandpredictingtasksatriskinteamtaskmanagement |