Task analysis

About: Task analysis is a research topic. Over the lifetime, 10432 publications have been published within this topic receiving 283481 citations.

Low-Performing Students and Teaching Fractions for Understanding: An Interactional Analysis

Abstract: This article presents an analysis of two low-performing students’ experiences in a firstgrade classroom oriented toward teaching mathematics for understanding. Combining constructs from interactional sociolinguistics and developmental task analysis, I investigate the nature of these students’ participation in classroom discourse about fractions. Pre- and post-instruction interviews documenting learning and analysis of classroom interactions suggest mechanisms of that learning. I propose that three main factors account for these two students’ success: use of tasks that elicited the students’ prior understanding, creation of a variety of participant frameworks (Goffman, 1981) in which the students were treated as mathematically competent, and frequency of opportunities for identity-enhancing interactions.

Task recommendation in crowdsourcing systems

Abstract: In crowdsourcing systems, tasks are distributed to networked people to complete such that a company's production cost can be greatly reduced. Obviously, it is not efficient that the amount of time for a worker spent on selecting a task is comparable with that spent on working on a task, but the monetary reward of a task is just a small amount. The available worker history makes it possible to mine workers' preference on tasks and to provide favorite recommendations. Our exploratory study on the survey results collected from Amazon Mechanical Turk (MTurk) shows that workers' histories can reflect workers' preferences on tasks in crowdsourcing systems. Task recommendation can help workers to find their right tasks faster as well as help requesters to receive good quality output quicker. However, previously proposed classification based task recommendation approach only considers worker performance history, but does not explore worker task searching history. In our paper, we propose a task recommendation framework for task preference modeling and preference-based task recommendation, aiming to recommend tasks to workers who are likely to prefer to work on and provide output that accepted by requesters. We consider both worker performance history and worker task searching history to reflect workers' task preference more accurately. To the best of our knowledge, we are the first to use matrix factorization for task recommendation in crowdsourcing systems.

The cognitive task analysis methods for job and task design: review and reappraisal

Abstract: This paper reviews and reappraises the current research on the cognitive task analysis methodology for job or task design and analysis. Specifically, it classifies the current cognitive task analysis methods for job or task design and analysis, sorts out commonalities and differences among all these cognitive task analysis methodology for job and task design and analysis by conducting pros and cons comparisons, and provides guidelines in selecting cognitive task analysis methods for job and task design and analysis. Moreover, based on the current literature review, a validated human-centered information-processing model for cognitive task performance was developed based on human information processing theory. This new model focuses on identifying all cognitive aspects of human performance in technical work, with the goal of assisting job (re)design to increase human job performance.

Actionable reminder entries

Abstract: Techniques for processing task items are provided. A task item is electronic data that represents a task to be performed, whether manually or automatically. A task item includes one or more details about its corresponding task, such as a description of the task and a location of the task. Specifically, techniques for generating task items, organizing task items, triggering notifications of task items, and consuming task items are described. In one approach, a task item is generated based on input from a user and context of the input. In another approach, different attributes of task items are used to organize the task items intelligently into multiple lists. In another approach, actions other than the generation of notification are enabled or automatically performed, actions such as emailing, calling, texting, and searching.