Task analysis

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

Variations in Decision Makers' Use of Information Sources: The Impact of Quality and Accessibility of Information

Abstract: Variations in the reported frequency of use of four information sources by decision makers was investigated. Although the perceived quality of information available for decision making was related ...

Instructional Development for Training Teachers of Exceptional Children: A Sourcebook.

Abstract: Presented in the sourcebook for the teacher rduCgtor is the Four -D model (define, design, develop, and disseminate) to be used for developing instructional materials for training teachers of exceptional children. Listed at the begOning of chapters are instructional objectives; included when-appropriate are guidelines, checklists, and flow charts. Given for use of the book are instructions such as reading chapter 1 for an overview, choosing a topic, and checking chapter objectives for essenttalnese to task accomplishment. Noted in the introdUction are the transition in special education that requires teachers to demonstrate competency, the efficacy and validity of special training programs, and the role of the Four-D model. The stage categorized as "define" is described to be analytical and to involve five steps: front-end analysis (problems facing the teacher trainer), learner analysis, task analysis, concept analysis, and the specifying of instructional objectives. The next stage is seen to involve the design of prototype instructional material and to comprise four steps: construction of criterion referenced tests, media selection, format selection, and initial design for presentation of instruction through media such as tests, textbooks, audiotutorial models, and computer assisted instruction. The developmental stage is said to comprise modification of the prototype material through expert appraisal and developmental testing. Described for the final stage (disseminate) are summative evaluation, final packaging activities such as securing copyright releases, and diffusion. (MC) U I DEPARTMENT OF HEALTH. EDUCATION & WELFARE NATIONAL INSTITUTE OF EDUCATION IH$S DOCJMENT HAS BEEN REPRO DUCE D EXACTLY AS RECEIVED FROM 1HE PERSON OR ORGANIZATION ORIGIN ATING IT POINTS OF VIEW OR OPINIONS STATED DO NOT NECESSARILY REPRE SENT OFFICIAL NATIONAL INSTITUTE OF EDUCATION POSITION OR POLICY

Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks

Abstract: Mobile-edge computing (MEC) is an emerging paradigm that provides a capillary distribution of cloud computing capabilities to the edge of the wireless access network, enabling rich services and applications in close proximity to the end users. In this paper, an MEC enabled multi-cell wireless network is considered where each base station (BS) is equipped with a MEC server that assists mobile users in executing computation-intensive tasks via task offloading. The problem of joint task offloading and resource allocation is studied in order to maximize the users’ task offloading gains, which is measured by a weighted sum of reductions in task completion time and energy consumption. The considered problem is formulated as a mixed integer nonlinear program (MINLP) that involves jointly optimizing the task offloading decision, uplink transmission power of mobile users, and computing resource allocation at the MEC servers. Due to the combinatorial nature of this problem, solving for optimal solution is difficult and impractical for a large-scale network. To overcome this drawback, we propose to decompose the original problem into a resource allocation (RA) problem with fixed task offloading decision and a task offloading (TO) problem that optimizes the optimal-value function corresponding to the RA problem. We address the RA problem using convex and quasi-convex optimization techniques, and propose a novel heuristic algorithm to the TO problem that achieves a suboptimal solution in polynomial time. Simulation results show that our algorithm performs closely to the optimal solution and that it significantly improves the users’ offloading utility over traditional approaches.

Cognitive task analysis

Abstract: Cognitive task analysis is defined as the extension of traditional task analysis techniques to yield information about the knowledge, thought processes and goal structures that underlie observable task performance. Cognitive task analyses are conducted for a wide variety of purposes, including the design of computer systems to support human work, the development of training, and the development of tests to certify competence. As part of its Programme of Work, NATO Research Study Group 27 on Cognitive Task Analysis has undertaken the task of reviewing existing cognitive task analysis techniques. The Group concludes that few integrated methods exist, that little attention is being paid to the conditions under which methods are appropriate, and that often it is unclear how the products of cognitive task analysis should be used. RSG.27 has also organized a workshop with experts in the field of cognitive task analysis. The most important issues that were discussed during the workshop were: (1) the use of CTA in the design of new systems, (2) the question when to use what technique, and (3) the role of CTA in system design. RSG.27 emphasizes: (1) that is important for the CTA community to be able to empirically demonstrate the added value of a CTA; (2) it is critical for the success of CTA to be involved in the design process from the start to finish, and to establish clear links with methods that are used by other disciplines, and (3) recommends that more research effort be directed to the issue of the reliability of CTA techniques. (P)