Task analysis

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

A comparison of performance on the Towers of London and Hanoi in young children.

Abstract: Background: The Towers of London (TOL) and Hanoi (TOH) have been viewed as equivalent measures of planning and/or problem solving, although recent evidence in adults suggests that the underlying measurement characteristics of these two tasks may differ As tower tasks are one of the few instruments that can be used to assess executive functioning in young children, the cognitive demands for both tasks merit further examination Methods: The relation among tower tasks and those of short-term memory, inhibition, and shifting ability were examined in a sample of 118 typically developing young children (M age = 4 years, 9 months, SD = 6 months) Half the children completed TOL and half completed TOH, with groups matched with respect to age, sex, and child vocabulary Results: Whilst performance on a shifting task uniquely predicted TOH performance, none of the executive function measures were related to TOL performance after statistically controlling for the influence of baseline naming speed For both tower tasks, performance on a shifting task contributed more strongly on complex trials that required more moves in the counter-intuitive direction relative to the end-state goal, whereas inhibition task performance only predicted performance on complex TOL trials Conclusions: Successful tower task performance may be determined, at least at higher levels of complexity, by mental flexibility in this age range However, overall the findings suggest that TOL and TOH are not interchangeable tasks even in young children, and more generally, raise methodological issues regarding the complex nature of executive function tasks

Teaching methods for modelling problems and students’ task-specific enjoyment, value, interest and self-efficacy expectations

Abstract: In this study which was part of the DISUM-project, 224 ninth graders from 14 German classes from middle track schools (Realschule) were asked about their enjoyment, interest, value and self-efficacy expectations concerning three types of mathematical problems: intra-mathematical problems, word problems and modelling problems. Enjoyment, interest, value and self-efficacy were assessed before and after a ten-lesson teaching unit promoting modelling competency related to the topics “Pythagoras’ theorem” and “linear functions”. The study aimed to answer the following research questions: (1) Do students’ enjoyment, value, interest and self-efficacy expectations differ depending on the type of task? (2) Does the treatment of modelling problems in classroom instruction influence these variables? (3) Are there any differential effects for different ways of teaching modelling problems, including a “directive”, teacher-centred instruction and an “operative-strategic”, more student-centred instruction emphasising group work and strategic scaffolding by the teacher? The findings show that there were no differences in students’ enjoyment, interest, value and self-efficacy between the three types of tasks. However, teaching oriented towards modelling problems had positive effects on some of the student variables, with the student-centred teaching method producing the most beneficial effects.

Task Design: A Literature Review

Abstract: The post-Hulin and Blood task design literature is reviewed, and several observations are made Individual differences (especially growth need strength) and organization variables moderate, affective responses (especially satisfaction with work) are most predictable, objective measures are needed; dimensionality is variable; optimal combinatory models are not widely accepted; and methodological problems are widespread.

Personalized Privacy-Preserving Task Allocation for Mobile Crowdsensing

Abstract: Location information of workers are usually required for optimal task allocation in mobile crowdsensing, which however raises severe concerns of location privacy leakage. Although many approaches have been proposed to protect the locations of users, the location protection for task allocation in mobile crowdsensing has not been well explored. In addition, to the best of our knowledge, none of existing privacy-preserving task allocation mechanisms can provide personalized location protection considering different protection demands of workers. In this paper, we propose a personalized privacy-preserving task allocation framework for mobile crowdsensing that can allocate tasks effectively while providing personalized location privacy protection. The basic idea is that each worker uploads the obfuscated distances and personal privacy level to the server instead of its true locations or distances to tasks. In particular, we propose a Probabilistic Winner Selection Mechanism (PWSM) to minimize the total travel distance with the obfuscated information from workers, by allocating each task to the worker who has the largest probability of being closest to it. Moreover, we propose a Vickrey Payment Determination Mechanism (VPDM) to determine the appropriate payment to each winner by considering its movement cost and privacy level, which satisfies the truthfulness, profitability, and probabilistic individual rationality. Extensive experiments on the real-world datasets demonstrate the effectiveness of the proposed mechanisms.