The effect that rounding to prototypical values has on expected duration estimation accuracy

The scheduling component of the time management process was used as a ‘paradigm’ to investigate the estimation of duration of future tasks. Two experiments looked at the effect that the tendency to provide estimates in the form of rounded close approximations had on estimation accuracy. Additionally, the two experiments investigated whether grouping tasks together prior to scheduling would decrease duration estimation error. The majority of estimates provided in both experiments were categorised as rounded close approximations, and were overestimates of the actual time required to complete the experimental tasks. The grouping together of the relatively short tasks used in Experiment 1 resulted in a significant increase in estimation accuracy. A similar result was found in Experiment 2 for relatively long tasks. The results are discussed in relation to the basic processes used to estimate the duration of future tasks, and means by which these scheduling activities can be improved

Prediction-Based Task Assignment in Spatial Crowdsourcing (Technical Report)

Spatial crowdsourcing refers to a system that periodically assigns a number of location-based workers with spatial tasks nearby (e.g., taking photos or videos at some spatial locations). Previous works on the spatial crowdsourcing usually designed task assignment strategies that maximize some assignment scores, which are however only based on available workers/tasks in the system at the time point of assigning workers/tasks. These strategies may achieve local optimality, due to the neglect of future workers/tasks that may join the system. In contrast, in this paper, we aim to achieve "globally" optimal task assignments, by considering not only those present, but also future (via predictions), workers/tasks. Specifically, we formalize an important problem, namely prediction-based spatial crowdsourcing (PB-SC), which expects to obtain a "globally" optimal strategy for worker-and-task assignments, over both present and predicted task/worker locations, such that the total assignment quality score is maximized under the constraint of the traveling budget. In this paper, we design an effective grid-based prediction method to estimate spatial distributions of workers/tasks in the future, and then utilize the predicted ones in our procedure of task assignments. We prove that the PB-SC problem is NP-hard, and thus intractable. Therefore, we propose efficient approximate algorithms to tackle the PB-SC problem, including greedy and divide-and-conquer (D&C) approaches, which can efficiently assign workers to spatial tasks with high quality scores and low budget consumptions, by considering both current and future task/worker distributions. Through extensive experiments, we demonstrate the efficiency and effectiveness of our PB-SC processing approaches on real/synthetic data.Comment: 15 page

Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks

How can we reuse existing knowledge, in the form of available datasets, when solving a new and apparently unrelated target task from a set of unlabeled data? In this work we make a first contribution to answer this question in the context of image classification. We frame this quest as an active learning problem and use zero-shot classifiers to guide the learning process by linking the new task to the existing classifiers. By revisiting the dual formulation of adaptive SVM, we reveal two basic conditions to choose greedily only the most relevant samples to be annotated. On this basis we propose an effective active learning algorithm which learns the best possible target classification model with minimum human labeling effort. Extensive experiments on two challenging datasets show the value of our approach compared to the state-of-the-art active learning methodologies, as well as its potential to reuse past datasets with minimal effort for future tasks

Developing Preservice Teachers’ Mathematical and Pedagogical Knowledge Using an Integrated Approach

This paper describes how an integrated mathematics content and early field-experience course provides opportunities for preservice elementary teachers to develop understanding of mathematics and mathematics teaching. Engaging preservice teachers in solving and discussing mathematical tasks and providing opportunities to implement these tasks with elementary students creates an authentic context for the future teachers to reflect on their own understanding of mathematics, mathematics teaching, and students’ mathematical thinking. Essential elements of the cycle of events in the integrated model of instruction are discussed: preservice students’ acquisition of mathematical concepts in the context of selected tasks in the content course; subsequent posing of mathematical tasks in early field experiences; reflection on work with students; and response to instructors’ feedback

What is a robot companion - friend, assistant or butler?

The study presented in this paper explored people's perceptions and attitudes towards the idea of a future robot companion for the home. A human-centred approach was adopted using questionnaires and human-robot interaction trials to derive data from 28 adults. Results indicated that a large proportion of participants were in favour of a robot companion and saw the potential role as being an assistant, machine or servant. Few wanted a robot companion to be a friend. Household tasks were preferred to child/animal care tasks. Humanlike communication was desirable for a robot companion, whereas humanlike behaviour and appearance were less essential. Results are discussed in relation to future research directions for the development of robot companions

A survey on tasks performed in eldercare

In the Netherlands, a vast increase of the expenses on eldercare is expected for the future. Currently, an IT system is under development that aims to assist care providers with their tasks in providing care services. Before such a system can be used in practice, insight is needed on the current work situation in eldercare. This paper presents interview surveys on tasks currently performed by professionals in two nursing houses. Both the professional population and details on how it spends its time are described. Little room is observed for automating tasks in nursing and/or caring houses