In this paper, we present an approach to select a subset of requirement elicitation technique for an optimum result in the requirement elicitation process. Our approach consists of three steps. First, we identify various attribute in three important dimensions namely project, people and the process of software development that can influence the outcome of an elicitation process. Second, we cons...

At an initial time, individual forms a belief about future random outcome. As time passes, the may obtain, privately or subjectively, further information, until outcome is eventually revealed. How can protocol be devised that induces individual, as strict best response, to reveal at outset his prior assessment of both final and information flows he anticipates and, subsequently, what receives? ...

A planner wants to elicit information about an agent's preference relation, but not the entire ordering. Specifically, preferences are grouped into “types,” and only type. We first assume that beliefs randomization subjective, show a space of types is elicitable if each type defined by what agent would choose from some list menus. If objective, then additional spaces can be elicited, though con...

This study investigates the effect of four types of oral corrective feedback, namely, explicit elicitation, implicit elicitation, explicit recast and implicit recast on the most commonly mispronounced phonological features among Iranian EFL learners through immediate uptake and retention. Five classes were randomly categorized into four experimental groups and one control group, each with 18 in...

BACKGROUND Expert opinion is often sought to complement available information needed to inform model-based economic evaluations in health technology assessments. In this context, we define expert elicitation as the process of encoding expert opinion on a quantity of interest, together with associated uncertainty, as a probability distribution. When availability for face-to-face expert elicitati...

The study of property elicitation is gaining ground in statistics and machine learning as a way to view and reason about the expressive power of emiprical risk minimization (ERM). Yet beyond a widening frontier of special cases, the two most fundamental questions in this area remain open: which statistics are elicitable (computable via ERM), and which loss functions elicit them? Moreover, recen...