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This study examined the reliability and validity of the Childbirth Self-Efficacy Inventory (CBSEI) (Lowe 1993) in a sample of 100 Australian women. Consistent with US data, the measure was shown to have high internal consistency. Validity of the instrument was determined by applying self-efficacy theory (Bandura 1982), which predicts that parity should have(More)
We present a model for detecting user disengagement during spoken dialogue interactions. Intrinsic evaluation of our model (i.e., with respect to a gold standard) yields results on par with prior work. However, since our goal is immediate implementation in a system that already detects and adapts to user uncertainty , we go further than prior work and(More)
This paper explores automatically detecting student zoning out while performing a spoken learning task. Standard supervised machine learning techniques were used to create classification models, built on prosodic and lexical features. Our results suggest these features create models that can outperform a Bag of Words baseline.
Algorithms for stable marriage and related matching problems typically assume that full preference information is available. While the Gale-Shapley algorithm can be viewed as a means of eliciting preferences incrementally, it does not prescribe a general means for matching with incomplete information , nor is it designed to minimize elicitation. We propose(More)
We explore the frequency and impact of misunderstandings in an existing corpus of tutorial dialogues in which a student appears to get an interpretation that is not in line with what the system developers intended. We found that this type of error is frequent, regardless of whether student input is typed or spoken, and that it does not respond well to(More)
While stable matching problems are widely studied, little work has investigated schemes for effectively eliciting agent preferences using either preference (e.g., comparison) queries or interviews (to form such comparisons); and no work has addressed how to combine both. We develop a new model for representing and assessing agent preferences that(More)
How families appraise difficult situations contributes to later adaptive functioning. We have observed in both research and practice that when appraising their infants' crying, mothers often compared their own infants' crying to actual or supposed much worse infants. They typically appraised their infants to be crying less than average infants. This(More)
Stable matching problems (SMPs) arising in real-world markets often have extra complementarities in the participants' preferences. These complementarities break many of the theoretical properties of SMP and make it computationally hard to find a stable matching. A common complementarity is the introduction of couples in labor markets, which gives rise to(More)
In this paper, we examine whether it is possible to automatically classify patterns of interactions using a state transition model and identify successful versus unsuccessful student Q&A discussions. For state classification, we apply Conditional Random Field and Hidden Markov Models to capture transitions among the states. The initial results indicate that(More)
Many dialogue system developers use data gathered from previous versions of the dialogue system to build models which enable the system to detect and respond to users' affect. Previous work in the dialogue systems community for domain adaptation has shown that large differences between versions of dialogue systems affect performance of ported models. Thus,(More)