Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

Statistical Dialog Management for Health Interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.

Propuestas para una reconceptualización surrealista y postmoderna de la sexualidad femenina en los textos de Cristina Escofet e Isabel Allende

Female sexuality has commonly been viewed as the passive counterpart of male sexuality. Building upon Adrienne Rich's theory of compulsive heterosexuality, I would suggest that the fundamental location of this problem lies within the subconscious. Cristina Escofet's stance on this issue is to argue in favor of a deconstruction of Jungian archetypes, revealing their constructed rather than intrinsic character. In this dissertation, I study representative texts by Escofet and Isabel Allende and show not only how they depict patriarchal compulsive heterosexuality, but also try to reconceptualize female sexuality through surrealist and postmodern techniques such as self-reflection, dialogue with our double or Other, and sensorial perception. These techniques are designed to create a new epistemology of jouissance and excess, as defined by contemporary French theory. The significance of my study resides in the interdisciplinary analysis of female sexuality in Hispanic feminist writers. The first chapter proposes that surrealism, postmodernism, and feminism are theoretical frameworks which create new paradigms for social change. In their feminist philosophies, Escofet and Allende emphasize the use of subconscious knowledge as a means of helping them understand the world and create alternative realities. The second chapter shows how Escofet and Allende deconstruct the mysoginist archetype of Eve, which has been largely responsible for identifying women's sexual identity with the disreputable qualities of the femme fatale and whose mirror-image has long plagued women. In accordance with this stereotype, Lillith (Adam's sexually active ex-partner), has typically been portrayed as the negative Other, and for generations the she-devil myth which surrounds her has resurfaced in the media, where she assumes the role of innumerable evil female characters. In the third chapter, I examine how class and race differences have been used to intensify the demonization of different types of sexuality. In the same manner as Lillith and Eve, black and indigenous characters express dissent by retelling their stories in words and performance, and by seeking to form a dialog with their readers. The last chapter deals with the importance of the senses for female characters as they try to create their own sexuality from the fragmented bodies we find in surrealist and postmodern art. In this section we shall see how Luce Irigaray and Hélène Cixous's theories about multiple sexualities are in evidence when Escofet and Allende reconceptualize female sexuality. As no previous scholarship has analyzed the use of the subconscious, the senses, and performance when understanding female sexuality in Latin American literature, this dissertation seeks to provide a tentative exploration of the issues that may help to open up a new field of research in Hispanic feminist cultural studies.

Professors’ Perspectives on Educational Cohorts

Cohort educational models (CEM) are used to support students in graduate degree completion. Studies around CEMs focus mainly on student benefits. Voices of professors who organize and ultimately teach educational cohorts have been missing from this dialog. This study seeks to uncover professors’ perspectives on CEMs.

A Basic Interpretive Study of the Experiences of University Students Who Have Dropped or Failed an Online Course

Online courses have increased in enrollments over the past few decades. As the number of students taking online courses have increased, so has the number of students who have dropped or failed an online course. According to the literature, online courses may have higher drop rates than traditional, face-to-face courses. The number of students who fail an online course is, also, of concern. As online courses may continue to grow over the next few decades, studies on persistence in online courses may benefit students, administrators, instructional designers, educators, and researchers. Although previous research studies have addressed persistence in online courses, very few examine it from the perspectives of students who were unsuccessful in their courses. These students may have unique insights about the online experience that may have related to their lack of success. The purpose of this study was to understand the experiences of university students who have failed or dropped an online course through the lenses of transactional distance theory and Kember’s model of dropout in distance education. Transactional distance theory discusses the dialog, structure, and learner autonomy involved in an online course, while, Kember’s model presents categories that may relate to dropping an online course. Together, the theory and model may help in understanding the experiences of students who have dropped or failed an online course. In this study, semi-structured interviews were conducted with 20 participants from a large Southeastern university in the United States. Based on the participants’ responses, the data was sorted and ranked according to the amount of transactional distance in their courses, as well as the categories of Kember’s model. Many of the participants who experienced low or high transactional distance have, also, expressed an issue with the goal commitment category of Kember’s model. Additionally, there were important differences in the student characteristics of those who dropped or failed an online course. Furthermore, suggestions for improving online courses were given by the participants. Some of these suggestions included more student-instructor interactions, the use of more technology tools in their online course, and for orientations to the online environment to be offered.

A basic interpretive study of the experiences of university students who have dropped or failed an online course

Online courses have increased in enrollments over the past few decades. As the number of students taking online courses have increased, so has the number of students who have dropped or failed an online course. According to the literature, online courses may have higher drop rates than traditional, face-to-face courses. The number of students who fail an online course is, also, of concern. As online courses may continue to grow over the next few decades, studies on persistence in online courses may benefit students, administrators, instructional designers, educators, and researchers. Although previous research studies have addressed persistence in online courses, very few examine it from the perspectives of students who were unsuccessful in their courses. These students may have unique insights about the online experience that may have related to their lack of success. The purpose of this study was to understand the experiences of university students who have failed or dropped an online course through the lenses of transactional distance theory and Kember’s model of dropout in distance education. Transactional distance theory discusses the dialog, structure, and learner autonomy involved in an online course, while, Kember’s model presents categories that may relate to dropping an online course. Together, the theory and model may help in understanding the experiences of students who have dropped or failed an online course. In this study, semi-structured interviews were conducted with 20 participants from a large Southeastern university in the United States. Based on the participants’ responses, the data was sorted and ranked according to the amount of transactional distance in their courses, as well as the categories of Kember’s model. Many of the participants who experienced low or high transactional distance have, also, expressed an issue with the goal commitment category of Kember’s model. Additionally, there were important differences in the student characteristics of those who dropped or failed an online course. Furthermore, suggestions for improving online courses were given by the participants. Some of these suggestions included more student-instructor interactions, the use of more technology tools in their online course, and for orientations to the online environment to be offered.^