A study of the effects of a service-learning experience on student success at an urban community college

The purpose of this study was to explore the effects of a service-learning experience on student success as measured by class attendance, course completion, final course grades, and end-of-term evaluation data. Though many outcomes of service-learning experiences have been studied, including ethical values, self-esteem, student personal development, and career preparation, relatively few studies have been conducted on the effects of such experiences on academic achievement, and the studies that have been done have primarily studied students at traditional, four-year, residential universities. The study consisted of 286 students enrolled in six paired courses taught by five instructors at a community college in the Fall term 1996. One section of each pair (the control group) was taught using traditional subject matter and course materials and the other section of each pair (the treatment group) participated in a 20-hour required service- learning activity in addition to the regular course curriculum. The courses in the study included American History, Sociology, College Preparatory English, and Introduction to English Composition. The results of this study indicate that, overall, students who participated in a class in which service-learning was a requirement, achieved higher final course grades and reported greater satisfaction with the course, the instructor, the reading assignments, and the grading system, and the treatment section of one course pair had fewer absences. In addition, the faculty members reported that, in the treatment sections, class discussions were more stimulating, the sections seemed more vital in terms of student involvement, the students seemed more challenged academically, more motivated to learn, and seemed to exert more effort in the course.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Effects of Repeated Readings on Reading Abilities of English Language Learners with Specific Learning Disabilities

This study investigated the effects of repeated readings on the reading abilities of 4, third-, fourth-, and fifth-grade English language learners (ELLs) with specific learning disabilities (SLD). A multiple baseline probe design across subjects was used to explore the effects of repeated readings on four dependent variables: reading fluency (words read correctly per minute; wpm), number of errors per minute (epm), types of errors per minute, and answer to literal comprehension questions. Data were collected and analyzed during baseline, intervention, generalization probes, and maintenance probes. Throughout the baseline and intervention phases, participants read a passage aloud and received error correction feedback. During baseline, this was followed by fluency and literal comprehension question assessments. During intervention, this was followed by two oral repeated readings of the passage. Then the fluency and literal comprehension question assessments were administered. Generalization probes followed approximately 25% of all sessions and consisted of a single reading of a new passage at the same readability level. Maintenance sessions occurred 2-, 4-, and 6-weeks after the intervention ended. The results of this study indicated that repeated readings had a positive effect on the reading abilities of ELLs with SLD. Participants read more wpm, made fewer epm, and answered more literal comprehension questions correctly. Additionally, on average, generalization scores were higher in intervention than in baseline. Maintenance scores were varied when compared to the last day of intervention, however, with the exception of the number of hesitations committed per minute maintenance scores were higher than baseline means. This study demonstrated that repeated readings improved the reading abilities of ELLs with SLD and that gains were generalized to untaught passages. Maintenance probes 2-, 4-, and 6- weeks following intervention indicated that mean reading fluency, errors per minute, and correct answers to literal comprehensive questions remained above baseline levels. Future research should investigate the use of repeated readings in ELLs with SLD at various stages of reading acquisition. Further, future investigations may examine how repeated readings can be integrated into classroom instruction and assessments.

A Comparison Study of the English III/American Literature Success of African American High School Students and That of Students Whose Home Language is Haitian Creole

The purpose of the study was to compare the English III success of students whose home language is Haitian Creole (SWHLIHC) with that of the more visible African American high school students in the Miami Dade County Public Schools System, in an effort to offer insight that might assist educators in facilitating the educational success of SWHLIHC in American Literature class. The study was guided by two important theories on how students interact with and learn from literature. They are Reader Response Theory which advocates giving students the opportunity to become involved in the literature experience (Rosenblatt, 1995), and Critical Literacy, a theory developed by Paolo Freire and Henry Giroux, which espouses a critical approach to analysis of society that enables people to analyze social problems through lenses that would reveal social inequities and assist in transforming society into a more equitable entity. Data for the study: 10th grade reading FCAT scores, English III/American Literature grades, and Promotion to English IV records for the school year 2010-2011 were retrieved from the records division of the Miami Dade County Public Schools System. The study used a quantitative methods approach, the central feature of which was an ex post facto design with hypotheses (Newman, Newman, Brown, & McNeely, 2006). The ex post facto design with hypotheses was chosen because the researcher postulated hypotheses about the relationships that might exist between the performances of SWHLIHC and those of African American students on the three above mentioned variables. This type of design supported the researcher’s purpose of comparing these performances. One way analysis of variance (ANOVA), two way ANOVAs, and chi square tests were used to examine the two groups’ performances on the 10th grade reading FCAT, their English III grades, and their promotion to English IV. The study findings show that there was a significant difference in the performance of SWHLIHC and African American high school students on all three independent variables. SWHLIHC performed significantly higher on English III success and promotion to English IV. African American high school students performed significantly higher on the reading FCAT.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^