Temporal pathways to learning: how learning emerges in an open-ended collaborative activity

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimodal Hidden Markov Model (HMM) based methodology to investigate the temporal learning processes of two types of learners that have learning gains and a type that does not have learning gains in an open-ended collaborative learning activity. Considering log data, speech behavior, affective states and gaze patterns, we find that all learners start from a similar state of non-productivity, but once out of it they are unlikely to fall back into that state, especially in the case of the learners that have learning gains. Those who have learning gains shift between two problem solving strategies, each characterized by both exploratory and reflective actions, as well as demonstrate speech and gaze patterns associated with these strategies, that differ from those who don't have learning gains. Further, the teams that have learning gains also differ between themselves in the manner in which they employ the problem solving strategies over the interaction, as well as in the manner they express negative emotions while exhibiting a particular strategy. These outcomes contribute to understanding the multiple pathways of learning in an open-ended collaborative learning environment, and provide actionable insights for designing effective interventions

Specific Language Impairments and Possibilities of Classification and Detection from Children's Speech

Many young children have speech disorders. My research focused on one such disorder, known as specific language impairment or developmental dysphasia. A major problem in treating this disorder is the fact that specific language impairment is detected in children at a relatively late age. For successful speech therapy, early diagnosis is critical. I present two different approaches to this issue using a very simple test that I have devised for diagnosing this disorder. In this thesis, I describe a new method for detecting specific language impairment based on the number of pronunciation errors in utterances. An advantage of this method is its simplicity; anyone can use it, including parents. The second method is based on the acoustic features of the speech signal. An advantage of this method is that it could be used to develop an automatic detection system. KeyKatedra teorie obvod

Evaluating the Teacher-Intern-Professor Model in a Professional Development School Partnership Setting using a Bayesian Approach to Mix Methods

Two needs of Georgia State University Professional Development School Partnerships are to show increases in both student academic achievement and teacher efficacy. The Teacher-Intern-Professor (TIP) Model was designed to address these needs. The TIP model focuses on using the university and school partnership to support Georgia State University student intern preparedness and student academic achievement for those participating in the program. TIP Model outcomes were analyzed using a quasi-experimental design for achievement data and a Bayesian approach to mix methods for efficacy data. Quantitative data, in the form of test scores, were analyzed to compare mean student academic achievement at the classroom level. Mean differences between treatment and comparison groups were not significant for the TIP treatment factor (F(1, 60) = .248, p =.620) as measured by a benchmark test. Results favored the treatment group over control group for the TIP treatment factor (F(1, 56) = 17.967, p \u3c .001) on a geometry test. A methodological contribution is the exploration and development of an approach to mix methods using Bayesian statistics to combine quantitative and qualitative data. Bayesian statistics allows for incorporation of the researcher’s prior belief into the data analysis. Narrative Inquiry was the qualitative framework employed to gain understanding of the participants’ qualitative data, thus providing a particular way of prior belief elicitation. More specifically, a content analysis of the qualitative data, which included interviews, observations, and artifacts, was used in conjunction with quantitative historical data to elicit prior beliefs. The Bayesian approach to mix methods combined prior beliefs from the teacher efficacy qualitative data with the quantitative data from Gibson’s and Dembo’s Teacher Efficacy Scale to obtain posterior distributions, which summarized beliefs for the themes of teacher efficacy and personal efficacy

Enhancing electronic intelligent tutoring systems by responding to affective states

The overall aim of this research is the exploration mechanisms which allow an understanding of the emotional state of students and the selection of an appropriate cognitive and affective feedback for students on the basis of students' emotional state and cognitive state in an affective learning environment. The learning environment in which this research is based is one in which students learn by watching an instructional video. The main contributions in the thesis include: - A video study was carried out to gather data in order to construct the emotional models in this research. This video study adopted a methodology in qualitative research called “Quick and Dirty Ethnography”(Hughes et al., 1995). In the video study, the emotional states, including boredom, frustration, confusion, flow, happiness, interest, were identified as being the most important to a learner in learning. The results of the video study indicates that blink frequencies can reflect the learner's emotional states and it is necessary to intervene when students are in self-learning through watching an instructional video in order to ensure that attention levels do not decrease. - A novel emotional analysis model for modeling student’s cognitive and emotional state in an affective learning system was constructed. It is an appraisal model which is on the basis of an instructional theory called Gagne’s theory (Gagne, 1965). - A novel emotion feedback model for producing appropriate feedback tactics in affective learning system was developed by Ontology and Influence Diagram ii approach. On the basis of the tutor-remediation hypothesis and the self-remediation hypothesis (Hausmann et al., 2013), two feedback tactic selection algorithms were designed and implemented. The evaluation results show: the emotion analysis model can be used to classify negative emotion and hence deduce the learner’s cognitive state; the degree of satisfaction with the feedback based on the tutor-remediation hypothesis is higher than the feedback based on self-remediation hypothesis; the results indicated a higher degree of satisfaction with the combined cognitive and emotional feedback than cognitive feedback on its own

Development and Specification of Virtual Environments

This thesis concerns the issues involved in the development of virtual environments (VEs). VEs are more than virtual reality. We identify four main characteristics of them: graphical interaction, multimodality, interface agents, and multi-user. These characteristics are illustrated with an overview of different classes of VE-like applications, and a number of state-of-the-art VEs. To further define the topic of research, we propose a general framework for VE systems development, in which we identify five major classes of development tools: methodology, guidelines, design specification, analysis, and development environments. Of each, we give an overview of existing best practices

An Integrated Formal Task Specification Method for Smart Environments

This thesis is concerned with the development of interactive systems for smart environments. In such scenario different interaction paradigms need to be supported and according methods and development strategies need to be applied to comprise not only explicit interaction (e.g., pressing a button to adjust the light) but also implicit interactions (e.g., walking to the speaker’s desk to give a talk) to assist the user appropriately. A task-based modeling approach is introduced allowing basing the implementing of different interaction paradigms on the same artifact