Recognizing emotional state of user based on learning method and conceptual memories

With the increased use of computers, electronic devices and human interaction with computer in the broad spectrum of human life, the role of controlling emotions and increasing positive emotional states becomes more prominent. If a user's negative emotions increase, his/her efficiency will decrease greatly as well. Research has shown that colors are to be considered as one of the most influential basic functions in sight, identification, interpretation, perception and senses. It can be said that colors have impact on individuals' emotional states and can change them. In this paper, by learning the reactions of users with different personality types against each color, communication between the user's emotional states and personality and colors were modeled for the variable "emotional control". For the sake of learning, we used a memory-based system with the user’s interface color changing in accordance with the positive and negative experiences of users with different personalities. The end result of comparison of the testing methods demonstrated the superiority of memory-based learning in all three parameters of emotional control, enhancement of positive emotional states and reduction of negative emotional states. Moreover, the accuracy of memory- based learning method was almost 70 percent

Using music to create effective curriculum for English language development

Research supporting the viability of music to promote language and literacy development as well as the theory of multiple intelligences suggests that any sound educational program employ a multifaceted approach to teaching and learning. This project created a thematically based multiple intelligence curriculum for first grade English language learners that emphasized the use of song

Effet des actions pédagogiques sur l'état émotionnel de l'apprenant dans un système tutoriel intelligent

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

The Development and Design of Activities to Support Performance Based and Integrated Math Instruction for Fifth Grade Students

The purpose of the project was to develop and design activities and materials to support performance based integrated mathematics instruction for fifth grade students in the concept areas of place value, decimals, percents, and fractions. The activities and materials were prepared in conjunction with other disciplines, namely reading, writing, art, science, and social studies. The intent was to make mathematics relevant to real life with stress on student performance as an indicator of knowledge, understanding, and application. The activities make use of performance based, integrated, and real life situations, and the materials include technology, field trips, gaming, manipulatives, recording sheets, and portfolios. The activities and materials are presented in the form of a handbook

C.A.M.E.L.E.O. : a cultural adaptation methodology for E-learning environment optimization

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Detecting and Modelling Stress Levels in E-Learning Environment Users

A modern Intelligent Tutoring System (ITS) should be sentient of a learner's cognitive and affective states, as a learner’s performance could be affected by motivational and emotional factors. It is important to design a method that supports low-cost, task-independent and unobtrusive sensing of a learner’s cognitive and affective states, to improve a learner's experience in e-learning, as well as to enable personalized learning. Although tremendous related affective computing research were done in this area, there is a lack of empirical research that can automatically measure a learner's stress using objective methods. This research is set to examine how an objective stress measurement model can be developed, to compute a learner’s cognitive and emotional stress automatically using mouse and keystroke dynamics. To ensure the measurement is not affected even if the user switches between tasks, three preliminary research experiments were carried out based on three common tasks during e-learning − search, assessment and typing. A stress measurement model was then built using the datasets collected from the experiments. Three stress classifiers were tested, namely certainty factors, feedforward back-propagation neural network and adaptive neuro-fuzzy inference system. The best classifier was then integrated into the ITS stress inference engine, which is designed to decide necessary adaptation, and to provide analytical information of learners' performances, which include stress levels and learners’ behaviours when answering questions

Affective learning companions : strategies for empathetic agents with real-time multimodal affective sensing to foster meta-cognitive and meta-affective approaches to learning, motivation, and perseverance

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (leaves 93-98).This thesis has developed an affective agent research platform that advances the architecture of relational agents and intelligent tutoring systems. The system realizes non-invasive multimodal real-time sensing of elements of user's affective state and couples this ability with an agent capable of supporting learners by engaging in real-time responsive expressivity. The agent mirrors several non-verbal behaviors believed to influence persuasion, liking, and social rapport, and responds to frustration with empathetic or task-support dialogue. Pilot studies involved 60 participants, ages 10-14 years-old, and led to an experiment involving 76 participants, ages 11-13 years-old, engaging in the Towers of Hanoi activity. The system (data collection, architecture, character interaction, and activity presentation) was iteratively tested and refined, and two "mirroring" conditions were developed: "sensor driven non-verbal interactions" and "pre-recorded non-verbal interactions". The development and training of the classifier algorithms showed the ability to predict frustration/help seeking behavior with 79% accuracy across a pilot group of 24 participants.(cont.) Informed by the theory of optimal experience (Flow) and a parallel theory of a state of non-optimal experience (Stuck), developed in this thesis, the effects of "affective support" and "task support" interventions, through agent dialogue and non-verbal interactions, were evaluated relative to their appropriateness for the learner's affective state. Outcomes were assessed with respect to measures of agent emotional intelligence, social bond, and persuasion, and with respect to learner frustration, perseverance, metacognitive and meta-affective ability, beliefs of one's ability to increase one's own intelligence, and goal-mastery-orientation. A new simple measure of departure dialogue was shown to have a significant relationship with the more lengthy and explicit social bond Working Alliance Inventory survey instrument; its validity was further supported through its use in assessing the social bond relationship with other measures. Over-estimation of the duration of the activity was associated with increased frustration. Gender differences were obtained with girls showing stronger outcomes when presented with affect-support interventions and boys with task-support interventions. Coordinating the character's mirroring with intervention type and learners' frustration was shown to be important.by Winslow Burleson.Ph.D

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

Real-Time Affective Support to Promote Learner’s Engagement

abstract: Research has shown that the learning processes can be enriched and enhanced with the presence of affective interventions. The goal of this dissertation was to design, implement, and evaluate an affective agent that provides affective support in real-time in order to enrich the student’s learning experience and performance by inducing and/or maintaining a productive learning path. This work combined research and best practices from affective computing, intelligent tutoring systems, and educational technology to address the design and implementation of an affective agent and corresponding pedagogical interventions. It included the incorporation of the affective agent into an Exploratory Learning Environment (ELE) adapted for this research. A gendered, three-dimensional, animated, human-like character accompanied by text- and speech-based dialogue visually represented the proposed affective agent. The agent’s pedagogical interventions considered inputs from the ELE (interface, model building, and performance events) and from the user (emotional and cognitive events). The user’s emotional events captured by biometric sensors and processed by a decision-level fusion algorithm for a multimodal system in combination with the events from the ELE informed the production-rule-based behavior engine to define and trigger pedagogical interventions. The pedagogical interventions were focused on affective dimensions and occurred in the form of affective dialogue prompts and animations. An experiment was conducted to assess the impact of the affective agent, Hope, on the student’s learning experience and performance. In terms of the student’s learning experience, the effect of the agent was analyzed in four components: perception of the instructional material, perception of the usefulness of the agent, ELE usability, and the affective responses from the agent triggered by the student’s affective states. Additionally, in terms of the student’s performance, the effect of the agent was analyzed in five components: tasks completed, time spent solving a task, planning time while solving a task, usage of the provided help, and attempts to successfully complete a task. The findings from the experiment did not provide the anticipated results related to the effect of the agent; however, the results provided insights to improve diverse components in the design of affective agents as well as for the design of the behavior engines and algorithms to detect, represent, and handle affective information.Dissertation/ThesisDoctoral Dissertation Computer Science 201