9,941 research outputs found

    A model for providing emotion awareness and feedback using fuzzy logic in online learning

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    Monitoring users’ emotive states and using that information for providing feedback and scaffolding is crucial. In the learning context, emotions can be used to increase students’ attention as well as to improve memory and reasoning. In this context, tutors should be prepared to create affective learning situations and encourage collaborative knowledge construction as well as identify those students’ feelings which hinder learning process. In this paper, we propose a novel approach to label affective behavior in educational discourse based on fuzzy logic, which enables a human or virtual tutor to capture students’ emotions, make students aware of their own emotions, assess these emotions and provide appropriate affective feedback. To that end, we propose a fuzzy classifier that provides a priori qualitative assessment and fuzzy qualifiers bound to the amounts such as few, regular and many assigned by an affective dictionary to every word. The advantage of the statistical approach is to reduce the classical pollution problem of training and analyzing the scenario using the same dataset. Our approach has been tested in a real online learning environment and proved to have a very positive influence on students’ learning performance.Peer ReviewedPostprint (author's final draft

    Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples

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    Machine Learning has been a big success story during the AI resurgence. One particular stand out success relates to learning from a massive amount of data. In spite of early assertions of the unreasonable effectiveness of data, there is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. In this paper, we discuss the indispensable role of knowledge for deeper understanding of content where (i) large amounts of training data are unavailable, (ii) the objects to be recognized are complex, (e.g., implicit entities and highly subjective content), and (iii) applications need to use complementary or related data in multiple modalities/media. What brings us to the cusp of rapid progress is our ability to (a) create relevant and reliable knowledge and (b) carefully exploit knowledge to enhance ML/NLP techniques. Using diverse examples, we seek to foretell unprecedented progress in our ability for deeper understanding and exploitation of multimodal data and continued incorporation of knowledge in learning techniques.Comment: Pre-print of the paper accepted at 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI). arXiv admin note: substantial text overlap with arXiv:1610.0770

    Pattern recognition in narrative: Tracking emotional expression in context

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    Using geometric data analysis, our objective is the analysis of narrative, with narrative of emotion being the focus in this work. The following two principles for analysis of emotion inform our work. Firstly, emotion is revealed not as a quality in its own right but rather through interaction. We study the 2-way relationship of Ilsa and Rick in the movie Casablanca, and the 3-way relationship of Emma, Charles and Rodolphe in the novel {\em Madame Bovary}. Secondly, emotion, that is expression of states of mind of subjects, is formed and evolves within the narrative that expresses external events and (personal, social, physical) context. In addition to the analysis methodology with key aspects that are innovative, the input data used is crucial. We use, firstly, dialogue, and secondly, broad and general description that incorporates dialogue. In a follow-on study, we apply our unsupervised narrative mapping to data streams with very low emotional expression. We map the narrative of Twitter streams. Thus we demonstrate map analysis of general narratives

    Correlation of Pain Scores, Analgesic Use, and Beck Anxiety Inventory Scores During Hospitalization in Lower Extremity Amputees

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    Post amputation pain can be debilitating for patients and families. Chronic pain is a common phenomenon after lower extremity amputation, occurring in up to 80% of this population. The purpose of this pilot study was to correlate post amputation pain scores to opioid analgesic consumption and Beck Anxiety Inventory (BAI) scores. Twenty-three patients with lower extremity amputation at an 827-bed acute care inner-city hospital were surveyed pre-operatively and post-operatively to determine if there was a significant correlation between anxiety and pain. A numeric scale was utilized by patients to rate their pain level, while the BAI was utilized to measure their anxiety levels

    The Effect of COBRA Training on First Responder Self-confidence to Work in a Toxic Chemical or Biological Agent Environment

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    First responders are our nation’s front line defense against intentional or accidental releases of toxic chemical or biological agents. Self-confidence which is a building block of self-efficacy is hypothesized to be malleable and increased through training. The purpose of this study was to determine the change if any, which first responders undergo during Chemical, Ordnance, Biological, and Radiological (COBRA) training, in their self-confidence to operate in a toxic chemical or biological agent environment. That is to determine if there is a correlation between increased self-confidence and COBRA training. The methodology of this study was based on quantitative methods of analysis and surveys to collect data from students attending COBRA training at the Center for Domestic Preparedness (CDP), Aniston, Alabama. Collaboration with the CDP ensured the data collected was captured from every student attending COBRA training, thus creating a survey environment wherein there was a 95% plus survey completion rate. The data was collected through a pre and post-training survey, which provided the before and after groups for the study. Descriptive statistics were used to analyze the delta between the groups, and the interrater agreement. Hypothesis testing was through paired sample t-testing, ANOVA, and regression analysis. Analysis of the data collected from students was conducted using SPSS statistical sampling software and a spreadsheet. Confidence was set at 95% with a t-score of 1.984 or greater, and a total case sample of 184 participants. Case sampling is based on standard probability sampling for the entire population of paid first responders in the United States

    Development of Intelligent Multi-agents System for Collaborative e-learning Support

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    The aim of this paper is the introduction of intelligence in e-learning collaborative system. In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action. However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible. Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent. This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors. After the implementation of intelligent collaborative system by using Moodle platform, we have tested it. The reader will discover our approach and relevant results

    An Immersive Serious Game for the Behavioral Assessment of Psychological Needs

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    [EN] Motivation is an essential component in mental health and well-being. In this area, researchers have identified four psychological needs that drive human behavior: attachment, self-esteem, orientation and control, and maximization of pleasure and minimization of distress. Various self-reported scales and interviews tools have been developed to assess these dimensions. Despite the validity of these, they are showing limitations in terms of abstractation and decontextualization and biases, such as social desirability bias, that can affect responses veracity. Conversely, virtual serious games (VSGs), that are games with specific purposes, can potentially provide more ecologically valid and objective assessments than traditional approaches. Starting from these premises, the aim of this study was to investigate the feasibility of a VSG to assess the four personality needs. Sixty subjects participated in five VSG sessions. Results showed that the VSG was able to recognize attachment, self-esteem, and orientation and control needs with a high accuracy, and to a lesser extent maximization of pleasure and minimization of distress need. In conclusion, this study showed the feasibility to use a VSG to enhance the assessment of psychological behavioral-based need, overcoming biases presented by traditional assessment.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness funded project "Advanced Therapeutically Tools for Mental Health" (DPI2016-77396-R) and by the European Union through the Operational Program of the European Regional Development Fund (ERDF) on the Valencian Community 2010-2020 (IDIFEDER/2018/029)Chicchi-Giglioli, IA.; Carrasco-Ribelles, LA.; Parra Vargas, E.; Marín-Morales, J.; Alcañiz Raya, ML. (2021). An Immersive Serious Game for the Behavioral Assessment of Psychological Needs. Applied Sciences. 11(4):1-17. https://doi.org/10.3390/app11041971S11711
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