316,581 research outputs found
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 userâs 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
Pengaruh Kompetensi Guru dan Motivasi Belajar terhadap Prestasi Belajar Siswa SDN Gugus 1 Bumi Nikel Bahodopi Morowali
Teachers must have several competencies including teaching, personality, professional, and social. The application of teacher competence can be seen from the teacher's work. The competence possessed by a teacher is reflected in the achievement of learning outcomes which are realized in the form of values ââthat describe the learning achievements of their students. In addition, student learning motivation also has an important role in student learning outcomes. The main objective of this study was to identify and analyze the influence of teacher competence and motivation on student achievement at SDN Gugus 1 Bumi Nickel Bahodopi Morowali. This study uses a quantitative approach with a correlational survey. The research population was students of class V Cluster 1 Bumi Nickel Morowali, totaling 597 students, so the sampling technique in this study used purposive sampling. The research instrument was a questionnaire and data analysis used multiple linear regression which was completed with the help of the SPSS 16 for Windows computer program. Based on the results of data analysis, teacher competence has no effect on student achievement with a significance value of 0.520, so p > 0.05. Learning motivation has no effect on student achievement with a significance value of 0.241, so that p> 0.05.Teachers must have several competencies including teaching, personality, professional, and social. The application of teacher competence can be seen from the teacher's work. The competence possessed by a teacher is reflected in the achievement of learning outcomes which are realized in the form of values ââthat describe the learning achievements of their students. In addition, student learning motivation also has an important role in student learning outcomes. The main objective of this study was to identify and analyze the influence of teacher competence and motivation on student achievement at SDN Gugus 1 Bumi Nickel Bahodopi Morowali. This study uses a quantitative approach with a correlational survey. The research population was students of class V Cluster 1 Bumi Nickel Morowali, totaling 597 students, so the sampling technique in this study used purposive sampling. The research instrument was a questionnaire and data analysis used multiple linear regression which was completed with the help of the SPSS 16 for Windows computer program. Based on the results of data analysis, teacher competence has no effect on student achievement with a significance value of 0.520, so p > 0.05. Learning motivation has no effect on student achievement with a significance value of 0.241, so that p> 0.05
The Impact of Two Proposed Strategies Based on Active Learning on Students' Achievement at the Computer and Their Social Intelligence
Active learning is a teaching method that involves students actively participating in activities, exercises, and projects within a rich and diverse educational environment. The teacher plays a role in encouraging students to take responsibility for their own education under their scientific and pedagogical supervision and motivates them to achieve ambitious educational goals that focus on developing an integrated personality for todayâs students and tomorrowâs leaders. It is important to understand the impact of two proposed strategies based on active learning on the academic performance of first-class intermediate students in computer subjects and their social intelligence. The research sample was intentionally selected, consisting of 99 students. The experimental group comprised 33 students from division (B) who were taught according to the first proposed strategy, while the second experimental group, represented by division (A), and also consisted of 33 students. The control group, made up of 33 students from division (C), was taught using the usual method. Two tools have been prepared: an achievement test with 40 items and a measure of social intelligence consisting of 20 items. The research results indicated that the experimental groups, which utilized the first and second proposed strategies based on active learning, outperformed the control group. As a result, several conclusions, recommendations, and proposals were made
Designing friends
Embodied Conversational Agents are virtual humans that can interact with humans using verbal and non-verbal forms of communication. In most cases, they have been designed for short interactions. This paper asks the question how one would start to design synthetic characters that can become your friends. We look at insights from social psychology and propose a methodology for designing friends
Towards Learning âSelfâ and Emotional Knowledge in Social and Cultural Human-Agent Interactions
Original article can be found at: http://www.igi-global.com/articles/details.asp?ID=35052 Copyright IGI. Posted by permission of the publisher.This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modeling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottomup approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.Peer reviewe
Interacting with educational chatbots: A systematic review
Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learnersâ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to studentsâ learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness
Predicting mental imagery based BCI performance from personality, cognitive profile and neurophysiological patterns
Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands
to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphyâ
EEG), which is processed while they perform specific mental tasks. While very
promising, MI-BCIs remain barely used outside laboratories because of the difficulty
encountered by users to control them. Indeed, although some users obtain good control
performances after training, a substantial proportion remains unable to reliably control an
MI-BCI. This huge variability in user-performance led the community to look for predictors of
MI-BCI control ability. However, these predictors were only explored for motor-imagery
based BCIs, and mostly for a single training session per subject. In this study, 18 participants
were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2
of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships
between the participantsâ BCI control performances and their personality, cognitive
profile and neurophysiological markers were explored. While no relevant relationships with
neurophysiological markers were found, strong correlations between MI-BCI performances
and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive
model of MI-BCI performance based on psychometric questionnaire scores was proposed.
A leave-one-subject-out cross validation process revealed the stability and reliability of this
model: it enabled to predict participantsâ performance with a mean error of less than 3
points. This study determined how usersâ profiles impact their MI-BCI control ability and
thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of
each user
What your Facebook Profile Picture Reveals about your Personality
People spend considerable effort managing the impressions they give others.
Social psychologists have shown that people manage these impressions
differently depending upon their personality. Facebook and other social media
provide a new forum for this fundamental process; hence, understanding people's
behaviour on social media could provide interesting insights on their
personality. In this paper we investigate automatic personality recognition
from Facebook profile pictures. We analyze the effectiveness of four families
of visual features and we discuss some human interpretable patterns that
explain the personality traits of the individuals. For example, extroverts and
agreeable individuals tend to have warm colored pictures and to exhibit many
faces in their portraits, mirroring their inclination to socialize; while
neurotic ones have a prevalence of pictures of indoor places. Then, we propose
a classification approach to automatically recognize personality traits from
these visual features. Finally, we compare the performance of our
classification approach to the one obtained by human raters and we show that
computer-based classifications are significantly more accurate than averaged
human-based classifications for Extraversion and Neuroticism
- âŠ