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A New E-learning System Focusing on Emotional Aspect Using Biological Signals
Abstract
E-learning is the computer and network-enabled transfer of skills and knowledge. It is widely accepted that new technologies can make a big difference in education. Although the advantages of e-learning over person to person teaching are still under debate, the latter is considered to be superior with respect to teaching effectiveness. One reasons for this advantage of human expert tutors is their ability to deal with the emotional aspects of the learner. In an e-learning system, emotions are important in the classroom. We thus proposed a new e-learning system that focuses on affective aspects. Our system equips sensors to measure biological signals and analyzes user emotions for the improvement of the e-learning system’s effectiveness.
... Our current system, which is based on our previously designed e-learning scheme (Charoenpit, 2013), consists of the following five modules ( Figure 1): 1. Learners: they register for e-learning through e-learning systems and can choose any of the courses provided by learning management systems (LMS). 2. Instructors: these critical elements of this system create and design courses, content, tests, quizzes, and evaluations in the LMS. 3. Servers are the web, database, and LMS. ...
... E-learning system design(Charoenpit, 2013) ...
For e learning, we must create effective interaction between e-learning content and learners. In particular, increasing learner motivation by stimulating their interest is crucial. Eye tracking devices measure eye positions and eye movement. To date, few e-learning systems have derived emotions from eye tracking data. In this study, we explore which eye tracking indexes are related to learner emotions. We designed and implemented a prototype and evaluated it experimentally.
... Our previously designed e-learning system [11] consists of the following five modules (Figure 1): 1. Learners register through e-learning systems and can choose any of the courses provided by learning management systems (LMS). 2. Instructors: these critical system elements create and design courses, content, tests, quizzes, and evaluations in the LMS. ...
... 5. Analysis of learner emotions: We devised this design system to understand how learner emotions evolve during the learning process to develop learning systems that recognize and respond appropriately to learner emotional changes. We employed three modelsFigure 1: E-learning system design [11] Exploring Emotion in an E-learning System Using Eye Tracking ...
E-learning is the computer and network-enabled transfer of skills and knowledge. In e-learning systems, emotions are critical for learners to create positive contexts for optimal learning. In particular, increasing learner motivation by stimulating their interest is crucial. To data, however, few e-learning systems have derived emotions from eye tracking data. With eye tracking equipment, we recorded the eye movements of learners and calculated their eye metric indexes, which we focused on to explore their relationship to two learners' emotions groups: interest and boredom groups. We designed and implemented a prototype and experimentally evaluated it.
Fama French model is called the application of the combination of theory and practice in modern financial industry. It is based on the whole market and uses the value of assets to calculate the expected return of the target amount of assets, thus confirming the pricing formula of the capital market. Fama French model puts forward three factor models in the research, and thinks that the market risk can not reflect the change mode of the rate of return, except for the risk factors of market conditions, the rest have obvious changes on the rate of return. This paper uses a company's human resource management model as the object of analysis, using the company's existing human resource management problems, from which the corresponding solutions and management mechanism are obtained. This result shows that in the aspect of optimizing management, enterprises should regard performance planning, performance implementation, performance evaluation level and performance reflection as a unity, take performance plan as the starting point of the whole enterprise management mode, and take performance implementation details as the core part of management. In terms of management measures and mechanisms, enterprises need to strengthen the implementation of human resource management ideas, enhance the promotion of the enterprise in the field of culture, and get the attention of leaders to establish a more professional team to lead the company, so as to optimize the company's human resource model for better development.
Various e-learning environments have been developed to provide sufficient materials for learners and thereby guide them to gain knowledge in any domain. Even though there were several factors that determine the motivation of the student, the skill set possessed by them is definitely an important factor. Hence in our proposed work, the behavioural and educational skill of the learners is tested by a skill test and learning content is provided only based on their skill test evaluation reports. The entire process is done by real time personalization based Adaptive Learning Management System and Personalized Page Rank algorithm. Finally, the Navies’ Bayes classifier was employed to classify the learners based on the performance over the skill test. Learners on their own can express both the optimistic and adverse skills that considerably impact the adaptive learning in e-learning environment. High skilled categorized learners are offered with advanced, intermediate learners with moderate and beginner or slow learners are provided with basic level of study content. The results are analysed based on their skills, individual's method of learning and time constraints.
It is becoming a trend to apply an emotional lens and to position emotions as central to educational interactions. Recently, affective computing has been one of the most actively research topics in education, attracting much attention from both academics and practitioners. However, despite the increasing number of papers published, there still are deficiencies and gaps in the comprehensive literature review in the specific area of affective computing in education. Therefore, this study presents a review of the literature on affective computing in education by selecting articles published from 2010 to 2017. A review protocol consisting of both automatic and manual searches is used to ensure the retrieval of all relevant studies. The final 94 selected papers are reviewed and relevant information extracted based on a set of research questions. This study classifies selected articles according to the research purposes, learning domains, channels and methods of affective recognition and expression, and emotion theories/models as well as the emotional states. The findings show the increased number and importance of affective computing studies in education domain in recent years. The research purposes of most affective computing studies are found to be designing emotion recognition and expression systems/methods/instruments as well as examining the relationships among emotion, motivation, learning style, and cognition. Affective measurement channels are classified into textual, visual, vocal, physiological, and multimodal channels, while the textual channel is recognized as the most widely-used affective measurement channel. Meanwhile, integration of textual and visual channels is the most widely-used multimodal channel in affective computing studies. Dimensional theories/models are the most preferred models for description of emotional states. Boredom, anger, anxiety, enjoyment, surprise, sadness, frustration, pride, hopefulness, hopelessness, shame, confusion, happiness, natural emotion, fear, joy, disgust, interest, relief, and excitement are reported as the top 20 emotional states in education domain. Finally, this study provides recommendations for future research directions to help researchers, policymakers and practitioners in the education sector to apply affective computing technology more effectively and to expand educational practices.
In this chapter, Linnenbrink-Garcia and her colleagues discuss the assessment of students’ affect based on a circumplex model. First an overview of circumplex models of affect is provided. Next, several approaches they employed in their own research using this approach (e.g., multi-item self-report scales assessing each dimension of the circumplex, bi-polar self-report items, observations) are described in order to highlight the respective strengths and weaknesses of these various methods. The authors conclude with more general remarks about the state of the field and suggestions for researchers, focusing on issues such as what forms of affect to measure, the level (trait vs. state) at which to assess affect, and consideration of other methods of assessment beyond self-report.
In this paper, a new technique for face recognition is proposed. This technique has great degree of applications including identification, authentication, psychology, e-learning, security, marketing and human-computer interaction. The important role of the proposed technique with e-learning systems, it will identify users when they first log into a program, also will confirm whether they're the one taking the test. The first step of our technique is detecting the face location in an image. Then the important points of face can be recognized by the proprieties of face such as symmetric location of eyes and different colors of face segments. The experimental results have shown the efficient of the proposed technique. It can be invoked in online system.
Though e-learning is being debated to have some advantages over person to person teaching, the latter is considered to be superior with respect to the effectiveness of teaching. One of the reasons for this advantage of human expert tutors is their ability to deal with the emotional aspects of the learner. We introduce an emotion sensitive e-learning model which is sensitive to both emotional aspects as well as the learning ability of the learner. This is a major difference with the other similar attempts to make effective e-learning systems and the preliminary analyses indicate considerable promise. We hope this would complement the effectiveness of e-learning.
Factor-analytic evidence has led most psychologists to describe affect as a set of dimensions, such as displeasure, distress, depression, excitement, and so on, with each dimension varying independently of the others. However, there is other evidence that rather than being independent, these affective dimensions are interrelated in a highly systematic fashion. The evidence suggests that these interrelationships can be represented by a spatial model in which affective concepts fall in a circle in the following order: pleasure (0), excitement (45), arousal (90), distress (135), displeasure (180), depression (225), sleepiness (270), and relaxation (315). This model was offered both as a way psychologists can represent the structure of affective experience, as assessed through self-report, and as a representation of the cognitive structure that laymen utilize in conceptualizing affect. Supportive evidence was obtained by scaling 28 emotion-denoting adjectives in 4 different ways: R. T. Ross's (1938) technique for a circular ordering of variables, a multidimensional scaling procedure based on perceived similarity among the terms, a unidimensional scaling on hypothesized pleasure–displeasure and degree-of-arousal dimensions, and a principal-components analysis of 343 Ss' self-reports of their current affective states. (70 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
This paper reports on work undertaken within a pilot study concerned with the design, development, and evaluation of online computer science training courses. Drawing on recent developments in e-learning technology, these courses were structured around the principles of a learner-oriented approach for use with adult learners. The paper describes a methodological framework for the evaluation of three main educational issues involved in the learning process of Web-based computer science training courses, and analyzes the results of this study with the aim of providing an improved learning design, and environment, for these courses. The findings highlight a number of potential barriers to learning and indicate the failed indicators that need to be improved in order to enhance effective performance. The authors give their views both on ways to improve the proposed learning environment and on the need for an optimal balance between asynchronous and synchronous activities, enhanced collaboration, and interactions among adult learners and e-tutors.
Using emotion detection technologies from biophysical signals, this study explored how emotion evolves during learning process and how emotion feedback could be used to improve learning experiences. This article also described a cutting-edge pervasive e-Learning platform used in a Shanghai online college and proposed an affective e-Learning model, which combined learners' emotions with the Shanghai e-Learning platform. The study was guided by Russell's circumplex model of affect and Kort's learning spiral model. The results about emotion recognition from physiological signals achieved a best-case accuracy (86.3%) for four types of learning emotions. And results from emotion revolution study showed that engagement and confusion were the most important and frequently occurred emotions in learning, which is consistent with the findings from AutoTutor project. No evidence from this study validated Kort's learning spiral model. An experimental prototype of the affective e-Learning model was built to help improve students' learning experience by customizing learning material delivery based on students' emotional state. Experiments indicated the superiority of emotion aware over non-emotion-aware with a performance increase of 91%.
This paper presents results of a master thesis at the Fraunhofer Institute for Computer Graphics Rostock (IGD-R) at the department for Human-Centered Interaction. Using an emotion recognition sensor system, an e-learning system was enhanced with affective abilities. By taking certain actions, the user is supported to handle negative emotions, which should enable a better learning as well as a greater satisfaction. The affective communication and actions are encapsulated by an Affective Component, which was implemented as a prototype and evaluated at a first glance.
The Learning Classroom: Theory Into Practice
- D H Linda
- R Jim
- A Kim
- O Suzanne
- M Daisy