A Survey of E-Learning Techniques and the Role of Agent Based Assistance

2013 ◽  
Author(s):  
Nwar C. Shaukat ◽  
Shehzad Khalid
Keyword(s):  
Agent Based ◽  
Learning Techniques ◽  
E Learning

scholarly journals The role of the ICT teacher in e-learning-based teaching

2021 ◽  
Vol 26 ◽  
pp. 93-100
Author(s):  
Fetri Sukisworo ◽  
Marsono Marsono ◽  
Widiyanti Widiyanti
Keyword(s):  
Online Learning ◽  
Distance Learning ◽  
Learning Process ◽  
Teaching And Learning ◽  
Human Life ◽  
Face To Face ◽  
Use Of Technology ◽  
Learning Techniques ◽  
E Learning

The Covid-19 pandemic has had a fundamental impact on various aspects of humanity. Starting from attacking health, this pandemic has hit the education sector which is quite influential on human life. Enforcement of regulations while maintaining a distance of about one meter has implications for the education process in Indonesia. Therefore, the educational element must encourage the distance learning process. The term arises because it sees distance learning as an alternative to face-to-face methods so that education can always be held without controversy under any circumstances. This activity raises the use of technology that is used as teaching material for distance education. Distance learning techniques allow users to take advantage of technologies such as online learning. Teachers will be required to abandon using traditional techniques whose methods are somewhat indifferent. Online learning creates internet connectivity and the use of information technology in helping the teaching and learning process that can be applied in Google Classroom. In this article, researchers focus on using Google Classroom in the context of implementing distance learning during the Covid-19 pandemic.

The Role of Affect in an Agent-Based Collaborative E-Learning System Used for Engineering Education

2009 ◽  
pp. 510-528
Author(s):  
Mohamed Ben Ammar ◽  
Mahmoud Neji ◽  
Adel M. Alimi
Keyword(s):  
Facial Expressions ◽  
Affective Computing ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Learning Systems ◽  
Learning System ◽  
Agent Based ◽  
Affective Behaviors ◽  
E Learning

Affective computing is a new artificial intelligence area that deals with the possibility of making computers able to recognize human emotions in different ways. This chapter represents an implemented framework, which integrates this new area with an intelligent tutoring system. The authors argue that tutor agents providing socially appropriate affective behaviors would provide a new dimension for collaborative learning systems. The main goal is to analyse learner facial expressions and show how affective computing could contribute to learning interactions, both by recognizing learner emotions during learning sessions and by responding appropriately.

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

The Role of Satisfaction and Ease of Use on User Attitudes of E-Learning: Case Study MI Mumtaza

2020 ◽  
Author(s):  
Sururin ◽  
Munzier Suparta ◽  
Herlino Nanang ◽  
Amelia Zakiyyatun Nufus ◽  
Kamarusdiana ◽  
...  
Keyword(s):  
Ease Of Use ◽  
User Attitudes ◽  
E Learning

Exploring Effect Factors of E-Learning Behavioral Intention on Cross-Level Analysis

2011 ◽  
Vol 204-210 ◽  
pp. 174-177 ◽  
Author(s):  
Pei Wen Liao ◽  
Chien Yu ◽  
Chin Cheh Yi
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Behavioral Control ◽  
Hierarchical Linear Model ◽  
Perceived Behavioral Control ◽  
Performance Expectations ◽  
Individual Level ◽  
Use Of Technology ◽  
E Learning

The study, based on the unified theory of acceptance and use of technology (UTAUT), investigates the determinants of e-learning acceptance. We create a cross-level variable of the incentive and social influence to explore with the other variable context effect and the interaction effects in the acceptance of e-learning. Data collected from 932 respondents in Taiwan were tested against the research model using the hierarchical linear model approach. This model improved Yu, Liao, Wen’s research to detailed intended the learning environment. The results showed that individual-level variables (performance expectations, effort expectancy, perceived behavioral control), and group-level variables (incentive, social influence) have a positive effect on behavioral intention. The incentive has an effect on behavioral intention through the moderating role of manager influence.

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