scholarly journals Opinion Prediction of Hungarian Students for Real-Time E-Learning Systems: A Futuristic Sustainable Technology-Based Solution

2020 ◽  
Vol 12 (16) ◽  
pp. 6321 ◽  
Author(s):  
Chaman Verma ◽  
Zoltán Illés ◽  
Veronika Stoffová ◽  
Viktória Bakonyi
Keyword(s):  
Real Time ◽  
Opinion Mining ◽  
Positive Association ◽  
Sustainable Technology ◽  
Use Of Technology ◽  
Momentum Correlation ◽  
E Learning ◽  
Impact Of Technology ◽  
Technology Benefits ◽  
Mining Model

This work is a new step towards the understanding of students’ opinions about the use of technology in learning and improvements to provide sustainable E-learning solutions. Every higher educational university tries to provide well-suited, updated, and trending technology-based education facilities to its students. The task of analyzing the student’s sentiment about technology delivers benefits not only to ICT administrators, but also to management to become aware of the technological concerns. The opinions of Hungarian university students were analyzed using the regression method. We investigated 165 primary samples supported by the four hypotheses. The reliability of the data sample was calculated as 0.91 with Cronbach alpha testing. The Pearson Momentum Correlation (PMC) proved that the suggested technology benefits had a linear positive association with the student’s opinion. Furthermore, technology usability was positively correlated with the benefits. The supporting results of the regression model evidenced the significant impact of technology usability and benefits on the opinions. Using Exploratory Factor Analysis (EFA), we proposed significant features for the model that predicted students’ opinions using the educational benefit and usability parameters. These parameters statistically significantly predicted student’s opinions: F (2, 162) = 104.9, p < 0.05, R2 = 0.559. This study may be supportive of implementing the opinion mining model online and useful to university authorities to understand better the students’ sentiments about the current technological facilities provided. The authors proposed an opinion mining model to deploy on the university’s real-time “E-lection” sustainable technology.

Activity Theory for Studying Technology Integration in Education

2011 ◽  
pp. 14-21
Author(s):  
Lorna Uden ◽  
Griff Richards ◽  
Dragan Gaševic
Keyword(s):  
Technology Integration ◽  
Activity Theory ◽  
Cultural Issues ◽  
Ict Integration ◽  
Use Of Technology ◽  
Integration Of Technology ◽  
E Learning ◽  
Cultural Historical Activity ◽  
Impact Of Technology ◽  
The Impact

As can be seen, successful integration of technology into the classrooms depends on many factors. How do we study the effectiveness of technology integration in schools? We believe that cultural historical activity Activity Theory for Studying Technology Integration in Education a theory can be used as a framework to study the ICT integration processes in schools. This paper describes how learning activities in ICT-mediated classrooms must be understood in the context of larger socio-cultural issues. The structure of the paper is as follows. In the next section, we briefly review the use of technology for e-learning, followed by the impact of technology integration. A brief review of activity theory is then given, followed by how it can be used to study the effectiveness of technology integration. The final section of the paper presents the conclusion.

Opinion Mining with Real Time Ontology Streaming Data

2019 ◽  
Vol 23 (1) ◽  
pp. 346-357
Author(s):  
Vithya G ◽  
Naren J ◽  
Varun V
Keyword(s):  
Real Time ◽  
Opinion Mining ◽  
Streaming Data

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

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.

scholarly journals Detection of Mycobacterium avium Subspecies Paratuberculosis in Pooled Fecal Samples by Fecal Culture and Real-Time PCR in Relation to Bacterial Density

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1605
Author(s):  
Annika Wichert ◽  
Esra Einax ◽  
Natalie Hahn ◽  
Anne Klassen ◽  
Karsten Donat
Keyword(s):  
Real Time ◽  
Mycobacterium Avium ◽  
Detection Probability ◽  
Mycobacterium Avium Subspecies Paratuberculosis ◽  
Positive Association ◽  
Significant Loss ◽  
Positive Sample ◽  
Bacterial Density ◽  
Fecal Samples ◽  
Real Time Quantitative Pcr

Within paratuberculosis control programs Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds have to be detected with minimum effort but with sufficient reliability. We aimed to evaluate a combination of random sampling (RS) and pooling for the detection of MAP-infected herds, simulating repeated RS in imitated dairy herds (within-herd prevalence 1.0%, 2.0%, 4.3%). Each RS consisted of taking 80 out of 300 pretested fecal samples, and five or ten samples were repeatedly and randomly pooled. All pools containing at least one MAP-positive sample were analyzed by culture and real-time quantitative PCR (qPCR). The pool detection probability was 47.0% or 45.9% for pools of size 5 or 10 applying qPCR and slightly lower using culture. Combining these methods increased the pool detection probability. A positive association between bacterial density in pools and pool detection probability was identified by logistic regression. The herd-level detection probability ranged from 67.3% to 84.8% for pools of size 10 analyzed by both qPCR and culture. Pools of size 10 can be used without significant loss of sensitivity compared with pools of size 5. Analyzing randomly sampled and pooled fecal samples allows the detection of MAP-infected herds, but is not recommended for one-time testing in low prevalence herds.

An Opinion-Tree Based Flexible Opinion Mining Model

2009 ◽  
Author(s):  
Juling Ding ◽  
Zhongjian Le ◽  
Ping Zhou ◽  
Gensheng Wang ◽  
Wei Shu
Keyword(s):  
Opinion Mining ◽  
Mining Model

Real-time imaging-based assessment model for improving teaching performance and student experience in e-learning

2017 ◽  
Vol 13 (3) ◽  
pp. 491-504 ◽  
Author(s):  
Muhammad Farhan ◽  
Muhammad Aslam ◽  
Sohail Jabbar ◽  
Shehzad Khalid ◽  
Mucheol Kim
Keyword(s):  
Real Time ◽  
Student Experience ◽  
Assessment Model ◽  
Teaching Performance ◽  
Real Time Imaging ◽  
E Learning

scholarly journals EXPLORATION OF E-LEARNING VS TRADITIONAL LEARNING IN INDIA

2020 ◽  
Vol 8 (2) ◽  
pp. 69-76 ◽  
Author(s):  
Gulbir Singh ◽  
Vivek Bhatnagar ◽  
Rajeev Gupta ◽  
Gautam Kumar
Keyword(s):  
Comparative Analysis ◽  
Real Time ◽  
Real Life ◽  
Research Data ◽  
University Education ◽  
Traditional Learning ◽  
Analysis Method ◽  
The Real ◽  
Huge Impact ◽  
E Learning

Purpose of Study: The purpose of the study is to carry out the comparison of traditional learning and e-learning with reference to university education. Methodology: A comparative analysis method that has been selected to fulfill the purpose of the study. The research data has been collected by various sources internet, previous research studies published in the Journal, universities which offer different technical and nontechnical programs .and further analyzed by in-depth understanding approach. Result: The outcome of this study will show the effect of e-learning in the current era. As we have compared e-learning with traditional learning and the result shows us that e-learning has filled the gap between the universities and the real-life industries' demands. Main finding: The result of this study showed that e-learning is the need of the present era in order to fulfill the gap between the universities and the real-life industries' demands. Additionally, e-learning based courses will have more impact and provide more skill and exposure to students as compared to traditional learning mode. Implications/Applications: This article can help the different universities and students to introduce more e-learning courses in their curriculum and they can fill the real-time industries' demands. Novelty/originality of the study: Our research can ensure that e-learning has a huge impact on our students and can help to increase the skills and exposure of them according to the current demands.

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