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electronic-learning
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Customer Satisfaction’s Index Identification in E-learning Courses Case Study in a Virtual University
, M.Sc. Thesis Sharif University of Technology ; Eissaei, Mohammad Taghi (Supervisor)
Abstract
E-learning is a broad set of methodologies and software’s, based on information technology, which provides learning opportunities for people of different backgrounds regardless of their location and time. E-learning has not only recently experienced a major uptake in business and academia, but has also proven itself as a necessity for most learners in different fields. This said, it is needless to mention that it has also encountered some difficulties and setbacks along its way to educational dominance. User satisfaction or customer satisfaction is one of the major means by which one can evaluate the success of such programs. Organizations on the other hand are incorporating behavioral...
An Investigation of Data Mining Methods in E-Learning
, M.Sc. Thesis Sharif University of Technology ; Habibi, Jafar (Supervisor)
Abstract
In the pas few years, the use of web-based education systems have grown exponentially spurred by the fact that neither students nor teachers are bound to a specific location and that this form of computer-based education is virtually independent of any specific hardware platforms. These systems can offer a great variety of channels and workspaces to facilitate information sharing and communication between participants in a course, let educators distribute information to students, produce content material, prepare assignments and tests, engage in discussions, manage distance classes and enable collaborative learning with virtual classroom sessions, forums, chats, file storage areas, news...
Fundamental Factors Influencing Selection and Continuous use of Online Learning Solutions and Identifiying their Values by Conjoint Analysis Method
, M.Sc. Thesis Sharif University of Technology ; Aslani, Shirin (Supervisor)
Abstract
With the easy access to internet and connected devices ubiquities, Today more than 50 million people use online education platforms to improve their skills and broaden their knowledge. In this research we tend to answer two questions based on data from Iranian students from top domestic universities.First question is which factors would these users consider in choosing their online education platform. This would be especially interesting to know in context of Iran’s cultural and job market situations.Second question we are interested in the same context is what are the factors that make users of these platforms to stop using them. This is very important since stoppage rate of online...
The Effect of Learner-Centered Blogging on the Iranian Students’ Essay Writing Skill and Attitude
, M.Sc. Thesis Sharif University of Technology ; Jahangard, Ali (Supervisor)
Abstract
Computer-assisted language learning (CALL) has been the focus of investigation in the field of foreign language learning for many years. This study aimed to investigate the impact of learning through blogging on the students’ essay writing skill and attitude in the Iranian context. As an extension of the research conducted earlier by Lin (2015) 32 Sharif University of Technology students were selected as the participants of the study. To this end, the students were divided into two groups of experimental group and control group. Then, they were instructed in two different ways by using different teaching methodologies. The bloggers, experimental group students, did not receive any direct...
Cloud computing based technologies, applications and structure in U-learning
, Article Proceedings 2012 17th IEEE International Conference on Wireless, Mobile and Ubiquitous Technology in Education, WMUTE 2012, 27 March 2012 through 30 March 2012 ; March , 2012 , Pages 196-198 ; 9780769546629 (ISBN) ; Manouchehry, M ; Sharif University of Technology
2012
Abstract
This article mainly focuses on the characteristic, technologies and applications of cloud computing in mobile and electronic learning, and analyzes the features of this concept. We firstly tried to clarify the meaning of cloud computing as well as its features, secondly, proposed different models of using cloud computing in different learning environments, including web-based learning, mobile video learning and observational learning
Massive Online Open Courses and Higher Education Policy in Iran
, M.Sc. Thesis Sharif University of Technology ; Miremadi, Iman (Supervisor) ; Honarvar, Ruhollah (Co-Supervisor)
Abstract
The digital age and its interlace with the pandemic has led to rapid changes in various institutions, including higher education. One of the factors that changes higher education is the expansion of E-learning and Massive Online Open Courses (MOOCs). Although about 15 years have passed since its creation, the pandemic has expanded the E-learning infrastructure and given it more attention, so that now everyone Confesses the possibility of distance education. On the other hand, although the development of MOOCs platforms and their considerable acceptance has attracted the attention of higher education professors and future researchers in this field, it is not properly considered by the...
Localized discriminative Gaussian process latent variable model for text-dependent speaker verification
, Article 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016, 27 April 2016 through 29 April 2016 ; 2016 , Pages 183-188 ; 9782875870278 (ISBN) ; Sameti, H ; Zeinali, H ; Sharif University of Technology
i6doc.com publication
2016
Abstract
The duration of utterances is one of the effective factors on the performance of speaker verification systems. Text dependent speaker verification suffers from both short duration and unmatched content between enrollment and test segments. In this paper, we use Discriminative Gaussian Process Latent Variable Model (DGPLVM) to deal with the uncertainty caused by short duration. This is the first attempt to utilize Gaussian Process for speaker verification. Also, to manage the unmatched content between enrollment and test segments we proposed the localized-DGPLVM that trains DGPLVM for each phrase in dataset. Experiments show the relative improvement of 27.4% in EER on RSR2015
Direct solution of the parametric stochastic distribution control problem
, Article Proceedings of the IEEE Conference on Decision and Control, 15 December 2009 through 18 December 2009, Shanghai ; 2009 , Pages 2616-2621 ; 01912216 (ISSN) ; 9781424438716 (ISBN) ; Nobakhti, A ; Wang, H ; Sharif University of Technology
Abstract
The Stochastic Distribution Control (SDC) problem is a generalised form of the minimum variance control problem where non-Gaussian noise distributions are encountered. The problem has been previously solved using two alternative approaches. When it is assumed that the output Probability Distribution Function (PDF) is measurable, then a parameterized controller is obtained. If on the other hand this assumption is removed (which corresponds to most practical cases), then the controller found is no longer parameterisable (i.e. it is a control action sequence). Both these approaches have thus far been solved using local Newtonian methods. In this paper a third alternative is presented which...
Learning linear non-Gaussian causal models in the presence of latent variables
, Article Journal of Machine Learning Research ; Volume 21 , 2020 ; Ghassami, A ; Kiyavash, N ; Zhang, K ; Sharif University of Technology
Microtome Publishing
2020
Abstract
We consider the problem of learning causal models from observational data generated by linear non-Gaussian acyclic causal models with latent variables. Without considering the effect of latent variables, the inferred causal relationships among the observed variables are often wrong. Under faithfulness assumption, we propose a method to check whether there exists a causal path between any two observed variables. From this information, we can obtain the causal order among the observed variables. The next question is whether the causal effects can be uniquely identified as well. We show that causal effects among observed variables cannot be identified uniquely under mere assumptions of...
A data-driven robust optimization algorithm for black-box cases: An application to hyper-parameter optimization of machine learning algorithms
, Article Computers and Industrial Engineering ; Volume 160 , 2021 ; 03608352 (ISSN) ; Azizi, M. J ; Akhavan Niaki, S. T ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
The huge availability of data in the last decade has raised the opportunity for the better use of data in decision-making processes. The idea of using the existing data to achieve a more coherent reality solution has led to a branch of optimization called data-driven optimization. On the one hand, the presence of uncertain variables in these datasets makes it crucial to design robust optimization methods in this area. On the other hand, in many real-world problems, the closed-form of the objective function is not available and a meta-model based framework is necessary. Motivated by the above points, in this paper a Gaussian process is used in a Bayesian optimization framework to design a...