Jayakumar Sadhasivam

Abstract: This paper summarizes the findings from an empirical study carry out the online learning. The impact of information technology in our day-to-day life has been profound. Among many cross disciplines that have been enriched (or benefited) by information technology, educational media is not an exception. MOOC (Massive Open Online Courses brings learning, teaching and assessment. MOOC is a Web-based distance-learning program that is designed for the participation of large numbers of geographically dispersed students. In addition, Google and other companies are involving to design and fund to low-cost eLearning. Niche market provides nine certification courses via MOOC, to satisfy the employees specific needs. However, in the present day context the opinion on embracing MOOC by an University has been quite debatable. Addressing this debate on both sides, this papers presents the opinion expressed by the stakeholders in education towards embracing MOOC. Based on the findings from the study, the paper will discuss the challenge and broad concerns applicable to eLearning. The survey is focused on providing a consolidated fact that based on penetration of eLearning. This paper is aimed at providing a solid analysis of eLearning with the help of IT infrastructure in India. The survey contains demographic distribution of faculties; student and system administrator ratio is 39.6. Among a total of 792 of 2000 participants. It is focused that eLearning strategy in India.

Abstract: In recent years, Sentimental Analysis is used in all online product firms. The number of users using the particular product has increased which makes the industry to improvise the characteristics of the product. These days, many users who are using websites, blogs, online shopping tends to review the products they used. These reviews were taken into consideration by other users during their search for products. Hence the industry has found the root of delivering the correct product searched by the user based on the reviews of the users using the concept of sentimental analysis. Sentimental Analysis is the concept of data analysis where the collections of reviews are taken into consideration, and those reviews are analyzed, processed and recommended to the user. The reviews given are longer and which consist of a few paragraphs of content. In this paper, the dataset is collected from the official product sites. Initially, these reviews must be pre-processed in order to remove the unwanted data’s such as stop words, be verbs, punctuations, and conjunctions. Once, the pre-processing is over the trained dataset is classified using Naive Bayes and SVM algorithm. These existing algorithms provided the accuracy which is not worth enough. Hence, an ensemble approach has been applied to enhance the accuracy of the given reviews. An ensemble is a classification approach by combining two or more algorithms and calculate the mode value based on the vote reference for every algorithm which is used. In this paper, Naive Bayes, SVM, and Ensemble algorithm are combined. We proposed an Ensemble method that helps in providing better accuracy than the current existing algorithm. Once the accuracy is calculated, based on the reviews, the particular product is recommended for the user.

Abstract: A modern problem of current societies is the excellence of their education structures. MOOCs are innovative devices that have been utilized to enhance and augment the traditional educational framework. MOOC is defined to have enormous profit by its technological advances. When an instructive stage is available and still there is a scope for components to give virtual instructive situations where each learner is viewed as a principle performer in the outline of the learning process, thereby adding to expand the quality of education. It is essential for the MOOCs providers to see if learning is more powerful when it is introduced through one methodology as opposed to another methodology. This is especially essential when working with understudies with particular learning challenges who frequently experience issues get to realize when it is just exhibited through their weaker methodology. What we should remember is that people are different, and each of us learn differently (1) . The very same learning conditions, guidance and instructions (2) that can be so effective for one person can cause problems for another (3) . The learning styles must be anticipated deliberately, in light of the fact that the mental equalization is variable in nature and the MOOC are differentiated in light of the learning design, environment, time and their state of mind. Since 1930 the term learning style has been broadly utilized in psychology and pedagogy. Specifically, MOOC more often need components for perceiving users' learning styles, which depict the way a learner procures and process data. In this plan, we adduce a framework for automated identification of learning styles in MOOC. A key objective of this system design is to furnish and understand the user learning styles in MOOC.

Abstract: In today’s scenario, sentiment classification has been acknowledged as a significant aspect, as it delivers the techniques for automatically analyzing people’s reviews to extract useful information on a product or service. Polarity classification is one among those techniques which determine the text polarity in the opinion. In this regard, the given paper explains a method for sentiment classification of online course reviews using a novel classifier, whale-based deep belief network (WDBN). The input course review data is pre-processed in the given technique, and the key features are extracted from the data using emotion-SentiWordNet based feature extraction process. To classify sentiments in the feature extracted data, WDBN is brought in by combining deep belief networks and whale optimization algorithm such that the weights of the network layers are selected optimally. The given technique, with the application of WDBN, classifies the course reviews into two classes, such as positive and negative class reviews. The given WDBN classifier is tested with the help of a publicly accessible online course review dataset, and the performance of the classifier is assessed using three metrics, such as sensitivity, specificity, and accuracy, where it could attain maximum performance of 86.3% sensitivity, 81.1% specificity and 86% accuracy.

Abstract: The Delphi technique is a research method that involves experts and stakeholders in structured deliberation about topics through multiple, iterative rounds of data collection such as surveys or in-...

Abstract: In this paper we will explain massive open online courses (MOOCs)-how they started, their targeted audience, and what services they provide- and demonstrate selected MOOC service providers that best suit the Arabian Gulf region. The record annual growth for MOOCs has made many respected institutions reconsider their educational strategies. Many elite universities have started to join the stream; others are expected to join very soon. In this paper we will focus on select MOOC providers that will help institutions or individual instructors ride the stream before it is too late. All MOOC providers have been carefully selected to meet the author’s criteria of either having crossed a capacity range limit or being tailored to meet the Arabian Gulf region needs. Finally, the paper summarizes the best practices and gives recommendations for any Gulf region institution or individual for better implementation of MOOCs into their learning system.

Abstract: The process of developing education is a vital and important issue around the world as it is an issue that is inherited through time, and it is one of the most important challenges facing the world. Distance education is one of the means of developing education through which knowledge can be spread and which can help people to overcome obstacles of time and space. Recently, teaching and learning systems have become completely dependent on e-learning, especially during the corona virus disease (COVID-19) pandemic since the world has turned to electronic transactions in all areas, especially in education, and the most used technology includes the use of online training courses such as massive open online courses (MOOCs). It provides great support to the distance learning process as it can facilitate the learning process by diversifying its contents via media, such as text and video. In addition, MOOCs are the most popular and effective online courses. The aim of this paper is to provide an in-depth analysis of the definition, characteristics and patterns of MOOCs. Also, this paper discusses the specific advantages and disadvantages of taking up MOOCs along with the different challenges that MOOCs are facing. In addition, various suggestions will be given to make improvements that can help in making process enhancements to MOOCs. Finally, this paper presents the importance of MOOCs in the COVID-19 era. We hope this paper will help instructors to understand how MOOCs can be made more efficient, enable learners to become more organised and increase their understanding of MOOCs, and will help education development system specialists to find suitable solutions for problems that MOOCs are facing. Keywords: Massive open online courses, e-learning, online courses, distance education, COVID-19.

Abstract: Massive Open Online Courses (MOOCs) provides an effective learning platform with various high-quality educational materials accessible to learners from all over the world. In this paper, the types of learner characteristics in MOOCs second language learning are discussed. However, there are still problems and challenges including assessment. A quantitative research method approach has been utilized in this study. Results of the study are then used for implementing suitable adaptive self-assessment activities in MOOCs learning. Findings of this study are two folds: (1) The dimension of learner characteristics (learning styles and cognitive style) for improving student performance in MOOCs learning and (2) suitable self-assessment activities that consider learners requirement or adaptive to learner characteristics for improving MOOCs learning performance. Based on the findings, the data indicate that visual, active, thinking and intuitive learner is the proposed dimension used in this study. In this study, our aim is to propose adaptive self-assessment activities for improving MOOCs learning in the second language course. In the future study, students will be investigated about their engagement using MOOC assessment in the second language.

Abstract: Countless problems have been caused by the excessive emission of polluting gases, such as carbon dioxide (CO2), into the atmosphere. Therefore, more effective monitoring of CO2 is essential, especially in central or industrial regions. Thus, this work shows the development of a platform for monitoring the CO2 concentration, which is composed of autonomous and independent sensors that have their own energy source, storage capacity, and data replication for the central server. To validate the platform, CO2 measurements were taken at three strategic points in an outdoor environment in a Brazilian urban center. This platform proved to be an evolution over another system previously proposed by the group that was based on the use of a wireless network of sensors to monitor CO2. This new project managed to overcome limitations that compromised the efficiency of the first platform, which were mainly related to the interference in the communication signals between the network sensors due to the existence of physical barriers in the monitoring environment. With that, this new platform showed greater security in the maintenance of collected data and allowed for the expansion of the physical complexity of the environments that can be monitored.