Progress in Education Technologies

Author(s):  
Mediha Tezcan

The revolutions in the communication and information technologies in the 21st century have led to tremendous innovations in education technologies. From the advances in education technologies, all education programs, such as traditional education, open education, distance education, e-learning, massive open online courses, adult education and lifelong learning, are being positively influenced in our day, as a consequence of the digital revolution, education is in a process of rapid transformation. In this chapter; first the development of education technologies in the historical process has been examined, as divided into periods. In the second step, the structural characteristics of the development in education technologies have been defined. Third, the innovations and developments in education technologies during the 1980-2013 periods have been examined by grouping under the education media titles. Fourth, the contributions of the communication and information technologies to education have been defined. And finally, the impacts of the revolution in the education technologies on economic development have been interpreted.

Author(s):  
Abhishek Kumar ◽  
Shweta Nishad Brahmbhatt

This chapter aims to provide an up-to-date snapshot of the current state of application called MOOCs, which are one of the subset of e-Learning. MOOCs (Massive Open Online Courses) provide a new way of learning, which is open, participatory, distributed and lifelong. Various premier universities of the world are now offering courses in the form of MOOCs. The MHRD, Government of India has also started a MOOCs platform called SWAYAM. This chapter covers the definition of MOOCs, its features and different MOOC platforms being used for e-learning i.e. edX, Coursera, SWAYAM, Udacity.


This chapter covers the field of e-learning. The authors explain what e-learning is and what tools are currently available. The chapter will contain examples of said tools with information about whether the tools are useful for people with dyslexia. The MOOC (massive open online courses) is the most widely used and will be covered in detail. At the end of the chapter, the authors will also provide examples of emerging trends in the area of e-learning.


Author(s):  
Triloki Pant ◽  
Swati Pant

Massive open online courses (MOOCs) have evolved in past decade and become one of the prominent parts of the higher education system. The MOOCs provided a promising platform to aspirants who wanted to study further to either enhance their educational status or learn new technologies. With the evolution of MOOC, many platforms started to offer such courses, and many of them are not free as these courses need to register with some nominal fee. The role and need of libraries come at this point for MOOC courses as the courses are bundled with corresponding study material. The print library needs to assist e-library so that it may be compatible with the MOOCs and corresponding resources. The technological shift from print to e-library has a great impact on e-learning followed by MOOCs; however, the issue of MOOC libraries and resources is yet to be resolved to ensure the availability to all the users. The chapter deals with the need of library for MOOCs, its structure and technology shift from print library to e-library, along with the differentiation between e-learning and MOOCs.


2017 ◽  
Vol 15 (1) ◽  
pp. 69-81 ◽  
Author(s):  
Di Zou ◽  
Haoran Xie ◽  
Yanghui Rao ◽  
Tak-Lam Wong ◽  
Fu Lee Wang ◽  
...  

The world has encountered and witnessed the great popularity of various emerging e-learning resources such as massive open online courses (MOOCs), textbooks and videos with the development of the big data era. It is critical to understand the characteristics of users to assist them to find desired and relevant learning resources in such a large volume of resources. For example, understanding the pre-knowledge on vocabulary of learners is very prominent and useful for language learning systems. The language learning effectiveness can be significantly improved if the pre-knowledge levels of learners on vocabulary can be accurately predicted. In this research, the authors model the vocabulary of learners by extracting their history of learning documents and identify the suitable vocabulary knowledge scales (VKS) for pre-knowledge prediction. The experimental results on real participants verify that the optimal VKS and the proposed predicting model are powerful and effective.


Author(s):  
Xue Yang ◽  
Zhen Song

It is compulsory for us to strength the students’ law education in China in order to develop their overall qualities. It is also what we need to build a harmonious society. Along with the steady advancement of society, the surge of information technologies has contributed to the integration of various new teaching methods, models and platforms into the law education. This paper, based on the browser/server (B/S) architecture and the concept of Massive Open Online Courses (MOOCs), attempt s to profoundly analyze relevant situation of students' law education in universities. According to the findings, it is found that the teaching of MOOCs in China is evolving at full speed. User groups show different preferences for the disciplines since they have a great demand for vocational skills and undergraduate education. In China, there are some gaps in the law education in universities, for example, the teaching and evaluation methods look like relatively single, there is lack of pedagogical practices, teachers' pedagogies remain to be improved, and students' enthusiasm of legal education is low. The curriculum refinement and the mobile clients developed intensively constantly improve the design of the law education platform for students in universities. The study is beneficial to the construction of law education platform for students in universities in China.


2020 ◽  
Vol 17 (3) ◽  
pp. 236-252
Author(s):  
Samaa Haniya ◽  
Luc Paquette

Understanding learner participation is essential to any learning environment to enhance teaching and learning, especially in large scale digital spaces, such as massive open online courses. However, there is a lack of research to fully capture the dynamic nature of massive open online courses and the different ways learners participate in these emerging massive e-learning ecologies. To fill in the research gap, this paper attempted to investigate the relationship between how learners choose to participate in a massive open online course, their initial motivation for learning, and the barriers they faced throughout the course. This was achieved through a combination of data-driven clustering approaches—to identify patterns of learner participation—and qualitative analysis of survey data—to better understand the learners’ motivation and the barriers they faced during the course. Through this study we show how, within the context of a Coursera massive open online course offered by the University of Illinois, learners with varied patterns of participation (Advanced, Balanced, Early, Limited, and Delayed Participation) reported similar motivations and barriers, but described differences in how their participation was impacted by those factors. These findings are significant to gain insights about learners’ needs which in turn serve as the basis to innovate more adaptive and personalized learning experiences and thus advance learning in these large scale environments.


2016 ◽  
Vol E99.D (8) ◽  
pp. 2140-2150 ◽  
Author(s):  
Sila CHUNWIJITRA ◽  
Chanchai JUNLOUCHAI ◽  
Sitdhibong LAOKOK ◽  
Pornchai TUMMARATTANANONT ◽  
Kamthorn KRAIRAKSA ◽  
...  

Author(s):  
Abdessamad Chanaa ◽  
Nour-eddine El Faddouli

Massive Open Online Courses (MOOCs) have recently become a very motivating research field in education. Analyzing MOOCs discussion forums presents important issues since it can create challenges for understanding and appropriately identifying student sentiment behaviours. Using the high effectiveness of deep learning, this study aims to classify forum posts based on their sentiment polarity using two experiments. The first use the three known sentiment labels (positive/negative/neutral) and the second one employs sevens labels. The classification method implemented the Hierarchical Attention Network (HAN) algorithm; it combines the attention mechanism with a hierarchical network that simulates the same hierarchical structure of the document. The analysis of 29604 discussion posts from Stanford University affirms the effectiveness of our model. HAN achieved a classification accuracy of 70.3%, which surpassed the other prediction results using usual text classification models. These results are promising and have implications on the future development of automated sentiment analysis tool on e-learning discussion forum.


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