scholarly journals The conception and design of e-learning systems viewed from the standpoint of a language teaching platform: Learning English v. 2.0

2006 ◽  
Vol 3 (2) ◽  
Author(s):  
Leydier Argüelles
Keyword(s):  
Language Teaching ◽  
Learning Systems ◽  
Teaching Platform ◽  
E Learning ◽  
Learning English

scholarly journals IMPROVING THE ERGONOMIC QUALITY OF AR-BASED E-LEARNING SYSTEMS: A TASK-BASED DESIGN APPROACH

2014 ◽  
Vol 9 (2) ◽  
pp. 150-157
Author(s):  
Costin Pribeanu
Keyword(s):  
Augmented Reality ◽  
Learning Systems ◽  
Design Approach ◽  
Learning Goals ◽  
Teaching Platform ◽  
User Centred Design ◽  
Usability Problem ◽  
E Learning ◽  
Task Sequences

Augmented reality (AR) is a challenging technology for e-learning. Nevertheless, the benefits of AR in terms of increased engagement and motivation could be undermined by a low ergonomic quality. A challenge for designers is to provide students with a usable AR environment that is able to support an effective and efficient achievement of their learning goals. A user-centred design approach requires understanding users and the tasks they perform. This analysis focuses on task modelling and presents a task-based approach to the development of a Chemistry application implemented on an AR teaching platform. The task model enables an analysis of critical task sequences, helps to prevent potential usability problem, and provides with a basis for a task-based approach to evaluation. Key words: ergonomic quality, user-centred design, usability, task modelling, e-learning, augmented reality.

Platform for Analysing and Encouraging Student Activity on Contest and E-learning Systems

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Educational Policy ◽  
Learning Systems ◽  
Data Sources ◽  
Or Education ◽  
Student Activity ◽  
The World ◽  
E Learning ◽  
Analyse Data

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

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