Intelligent Tutoring Systems for Generation Z's Addiction

As generation Z's big data is flooding the Internet through social nets, neural network based data processing is turning an important cornerstone, showing significant potential for fast extraction of data patterns. Online course delivery and associated tutoring are transforming into customizable, on-demand services driven by the learner. Besides automated grading, strong potential exists for the development and deployment of next generation intelligent tutoring software agents. Self-adaptive, online tutoring agents exhibiting "intelligent-like" behavior, being capable "to learn" from the learner, will become the next educational superstars. Over the past decade, computer-based tutoring agents were deployed in a variety of extended reality environments, from patient rehabilitation to psychological trauma healing. Most of these agents are driven by a set of conditional control statements and a large answers/questions pairs dataset. This article provides a brief introduction on Generation Z's addiction to digital information, highlights important efforts for the development of intelligent dialogue systems, and explains the main components and important design decisions for Intelligent Tutoring System.Comment: 4 page

Attention Patterns Detection using Brain Computer Interfaces

The human brain provides a range of functions such as expressing emotions, controlling the rate of breathing, etc., and its study has attracted the interest of scientists for many years. As machine learning models become more sophisticated, and bio-metric data becomes more readily available through new non-invasive technologies, it becomes increasingly possible to gain access to interesting biometric data that could revolutionize Human-Computer Interaction. In this research, we propose a method to assess and quantify human attention levels and their effects on learning. In our study, we employ a brain computer interface (BCI) capable of detecting brain wave activity and displaying the corresponding electroencephalograms (EEG). We train recurrent neural networks (RNNS) to identify the type of activity an individual is performing

Hybrid Courses and Associated Distributed Learning Paradigms

Current learning management system (LMS) are distributed learning environments that allow administration, documentation, tracking and delivery of educational programs worldwide. LMSs are targeted mainly towards online learning delivery but they also support hybrid forms. In this paper we present a brief review of current trends in LMS development and a case study targeted at student-student interaction improvement. We show how the hybrid version of a course can overcome some of the challenges associated with student retention, as well as present specific web-based tools and methods that can positively impact student learning and interaction. The experimental results prove that student retention can be improved by adopting specific early warning systems while student learning is positively affected through the employment of specific tools available in the LMS

Intelligent Tutoring Systems for Generation Z’s Addiction

This article was published in the Proceedings of the 12th International Conference on Mobile, Hybrid, and On-line Learning

Multimodal, Visuo-Haptic Games for Abstract Theory Instruction: Grabbing Charged Particles

An extensive metamorphosis is currently taking place in the education industry due to the rapid adoption of different technologies and the proliferation of new student-instructor and student–student interaction models. While traditional face-to-face interaction is still the norm, mobile, online and virtual augmentations are increasingly adopted worldwide. Moreover, with the advent of gaming technology besides the 3D visual paradigm, the “touch” and “feel” paradigm is slowly taking its place in the user interface design through gamification. While haptic (force feedback) devices were barely available a decade ago outside research laboratories, the rapid rise in gaming technology has driven the cost significantly lower enabling the spread of these devices in many households and the wide public. This article presents a novel haptic-based training tool implemented as a gaming scenario to assist students in learning of abstract concepts in Physics. The focus is on electromagnetism as one of the fundamental forces in nature and specifically the abstractions used as building blocks around the Lorentz force. Experimental results suggest that by introducing well designed visual-haptic interfaces in presenting abstract concepts, students become better engaged in the classrooms and superior learning outcomes can be achieved

Survey on e-Learning Implementation in Eastern-Europe - Spotlight on Romania

Rapid proliferation of mobile technology and the Internet in Eastern-Europe for the past decade has had a significant impact on information distribution and has facilitated the introduction of novel e-Learning systems and technologies. The rapid growth and use of technology, as well as the ongoing transition towards a knowledge-based society of the workforce, has triggered in Romania the need and pressure to learn continuously. The paper provides an overview on e-Learning developments in Eastern-Europe taking as case-study Romania. As part of the European Union (EU), Romanian’s education system is developed and evolves in the context of EU’s regulations. However, recent developments in the area of online learning in Eastern Europe, specifically the fast pace of development of these systems in Russia could have a strong impact on regional markets. A comparison with US developments in e-Learning is provided to emphasize common issues in the development and adoption of e-Learning systems

Survey on Intelligent Dialogue in e-Learning Systems

Ever since ancient times, learning was a two-way process, a dialogue among the tutor and the learner. The transfer of knowledge implies social interaction, hence the dialogue is of utmost importance. With the widespread of social media and mobile systems, learners expect quick, easy responses to their questions any time of the day. As e-Learning systems promote time and location flexibility, synchronous dialogue in such systems should not be bound to the time frames that the instructor is available, but should allow learners active real-time feedback throughout the day. Such synchronous interaction is possible through a variety of tools like: automated intelligent grading, intelligent tutoring systems and intelligent facilitator agents embedded in the Learning Management System or social networks. This paper provides an overview of automated dialogue characteristics and a survey on recent research efforts in academia and industry in building intelligent dialogue capable systems. Imagine a system that adapts intelligently to learners’ requests and allows them to take control of their own learning, making the bulky learning interface transparent to the user

Survey on Intelligent Dialogue in e-Learning Systems

Ever since ancient times, learning was a two-way process, a dialogue among the tutor and the learner. The transfer of knowledge implies social interaction, hence the dialogue is of utmost importance. With the widespread of social media and mobile systems, learners expect quick, easy responses to their questions any time of the day. As e-Learning systems promote time and location flexibility, synchronous dialogue in such systems should not be bound to the time frames that the instructor is available, but should allow learners active real-time feedback throughout the day. Such synchronous interaction is possible through a variety of tools like: automated intelligent grading, intelligent tutoring systems and intelligent facilitator agents embedded in the Learning Management System or social networks. This paper provides an overview of automated dialogue characteristics and a survey on recent research efforts in academia and industry in building intelligent dialogue capable systems. Imagine a system that adapts intelligently to learners’ requests and allows them to take control of their own learning, making the bulky learning interface transparent to the user

Attention Patterns Detection Using Brain Computer Interfaces

This publication was published in the Proceedings of the Annual ACM Southeast Conference (ACMSE 2020). The human brain provides a range of functions such as expressing emotions, controlling the rate of breathing, etc., and its study has attracted the interest of scientists for many years. As machine learning models become more sophisticated, and biometric data becomes more readily available through new non-invasive technologies, it becomes increasingly possible to gain access to interesting biometric data that could revolutionize Human-Computer Interaction. In this research, we propose a method to assess and quantify human attention levels and their effects on learning. In our study, we employ a brain computer interface (BCI) capable of detecting brain wave activity and displaying the corresponding electroencephalograms (EEG). We train recurrent neural networks (RNNS) to identify the type of activity an individual is performing