Robotics E-Learning Supported by Collaborative and Distributed Intelligent Environments

Robotics e-learning environment that facilitates tailored learning for individual students studying robotics is developed. The developed collaborative and distributed intelligent environment (CoDIE) enables multi-users to access simultaneously remote and integrated mixed reality facilities through the web. The developed system constitutes a robotic center to help in transferring theoretical knowledge enhanced by simulation and practical experience. It enables realistic interaction by immersing users in a shared 3D CoDIE. The system enables users to do programming, simulations, experiments, manipulating data and objects, diagnostics and analyses, control and monitor actions. Also, users can receive feedback from the system or instructors. The developed system has been implemented and tested using two real manipulators and virtual robots supporting real-time tracking and simulation. Three modes of operations have been implemented, individual robot training mode through virtual robot models, multi-user mode working together, and individual or group-based training by instructor.

AI and Individualized Education in Phys Ed and Sport

The development of AI technologies in recent years has opened the doors to a wide array of application domains. One field of study in particular has great potential to use this knowledge: physical education and sport. New devices and software have made their way into the field of physical activity, motivating the investigation of AI-driven technologies as a tool in developing a new type of educational system. The general scope of this chapter is to analyze the use of AI individualized education in one major field of study: physical education and sport. The use of AI technologies in training future teachers is also discussed and analyzed. The implementation of AI software in sport is brought to attention, along with relevant case studies. Limitations and hurdles in constructing intelligent support systems for training were identified. Accessibility of an AI-driven educational system was detailed, pointing out barriers with regard to culture, social environment, and age differences.

The Changing Roles of Teachers With AI

Artificial intelligence (AI) is ubiquitous in our lives and is progressing at an accelerated rate in the past 60 years. AI application is diverse and AI technology continues to grow. It enables a machine to think like human beings and has opened a new horizon for industries, businesses, transportation, hospitals, and schools. How is AI applied to educational settings? How will the emergence of AI technology assist teachers' teaching and improve students' learning? Will the implementation of AI technology in education replace schoolteachers? What would be the ethical concerns of AI technology? What role do teachers play with AI in education? The purpose of this chapter is to explore the roles that teachers play in the innovation and evolution of AI and to seek approaches teachers should take in coping with AI technology. Issues and problems of teaching with AI will be discussed; solutions will be recommended.

The Wit-Learning Methodology as a Means for Research Skills Acquisition

The present blistering modernization, epitomized by artificial intelligence, demands engineering graduates to address holistic, fast-changing, and even unknown problems. Thus, skills development, such as self-learning, is gaining importance against the traditional educational approach. To this regard, the wit-learning methodology was designed to stimulate the research skills during a course, supported on the similitude of the research endeavor with the desired engineers' profile. It stands out from other proposed alternatives targeting the students' capabilities that do not focus on research skills or misses their quantitative evaluation. In this chapter, the wit-learning methodology is presented together with its assessment regarding research skills acquisition, using direct and indirect measurements. Notably, it was verified to help improve the research skills through three criteria: the improvement of the students' research reports, the increased students' agreement to researchers while evaluating research reports, and their understanding of the research goals and processes.

Concerning the Integration of Machine Learning Content in Mechatronics Curricula

Machine learning is becoming more and more important for mechatronic systems and will become an ordinary part of today's student life. Thus, it is obvious that machine learning should be part of today's student's curriculum. Unfortunately, machine learning seldomly is implemented into the curriculum in a substantial or linking manner, but rather offered as an elective course. This chapter provides an analysis of how machine learning can be integrated as a mandatory part of the curriculum of mechatronic degree courses. It is considered what the required minimal changes in fundamental courses should be and how traditional subjects like robotics, automation, and automotive engineering can profit most of this approach. As a case study, this chapter utilizes an existing German mechatronic degree course specialized on information technology, which covers most of the discussed aspects.

Virtual Laboratory to Face New Challenges in the Industry

The fast-growing field of technology allows for the development, design, and implementation of smart solutions to several industries such as smart grid, manufacturing, automotive, and robotics. Trends in smart solutions are based on providing a certain degree of intelligence to the process and products through intelligent artificial and machine learning algorithms. It also involves further use of devices based on power electronics elements, fast microcontrollers, intelligent algorithms, and processing of information via local or cloud. Hence, a new workforce that possesses multidisciplinary skills (i.e., dealing with different fields of knowledge in order to find solutions to complex problems) is required. Recently, virtual laboratories have emerged so as to aid in the improvement of forming engineers. In this chapter, a virtual co-simulation laboratory is proposed to deal with the lack of engineers with multidisciplinary skills in mind; additionally, a new framework based in co-simulation, co-modeling, and co-design is proposed in order to maximize the use of the laboratory proposed.

Revolution by Evolution

This chapter will discuss the development of intelligent tutoring systems (ITSs) for education in the last decade and will trace the challenges they meet. The author will examine the social and cultural impacts of several types of ITSs, from data-driven ITSs, which became the backbone of educational data mining approaches, to model-based adaptive systems. The latter utilizes artificial-intelligence-based tools that can provide dialogue to engage students in the learning process, to provide open learning models in order to promote self-awareness, to adopt meta-cognitive scaffolding, to use social simulation models, and to use cultural models. The layout of the chapter is as follows: the author will describe the technology of various ITSs with a focus on implementation of different techniques and algorithms in ITS modules (e.g., student modeling module, pedagogical module, and interface), followed by a discussion of how these ITSs begin to change the whole spectra of educational paradigms toward open everyone-is-a student models.

A New Paradigm for Acceptance of Analytics in Learning Management Systems at Jordanian Universities (JLMS)

E-learning or learning management systems (LMS) are broadly used in higher education systems. They've become a necessity to help the participants (instructors, students, and administrators) in their daily use. Learning analytics presents an auspicious approach. This chapter aims to examine the acceptance of analytics and use of an LMS at Jordanian universities. It also focuses on the factors influencing acceptance of analytics in LMS at Jordanian universities. Therefore, the chapter presents a new model for acceptance of analytics in learning management systems at Jordanian universities. It calls Jordanian learning management system (JLMS). This chapter is based on the most recent and related literature explaining various scenarios where learning management systems address learning issues in the digital environment in a way that was not possible in the previous confines of print logics.

Intelligent Tutoring Systems for Filipino Learners

Intelligent tutoring systems (ITS) research is not a new field of study. Despite its pedagogical value, very few ITS are developed intended for Filipino learners. The dearth of ITS research in a local setting discounted the fact Filipino learners might need a different learning approach. This chapter presented the state of ITS research in the Philippines. Readers would be informed that there is a need for multidisciplinary studies relating to Filipino learners that could serve basis for the development of culturally-related ITS. It also described Filipino learners in terms of culture, and it will attempt to link these descriptions as design considerations for the development of ITS. Finally, it provided insights and directions on how to develop an ITS for Filipino learners.

Impact of Social and Cultural Challenges in Education Using AI

Learning is the main feature that is connected to education. Education increases the power of visualization and to differentiate between the right and wrong. Education in these days has become expensive for the poor guardians. Education indeed helps to know the real values in relation to social and cultural behavior so that one can become a decent person in nature in society. The role of technology in modern education helps to lookout the current trends and to solve the problems using artificial intelligence in education. AI tools play a vital role in research and help to access the literature worldwide. AI can also provide the solution to social challenges like diversity in nature, security, and privacy of the person. Apart from education, AI has made an impact in other fields like social media, communication, and technology.