Dynamics of a Classical Particle in a Quasi Periodic Potential

We study the dynamics of a one-dimensional classical particle in a space and time dependent potential with randomly chosen parameters. The focus of this work is a quasi-periodic potential, which only includes a finite number of Fourier components. The momentum is calculated analytically for short time within a self-consistent approximation, under certain conditions. We find that the dynamics can be described by a model of a random walk between the Chirikov resonances, which are resonances between the particle momentum and the Fourier components of the potential. We use numerical methods to test these results and to evaluate the important properties, such as the characteristic hopping time between the resonances. This work sheds light on the short time dynamics induced by potentials which are relevant for optics and atom optics

Informing Science & IT Education Conference (InSITE)

PRACTIS (Privacy Appraising Challenges to Technologies and Ethics) is a research project initiated by the EU. It was carried out over three and one half years by research institutes of six countries: Israel (project coordinator), Poland, Germany, Finland, Belgium, and Austria. PRACTIS was concluded in April 2013 with the submission of a list of recommendations to the EU. PRACTIS focused on three major research tracks: Technological forecast, ethics and legal aspects of privacy, and the changing perception of privacy among younger generations (Internet &quot;natives&quot;). This paper consists of two parts. The first part describes one of the most interesting studies which were carried out within PRACTIS &ndash; the high-school children survey about their perception of privacy. The second part outlines some policy recommendation mostly for governments and regulators. The major conclusion of the high-school survey indicates that there is, indeed, a different perception of privacy among teenagers. For them, the individual sphere in which they wish to protect their privacy is not limited only to their immediate physical environment (home, diary, body), but it is expanded also to their virtual environment such as social networks sites (SNS). They are also willing to trade benefits provided by the digital environment for privacy. &nbsp; The major recommendation conveyed to the EU is that there is no one &quot;deus ex machine&quot; solution to the threats privacy faces due to emerging technologies such as ICT, Genetics, Nanotechnology, Cognitive and Brain Sciences, and the like. There should be a comprehensive strategy and policy and a basket of solutions adhering to technology, law and regulations, organizational issues, education, and social issues. A detailed list of recommendations is exhibited in the article.</p

Implementation of Tel Aviv University MOOCs in Academic Curriculum: A Pilot Study

The study presented in this paper examines the feasibility of using MOOCs as a learning environment in academic courses. This paper focuses on the students who participated in two MOOCs offered by Tel Aviv University (TAU) during the year 2013. The preliminary findings of this pilot study illustrate the scope of student activity, the learning intensity, and learner path. In addition, attitudes of TAU students who participated in these courses as part of their curriculum are presented. From TAU’s perspective, the presented MOOCs are considered to be a successful experience for all those involved: the students, who were very satisfied with their learning and high achievements; the lecturer team, who were very enthusiastic and satisfied with the learning process as well as the new experience; and the University policy makers, who took the challenge and integrated this new model of learning into the academic environment

Patterns of Students’ Utilization of Flexibility in Online Academic Courses and Their Relation to Course Achievement

Online academic courses provide students with flexible learning opportunities by allowing them to make choices regarding diverse aspects of their learning process; hence, such courses support personalized learning. This study aimed to analyze the ways students make use of flexibility in online academic courses based on learning time, place, and access to learning resources, as well as to investigate how this relates to differences in course achievement. The study examined 587 students in four online courses. Educational data mining (EDM) methodology was used to trace students’ behavior in the courses and to compute 34 variables, which describe their use of flexibility. The results show that students developed different patterns of learning time, place, and access to content, which indicates that flexibility was used substantially. Students’ achievements were significantly related to patterns of learning time and access to learning resources. Understanding the different patterns of flexibility usage may support the design of personalized learning and increase collaboration among students with similar characteristics

Types of Participant Behavior in a Massive Open Online Course

In recent years there has been a proliferation of massive open online courses (MOOCs), which provide unprecedented opportunities for lifelong learning. Registrants approach these courses with a variety of motivations for participation. Characterizing the different types of participation in MOOCs is fundamental in order to be able to better evaluate the phenomenon and to support MOOCs developers and instructors in devising courses which are adapted for different learners' needs. Thus, the purpose of this study was to characterize the different types of participant behavior in a MOOC. Using a data mining methodology, 21,889 participants of a MOOC were classified into clusters, based on their activity in the main learning resources of the course: video lectures, discussion forums, and assessments. Thereafter, the participants in each cluster were characterized in regard to demographics, course participation, and course achievement characteristics. Seven types of participant behavior were identified: Tasters (64.8%), Downloaders (8.5%), Disengagers (11.5%), Offline Engagers (3.6%), Online Engagers (7.4%), Moderately Social Engagers (3.7%), and Social Engagers (0.6%). A significant number of 1,020 participants were found to be engaged in the course, but did not achieve a certificate. The types are discussed according to the established research questions. The results provide further evidence regarding the utilization of the flexibility, which is offered in MOOCs, by the participants according to their needs. Furthermore, this study supports the claim that MOOCs' impact should not be evaluated solely based on certification rates but rather based on learning behaviors

A Methodology for Training Toolkits Implementation in Smart Labs

Funding Information: This study was supported by the Center of Technology and Systems (CTS-UNINOVA). Funding Information: European Commission ERASMUS + through grant number ° 2021-1-RO01-KA220-HED-000032176 LLSF. Publisher Copyright: © 2023 by the authors.Globally, educational institutes are trying to adapt modernized and effective approaches and tools to their education systems to improve the quality of their performance and achievements. However, identifying, designing, and/or developing promising mechanisms and tools that can impact class activities and the development of students’ outputs are critical success factors. Given that, the contribution of this work is to propose a methodology that can guide and usher educational institutes step by step through the implementation of a personalized package of training Toolkits in Smart Labs. In this study, the package of Toolkits refers to a set of needed tools, resources, and materials that, with integration into a Smart Lab can, on the one hand, empower teachers and instructors in designing and developing personalized training disciplines and module courses and, on the other hand, may support students (in different ways) in developing their skills. To demonstrate the applicability and usefulness of the proposed methodology, a model was first developed, representing the potential Toolkits for training and skill development. The model was then tested by instantiating a particular box that integrates some hardware to be able to connect sensors to actuators, with an eye toward implementing this system mainly in the health domain. In a real scenario, the box was used in an engineering program and its associated Smart Lab to develop students’ skills and capabilities in the areas of the Internet of Things (IoT) and Artificial Intelligence (AI). The main outcome of this work is a methodology supported by a model able to represent Smart Lab assets in order to facilitate training programs through training Toolkits.publishersversionpublishe