The rapid evolution of information and communication technologies (ICT) has created a new paradigm of the Internet, known as the Internet of Things (IoT), which represents a group of connected objects Using wireless links (WiFi, RF, NFC, Zigbee…)to exchange information between objects and persons. The Internet of Things has changed the way people and objects interact with each other, and education has not been immune to this change, which has created new forms of interaction between teachers and learners that helps improve the teaching and learning process.In the field of education, we can imagine that students use new technologies to carry out projects and educational activities in the classroom. In this research,the focus is on the application of Internet of Things in the Smart Classrooms.This paper presents and discusses the need of integrating the Internet of Things to improve learning at the basic and secondary school, mainly through information and communication technologies (ICT) at its disposal.

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Schools are responsible for helping students in their vocational career development in the sense that they should sustain students in developing skills required by the job market. Pre-tertiary school guidance is an indispensable aspect, since poor scholar guidance is always associated with failure at school. In the context of career paths, we propose an innovative approach, a solution to guide pre-tertiary students to choose the optimum vocational path. The purpose of the current study is to develop a school guidance system called "IoT-School Guidance". The latter is supposed to create a smart and conducive environment for the successful adoption of school guidance using the Internet of things (IoT), given the fact that the IoT is the next revolutionary technology in the world where anything can transmit and receive information in real time. It is a new approach that includes implementing an adaptive orientation process using smart technologies to guide pre-tertiary students choose and follow the best professional career generated automatically by the IoT-school guidance system.

Nowadays, the world has known great changes which accelerated the mode of life. Students, on their part have become to expect a stimulating and simple learning experience which takes into consideration this quick pace and helps them solve the stereotypical problems of learning. The analyses conducted in this paper revealed that the recording of attendance in classrooms is done at the expense of the teaching- learning time. Therefore, the article at hand seeks to investigate an effective means to record attendance in a way which doesn’t hinder learning. Differently put, the educational and administrative staffs need to find an effective way to record students’ attendance at presential at the beginning of each learning session without affecting the time allotted to teaching and learning. This article presents and discusses the smart attendance monitoring system in smart classroom as a means to reduce the dropout rate, using connected objects and RFID technology. This system can facilitate the recording of students’ attendance via the Internet of things (IoT) at presential while transmitting attendance record to the administration. At the same time, parents can keep track of their children's attendance to classes through a notification they receive via Email or SMS. In addition, the system automatically sends missed lessons to absent students.

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School guidance is declared an integral part of the education and training process, as it accompanies students in their educational and professional choices. Accordingly, the current situation in light of the Covid-19 epidemic requires a reconsideration of school guidance together with the methods of accompanying the student to choose the field that suits his/her personality, knowledge qualifications, perceptual and intellectual skills in order to achieve an excellent educational level that enables the learner to work in future professions. The current study aims to predict a student's potential and provide support for academic guidance. This paper emphasizes the importance of supervised machine learning and classification algorithms to predict the personality type based on student traits. Based on the information gathered, the results of this study indicate that it contributes significantly to providing a comprehensive approach to support academic self-orientation.