Prototype System for Multiple Sources Multiple Search Techniques Prediction (Algorithm and architecture)

The future of health care may be in “predictive health” that emphasizes prediction instead of diagnosis. Nowadays, the researchers are mining the data provided in social networks, aiming in prediction of diverse phenomena like social, political, medical, etc. The first part of the paper outlines the e-Health revolution phenomena. Next, we are focused on proposing a searching algorithm for predicting children general diseases in FYROM. The prediction task of the health related issues of specific people from noisy data is taken into consideration. We offer a model that can predict children general diseases with high percentage precision and good semantic recall on the basis of special designed ontology and social ties with other people, as revealed by their posts in social networks which is advised to be used by young mothers in our country. Also the architecture for ontology to database conversion is suggested and ready for implementation

A Google Classroom-Based Learning Management System: Empirical Evidence from SEEU

The use of e-learning in a higher education institution is identified by the implementation of Learning Management Systems (LMS). South East European University’s LMS experience is longer than a decade. From last year SEE – University is adopting Google Classroom (GC). However, despite adoption of these systems, there are considerable challenges facing the usage of the systems. Hence, a tool has been developed to track the activity of the teachers in the system and to analyze the factors that maximize its usage. Moreover, a module for course and users’ management was also implemented. The purpose of this paper is to introduce a new approach of investigating the usage of GC, i.e. identifying the determinants of undertaking GC activities, by conducting empirical analysis for the case of SEEU. Using SEEU Usage Google Classroom Report &amp; Analysis Data for 2016–2017 (SUGCR dataset 2017), we argue that (i) GC activities are affected by demographic characteristics and (ii) level, number of courses, and department affect the usage of GC. We apply appropriate estimation technique such as mlogit methodology. Identifying factors which encourage GC activities, with special emphasis on SEEU, might be of crucial importance for Higher Education academic leaders as well as software developers who design tools related to fostering GC. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

LMS Solution: Evidence of Google Classroom Usage in Higher Education

Background: Learning Management Systems (LMS) represent one of the main technology to support learning in HE institutions. However, every educational institution differs in its experience with the usage of these systems. South East European University’s LMS experience is longer than a decade. From last year SEE – University is adopting Google Classroom (GC) as an LMS solution. Objectives: Identifying factors which encourage LMS activities, with special emphasis on SEEU, might be of crucial importance for Higher Education academic leaders as well as software developers who design tools related to fostering LMS. Methods/Approach: This paper introduces new approach of investigating the usage of LMS, i.e. identifying the determinants of increasing usage of LMS activities, by conducting empirical analysis for the case of SEEU. We apply appropriate estimation technique such as OLS methodology. Results: Using SEEU Usage Google Classroom Report & Analysis Data for spring semester (2016–2017) and winter semester (2017–2018) - SUGCR dataset 2017, we argue that (i) LMS activities are affected by demographic characteristics and (ii) the students’ LMS usage is affected by level and resources of instructors’ LMS usage. Conclusions: The empirical results show positive relationship between student and instructors’ LMS usage

LMS Solution: Evidence of Google Classroom Usage in Higher Education

Background: Learning Management Systems (LMS) represent one of the main technology to support learning in HE institutions. However, every educational institution differs in its experience with the usage of these systems. South East European University’s LMS experience is longer than a decade. From last year SEE – University is adopting Google Classroom (GC) as an LMS solution