Lms Selection Process For Effective Distance Education System In Organizations

 Towards the end of the 20th century, especially development of science and technology brought some innovation to some conceptual area such as education. In society, to build a quality and civilized life, education emerges as a one of the most important actors. Unfortunately, the rights in education of the every person in society may be delayed due to financial problems, physical disabilities, time pressure, geographical distances or any other reasons. Distance learning is a one of the method that provides education for people by eliminating these disadvantages. Since end of the 19th century, distance education has been provided with some methods such as TV, radio, mail and etc. Especially, in the beginning of 21th century; internet is widely used by everybody. New technological environment has brought a new opportunity for distance education. Learning Management System (LMS) is the most important actor of the internet based distance learning that brings together educators and students for training. LMS allows to deliver materials, having assignment and quizzes and other educational activities. Whether educational institutions or organizations that are emphasis on the training of employees can use LMS platform. Every organization has to decide which LMS is suitable for them. Decision makers face to solve this kind of problems because every LMS has different characteristics and different learning process. This study is focused on choosing suitable LMS for organizations by using AHP methods. Two groups of LMS, open source software’s (Moodle and Sakai) and commercial software’s (BlackBoard and Sharepoint LMS), are compared by using selecting criteria’s. These criteria’s are license costs, flexibility, security, user interface and prevalence of use. In the decision process, different weight ratios are used depending on their priority. The findings of this AHP Process are discussed. Keywords: Distance Learning, LMS, AHP, Decision Making Proces

Evaluation of learning management systems using interval valued intuitionistic fuzzy-z numbers

The use of online education tools has increased rapidly with the transition to distance education caused by the pandemic. The obligation to carry out all activities of face-to-face education online made it very important for the tools used in distance education to meet the increasing needs. In line with these needs, radical changes have occurred in the learning management systems used in distance education. Therefore, in this study, it is aimed to determine the features that the systems used in distance education should have and to compare the existing systems according to these features. For this purpose, a novel fuzzy extension, interval valued intuitionistic fuzzy Z-numbers, is defined for modeling uncertainty, and AHP and WASPAS methods using proposed fuzzy numbers are developed to determine the importance of decision criteria and compare alternatives.WOS:0010834495000112-s2.0-85173691458Emerging Sources Citation IndexArticleUluslararası işbirliği ile yapılmayan - HAYIRKasım2023YÖK - 2022-23Eki

The Assessment of the Usability of Digital Educational Resources: An interdisciplinary analysis from two systematic reviews

Producción CientíficaInternational reports analyzing current and future educational trends with an emphasis on technologies applied to education declare the importance of the design and application of digital educational resources. Guaranteeing its usability allows obtaining an adequate resource with a high pedagogical and technological quality. The objective of this paper is to analyze the empirical researches to determine if exists convergence between educational and computational researches on the assessment of the usability of digital educational resources. To fulfill the objective, the PRISMA protocol was used to carry out two systematic reviews and answer the two scientific questions. The results show that in few cases an adequate integration is achieved between: (1) the criteria for assessing usability as established by Software Engineering; (2) the methods and computational models to assess usability and, (3) the criteria established in pedagogical usability. Due to these shortcomings, a model for evaluating the usability of digital educational resources is proposed as future work. It concludes with the importance of interdisciplinary integration to assess the usability of digital educational resources

Automatic management tool for attribution and monitorization of projects/internships

No último ano académico, os estudantes do ISEP necessitam de realizar um projeto final para obtenção do grau académico que pretendem alcançar. O ISEP fornece uma plataforma digital onde é possível visualizar todos os projetos que os alunos se podem candidatar. Apesar das vantagens que a plataforma digital traz, esta também possui alguns problemas, nomeadamente a difícil escolha de projetos adequados ao estudante devido à excessiva oferta e falta de mecanismos de filtragem. Para além disso, existe também uma indecisão acrescida para selecionar um supervisor que seja compatível para o projeto selecionado. Tendo o aluno escolhido o projeto e o supervisor, dá-se início à fase de monitorização do mesmo, que possui também os seus problemas, como o uso de diversas ferramentas que posteriormente levam a possíveis problemas de comunicação e dificuldade em manter um histórico de versões do trabalho desenvolvido. De forma a responder aos problemas mencionados, realizou-se um estudo aprofundado dos tópicos de sistemas de recomendação aplicados a Machine Learning e Learning Management Systems. Para cada um desses grandes temas, foram analisados sistemas semelhantes capazes de solucionar o problema proposto, tais como sistemas de recomendação desenvolvidos em artigos científicos, aplicações comerciais e ferramentas como o ChatGPT. Através da análise do estado da arte, concluiu-se que a solução para os problemas propostos seria a criação de uma aplicação Web para alunos e supervisores, que juntasse as duas temáticas analisadas. O sistema de recomendação desenvolvido possui filtragem colaborativa com factorização de matrizes, e filtragem por conteúdo com semelhança de cossenos. As tecnologias utilizadas no sistema centram-se em Python no back-end (com o uso de TensorFlow e NumPy para funcionalidades de Machine Learning) e Svelte no front-end. O sistema foi inspirado numa arquitetura em microsserviços em que cada serviço é representado pelo seu próprio contentor de Docker, e disponibilizado ao público através de um domínio público. O sistema foi avaliado através de três métricas: performance, confiabilidade e usabilidade. Foi utilizada a ferramenta Quantitative Evaluation Framework para definir dimensões, fatores e requisitos(e respetivas pontuações). Os estudantes que testaram a solução avaliaram o sistema de recomendação com um valor de aproximadamente 7 numa escala de 1 a 10, e os valores de precision, recall, false positive rate e F-Measure foram avaliados em 0.51, 0.71, 0.23 e 0.59 respetivamente. Adicionalmente, ambos os grupos classificaram a aplicação como intuitiva e de fácil utilização, com resultados a rondar o 8 numa escala de 1 em 10.In the last academic year, students at ISEP need to complete a final project to obtain the academic degree they aim to achieve. ISEP provides a digital platform where all the projects that students can apply for can be viewed. Besides the advantages this platform has, it also brings some problems, such as the difficult selection of projects suited for the student due to the excessive offering and lack of filtering mechanisms. Additionally, there is also increased difficulty in selecting a supervisor compatible with their project. Once the student has chosen the project and the supervisor, the monitoring phase begins, which also has its issues, such as using various tools that may lead to potential communication problems and difficulty in maintaining a version history of the work done. To address the mentioned problems, an in-depth study of recommendation systems applied to Machine Learning and Learning Management Systems was conducted. For each of these themes, similar systems that could solve the proposed problem were analysed, such as recommendation systems developed in scientific papers, commercial applications, and tools like ChatGPT. Through the analysis of the state of the art, it was concluded that the solution to the proposed problems would be the creation of a web application for students and supervisors that combines the two analysed themes. The developed recommendation system uses collaborative filtering with matrix factorization and content-based filtering with cosine similarity. The technologies used in the system are centred around Python on the backend (with the use of TensorFlow and NumPy for Machine Learning functionalities) and Svelte on the frontend. The system was inspired by a microservices architecture, where each service is represented by its own Docker container, and it was made available online through a public domain. The system was evaluated through performance, reliability, and usability. The Quantitative Evaluation Framework tool was used to define dimensions, factors, and requirements (and their respective scores). The students who tested the solution rated the recommendation system with a value of approximately 7 on a scale of 1 to 10, and the precision, recall, false positive rate, and F-Measure values were evaluated at 0.51, 0.71, 0.23, and 0.59, respectively. Additionally, both groups rated the application as intuitive and easy to use, with ratings around 8 on a scale of 1 to 10

A Structured Methodology For Tailoring And Deploying Lean Manufacturing Systems

The seminal works of Peter Drucker and James Womack in the 1990’s outlined the lean manufacturing practices of Toyota Motor Corporation (TMC) to become a world leader in manufacturing. These philosophies have since become the springboard for a significant paradigm shift in approaching manufacturing systems and how to leverage them to optimize operational practices and gain competitive advantage. While there is no shortage of literature touting the benefits of Lean Manufacturing Systems (LMS), there has been significant difficulty in effectively deploying them to obtain and sustain the performance that TMC has achieved. This body of work provides a novel methodology to break the deployment process into different elements by assessing the current business practices/interests and relating them to variables that support the philosophies of LMS. It also associates the key areas of lean from an operational perspective and connects the tools to business requirements by guiding the selection process to more effectively choose tools/processes that best fit the business needs. Finally, this methodology looks at different aspects of the deployment variables to provide a structured approach to tailoring the deployment planning strategy based on better understanding of the different interactions/requirements of LMS. The research also provides a validation of the proposed structured methodology to help practitioners leverage the resulting objective/quantitative information from assessing the current business to help coordinate deployment planning effort. The framework considers aspects prior to deployment planning by providing an approach for pre-deployment assessment to provide critical input for tailoring the LMS deployment

DEVELOPMENT OF AHP BASED MODEL FOR DECISION MAKING ON E-LEARNING IMPLEMENTATION

Strategic planning of e-learning implementation includes decision making about the most suitable form of implementing e-learning on different levels. Decision making about e-learning implementation has been covered as consisting of four phases: (1) intelligence, (2) design, (3) choice and (4) implementation. During the Intelligence phase we have precisely identified our central decision problem and have conducted situation analysis. In the Design phase we have developed alternatives and established criteria and subcriteria. Then, we have created the questionnaire about the importance of the advantages and goals of e-learning implementation and about criteria and subcriteria essential for decision making. The survey has been conducted on the sample of 90 elearning experts in Croatia. Further, we connected these findings with the results of the factor analysis which was performed on the complete survey. The results of the factor analysis have served as input in the multicriteria decision model (AHP) that we have developed in the Choice phase. The AHP model will be presented in the article and qualitative and quantitative evaluation of the model will be indicated

VALIDATION OF THEORETICAL MODEL FOR DECISION MAKING ABOUT E-LEARNING IMPLEMENTATION

In the paper the possibility to use mathematical models and statistical techniques in strategic planning and decision making about e-learning is presented. Strategic planning and decision making has been covered as consisting of four phases: (1) intelligence, (2) design, (3) choice and (4) implementation. Each of the phases will be described in this paper, but the accent will be put on the statistical evaluation of the results of the questionnaire which was based on the developed theoretical model for decision making about e-learning implementation in the higher education sector. In general, the main objectives of this paper are: (1) validation of the first theoretical model for decision making about e-learning implementation in the higher education sector, by means of factor analysis and (2) reduction of a large number of variables to a smaller number of factors, i.e. designing the improved theoretical model, for modelling purposes (developing AHP & ANP models)

The Selection of Learning Platforms to Support Learning Using Fuzzy Multiple Attribute Decision Making

The utilization of information technology in learning has functioned as a tool in the teaching and learning process during the Covid-19 pandemic. The need for the availability of a learning platform using LMS (Learning Management System) or free e-learning that is easily obtained from the public network (internet) makes the utilization of the learning platform indispensable for the teaching and learning process. Learning platforms available on the internet can also be used independently by students. However, not all existing learning platforms can be used as the appropriate means to improve the quality of education. The educator policies are needed to utilize the existing learning platforms so that learning objectives can be achieved. This study will analyze how to choose the right learning platform for an educational institution using SAW (Simple Additive Weighting)-based Fuzzy Multiple Attribute Decision Making (FMADM) method. FMADM is a method used to find the optimal alternative from a number of alternatives with certain criteria. The purpose of this study is to assist educators in deciding the most appropriate learning platform that can be used to support the teaching and learning process during the Covid 19 pandemic

Teaching Film in New Normal Era at Film Department, Universitas Multimedia Nusantara

COVID-19 has forced many people to adjust to the new situation. The Indonesian education system has been changed drastically because of this pandemic. Although online learning differs from traditional class meetings, most academic institutions switch directly to online without necessary adjustments. As a result, many students experience zoom fatigue. The same thing also happened in the writer's university. Thus, adjustment toward the teaching-learning strategies is needed to avoid this exhaustion. In this research, the writer applied asynchronous learning in one of the film courses. The asynchronous was applied in ten meetings uploaded on the university's online platform. At the end of the semester, a survey was conducted to evaluate the method. This research is aimed to explore other possible methods in teaching film. It is necessary because teaching film requires a lot of physical and social interaction, which is impossible during this era.Pengajaran Film Pada Era Kenormalan Baru di Prodi Film Universitas Multimedia Nusantara ABSTRAK COVID-19 telah membuat sistem pendidikan Indonesia berubah secara drastis. Sebagian besar institusi akademik beralih langsung ke pembelajaran daring, tanpa membuat penyesuaian dengan media daring yang memiliki karakteristik sangat berbeda dari pembelajaran tatap muka di kelas. Akibatnya, banyak siswa yang mengalami kelelahan karena tatap muka daring. Hal yang sama juga terjadi di universitas penulis. Oleh karena itu, penyesuaian terhadap strategi belajarmengajar diperlukan untuk menghindari kelelahan ini. Dalam penelitian ini penulis menerapkan pembelajaran asinkron di salah satu mata kuliah film. Pembelajaran asinkron diterapkan pada sepuluh pertemuan yang diunggah ke media daring milik universitas. Pada akhir semester dilakukan survei untuk mengevaluasi metode tersebut. Penelitian ini bertujuan untuk mengeksplorasi metode lain yang mungkin digunakan dalam pengajaran film. Hal ini diperlukan karena pengajaran film membutuhkan banyak interaksi fisik dan sosial, yang tidak mungkin dilakukan pada era ini

Designing a Model of Student Support in e-Learning Using Qualitative Content Analysis and Analytic Hierarchy Process

Student support services, especially for students who study virtually, increase satisfaction, attract new students, complete the course, and improve overall student performance. Given the importance of student support in e-learning and the fact that student support models should be specific to the culture and economic conditions and technology of their context, the present study set to design a native model of student support in e-learning for post-graduate students. To conduct the research, first a systematic search was performed to extract the existing models of student support. Through forming an expert panel and rating the models, more compatible models with the context of Iran were selected. The interview questions were then extracted from the concepts of the models who scored the most in the expert panel session. In relation to the examples of student support, interviews were conducted with 22 university teachers, education officials, and post-graduate students studying in educational branches leading to a virtual degree of medical sciences. Using content analysis of codes, sub-categories and the resulting categories were extracted from the interviews. Finally, in the expert panel session, using the (analytic hierarchy process) AHP, the categories were prioritized and the model was designed. After analyzing the content of the interviews, four main categories, namely teaching and learning, interactions and communications, empowerment, and structural support were extracted and the final model of student support was designed using the opinions of e-learning instructors. Despite relatively similar similarities between the native model of student support for e-learning students and the existing models, this model, which is designed based on the needs of students and faculty and e-learning officials, places more emphasis on teaching, learning, interactions, and communications