Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements

Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning

The realities of the 21st-century learner require that schools and educators fundamentally change their practice. "Educators must produce college- and career-ready graduates that reflect the future these students will face. And, they must facilitate learning through means that align with the defining attributes of this generation of learners."Today, we know more than ever about how students learn, acknowledging that the process isn't the same for every student and doesn't remain the same for each individual, depending upon maturation and the content being learned. We know that students want to progress at a pace that allows them to master new concepts and skills, to access a variety of resources, to receive timely feedback on their progress, to demonstrate their knowledge in multiple ways and to get direction, support and feedback from—as well as collaborate with—experts, teachers, tutors and other students.The result is a growing demand for student-centered, transformative digital learning using competency education as an underpinning.iNACOL released this paper to illustrate the technical requirements and functionalities that learning management systems need to shift toward student-centered instructional models. This comprehensive framework will help districts and schools determine what systems to use and integrate as they being their journey toward student-centered learning, as well as how systems integration aligns with their organizational vision, educational goals and strategic plans.Educators can use this report to optimize student learning and promote innovation in their own student-centered learning environments. The report will help school leaders understand the complex technologies needed to optimize personalized learning and how to use data and analytics to improve practices, and can assist technology leaders in re-engineering systems to support the key nuances of student-centered learning

Estilo de aprendizaje en entorno virtual: un estudio con profesores de educación básica em la formación continua

In learning scenarios, the main focus should be on knowledge about the learner's strengths and weaknesses. In this context, this article aims to present the results obtained in the previous investigation of the learning styles of teachers in continuing education, in the perspective of the development of strategies that take into account the singularities of the teacher / student. This investigation deals with a case study on teachers in a broad sense in the area of Environmental Education, in a hybrid model, with classroom and virtual environment, offered by a public University. We sought to analyze the responses to promote personalization in the classroom and virtual classroom activities based on pedagogical strategies that included all styles of trainees present. To identify the learning style, an open questionnaire was applied, based on the model by Kolb, where a sample of 57 respondents was obtained, where different learning styles were identified among the course participants. The results indicate that training courses designed for the teaching professional who seek knowledge about the specificities of this professional, using instruments that value and recognize their opinion, favor them to be protagonists of their own training.Em cenários de aprendizado, o foco principal deve estar no conhecimento sobre as potencialidades e fragilidades do aprendente. Neste contexto, o presente artigo tem como objetivo apresentar os resultados obtidos na investigação prévia dos estilos de aprendizagem de professores em formação continuada, na perspectiva da elaboração de estratégias que levem em consideração as singularidades do professor/cursista. Esta investigação trata de um estudo de caso sobre professores em curso lato sensuna área de Educação Ambiental, em modelo híbrido, com ambiente presencial e virtual, ofertado por uma Universidade pública. Buscou-se analisar as respostas para promover uma personalização nas atividades da sala de aula presencial e virtual baseando-se em estratégias pedagógicas que contemplassem todos os estilos dos formandos presentes. Para identificação do estilo de aprendizagem foi aplicado questionário aberto, baseado no modelo de Kolb, onde se obteve uma amostra de 57 respondentes, onde se identificou estilos de aprendizagem diversos entre os cursistas. Os resultados apontam que formações elaboradas para o (a) profissional docente que buscam o conhecimento sobre especificidades deste profissional, a partir de instrumentos que valorizem e reconheçam sua opinião, favorecem para que sejam protagonistas da própria formação.En los escenarios de aprendizaje, el enfoque principal debe estar en el conocimiento sobre las fortalezas y debilidades del alumno. En este contexto, esteartículo tiene como objetivo presentar los resultados obtenidos en la investigación previa de los estilos de aprendizaje de los docentes en educación continua, en la perspectiva del desarrollo de estrategias que tengan en cuenta las singularidades del profesor / alumno. Esta investigación aborda un estudio de caso sobre docentes en un curso de sentido amplio en el área de Educación Ambiental, en un modelo híbrido, con aula y entorno virtual, ofrecido por una universidad pública. Intentamos analizar las respuestas para promover la personalización en el aula y las actividades del aula virtual basadas en estrategias pedagógicas que incluían todos los estilos de aprendices presentes. Para identificar el estilo de aprendizaje, se aplicó un cuestionario abierto, basado en el modelo de Kolb, donde se obtuvo una muestra de 57 encuestados, donde se identificaron diferentes estilos de aprendizaje entre los participantes del curso. Los resultados indican que los cursos de capacitación diseñados para el profesional docente que busca conocimiento sobre las especificidades de este profesional, utilizando instrumentos que valoran y reconocen su opinión, les favorecen para ser protagonistas de su propia capacitación

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

Teacher competence development – a European perspective

This chapter provides an European perspectives on teacher competence development

Proposal of a learning styles identification tool for sakai virtual learning environment

We are living in an essentially technological world, in which technology facilitates and promotes the development of institutions and the people who work or study in these institutions. Thus, it is claimed that technology should increasingly meet people’s needs according to their goals, interests and learning styles. Aiming to improve the teaching and learning process, and based on a perspective of adaptation of the learning environment to the learner’s needs, we present, in this article, the integration of learning styles in learning management systems by integrating the Honey-Alonso Learning Styles Questionnaire (CHAEA) in Sakai collaborative learning environment, which was adopted in a higher education institution

Individual Tariffs for Mobile Communication Services

This paper introduces a conceptual framework and a computational model for individual tariffs for mobile communication services. The purpose is to provide guidance for implementation by communication service suppliers or user groups alike. The paper first examines the sociological and economic incentives for personalized services and individual tariffs. Then it introduces a framework for individual tariffs which is centered on user and supplier behaviours. The user, instead of being fully rational, has "bounded rationality" and his behaviours are subject to economic constraints and influenced by social needs. The supplier can belong to different types of entities such as firms and communities; each has his own goals which lead to different behaviors. Individual tariffs are decided through interactions between the user and the supplier and can be analyzed in a structured way using game theory. A numerical case in mobile music training is developed to illustrate the concepts.risks;mobile communication services;Individual tariffs;computational games

Community-based mentoring and innovating through Web 2.0

The rise of social software, often termed Web 2.0, has resulted in heightened awareness of the opportunities for creative and innovative approaches to learning that are afforded by network technologies. Social software platforms and social networking technologies have become part of the learning landscape both for those who learn formally within institutions, and for those who learn informally via emergent web-based learning communities. As collaborative online learning becomes a reality, new skills in communication and collaboration are required in order to use new technologies effectively, develop real digital literacy and other 21st century skills