What do business and education have in common when it comes to continuous improvements? The answer is Lean Principles. Case studies and implementation challenges from some pilot PBL projects in one ...university, in Romania, are analysed and described in depth, while comparing the educational experience in the university to the challenges and resistance to change that facilitators in the private sector face inside their own companies. Taking this into consideration and based on qualitative data retrieved from interviews carried out in the private sector and in the educational sector, the authors of this paper will present deep insights that are meant to serve as a basis for understanding the “wicked problem” of scalling continuous improvements like Problem Based Learning throughout the entire teaching organization.
Developments in the IT field have led to the development and variety of e-learning objects so that video or gaming lessons are found in most online courses and are developed in order to maintain the ...student’s interest. The current Learning Management Systems challenges refer to how to generate a dynamic content that automatically adapts to the a priori level of a student’s knowledge and behavior during lessons. Starting from the model student, the component of adaptive learning, the aim of this paper is to keep student motivation by designing a course with content related to the level of knowledge of the students. At the same time, lessons combine elements of gamification with quizzes, textual contexts and infographics in order to make the content more varied, and in order for the student to be more engaged, to assimilate, to understand or to recall the concepts presented in the course.
The paper investigates experiences of employees and middle managers in relation to the transition from working from office to working from home in the context of COVID-19 pandemic in Romania. Three ...online focus groups were conducted to explore working experience in the new mode of work. The conclusions are multifaceted, covering four dimensions: time, spatial, social and technical, and point out how employees and middle managers understand the transition and what impact telework had on their job satisfaction and work productivity.
In this paper, the authors aim to develop an intelligent learning environment model designed to improve students’ academic performance. Methodology: Referring to the litarature, the authors ...identified and analyzed a number of relevant issues that influence the specific components of an intelligent learning environment. These aspects were quantified using performance indicators defined on the basis of the specific objectives of each aspect chosen. Results: Following the analysis, the authors developed a model of intelligent learning space, and for its representation, we used conceptual modeling. Conclusions: Finally, the authors propose the prevalidation of the model using the dynamic modeling process and then the model will be piloted for final validation in both physical and virtual environment. These aspects are proposed because in the present study, the model was validated only based on the results from studies in scientific literature.
It often happens in teaching that due to complexity of a subject or unavailability of an expert instructor the subject undergoes in a situation that not only affects its outcome but the involvement ...and learning development of students also. Although contents are covered even in such a situation but their inadequate explanation leaves many question marks in students’ mind. Artificial Intelligence helps represent knowledge graphically and symbolically which can be logically inferred. Visual and symbolic representation of knowledge is easy to understand for both teachers and students. To facilitate students understanding teachers often structure domain knowledge in a visual form where all important contents of a subject can be seen along with their relation to each other. These structures are called ontology which is an important aspect of knowledge engineering. Teaching via ontology is in practice since last two decades. Natural Language Processing (NLP) is a combination of computation and linguistic and is often hard to teach. Its contents are apparently not tied together in a reasonable way which makes it difficult for a teacher that where to start with. In this article we will discuss the design of ontology to support rational learning and efficient teaching of NLP at introductory level.
The professional standards for teachers provide the competences needed for this occupation, in function of the level of education and of the career stages. This study aims to discover the most ...important training factors which contribute to the acquisition of teacher competences and to establish the implications for teacher education. We have used a mixed-method design as the procedure for collecting, analyzing, and combining both quantitative and qualitative data. To detect the main agents in the teacher competences’ achievement, we applied a questionnaire and we asked the personal opinion of the teachers regarding their evolution in the career. The findings indicated that the principal factor was the individual study, followed by the continuing professional development, through training courses, the collaborative learning, and, almost on the last place, the initial teacher education. Implications for teacher education: the changes in the future are incalculable, so we have to rethink the teacher education to ensure future teachers able to learn and adapt themselves to different conditions. We appreciate the recommendations to reform teacher education in the context of lifelong learning very useful (Dolan, 2012) and we will study the applicability of them in our university.
Failure Mode and Effects Analysis (FMEA) is a systematic method forprocedure analyses and risk assessment. It is a structured way to identify potentialfailure modes of a product or process, ...probability of their occurrence, and their overalleffects. The basic purpose of this analysis is to mitigate the risk and the impactassociated to a failure by planning and prioritizing actions to make a product or aprocess robust to failure. Effective manufacturing and improved quality productsare the fruits of successful implementation of FMEA. During this activity valuableknowledge is generated which turns into product or process quality and efficiency. Ifthis knowledge can be shared and reused then it would be helpful in early identificationof failure points and their troubleshooting, and will also help the quality managementto get decision support in time. But integration and reuse of this knowledge is difficultbecause there are number of challenges e.g., unavailability of unified criteria of FMEAknowledge, lack of semantic organization, natural language text based description ofknowledge, most of the times FMEA is started from scratch instead of using existingknowledge that makes it incomplete for larger systems, and above all its successdepends on the knowledge which is stored in the brains of perfectionists in the formof experience which may or may not be available anytime anywhere. In this article weare proposing an Information and Communication Technology (ICT) based solutionto preserve, reuse, and share the valuable knowledge produced during FMEA. Inproposed system existing knowledge available in repositories and experts head will begathered and stored in a knowledge base using an ontology, and at the time of need thisknowledge base will be inferred to make decisions in order to mitigate the probablerisks. Ontology based approaches are best suited for the knowledge managementsystems, in which human experts are required to model and analyze their expertisein order to feed them in a conceptual knowledge base for its preservation and reuse.
Failure Mode and Effect Analysis (FMEA) is among the most widely used safety analysis procedures in the various industries. The procedure is generally perceived as complex and time-consuming, ...hindering an effective reuse of previous knowledge. In this paper we present an innovative usage of knowledge system into FMEA process using the Case-based reasoning to reduce the time and effort associated with this analysis. Knowledge system is built to serve multi-projects work that nowadays are in place in any manufacturing or services provider, and knowledge must be retained and reused at the company level and not only at project level. Collaboration is assured trough web-based GUI that supports multiple users access at any time. Initial results confirm the viability of this system for industrial application.
PDF
