Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model

BACKGROUND: E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. METHODS: We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. RESULTS: Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. CONCLUSION: This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Process Performance Management in Higher Education

Process performance management (PPM) has become one of the most important management tools in profit organizations. However, non-profit organizations also started to benefit from PPM aimed at the efficiency improvement. The goal of the paper is to investigate usefulness of embedding the simulation modelling approach for process performance management based on the case study of collaboration improvement in higher education. The case study methodology has been used in the study and the paper presents simulation modelling for PPM with the purpose of collaboration improvement at the University of Zagreb, Croatia

Assembly line balancing problem with ergonomics: a new fatigue and recovery model

Assembly lines are production lines used to manufacture products, ranging from mass-production products to mass-customisation with low unit products. Assembly lines consume the largest parts of investment funds and involve the largest proportion of companies' labour force. However, workers in assembly lines are exposed to work-related musculoskeletal disorders (MSDs) and ergonomics problems. Poor distribution of workloads reduces the performance of assembly lines and causes workers MSDs and injuries, largely affecting the economics of production systems and resulting in high workers' compensation and absenteeism costs. Furthermore, ergonomics problems and MSDs impact product quality and decrease productivity. We propose a methodology for taking physical ergonomics into account as early as in the design phase of assembly lines. This methodology is based on Integer Linear Programming for the assembly line balancing problem with consideration of ergonomics with a quantitative fatigue and recovery criterion. As solving approach, we develop a dedicated exact algorithm, denoted Iterative Dichotomic Search, to solve low and medium-size instances of the problem. We validate our approach by proposing numerical experiments and analysis on instances from the literature

Multi-objective optimization of assembly lines with workers fatigue consideration

The work-related musculoskeletal disorders (MSDs) occur when the worker's capabilities do not match the physical demands of work. In assembly lines, with the execution of repetitive tasks, workers are exposed to fatigue and ergonomics risks. Thus, there is a need to find compromises between assembly lines performance and physical demands and ergonomics. In this work, we introduce a general fatigue criterion for assessing workers fatigue. We propose a multi-objective mixed-integer linear programming model for the assembly line balancing problem with consideration of workers fatigue. We use ε-constraint approach to address both objectives and present the Pareto front. Experiments on instances from the literature are performed and discussed to highlight the trade-off between the numbers of workstations and fatigue