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This study aims to propose a service quality evaluation model for health-care services.

In this study, a service quality evaluation model is proposed based on the service quality measurement (SERVQUAL) scale and machine learning algorithm. Primarily, items that affect the quality of service are determined based on the SERVQUAL scale. Subsequently, a service quality assessment model is generated to manage the resources that are allocated to improve the activities efficiently. Following this phase, a sample of classification model is conducted. Machine learning algorithms are used to establish the classification model.

The proposed evaluation model addresses the following questions: What are the potential impact levels of service quality dimensions on the quality of service practically? What should be prioritization among the service quality dimensions and Which dimensions of service quality should be improved primarily? A real-life case study in a public hospital is carried out to reveal how the proposed model works. The results that have been obtained from the case study show that the proposed model can be conducted easily in practice. It is also found that there is a remarkably high-service gap in the public hospital, in which the case study has been conducted, regarding the general physical conditions and food services.

The primary contribution of this study is threefold. The proposed evaluation model determines the impact levels of service quality dimensions on the service quality in practice. The proposed evaluation model prioritizes service quality dimensions in terms of their significance. The proposed evaluation model finds out the answer to the question of which service quality dimensions should be improved primarily?

The University of Mauritius (UoM) established as a traditional face-to-face university has been engaged in distance education since 1993 and in e-learning since 2001 to establish itself as a dual-mode institution. In a context where it has engaged itself to promote its internationalization of online courses and a digital learning transformation process, there is a need to assess and evaluate its current e-learning capability to identify areas of good practices and opportunities for improvement to ensure a high quality of e-learning provisions. The paper reports the results of an assessment of the e-learning capability and the related quality assurance processes of the University of the Mauritius using the e-learning Maturity Model (eMM). Quality assurance in higher education is still a key issue, especially with the ever-growing influence of technology and the disruption that the Internet has caused with respect to e-learning and distance education provisions. No university in Mauritius has ever engaged in such an assessment of their e-learning capabilities.

The EMM and the Open Learning Consortium Quality Scorecard Suite were found to be the most complete models in terms of available documentation and description of how to carry out the evaluation with respect to each process area as compared to the other models described in the literature review section. The EMM was, however, chosen as the model to be used for the UoM, given that there already exists a body of knowledge about its applications in different universities that operate in similar contexts. The researcher is at the heart of the process in the role of an ‘eLearning quality auditor’. Therefore, the research used mainly desk studies, and analysis of annual reports as well as a consultative approach with key stakeholders based on a consensus model to reach a rating for each element in the EMMv2.3 instrument. The rating is based on evidence that is available and verifiable through desk research and documentation.

We found out that the main strengths of the university were in the learning process areas mainly because of the need to follow existing quality assurance procedures in place at different phases of a course of life cycle, irrespective of the course modality. On the other hand, across all process areas, the university fared well in the delivery dimension, and this finding is consistent with other universities that were assessed using the EMM. However, it was found that the EMM in current form was more adapted for the assessment of universities operating fully as open or virtual universities rather than those operating as dual-mode institutions or as traditional universities promoting technology-enabled learning. The weakest link was the optimization dimension across all process areas, and the process area that needs more attention for improvement was the evaluation process area. Overall, the university can reasonably be pitched at level two (Repeatable) of the capability maturity model scale used for information systems maturity assessment, but operating towards level three (Defined).

The work presented here has never been carried out for any university in Mauritius, and there have been no reported evaluations or applications within the African region. It allows the university to benchmark and compare its standing with respect to other universities operating as dual-mode institutions and as a reference for other universities in Mauritius as well.

Describes a case study in which the Kolb learning model was used in the implementation and evaluation of a facilitation skills training programme associated with organizational change. Demonstrates the usefulness of experimental learning theory and Kolb′s learning model to facilitator and participants in process evaluation. Achieves evaluation without complex descriptions of learning theory and psychometric instruments; simply relies on the model to guide participants through the learning cycle. Suggests the approach may be used to encourage participants to recognize their learning preferences and understand the importance of exploring the full range of learning activities. To main links between theory and application of facilitation skills, participants kept a journal of their activities and learnings. Describes how journalized comments were plotted on to sectors in the model which described learning outcomes to serves as preliminary feedback of participants′ learning experiences and the programme.

The purpose of this paper is to demonstrate the importance of undertaking a systemic view of learning management systems (LMSs) evaluation addressing the conceptualization and measurement of e‐learning systems success in higher education.

The paper adopts a quantitative case perspective and derives a conceptual model for e‐learning assessment (Hexagonal e‐learning assessment model – HELAM). The model is empirically tested for validity and reliability in the university setting.

Qualitative and quantitative findings have been presented, which will be valuable for academics and practitioners doing research in e‐learning evaluation. The findings support the flexibility and relevance of HELAM as an e‐learning assessment model. It highlights a number of success measures which are grouped under six dimensions.

Further research efforts should explore new dimensions or test the causal relationships among proposed dimensions within the boundary of e‐learning. In that, the paper is limited contextually where attention should be made not to generalize the findings beyond the empirical findings within the case analysis.

The paper supports a practitioner perspective through a consideration of a holistic approach to e‐learning assessment. E‐learning system developers may find the findings useful when designing and implementing the LMS.

The paper is original as the conceptual model has been derived through both theoretical constructs and empirical analysis. It provides an innovative approach to e‐learning assessment.

The purpose of this paper is to show how rapidly evolving information technology has dramatically changed the knowledge dissemination process. However, many of them lack a generic evaluation process to verify the system's performance. In an attempt to solve this problem, this study seeks to propose an agent‐based model to provide a dynamic, flexible framework for performance evaluations of e‐learning projects.

The paper proposes an agent‐based model which comprises a learning model, balanced scorecard and option‐pricing approach to evaluate the performance of an e‐learning project.

E‐learning could be the paradigm shift of traditional education. Thus, the paper provides organizations with a methodology to deliberately evaluate their e‐learning projects by treating it as a continuous improvement process.

The original contributions in this paper are: application of a balance scorecard to weigh different perspectives; application of a real options approach for risk management of e‐learning projects; construction of an agent‐based system for autonomous qualitative/quantitative information gathering.

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R², were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

Industry skills council (ISC) in Korea is at an earlier stage in terms of its formation and incubation. As a governance model similar to sector councils in Canada and UK, it still requires training and development of talents who work for ISCs. The purpose of this study is to analyze the effectiveness of training programs that are currently provided to personnel of the ISC to foster their learning systematically and to develop measures for effectiveness of the training programs.

This study evaluated the training program for the staff of the ISC secretariat as a tool to activate the councils’ main functions. In terms of methodology, we developed an effective training model to measure the training transfer and used it as an analytical framework for evaluation. Success case method was applied to identify the best case of training transfer that reinforces the role and function of ISC.

Learning transfer can help not only the transfer of the learning contents but also the role of the organization that the members belong to and strengthen the function of the ISC. By transferring the content matter of the learning, it can help strengthen the capacity of members to carry out the roles and functions of the ISC, and further strengthen the functions of the council and the role of key players in labor markets.

An effective training model for the personnel of national sectoral bodies or non-profit organization can be further investigated.

The learning transfer evaluation model for ISC staff has unique characteristics that are different from previous studies. ISC has the characteristics of public goods that are established with government support and are active in developing human resources in each industry sector.

Incubating ISC in South Korea is at an earlier stage in terms of research and policy practice. The research findings in this study lay the foundations for further empirical explorations.

This paper aims to propose a learning evaluation model for Green Belts and Black Belts at the training level. A question bank has been developed on the basis of Bloom’s learning classification and applied to a group of employees who were being trained in Six Sigma (SS). Their results were then used to decide on the students’ approval and to guide the instructor’s plan of teaching for the next classes.

An action research has been conducted to develop a question bank of 310 questions based on the revised Bloom’s Taxonomy, to implement the evaluation model, and to apply it during the SS training.

The evaluation model has been designed so that the students do not proceed unless they have acquired the conceptual knowledge at each step of the DMAIC (Define, Measure, Analyze, Improve and Control) roadmap. At the end of the evaluation process, the students’ results have been analyzed. The number of mistakes in all stages of DMAIC was equal, implying that the training was uniform the entire roadmap. However, the opposite happened in each of the Bloom’s Taxonomy levels, showing that some skills need to be better stimulated by the instructor than others.

The learning evaluation model proposed in this paper has been applied to a group of 70 employees who were being trained in SS at a Brazilian aircraft manufacturer. The data have been analyzed using Microsoft Excel^® and Minitab^® 17 Statistical Software.

Despite the abundance of courses offering the SS Green Belt and Black Belt certifications, there is no standard evaluation to ensure the training quality. Thus, this paper proposes an innovative learning evaluation model.

The purpose of this paper is to present the process of building a model that identifies criteria that determine the quality of virtual postgraduate programs. In the Colombian context, there are no national criteria/standards to evaluate the quality of this type of program. This proposed model is implemented in a public university that has several virtual postgraduate courses within the framework of university autonomy.

This study implements a descriptive methodology through documental research based on the study of 414 documents and the analysis of 39 and research based on the design of the proposal of a quality model, its validation by experts and its application in the academic community of a public university that has virtual postgraduate courses.

The results are presented in a structure composed of 10 quality factors: coherence between programs, virtual methodology and institutional horizon; attention to students; characteristics of author teachers, virtual teachers and researchers; academic, curricular and learning processes; research, knowledge generation and production; the relationship with the environment; articulation and impact; need satisfaction and ability to generate innovation processes; internationalization, alliances and insertion in scientific and global networks; and technological resources and production of virtual contents, among others.

This model can be prospectively incorporated into processes that have adapted online training elements in health emergency contexts.

This model combines theoretical and practice aspects and the validation of experts, which contributes to the reflection on the quality of virtual programs, with criteria different from those proposed for face-to-face and distance programs.

Even though the model resulting from this inquiry responds to the situated context of a particular virtual academic program, the research perspective may be oriented to perform longitudinal studies of its implementation, as well as its adaptation to other situated contexts, including those that make use of virtual processes and means of remote education. On the other hand, it provides elements to be taken into account in the construction of educational policies on the quality of virtual programs and future research.

This paper is the result of a research project and its content is original.

The research aims to discuss technical and vocational students' long-term and complete evaluation of learning effectiveness under school-wide thematic teaching design.

This study adopted a mixed qualitative and quantitative approach to measure the learning effectiveness of thematic teaching in technical vocational schools using the Kirkpatrick model. Qualitative research conducted in-depth interviews with 32 interviewees, including students, parents, teachers, graduate alumni and the supervisors of off-campus internship units. Quantitative research conducted a questionnaire survey on vocational students. A total of 221 valid questionnaires were collected. In addition, this research conducts another quantitative survey on cooperative enterprises to compare the actual effect of the implementation of the school-wide thematic teaching students with the others, and a total of 35 valid questionnaires were collected.

The results of the research found that the effectiveness of thematic teaching method can achieve the expected goals of each level of Kirkpatrick model. The students taking thematic teaching are significantly better and fitting in the industry expects. Therefore, this research suggests the comprehensive introduction of school-wide thematic teaching to other school operators.

This research is the first study used the Kirkpatrick model to evaluate the effectiveness of school-wide thematic teaching design in hospitality education and providing a practical case for schools. This research combined qualitative and quantitative research methods to investigate the effectiveness of the teaching method through multiple perspectives. Through the feedback from supervisors of the hospitality industry, the school-wide thematic teaching design provides a good foundation for technical and vocational graduates.