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The retention and success of engineering undergraduates are increasing concern for higher-education institutions. The study of success determinants are initial steps in any remedial initiative targeted to enhance student success and prevent any immature withdrawals. This study provides a comprehensive approach toward the prediction of student academic performance through the lens of the knowledge, attitudes and behavioral skills (KAB) model. The purpose of this paper is to aim to improve the modeling accuracy of students’ performance by introducing two methodologies based on variable selection and dimensionality reduction.

The performance of the proposed methodologies was evaluated using a real data set of ten critical-to-success factors on both attitude and skill-related behaviors of 320 first-year students. The study used two models. In the first model, exploratory factor analysis is used. The second model uses regression model selection. Ridge regression is used as a second step in each model. The efficiency of each model is discussed in the Results section of this paper.

The two methods were powerful in providing small mean-squared errors and hence, in improving the prediction of student performance. The results show that the quality of both methods is sensitive to the size of the reduced model and to the magnitude of the penalization parameter.

First, the survey could have been conducted in two parts; students needed more time than expected to complete it. Second, if the study is to be carried out for second-year students, grades of general engineering courses can be included in the model for better estimation of students’ grade point averages. Third, the study only applies to first-year and second-year students because factors covered are those that are essential for students’ survival through the first few years of study.

The study proposes that vulnerable students could be identified as early as possible in the academic year. These students could be encouraged to engage more in their learning process. Carrying out such measurement at the beginning of the college year can provide professional and college administration with valuable insight on students perception of their own skills and attitudes toward engineering.

This study employs the KAB model as a comprehensive approach to the study of success predictors. The implementation of two new methodologies to improve the prediction accuracy of student success.

This paper aims to explore the objectives and methods of teaching engineering and technology education (ETE) through the lens of three educational taxonomies in cognitive, knowledge and problem-solving perspectives. This analysis is useful in light of today's increasing interest in teaching engineering and technology in K-12 education, instead of crafts or manual skills.

This is an exploratory study. Technology and engineering education is a relatively new area in K-12 education, and little has been written about the use of general educational taxonomies for analysing and designing the teaching and learning of this subject.

The literature analysis teaches us that fostering students' higher-order capabilities such as design and problem solving in engineering and technology cannot take place in isolation from specific knowledge. Instruction should be designed to: develop a certain degree of factual, procedural, conceptual and meta-cognitive knowledge in relevant areas of technology, science and mathematics; and engage learners in assignments of increasing cognitive levels, from simple to complex ones.

This work is original and valuable in that it explores ETE through tools often used in the educational literature and research, rather than regarding technology education as an exceptional school subject. This could encourage making engineering and technology a core component in the overall curriculum.

The purpose of this paper is to explore the value of utilising a holistic ergonomic approach, covering engineering, cognitive and social perspectives, to cultivate beneficial and productive collaborative information seeking (CIS) systems and environments, specifically with regard to three main CIS pillars (control, communication and awareness).

A qualitative research approach, based on a selective corpus of CIS literature, was utilised to perform a content analysis to note if terms and concepts normally associated with engineering, cognitive and social ergonomics can be used to eliminate terms reflecting issues related to three CIS pillars (control, communication and awareness) that can benefit from a holistic ergonomic approach.

The content analysis revealed that a fairly extensive amount of holistic ergonomic terminology is prominent within the CIS literature, therefore establishing a connection between the two disciplines: CIS and ergonomics. This suggests that CIS system issues could benefit from the insights of a holistic ergonomic approach.

Since this is an exploratory study the scope of CIS literature utilised in the content analysis was limited to a selection considered most important by the authors; this should be supplemented by further research.

Intended to instigate interest in further exploration of the beneficial and productive implications and practical application of holistic ergonomics in designing CIS systems and environments.

This is the first research paper in the Library and Information Science literature that explores the potential of utilising holistic ergonomics to cultivate CIS systems and environments.

Only recently has physical space design become more widely recognized as playing a critical role in delivery of care, with an emerging body of literature on the application of human factors approaches to design and evaluation. This chapter describes the use of human factors approaches to develop and conduct an evaluation of a proposed Neonatal Intensive Care Unit redesign in a Midwestern children’s hospital. Methods included observations and knowledge elicitation from stakeholders to characterize their goals, challenges, and needs. This characterization is integral to informing the design of user-centered solutions, including physical space design. We also describe an approach to evaluating the proposed design that yielded actionable recommendations specific to hospital-driven design goals.

Guidelines for the design of knowledge-based e-learning usability systems are absent from the current recognized set of usability design heuristics and from an established evaluation methodology of e-learning system developments. Such systems can help Web designers and instructional designers design for different user needs and decide which properties are of a higher priority, thus meriting more design and development efforts. The authors aim to help students develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge.

The authors applied Merrill ' s first principles of instruction and usability properties as pedagogical and usability design guidelines, knowledge management (KM) and hierarchical task analysis as methodological knowledge bases. The authors proposed a KM e-learning usability framework which frames our mapping of Web usability attributes to e-learning usability properties. The authors aim to investigate whether adopting Merrill ' s first principles of instruction and usability properties as knowledge-based guidelines/design factors would help learners develop higher-order thinking skills and whether this design would result in positive technology acceptance. The authors also developed a method matrix to map the selected methods of cognitive engineering to its potential uses in the KM e-learning usability framework of this paper and mapped e-learning usability tools with components in the KM e-learning usability system.

Findings indicated that our design effectively helped learners to demonstrate higher-order thinking skills and positive technology acceptance, promising indications toward the design and development of knowledge-based usability frameworks and systems.

The sample size of this paper is small. Hence, conclusions are not generalizable at this moment.

The authors’ contributions are twofold: First, the authors proposed a KM e-learning usability framework, which frames the mapping of KM processes to e-learning principles and usability properties. Second, the authors proposed a method matrix which maps the selected methods of cognitive engineering to its potential uses in their KM e-learning usability framework. Based on these mappings and focusing on the usability properties navigation and learning support, the authors used ICT/Web2.0 tools to present/visualize information more clearly and more sensibly/manageably to students, to help trigger new knowledge and develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge and articulate information from different perspectives throughout the KM life cycle.

Single-valued neutrosophic sets (SVNSs) are efficient models to address the complexity issues potentially with three components, namely indeterminacy, truthness and falsity. Taking advantage of SVNSs, this paper introduces some new aggregation operators (AOs) for information fusion of single-valued neutrosophic numbers (SVNNs) to meet multi-criteria group decision-making (MCGDM) challenges.

Einstein operators are well-known AOs for smooth approximation, and prioritized operators are suitable to take advantage of prioritized relationships among multiple criteria. Motivated by the features of these operators, new hybrid aggregation operators are proposed named as “single-valued neutrosophic Einstein prioritized weighted average (SVNEPWA) operator” and “single-valued neutrosophic Einstein prioritized weighted geometric (SVNEPWG) operators.” These hybrid aggregation operators are more efficient and reliable for information aggregation.

A robust approach for MCGDM problems is developed to take advantage of newly developed hybrid operators. The effectiveness of the proposed MCGDM method is demonstrated by numerical examples. Moreover, a comparative analysis and authenticity analysis of the suggested MCGDM approach with existing approaches are offered to examine the practicality, validity and superiority of the proposed operators.

The study reveals that by choosing a suitable AO as per the choice of the expert, it will provide a wide range of compromise solutions for the decision-maker.

The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution.

The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments.

Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes.

The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept.

The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

To introduce a cognitive approach – cognitive task analysis (CTA) – for the usability evaluation of evidence‐based nursing (EBN) websites.

With the justification of the need for new evaluation methodologies for the usability of EBN websites and the provision of the theoretical framework and implications of CTA, the author proposes detailed steps for the usability evaluation of EBN websites.

CTA is a new approach that can be used for the evaluation of the usability of EBN websites. It has the advantages that conventional evaluation methods lack in characterizing the aspects of websites useful to nurses in carrying out evidence‐based practices.

This paper, with the introduction of a new cognitive approach, helps ensure the effective evaluation of the EBN websites, which can then be improved to adequately meet the requirements and information processing needs of the nurses practising evidence‐based nursing.

Based on information derived from bibliographic titles in Ergonomic Abstracts, this paper analyzes research done on human factors in disaster management. A bibliometric analysis is done to identify the most useful material in this important and timely subject area.