Search results

This research aims to assess and compare project-based learning (PBL) designs to deliver technopreneur in higher education, as a case student of the Industrial Engineering Department. So, it can facilitate students who play a role in facilitating the process of technological transformation so the student knows well how to solve the problem of commercialization.

Undergraduate students of Industrial Engineering teams were given hands-on, collaborative projects conducted with two incubation centers, such as the Technology Incubator Center from the Agency for the Assessment and Application of Technology (AAAT) from the government of Indonesia and the Centre of Excellence for Electrical Energy Storage Technology (CEfEEST) from Sebelas Maret University (UNS), Indonesia. After completing the project, students will develop a final project which will become the basis for evaluating the implementation of PBL. The basis for the assessment uses a rubric designed through three sub-assessments: curriculum planning, report and presentation. This research uses the paired t-test method to see the average difference between the two groups of PBL in pairs and compare based on assessment results.

Implementing PBL between the two incubation centers (AAAT and CEfEEST) based on paired t-tests for each rubric assessment indicator showed most of them were significantly related. The assessment result gives the alternative to design the proposed PBL from AAAT, CEfEEST and a blended scenario for technopreneur education in the future.

The experiences and findings presented can help future PBLs provide technopreneur education based on comparing and evaluating learning outcomes in both incubation centers. Thus, it can produce a better PBL design to encourage the success of technology commercialization.

The assessment of PBL on students' knowledge in technopreneur education by utilizing the paired t-test method to compare the assessment results of the final projects with the designed assessment rubric. This evaluation serves as the basis for comparing the effectiveness of PBL implementation between AAAT and CEfEEST.

As global issues such as climate change, economic growth, social equality and the wealth gap are widely discussed, education for sustainable development (ESD) allows every human being to acquire the knowledge, skills, attitudes and values necessary to shape a sustainable future. It also requires participatory teaching and learning methods that motivate and empower learners to change their behavior and take action for sustainable development. Teachers have begun rating pupils based on peer assessment for open evaluation. Peer assessment enables students to transition from passive to active feedback recipients. The assessors improve critical thinking and encourage introspection, resulting in more significant recommendations. However, the quality of peer assessment is variable, resulting in reviewers not recognizing the remarks of other reviewers, therefore the benefits of peer assessment cannot be fulfilled. In the past, researchers frequently employed post-event questionnaires to examine the effects of peer assessment on learning effectiveness, which did not accurately reflect the quality of peer assessment in real time.

This study employs a multi-label model and develops a self-feedback system in order to use the AIOLPA system in the classroom to enhance students' learning efficacy and the validity of peer assessment.

The research findings indicate that the better peer assessment through the rapid feedback system, for the evaluator, encourages more self-reflection and attempts to provide more ideas, so bringing the peer rating closer to the instructor rating and assisting the evaluator. Improve self-evaluation and critical thinking for the evaluator, peers make suggestions and comments to help improve the work and support the growth of students' learning effectiveness, which can lead to more suggestions and an increase in the work’s quality.

ESD consequently promotes competencies like critical thinking, imagining future scenarios and making decisions in a collaborative way. This study builds an online peer assessment system with a self-feedback mechanism capable of classifying peer comments, comparing them with scores in a consistent manner and providing prompt feedback to critics.

Assessing project criticality in a project portfolio (PP) is of great practical significance to improve robustness from damage. While project criticality assessment has increased diversity in approaches, the understanding of vulnerable project impacts is still limited. To promote a better understanding of assessing project criticality, a vulnerability measurement model is constructed.

First, integrating the tasks, projects and corresponding relationships among them, a project portfolio network (PPN) is constructed. Second, the project's vulnerability is measured by combining the topological structure and functional attributes. Third, project criticality is assessed by the vulnerability measurement results. Lastly, the proposed model is applied in a numerical example to illustrate its suitability and effectiveness.

For academia, this study provides a novel perspective on project vulnerability measurement and expands project criticality assessment tools. For practitioners, the straightforward model provides an effective tool for assessing project criticality and contributes to enhancing project portfolio management (PPM).

The impact of the task on the project is considered in this study. Topological structure and functional attributes are also integrated for measuring project vulnerability due to the impact of random attacks in an uncertain environment, providing a new perspective on the requirements of project criticality assessment and the measurement of project vulnerability.

The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.

The research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.

The key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.

Additional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.

This study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.

The purpose of this paper is to investigate the comment letters (CLs) in the standard-setting process of audits of less complex entities (LCEs). The objective is to gain insight into the overall picture of the CLs and to report on areas where comment providers agree or disagree with IAASB's Part 10.

A content analysis of 60 comment letter (CLs) was conducted to investigate the suggested additional Part 10 on audits of groups' financial statements in the proposed ISA for LCEs. Hence, this study examines three specific topics: (1) the views related to the use of the International Standard on Auditing (ISA) for LCEs for group audits in which component auditors are involved, (2) the proposed group-specific qualitative characteristics to describe the scope of group audits and, finally, (3) insights into the content of the proposed Part 10 and related conforming amendments. The Gioia method is used to provide a holistic approach to concept development of the arguments about the new Part 10.

The CLs stated that, while the proposed Part 10 has some weak points, it still provides a solid and practical structure within which to undertake an LCE group audit and a promising basis for further development. For instance, when discussing the improvements, the CLs stated that Part 10 should allow for more auditor judgment when determining when the involvement of component auditors renders a group audit complex. In addition, the CLs asserted that professional judgment should be engaged when considering the qualitative characteristics and the complexity of the group.

This study contributes to the very scarce research about the ISA for LCEs and the role of lobbying in shaping the audit standard-setting process.

Addressing Environmental, Social and Governance (ESG) issues has become a critical aspect of business strategy. Since ESG has primarily focused on ratings and measures for reporting, there is a scarcity of methods to assist stakeholders in better comprehending corporate risk and addressing ESG-related issues and problems. The purpose of this paper is to propose a new model to narrow the critical gap.

This study is based on several well-known structural frameworks for managing risks and projects in various industries. Two case studies on topics related to environment (E) and social (S) responsibility are used to demonstrate the practical implementation of the CEPAR® model.

The CEPAR® model, a trademarked five-step methodology (the Challenge-Evaluation-Planning-Action-Review model) was developed by the International Chamber of Sustainable Development (ICSD). The method and guidelines are outlined for easier appreciation by stakeholders of corporations to analyze ESG-related challenges and dilemmas, then able to make principled decisions, take actions, and review the outcomes. Each phase of the new model adheres to the theoretical and practical frameworks for problem-solving and decision-making, emphasizing the iterate process of addressing challenges, evaluating materiality, planning actions, taking actions, and reviewing the outcomes.

The new model is applicable for business corporations and organizations seeking to gain insight and tackle crucial ESG issues, ultimately improving their short- and long-term decision-making and business opportunities.

This paper aims to understand loneliness with a special focus on perceived loneliness using a multifaceted approach.

To the best of the author’s knowledge, this appears to be the first paper dedicated to investigating the perception of loneliness as its primary topic. Unfortunately, not much work is available on this specific focus. However, various facets and dimensions can be integrated to gain a better understanding. Therefore, the author has carefully selected four sections, each focusing on different aspects of loneliness. These sections can contribute to a better understanding of loneliness, keeping in mind its perception.

Section one examines the cognitive processes and self-assessment mechanisms that set lonely individuals apart from their non-lonely counterparts. These include heightened awareness, negative social cue interpretation and increased sensitivity to social threats. Section two examines the predictors of loneliness and associated emotional responses. This includes factors such as emotional responses, attributions, duration and situational variables. Section three challenges conventional definitions of loneliness by introducing social asymmetry. Within this framework, personality traits such as extraversion emerge as resilient against loneliness, even in social isolation. Section four discusses the significant influence of cultural diversity on perceptions of loneliness. Collectivist cultures rely on familial and community support to combat loneliness, whereas individualistic cultures require interventions that promote independence.

This comprehensive examination contributes insights for informing targeted interventions, reinforcing support systems and enhancing our understanding of human connectivity in an increasingly isolated world.

This article presents our experience in implementing the assessment for learning process (AfL) to enhance the teaching–learning quality, which has faced numerous challenges impacting educational quality. The effectiveness of this technique is demonstrated through a case study conducted in a core course of chemical engineering.

The article shares insights into the systematic course design and planning processes that were discussed and developed through AfL practices. Significant emphasis is placed on implementing formative and summative student self-assessment surveys as simple yet effective methods to meet this purpose. Quantitative data were collected and analyzed over three consecutive academic years (2020–2022) using various statistical parameters such as percentage, interquartile range and the program’s numerical goal (%G).

The AfL process via formative and summative surveys could significantly and effectively improve teaching–learning quality. These findings assist educators in identifying appropriate teaching methods and recognizing areas of weakness and strength, thereby facilitating continuous improvement in the teaching–learning quality. Validation methods, including quizzes and numerical grades, were employed to practically verify the outcome obtained from the questionnaires.

The AfL techniques demonstrated in this study can be directly implemented or adapted for various educational fields to enhance the teaching–learning quality.

The practical implementation of AfL in an engineering context has hardly been reported, particularly in chemical engineering. This work represents the practical implementation of AfL to enhance engineering field education.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.