Performance Evaluation Process Research Articles

Testing solar cookers for cooking efficiency

Solar Cookers International (SCI) staff developed and implemented a calculation to measure the cooking efficiency of solar thermal cookers. The calculation complements and enhances SCI's existing performance evaluation process (PEP), which can now be used for determining both the standard cooking power and the cooking efficiency for solar thermal cookers. The standard cooking power value is a single measure of solar cooker performance taken when the temperature of the test water load is specifically 50 °C greater than ambient temperature. Cooking efficiency values extend the perspective of solar cooker performance, as they are applicable to a continuum of load temperature measurements made during a heating cycle. Cooking efficiency is the ratio of energy absorbed by the solar cooking load divided by the input solar energy intercepted by the device during a test interval. Examples of cooking efficiency calculations using water loads during three days of testing for an anonymous group of different types of solar cookers are: solar box oven (18.9 %), reflective-panel solar cooker (28.5 %), parabolic reflector (35.2 %), and evacuated-tube solar cooker (34.6 %).

보육교사 양성과정에서 하브루타 학습법을 활용한 역량기반 ‘보육학개론’ 수업모형 개발

The purpose of this study is to develop a teaching model for Introduction to Childcare subjects based on the competency using the Havruta learning method in the child care teacher training course. To present a conclusion for each research problem, first, the composition process of the Introduction to Childcare class model using the Havruta learning method was carried out in five steps. The teaching model(draft) was devised by analyzing previous studies and literature, and the teaching model(draft) was revised and supplemented by reflecting the results of the first expert interview. Through the second expert interview, it was confirm that it was a model that could effectively achieve the goals of the Introduction to Childcare subject. Second, the teaching model of Introduction to Childcare using the Havruta learning method selected an appropriate Havruta type to effectively learn the content to be learned while successfully achieving the competencies needed by the future society. In addition, the stages of process evaluation and performance evaluation were added. It is expected that these research results will be used as basic data for the development of a teaching model using the Havruta learning method and the operation of classes to cultivate talented people with the competencies required by the future society.

An Explorative Review of the Constructs, Metrics, Models, and Methods for Evaluating e-Learning Performance in Medical Education

The performance evaluation of e-learning in medical education has been the subject of much research lately. Researchers are yet to achieve a consensus on the definition of performance or the suitable constructs, metrics, models, and methods to help understand student performance. Through a systematic review, this study put forward a working definition of what constitutes performance evaluation to reduce the ambiguity, arbitrariness, and multiplicity surrounding performance evaluation of e-learning in medical education. A systematic review of published articles on performance evaluation of e-learning in medical education was performed on the SCOPUS, Web of Science, PubMed, and EBSCOHost databases using search terms deduced from the PICOS model. Following the PRISMA guidelines relevant published papers were searched and exported to Endnote. Screening and quality appraisal were done on Rayyan. Three thousand four hundred and thirty-nine published studies were retrieved and screened using predetermined inclusion and exclusion criteria. One hundred and three studies passed all the criteria and were reviewed. The reviewed literature used 30 constructs to operationalize performance. The leading constructs are knowledge and effectiveness. Both constructs were used by 60% of the authors of the reviewed literature to define student performance. Knowledge gain, satisfaction, and learning outcome are the most common metrics used by 81%, 26%, and 15% of the reviewed literature to measure student performance. The study discovered that most researchers forget to evaluate the “e” or electronic component of e-learning when evaluating performance. The constructs operationalized and metrics measured were primarily focused on learning outcomes with minimal focus on technology-related metrics or the influence of the electronic mode of delivery on the learning process or evaluation outcome. Only 6% of the reviewed literature applied evaluation models to guide their evaluation process - mostly the Kirkpatrick evaluation model. Also, most of the included studies used randomization as an experimental control method, mainly using pre-and post-test surveys. Modern evaluation methods were rarely used. Only 1% of the reviewed literature used Google Analytics, and 2% used data from a learning management system. This study increments the existing body of knowledge in performance evaluation of e-learning in medical education by providing a convergence of constructs, metrics, models, and methods and proposing a roadmap to guide students’ performance evaluation process from the synthesis of findings and the gaps identified through the systematic review of existing literature in the domain. This roadmap will assist in informing researchers of grey areas to consider when evaluating performance to ensure more quality research outputs in the domain.

Maximizing Performance of Geopolymer Mortar: Optimizing Basalt and Carbon Fiber Content Composition

ABSTRACT This study focuses on the optimization of geopolymer composites, considering the parameters of composition and performance. The research explores the integration of algorithm-built hybrid implementations and a hybrid intelligent system to solve complex optimization problems in geopolymer composite materials. Firstly, an algorithm-built hybrid implementation is proposed, combining experimental results with various data processing methods. This approach enables the utilization of composite algorithms, offering several advantages, such as scalability and adaptability to different loads. The models developed in this study provide a flexible and extensible architecture, allowing for efficient problem-solving in optimization tasks. Secondly, a hybrid intelligent system is introduced, comprising statistical simulation models that combine different control and design problem-solving approaches. Markov chains are employed to address the quantitative aspects of loosely structured tasks and process performance evaluation. Criterion methods are utilized for quantitative conclusions, ensuring the optimal adaptation of the results from both applications. The research culminates in the identification of the optimal composition, denoted as G + FC + CFI, with specific weight content. This composition consists of cement, activator, fireclay, and carbon fiber I, with 100 g, 90 g, 100 g, and 2.5 g, respectively. The findings from this study provide valuable insights into the optimization of geopolymer composites, employing algorithm-built hybrid implementations and a hybrid intelligent system. The proposed approaches offer enhanced efficiency and accuracy in solving complex optimization problems in the field of geopolymer composite materials. The identified optimal composition demonstrates the potential for improving performance in composition and weight content.

Implementation Of Performance Management In Sarimart Minimarket Branch Bt. 8 Upper

Performance management applications for employees at minimum are a matter of concern. With that the company should always review all the aspects that build up inside the company. Surely the company needs a long-term planning process using performance management. The purpose of this study is to identify the implementation of performance management in employees at the bt branch minimum sarimart.8 tanjungpinang. The research method used in this study is qualitative. The results of this study show how the implementation of performance management at the bt branch sarimart minime.8, peers have implemented performance management through the following process of performance planning, performance planning, training, and guidance, performance assessment and evaluation.

The role of business school culture in building the non-PhD faculty's research attitudes and intention toward doctoral education.

Business schools face several challenges to keep business education relevant in a rapidly growing global environment. To overcome these challenges, business schools should hire or develop faculty with exceptional teaching abilities and high-quality research skills. This study examined the impact of business school culture on non-PhD permanent faculty in developing a research attitude that leads them to enroll in a PhD program. Through a self-administered questionnaire, data were collected using the proportionate method of stratified technique and analyzed using structural equation modeling. The findings suggest that business school culture significantly predicts research attitudes. Business schools that nurture a collaborative research culture are more likely to develop non-PhD faculty attitudes toward research. The development of this attitude helps business schools increase enrolment in PhD programs and thereby contribute to producing PhDs with high-quality research skills. The study recommends that business schools should develop a research-oriented culture that motivates non-PhD faculty to participate in research activities. In addition, research contributions should be rewarded and also acknowledged as a part of the faculty's annual performance evaluation process. This study contributes to the existing knowledge surrounding the social cognitive theory within business school culture.

Enhancing Privacy Preservation in Vehicular Trust Management Systems through Blockchain Technology

The advent of the Internet of Vehicles (IoV) has led to a significant surge in data generation from vehicles, prompting the innovative utilization of data transactions within the IoV environment. However, due to the inherent trustless nature of data transactions in IoV, concerns have arisen regarding the lack of trust between involved parties and the potential compromise of user privacy. To address these issues, blockchain technology emerges as a suitable decentralized distributed storage and security management solution, offering transparency and security in data transactions. In this study, we leverage blockchain to integrate with the IoV, devising a robust trust management framework, and devising a privacy protection scheme to safeguard user privacy concerns. Additionally, we employ the performance evaluation process algebra (PEPA) method for system modeling and performance analysis to assess the efficacy of our proposed solution. Empirical findings demonstrate that our approach effectively enhances the performance of data transactions within the IoV while ensuring that the privacy of users remains intact.

A NEEDS ASSESSMENT TO EXPLORE THE FEASIBILITY OF A UNIFIED EVALUATION FRAMEWORK FOR DIVERSE JOB SPECIALIZATIONS IN THE JOII WORKSTREAM

This study explores the possibility and potential benefits of creating a standardized evaluation framework for various job specializations within Joii Workstream. Joii Workstream is a business process outsourcing (BPO) company that provides office-based support to the construction industry. This research addresses subjectivity, bias, and inconsistency in performance assessments. The proposed solution is to establish a standard set of criteria for evaluation. The study uses a mixed-methods approach, combining surveys and interviews with key personnel. The results indicate that there are issues with the current evaluation practices. Although the employees remain neutral, they recognize that there is room for improvement. Challenges and opportunities are associated with implementing a unified framework, particularly regarding the diverse nature of job specializations. While most employees believe in the potential of a unified evaluation framework, they remain neutral about its feasibility. The study recommends a thorough assessment of current practices, transparent communication, stakeholder engagement, and a phased implementation approach to address concerns and enhance the effectiveness of the evaluation framework. Successful implementation is expected to lead to improved organizational efficiency, standardized evaluation criteria, and enhanced transparency in performance expectations. The research provides valuable insights into the broader field of human resource management, serving as a reference for organizations seeking to optimize their performance evaluation processes for diverse job specializations.

Miniaturization of an enclosed electrospinning process to enhance reproducibility in the fabrication of rapidly dissolving cell-based biosensors.

There is broad interest in producing electrospun films embedded with biological materials. It is well known that electrospinning requires careful control of the process conditions, especially the environmental conditions such as relative humidity (RH). Given that commercial electrospinning systems are expensive (>$10,000) and are typically too large to be used in standard biological safety cabinets (BSC), we designed and built a miniaturized electrospinning box (E-Box) that will fit inside a BSC, and the RH can be easily controlled using simple instrumentation (gas cylinder, regulator, needle valve, rotameter). It uses an inexpensive computerized numerical control machine to control the spinneret positioning and collector rotational speed-all the parts for the device (except the syringe pump and voltage supply) can be purchased for approximately $1000. We demonstrate the usefulness of our design in optimizing the production of Escherichia coli-embedded pullulan-trehalose films to be used as rapidly dissolving biosensors for environmental monitoring. At a fixed electrospinning recipe, we showed that decreasing the RH from approximately 48% to 22% resulted in the average fiber diameter increasing from 240(±11) nm to 314(±8) nm. We also demonstrate the usefulness of our design in performing sequential electrospinning experiments to evaluate process performance reproducibility. For example, from just 1mL of a polymer solution, we produced 16 electrospun films (approximately 3cm by 8cm each)-from those films we hole-punched approximately 80 biosensor discs which were then used in subsequent experiments to determine the amount of two different biocides (Grotan BK and triclosan) in aqueous samples. The technique developed in this study is ideal for creating electrospun materials in high quantities that are highly reproducible through the precise control of RH.

Prediction of Production Capability for Subcontractors in Automotive Rubber Part Supply Chain Using Neuro-Fuzzy System

The paper proposes prediction production capability for automotive rubber part supply chain subcontractors in order to remain competitive in the global market. Rubber parts are used widely in automotive, motorcycles, trucks and other types of vehicles which are mostly small sizes but huge quantities to support original equipment manufacturer (OEM) brands with specific parts. The rubber part manufacturing process is complex and uncertain with compression molding and rubber curing conditions. Therefore, good conditions can predict to obtain high production capability for customer commissioning and delivery on schedule. The Neuro-fuzzy system is adopted and developed to deal with the uncertain capability under multi-criteria decision making. The methodology development can be used in the actual situation of the rubber part manufacturing supply chain environment and can predict uncertain problems that might occur in the subcontractor factories. The prediction of the production capability of the rubber part supply chain might be more effective on the real-time monitoring control system and can be tracked location part progressive for further planning both successful or has to be rescheduled. The platform was applied to audit and test in the actual industrial supply chain in Thailand. The methodology development was originally created for the particular supply chain in rubber automotive parts that can replace the existing manual approach to obtain a more efficient process of monthly performance evaluation.

Sigma metric used to evaluate the performance of haematology analysers: choosing an internal reference analyser for the laboratory

ABSTRACTIntroductionThe sigma metric offers a quantitative framework for evaluating process performance in clinical laboratories. This study aimed to evaluate the analytical performance of automated analysers in haematology laboratories, using the sigma metric to choose the best analyser as an internal reference analyser.Materials and Methodsinternal quality control (IQC) data were collected for 6 months from SNCS, and the sigma value was calculated for 9 haematology analysers in the laboratory.ResultsFor the normal control level, a satisfactory mean sigma value ≥3 was observed for all of the studied parameters of all automated analysers. For the low control level, platelet (PLT) count by Instrument (Inst.) G performed poorly, with a mean sigma value <3. Inst. H, with all parameters’ sigma values >4, performed best and was chosen as the internal reference analyser.ConclusionThe sigma metric can be used as a guide to choose the QC strategy and plan QC frequency. It can facilitate the comparison of the same assay performed by multiple systems.

A Matter of Perspective: Mitigating the Outcome Effect in Auditor Performance Evaluations

SUMMARY We experimentally demonstrate that perspective taking improves the auditor performance evaluation process by mitigating the outcome effect and increasing evaluator focus on decision process quality. In a common setting in which a staff auditor exhibits appropriate skeptical behavior that correctly identifies no misstatement, supervising auditors prompted to take the perspective of the staff auditor evaluate the staff’s performance more highly than unprompted auditors—performance ratings that align with ratings provided to auditors who detect a misstatement. Results indicate that perspective taking mitigates the outcome effect by increasing supervisor attention to information cues about the staff’s decision process quality and away from cues about the nondiagnostic misstatement outcome. We also show that perspective taking increases evaluator consensus and reduces the variance in evaluator ratings that often plague performance reviews. Overall, our findings suggest that perspective taking can improve attention to process quality and help align reward structures with desired auditor behavior. JEL Classifications: M40; M42.

Performance Evaluation of Data Utility for a Differential Privacy Scheme Supporting Fault Tolerance

The evolution of smart grids improves the sustainability, controllability, stability, and efficiency of traditional power grids. There is a challenging issue in smart grids with protecting users’ privacy while collecting and controlling individual fine-grained data. To ensure data integrity and address the privacy issue, differential privacy protection is an efficient method to resist differential attacks on aggregated data. However, due to differential noise and faulty smart meters, the problem of differential noise deviation has a great impact on the utility of aggregated data. In this paper, we further supplement the previous work by improving the prediction method, forming a relatively complete DP protection scheme (DPP-UFT) with fault tolerance, and providing a detailed performance evaluation process. The experimental results show that the proposed method of adding differential noise based on the estimated failure rate is related to the estimated failure rate and the noise factor. Compared with several other related literature, it has achieved a higher data utilization effect.

An Active Learning Exercise for Teaching Process Strategy Alignment and Process Improvement

Abstract This hands-on active learning exercise uses an origami activity to teach students how to (1) achieve competitive priorities through process design and (2) monitor and evaluate process performance for potential improvement. Students are expected to explore current work processes for areas of improvement by focusing on process structure and resource management in process design and evaluation. Through the activity, students are exposed to linking process design with competitive priorities and challenged to evaluate their process for potential improvement. We provide several extensions of the activity that can be utilized to further its pedagogical utility.

Design and application of performance evaluation model of school education informatization based on artificial intelligence mode

&lt;p&gt;Educational informationization is an important part of educational reform. The performance evaluation of educational informationization plays an important role in promoting the development of informationization. Therefore, a performance evaluation model of school education informatization based on artificial intelligence mode is put forward. First, the current situation of school education informatization evaluation is briefly described, summarizing the artificial intelligence technology. The evaluation model of education informatization based on artificial intelligence is established, the performance evaluation index of school education informatization analyzed in detail. The index meets the requirement of input data through quantification and normalization, and the process of performance evaluation is designed. Feasibility and stability of the evaluation method are confirmed by the performance evaluation of school education informatization and the error analysis of the test results.&lt;/p&gt;

Lean performance evaluation of dairy cow farming processes with mathematical model development

Management sciences, especially controlling, are undergoing extensive changes. Various mathematical-statistical and IT solutions help organizations develop their systems and extract relevant information from data structures, thereby supporting effective decision-making and organizational operations. Agriculture is a special sector, but management functions apply here too, and modern tools and methods support the implementation of efficient operations. Dairy farming is a particularly important sector in agriculture, where controlling systems are developed in response to special requirements. The controlling activity of the sector is significantly influenced by the development of digitalization, which has resulted in the monitoring of processes and organizational performance evaluation becoming more extensive and detailed. Lean management is also an excellent method for increasing the efficiency of processes and organizational performance in the agricultural sector, which can be used to optimize processes, identify unnecessary activities and ensure appropriate task control. In this way, controlling systems must take into account the importance of lean management and contribute to the performance evaluation of organizational lean. In our study, we develop a lean performance evaluation model through an extended case study, which is suitable for evaluating the lean performance of the examined dairy farm. We used a fuzzy triangular function to evaluate the performance of enterprises, which represents the value of the given parameter with a triangular distribution. With dynamically growing and usable data, the model is able to provide continuous feedback on organizational lean operation and possible intervention points.

A multi-objective robust evolutionary optimization approach applied to the multivariate helical milling process of super duplex steel

This work presents an approach for multivariate modeling and multi-objective robust evolutionary optimization for processes presenting as inputs control and noise variables and as outputs a set of correlated responses regarding process performance and product quality. Factor analysis is applied to obtain a transformed output set that is uncorrelated and retains most part of the information of the original outputs. Models that are robust regarding noise variables relating this transformed output set with the control variables are obtained through robust parameter design. Response models in the function of process and noise variables are obtained through the least squares method. Mean and variance models as a function of process variables are obtained through error propagation. Robust mean square error models are obtained to model the bias and variance of each latent variable. Finally, multi-objective evolutionary optimization is performed. Three evolutionary algorithms were applied and compared through hypervolume. The approach is applied in the helical milling of super duplex stainless steel UNS S32760. Tool overhang length, hole depth, and lubri-cooling flow rate were set as noise factors. Cutting forces were monitored, while roughness and roundness were measured to evaluate process performance and product quality. The three factors, obtained to represent the six outputs, guaranteed dimensionality reduction and minimized the redundancy in output space. The mean square error models obtained to these three factors as a function of control variables minimize both bias and variance regarding noise factors. The AGE-MOEA multi-objective evolutionary algorithm obtained the best performance considering the hypervolume. Some solutions with high trade-off were selected through pseudo-weights to aid the decision-making.

Enhancing Fairness in Performance Appraisals: A Conceptual Framework Through a Systematic Literature Review

This study aims to comprehensively explore the multifaceted landscape of performance appraisals and, consequently, construct a coherent conceptual framework that augments the fairness and effectiveness of performance evaluation processes. The research design employs a meticulous, systematic literature review, drawing from 42 carefully selected articles from Scopus. This methodology facilitates in-depth analysis of diverse variables and dimensions associated with performance appraisals, particularly concerning the design of appraisal systems, the psychological elements at play, and the often-overlooked political influences. Within this intricate interplay, the study endeavors to unearth insights into the intricate mechanisms that govern the goal-setting process and the subsequent execution of performance appraisals within the dynamic public sector. Through an analytical lens, this study's findings enrich the development of a conceptual framework that transcends theoretical boundaries, finding practical resonance within the realm of performance appraisals. This framework, fortified by a holistic understanding of key dimensions and influential factors contributing to subjective bias, is a powerful instrument for unraveling and addressing fairness concerns inherent in performance appraisal practices. Ultimately, the framework presents a systematic trajectory for heightening the efficacy of performance appraisal design and execution, all underpinned by the overarching objectives of nurturing an environment of acceptable fairness.

Should I admit my wrongdoings? Examining stealing thunder in the context of performance evaluations

Stealing thunder is a self-disclosure strategy in which people reveal negative information about themselves before another person does so to reduce its negative impact on an audience. The present study examines stealing thunder as a trust tactic that employees might find useful for overcoming prior workplace mistakes during performance evaluation processes. Using hospitality managers in a between-subjects experimental design, Study 1 examined the impact of stealing thunder on manager evaluations of employees’ performance. The findings indicated that employees’ use of stealing thunder led to significantly better performance evaluations than when they did not apply the strategy. Study 2 confirmed the findings of Study 1 after controlling for mistake severity. Study 3 data examined the impact of accepting responsibility on performance evaluations. The results indicated that when employees adopted the stealing thunder strategy, their acceptance of responsibility resulted in significantly better performance evaluations than blaming others for the mistakes.

The Role of Time on Performance Assessment (Self, Peer and Teacher) in Higher Education: Rater Drift

This study aimed to investigate the change in teacher candidates' oral presentation skills over time through self, peer, and teacher assessments using the rater drift method. A longitudinal descriptive research model was used as a quantitative research approach to achieve this aim. The study group consisted of 47 teacher candidates receiving formation education at a state university in the Eastern Anatolia Region and an instructor teaching the course. An analytical rubric was used as a data collection tool to evaluate the candidates' oral presentation skills. The data collection process lasted six weeks in total. Since the performance evaluation process aimed to examine the change over time, the many-facet Rasch model was used. When the findings of the study were examined, it was determined that the rater behavior of teacher candidates had statistically significant differences at the group level over time. It was found that 26 out of 48 peer raters had rater drift in their evaluations. It was also found that the majority of rater drift over time was positive, meaning that evaluators became more generous over time. Another result obtained in the study was that teacher assessment did not show rater drift over time, with similar ratings for six weeks. The study’s findings were discussed with previous studies in the literature, and recommendations were made to researchers.