Research Performance Evaluation Research Articles

An Evaluation of Research Performance: A Survey Study of Undergraduate Media and Communication Students

Assessing research performance is essential for adopting enhancement procedures. The emphasis of the study was on undergraduate media students. The objectives of this study were to estimate their research abilities, evaluate the efficiency of some studies conducted, and identify areas for improvement. A survey was employed to collect data about the results of the final examination of the research methods subject. The study gathered 100 scores, representing three batches of male and female students. The study used the independent sample t-test to compare the means for the two groups of males and females and then explain the differences and effect size. The results showed that female students have much higher research method scores (79.3) than male students (74.9). The standard deviation for male research methods scores (10.9) is higher than that for male students (9.8), indicating higher variability in female scores. The standard error of the mean estimates the precision of the sample mean. It is higher for male students (1.5) than for female students (1.4). Hence, male students needed more accuracy in estimating the population mean due to the large variability in their scores. The effect size was (d = 0.41). There were differences (t (df = 98, p =.035) in the scores, with the mean score for the females (M = 79.3, SD = 9.8) being higher than the males (M = 74.9, SD = 10.9). In conclusion, testing students' research skills revealed a slight difference between male and female media B.Sc. students.

Tracking changes in CNCI: the complementarity of standard, collaboration and fractional CNCI in understanding and evaluating research performance

AbstractUsing a global set of ~ 300 institutions, standard, collaboration and fractional Category Normalised Citation Impact (CNCI) indicators are compared between 2009 and 2018 to demonstrate the complementarity of the three variants for research evaluation. Web of Science data show that Chinese institutions appear immune to the indicator used as CNCI changes, generally improvements, are similar for all three variants. Other regions tend to show greater increases in standard CNCI over collaboration CNCI, which in turn is greater than fractional CNCI; however, decreases in CNCI values, particularly in established research economies like North America and western Europe are not uncommon. These findings may highlight the differing extent to which the number of collaborating countries and institutions on papers affect each variant. Other factors affecting CNCI values may be citation practices and hiring of Highly Cited Researchers. Evaluating and comparing the performance of institutions is a main driver of policy, research and funding direction. Decision makers must understand all aspects of CNCI indicators, including the secondary factors illustrated here, by using a ‘profiles not metrics’ approach.

Performance evaluation and comparative research of underwater wireless optical communication system by using different structured beams

Structured beams have attracted increasing interest in free-space and fiber-based optical communications. Underwater wireless optical communication (UWOC) is becoming a prospective technique in marine exploration. We investigated UWOC performance using different representative structured beams. The transmission performances of the Gaussian, Bessel–Gaussian (BG), Ince–Gaussian (IG), and radially polarized Gaussian (RPG) beams were experimentally demonstrated and evaluated in underwater channels subjected to thermal gradient. The experimental results show that the BG, IG, and RPG perform better against the thermal gradient. Compared with the Gaussian beams, the beam wanders of BG, IG, and RPG beams under the thermal gradient have been reduced by 56.9%, 8.2%, and 59%, the scintillation indices have been decreased by 12.8%, 17.3%, and 28.9%, and the BER performance of the BG, IG, and RPG beams have been improved by ∼5.5, ∼3.7, and ∼5.2dB at the forward error correction threshold (FEC threshold). Based on the above results, the RPG beam is a more promising light source for UWOC. The experimental results provide a promising beam choice for UWOC.

Optimization of University Scientific Research Performance Evaluation Management Based on Back-Propagation Artificial Neural Network

Optimization of University Scientific Research Performance Evaluation Management Based on Back-Propagation Artificial Neural Network

Impact of community service on university performance and efficiency

Purpose This study aims to analyze the effectiveness and efficiency of research-based community service programs in Indonesia that used government funds in 2017–2021. Design/methodology/approach The design of this research is a quantitative research method using a data envelopment analysis to evaluate 370 leading universities in Indonesia. Furthermore, six analytical models were considered to compare effectiveness and efficiency between universities. It involved two resource (budget and staff academic involved), three output (intellectual property, prototype and publication) and three outcome variables (economic impact, social impact and capacity building). Findings The findings showed that several universities are considered necessary, with great potential to increase output and outcome efficiency in community involvement. The study mapped and divided the position of 370 universities for additional information. The effectiveness aspect provides another perspective in assessing the performance of tertiary institutions in Indonesia and can be an option for evaluating research performance to improve the quality of output. Originality/value The authors use data from research and community service management information systems used, both the resources used and the results. Efficiency and effectiveness of 370 universities were compared in this study, including comparing their position on the previous assessment with the assessment of the results of this study. Approach to the concept of Mandl et al. (2008) regarding the relationship between input, output and outcome as the main component of the indicators, the authors apply to analyze efficiency and effectiveness.

Research performance evaluation model in university: evidence from Indonesia

PurposeThis research aimed to examine the impact of input, process, output, productivity and outcome variables on university research performance and the indicators that represent them in order to improve academic quality and contribute to government policy.Design/methodology/approachThe quantitative approach was used through a survey method that obtained samples using questionnaires from 150 leaders of research institutions and continued analysis using the structural equation modeling-partial least square (SEM-PLS) to test the developed model.FindingsExcept for the relationship between process and productivity variables, all variable relationships had a positive and significant effect. Furthermore, the input, process, output, productivity and outcome variables each include seven, twelve, four and ten indicators.Research limitations/implicationsThis study has several ramifications because it provides a clear policy input and advances science. As a prelude to developing research performance assessment tools that take into account variances in a tertiary institution, this research aids in the implementation of national policies for assessing research performance in postsecondary institutions.Originality/valueTo improve the accuracy of the information acquired, we conducted a survey among the heads of research units at various higher-ranking Indonesian universities, taking into consideration their skill and experience in leading research organizations and conducting research. Other than that, our belief in the originality of our manuscript is strengthened by the way we applied systems theory to construct a performance evaluation model that examines each contribution made by each system aspect.

ANALISIS SENTIMEN VAKSIN COVID-19 PADA TWITTER MENGGUNAKAN RECURRENT NEURAL NETWORK (RNN) DENGAN ALGORITMA LONG SHORT-TERM MEMORY (LSTM)

The Coronavirus, also known as the Covid-19 pandemic, has reached every country worldwide, including Indonesia. Covid-19 is still prevalent and has killed many people in Indonesia. This makes it impossible to stop Covid-19 from spreading. The government's attempt to stop the Covid-19 pandemic is acquiring the vaccine. The administration of the Covid-19 vaccine has generated much discussion on social media, particularly Twitter. Tweets displaying public opinion on Twitter can be used for sentiment analysis and categorizing public opinion on the Covid-19 vaccine. 20,000 tweets were collected by Twitter crawling between January 10 and January 15, 2022. 3.290 tweets were left after pre-processing and meaningless tweets were eliminated. The data were processed using the Recurrent Neural Network method with the Long Short-Term Memory algorithm to determine its accuracy and identify topics often discussed by the public on Twitter. The LSTM method is capable of storing old information/data. A model with 70% training data, a learning rate of 0.01, 100 LSTM units, 32 batch sizes, 100 epochs, a cross-entropy loss function, and Adam optimizers was used to build the classification in this study. The accuracy value obtained from the performance evaluation of the Long Short-Term Memory model research was 80.34%.

Does Quality Matter? Quality Assurance in Research for the Chilean Higher Education System

This study analyzes the research quality assurance processes in Chilean universities. Data from 29 universities accredited by the National Accreditation Commission were collected. The relationship between institutional accreditation and research performance was analyzed using length in years of institutional accreditation and eight research metrics used as the indicators of quantity, quality, and impact of a university’s outputs at an international level. The results showed that quality assurance in research of Chilean universities is mainly associated with quantity and not with the quality and impact of academic publications. There was also no relationship between the number of publications and their quality, even finding cases with negative correlations. In addition to the above, the relationship between international metrics to evaluate research performance (i.e., international collaboration, field-weighted citation impact, and output in the top 10% citation percentiles) showed the existence of three clusters of heterogeneous composition regarding the distribution of universities with different years of institutional accreditation. These findings call for a new focus on improving regulatory processes to evaluate research performance and adequately promote institutions’ development and the effectiveness of their mission.

Congestion Control in Wi-Fi Networks - State of the Art, Performance Evaluation, and Key Research Directions

Congestion Control in Wi-Fi Networks - State of the Art, Performance Evaluation, and Key Research Directions

Congestion Control in Wi-Fi Networks—State of the Art, Performance Evaluation, and Key Research Directions

Congestion Control in Wi-Fi Networks—State of the Art, Performance Evaluation, and Key Research Directions

SELF-EFFICACY AS A MEDIATOR BETWEEN KNOWLEDGE STRUCTURE AND MUSIC STAGE PERFORMANCE OF MUSIC MAJOR STUDENTS: A PROPOSED MODEL

As an important part of music education, music stage performance has developed rapidly within the framework of modern university higher education. However, there are still many problems in the research and teaching practice. Music stage performance evaluation and related research did not consider students ' psychology, resulting in poor teaching effects. Most of the research objects of knowledge structure are teachers, ignoring the promotion of students ' knowledge structure to music stage performance. Besides, many existing studies focus on how music improves patients ' self-efficacy but ignore how self-efficacy improves music stage performance. Thus, this study aims to propose a model to explore the stage performance of music major students in universities and the covariates that can improve stage performance.

Discrete‐event simulation is still alive and strong: evidence from bibliometric performance evaluation of research during COVID‐19 global health pandemic

AbstractDuring the Annual Operational Research Society Simulation Workshop in Worchester, UK, in 2010, a panel discussion entitled “discrete‐event simulation (DES) is dead, long live agent‐based simulation (ABS)!” was held. Subsequent debates on the topic have captured the interest of many simulation professionals and researchers. This study lends credence to the discourse with evidence. In January 2020, a global health crisis named coronavirus disease (COVID‐19) occurred, infecting and killing millions of people globally, leading to community lockdowns and travel restrictions, and bringing the world to a standstill. Scientists scrambled for quick, practical solutions to stem the tide. Operational research (OR) and management science (MS) techniques, including modeling and simulation, provide effective methods to make COVID‐19 infection forecasts, assign/optimize intensive care unit beds, initiate healthcare management/control strategies, and decision‐making. The global pandemic problems offer an opportunity to evaluate the discourse on DES's continuous relevance and potency as an OR/MS technique. Utilizing bibliometric performance evaluation and text analytics of publications addressing various COVID‐19 pandemic problems, the results show an extensive use, relevance, and impact of the DES technique across multidisciplinary domains, including medical/healthcare, social and behavioral sciences, business, molecular biosciences, and more. The intellectual structure highlights strong multidisciplinary collaboration among sources in decision sciences, healthcare, natural, behavioral, and social sciences. The social network analysis of the publications shows the contributions and collaborations among authors, institutions, and countries. The study demonstrates that DES is still alive and robust, notwithstanding the hype about ABS.

Sustainable Transformation Evaluation and Obstacle Factor Analysis of Mature Coal Resource Cities: A Study Using Jinzhong City as an Example

Transformation and development performance evaluation and obstacle factor research are standard and important bases for measuring the transformation of mature resource cities. Based on the connotation of transformational development, this paper presents the selection of indices for the construction of a measurement index system that covers four aspects: economics, people’s well-being, resources, and the ecological environment. Taking Jinzhong City as an example, this study measures the implementation effect of sustainable development planning in resource cities and applies the entropy-weight TOPSIS method and obstacle degree model to evaluate its transformation and development performance and diagnose obstacle factors from 2007 to 2020. The results are as follows: (1) Jinzhong City has made remarkable achievements in transitional development. In the past 14 years, transformation performance has increased from 0.260 to 0.711, and there has been a change from the fair transformation stage to the good transformation stage. (2) The transformational development of Jinzhong City presents two phases: the initial exploratory phase (2007~2013) and the steadily improving phase (2014~2020). The four systems differ significantly in their drive for transformational development in the two stages. (3) The main obstacle factors for the transformation and development of Jinzhong City show stage differences. However, as a whole, economic development and the ecological environment were the main obstacle factors constraining the transformation and development of the city. Hence, it is essential for mature coal resource cities to improve transformation in the future and construct a long-term mechanism for sustainable development, cultivating continuous alternative industries and improving the ecological environment and the security of people’s livelihoods.

Statistical Confounding in Observational Research and Center Performance Evaluations in Organ Transplantation

Statistical Confounding in Observational Research and Center Performance Evaluations in Organ Transplantation

Отношение преподавателей вузов к системам оценки деятельности научно-педагогических работников

This article summarizes the results of a survey and semi-structured interviews of Russian university teachers regarding the systems of performance evaluation of research and teaching staff and their effectiveness. The results of the study revealed that university teachers have a positive attitude to the methods of stimulating research and teaching staff performance applied in higher education. At the same time, the degree of teachers’ satisfaction and evaluation of systems’ effectiveness directly depend on the specifics of their application in a particular higher education institution. The results of the study confirm the overall trend towards increasing importance of scientific components in the performance evaluation of research and teaching staff at universities. The results can become a prerequisite for the development of new criteria for ensuring the effectiveness of social and labor relations with university teachers.

Epigenetics research in eye diseases: a bibliometric analysis from 2000 to 2023

ABSTRACT Clinical relevance A bibliometric analysis is a quantitative study that utilises methods such as citation analysis to evaluate research performance. A bibliometric analysis could provide a valuable reference for ophthalmic researchers to understand the trends in epigenetics research. Background The number of studies on epigenetics in eye diseases has exceeded 5,000, but the progress and scope of epigenetic research on eye diseases remain unclear. The study aimed to bibliometrically analyse epigenetic research conducted in eye diseases. Methods Studies concerning epigenetic research on eye diseases from 2000–2023 were searched using the Web of Science Core Collection. Following this, the included studies were analysed for citations, journals, keywords, authors, and countries, using the Bibliometrix package in R Studio. Results In total, 3758 studies were included in the analysis, including 3099 original articles, 599 reviews, 11 editorials, and 49 early access articles. Investigative Ophthalmology & Visual Science was the most published journal with 185 articles, and Proceedings of the National Academy of Sciences of the United States of America was the most cited journal, with 8727 citations. The journal with the highest h-index was Oncogene (h-index = 38).Renu A Kowluru from the Kresge Eye Institute, Wayne State University, Detroit, USA, had the most citations with 1,690 and the highest h-index (h-index = 23). China and the USA were the countries with the highest number of publications (1739) and total citations (40533), respectively. Furthermore, from 2000–2023, the top five frequent research topics were diabetic retinopathy, 522; microribonucleic acid, 469; retinoblastoma, 370; apoptosis, 268; and epigenetics, 206. Conclusions The results of this bibliometric study provide the current status and trends of epigenetic research in eye diseases and will help researchers identify areas of current interest in the field, which should help highlight new research directions.

Systematic literature review of dermoscopic pigmented skin lesions classification using convolutional neural network (CNN)

The occurrence of pigmented skin lesions (PSL), including melanoma, are rising, and early detection is crucial for reducing mortality. To assist Pigmented skin lesions, including melanoma, are rising, and early detection is crucial in reducing mortality. To aid dermatologists in early detection, computational techniques have been developed. This research conducted a systematic literature review (SLR) to identify research goals, datasets, methodologies, and performance evaluation methods used in categorizing dermoscopic lesions. This review focuses on using convolutional neural networks (CNNs) in analyzing PSL. Based on specific inclusion and exclusion criteria, the review included 54 primary studies published on Scopus and PubMed between 2018 and 2022. The results showed that ResNet and self-developed CNN were used in 22% of the studies, followed by Ensemble at 20% and DenseNet at 9%. Public datasets such as ISIC 2019 were predominantly used, and 85% of the classifiers used were softmax. The findings suggest that the input, architecture, and output/feature modifications can enhance the model's performance, although improving sensitivity in multiclass classification remains a challenge. While there is no specific model approach to solve the problem in this area, we recommend simultaneously modifying the three clusters to improve the model's performance.

Mapping Two Decades of Research Productivity in the Middle Eastern and Arab Countries: A Comprehensive Bibliometric Analysis

Middle Eastern and Arab countries have been experiencing significant advancements in scientific research and development over the past few decades. Understanding the trends, patterns, and impact of research within this region can provide valuable insights into its scientific landscape, identify areas of strength, and uncover potential areas for improvement. This study presents a comprehensive bibliometric analysis of research productivity in the Middle Eastern and Arab region over a 20-year period. The findings revealed a consistent increase in research productivity, yet mapped significant disparities between countries in scholarly output, excellence, and impact. Adjusting for population size and GDP, Iran displayed the highest publication activity, trailed by Egypt and Turkey. Delving into the distribution of research output across different journal quartiles, the results revealed that this region has a lower percentage of scholarly output published in high-impact journals (both the top 10% and the top 25% categories). Compared to North America and the European Union, the Middle Eastern and Arab region consistently exhibited lower performance in terms of top 10% citations, average citations per publication, and field-weighted citation impact. The field of physical sciences took the lead as the most prevalent subject area in the Middle Eastern and Arab region, comprising about 60.5% of the research emphasis. Conversely, social sciences garnered comparatively less research attention, making up approximately 8.9% of the focus. The region showed strong international collaboration levels (40.5%), yet relatively low national (24.4%) and academic–corporate collaborations (1.5%). The outcomes of this study can facilitate international comparisons and benchmarking, allowing Middle Eastern and Arab countries to position themselves within the global scientific community. There remains a need to prioritize quality over quantity by emphasizing rigorous research practices and collaboration. An ongoing evaluation of research performance using a combination of indicators can help track progress and adjust strategies as needed.

Evaluating patient safety research performance in Arab world countries: Changing trends and reflections.

Patient safety is a major concern in health care. Research is an important tool to minimize preventable errors. Research performance and trends evaluation need to be identified for future guidance. Our objective was to evaluate the research performance in Arab World countries related to patient safety so that real picture is available to all stake holders for future application. This was a descriptive exploratory study carried at King Abdulaziz University Jeddah, using Bibliometric analyses on Web of Science extracted data, exploring the research publications related to Patient Safety from the Arab World in last two decades (2001-2020). Digital resources were used. Data collected was further explored to see the trends. Only 2% of total worldwide publications on Patient Safety were from Arab World. A positive trend, however, has emerged since 2015. Out of 5940 documents identified, only 383 had single authorship. Egypt and Saudi Arab were the major contributors. Other countries had less or even zero publications. Researchers are coordinating with others in Western countries to enhance the research productivity. Cairo University with 734 publications had most affiliations. Publications on safety culture and medication safety were frequent. Hospital Acquired Infections and error reporting had limited research. Researches on patient safety in the Arab World are not sufficient. Countries other than Egypt and Saudi Arabia also need to contribute more frequently. Critical problems, like Hospital Acquired Infections, should have regular research from all countries to assist those treating patients and those making health related policies.

Deep neural network-based analysis of the impact of ambidextrous innovation and social networks on firm performance

The motivation for analyzing the impact of deep neural networks on enterprise performance is mainly due to the continuous deepening of enterprise information construction, shifting from traditional paper-based data acquisition methods to electronic data management. The data generated by the sales, production, logistics and other links of enterprises is also becoming increasingly large. How to scientifically and effectively process these massive amounts of data and extract valuable information has become an important issue that enterprises need to solve. The continuous and stable growth of China's economy has promoted the development and growth of enterprises, however, it has also made enterprises face a more complex competitive environment. The question of how to improve the performance of enterprises to enhance their competitiveness in the market has become a major issue to be addressed in the face of fierce competition and to ensure the long-term development of enterprises. In this paper, based on the research of firm performance evaluation, deep neural network is introduced to analyse the influence of ambidextrous innovation and social network on firm performance, and the theories of social network, ambidextrous innovation and deep neural network are sorted out and analysed, and a deep neural network-based firm performance evaluation model is established, and finally the sample data is obtained using crawler technology, and then the response values are analysed. Innovation and the improvement of the mean value of social networks are helpful to firm performance.