Quality-based Evaluation Research Articles

Budaya Mutu dalam Pendidikan Islam: Tantangan dan Peluang

This study aims to examine the application of quality culture in Islamic education at MA Al Amiriyyah Blokagung. This study collects data from interviews with madrasah heads, teachers, and students as well as direct observation of the implementation of education policies and evaluations. Data analysis was carried out qualitatively with the stages of data reduction, data presentation, and conclusion drawn. The results of the study show that MA Al Amiriyyah has implemented a culture of quality with a focus on commitment to the quality of education, teacher competence, and quality-based evaluation. Although there have been significant efforts to maintain the quality of education through teacher development and the implementation of holistic evaluation, there are still some major challenges, such as limited facilities, time, and training for teachers. On the other hand, the support of the pesantren community and the existence of quality improvement programs provide a great opportunity to overcome these obstacles. The conclusion of this study is that the implementation of quality culture in MA Al Amiriyyah has shown positive results in improving the quality of Islamic education. However, to achieve more optimal results, madrasas need to strengthen infrastructure, provide more intensive training for teachers, and optimize synergy between madrasas, parents, and the pesantren community.

Evaluating Generative Artificial Intelligence on Multilingual Sentiment Analysis

This study shows that natural language processing (NLP), large language models (LLM), and generative Artificial Intelligence are becoming the most important. LLM is considered essential for many NLP tasks, including question-answering, classification, interpretation, and writing. New LLMs must be able to analyze and create documents in different languages as they know how to train training materials in different languages such as ChatGPT, BLOOMZ, and others. Considering how frequently LLMs are used, it is critical to assess the effectiveness in multi-lingual environments. In a zero-shot context, the present generative models are still useful in producing text in Indian languages. On the other hand, generative models routinely outperform human quality-based evaluation when it comes to English language generation and Indian languages. LLMs are not meant to be used in a zero-shot manner in downstream applications due to poor generating performance.

Community-Based Critical Literacy Practices: A Reflective Study of Literacy Implementation in School

This article examines critical literacy practices carried out by the informal education community thoughtfully and potentially so that they can be applied to developing the school literacy movement program. Statistically, 95.66% of Indonesia's population can read, but on the other hand, the reading literacy score in the PISA study is still below average. So far, there have been different perspectives regarding literacy as a reading activity and literacy as an activity to process information. These differences result in different interpretations and attitudes in processing information in a text. Critical literacy relates reading analysis skills to the realities faced by students. This study aimed to find patterns of critical literacy carried out by the Ngampar Boekoe community and Jamaah Maiyah Al Manhal about the inherent development of the school literacy movement program. The research method used is qualitative with an auto-ethnographic approach. The data comes from the researcher's personal experience, observation, in-depth interviews and artefacts. Data analysis uses triangulation with a bottom-up pattern to find critical literacy formulas and can be reflected in the school literacy movement program. The results found are in the form of alternative formulations which consist of critical material that can develop students' critical power, dialectical methods filled with a sense of trust, and quality-based evaluation using response journal instruments and written works. The results of this study can be used as policy-making considerations for relevant stakeholders to build the qualifications of a literate society.

Automatic Taxonomy Generation and Incremental Evolution on Apache Spark Parallelization Framework

The term “Big Data” refers to a large volume of information usually in terabytes and petabytes. It includes both structured and unstructured data. Unstructured data is conventionally text-heavy, but may also contain data such as facts, dates and numbers. To use this unstructured information effectively, it needs to be processed and organized. Taxonomy is considered as a powerful way of organizing the information. For automatic taxonomy generation, various techniques have been proposed in the past. However, the substantial nature of big data presently crosses the processing abilities of traditional techniques. Thus, to meet this challenge an extensible and scalable technique is required to potentially accelerate the process of taxonomy generation and its evolution upon arrival of new data, hence catering large amount of unstructured big data. This paper proposes a technique for both the taxonomy generation and evolution on Apache Spark infrastructure. The proposed technique is evaluated on a text dataset of a computing domain. The evaluation results show that the technique presented in this paper outperformed the existing techniques in terms of time and quality metrics. The time and quality-based evaluation showed that the use of MapReduce environment has resolved the scalability issues of current taxonomy generation and evolution process.

Algal wastewater treatment integrated with carbon adsorption and ozonation for water reclamation: Multi-criteria comparison with conventional pathways

Our previous reports have documented a mixotrophic algal wastewater treatment (A-WWT) system integrated with downstream technologies for recovering net energy and fertilizers from domestic wastewater. In the current study, we explore the potential for reclaiming reuse-quality water via the A-WWT system by treating its effluent further by granular activated carbon (GAC) adsorption or/and ozonation (O3). Our study also includes a comparison of water reclamation capability of a pilot-scale A-WWT system against that of a full-scale conventional activated sludge (CAS) system, both fed with the same primary effluent and followed by GAC and O3. In this preliminary evaluation, aggregate chemical water quality data collected from the following 8 treatment trains are compared: T1) CAS + GAC; T2) CAS + O3; T3) CAS + GAC + O3; T4) CAS + O3 + GAC; T5) A-WWT + GAC; T6) A-WWT + O3; T7) A-WWT + GAC + O3; and T8) A-WWT + O3 + GAC. Based on aggregate water quality measures, ozonation followed by GAC adsorption achieved the lowest concentrations of organics (dissolved organic carbon, chemical oxygen demand, and UV absorbance) and nutrients (total nitrogen and total phosphorus), irrespective of the treatment provided by the CAS and A-WWT systems. Despite the higher footprint requirement, all four algal-based treatment trains (T5 to T8) ranked better than the CAS-based trains (T1 to T4) when compared on the basis of energy demand and energy recoverability. Following these findings, a multi-criteria evaluation of the 8 treatment trains was performed considering 16 criteria spanning energy demand, energy recoverability, disinfection capability, emissions, areal footprint, and complexity. The multi-criteria evaluation ranked the A-WWT system integrated with ozonation and GAC adsorption (T8) highest among the eight treatment trains considered here. This preliminary evaluation adds further credence to the A-WWT system and warrants a detailed Water quality-based evaluation of its effluent and follow-up treatment to reclaim reuse-quality water.

Open Book Exam (OBE) through ICT: A Quality-Based Evaluation Approach at Present COVID-19 Pandemic Situation in Higher Education

The spread of pandemic COVID-19 has drastically disrupted every aspect of human life including education. It has created an unprecedented test on education. In several educational institutions across the globe, campuses have closing down and teaching-learning has shifted online. Internationalization has slowed down considerably. In India, around 32 crore learners have started moving schools/colleges and all educational practices have finished. Despite all these challenges, the Higher Education Institutions (HEIs) have reacted positively and managed to ensure the continuity of teaching-learning, research, and service to the society with some tools and techniques during the pandemic. This article highlights an open book exam as an evaluation approach through the use of ICT in HEIs in India. In this pandemic situation, it may be helpful for higher education. But some limitations are existing. However, through the efforts of all of us, we have to come forward for the overall welfare of the society by solving these problems while keeping ourselves as safe as possible.

Quality and Quantity of Organic Acid, Lipids and Acid Value Influence the Quality of Specialty Coffee

The quality of specialty coffee (SP) is evaluated based on the grading system (number of defects of green beans and sensory evaluation of roasted beans) of the Specialty Coffee Association of America, while the quality of commercial coffee (CO), which is a product with a wide variety of uses, is evaluated based on the export standards (number of defects and altitude) of its country of origin. Nevertheless, a physicochemical quality-based evaluation method has not yet been established. In this study, the pH, titratable acidity, organic acid content, total lipid content, and acid values of Kenyan, Guatemalan, and Columbian SP and CO samples were analyzed and evaluated to correlation with sensory scores to find new indicators for quality evaluation of coffee. Significant differences were shown to the pH and acid values of all SP samples, and in the titratable acidity and total lipid contents of some SP samples. In addition, the sensory evaluation scores for all the SP samples were more than 80, and were significantly higher than those for the CO samples. The significance of values obtained from the physicochemical analysis is reflected in the sensory evaluation scores, and it was suggested that they affect the coffee quality.

A decade of robot-assisted radical prostatectomy training: Time-based metrics and qualitative grading for fellows and residents

ObjectivesAs modern urology residency and fellowship training in robot-assisted surgery evolves toward standardized curricula (didactics, dry/wet-laboratory exercises, and surgical assistance), additional tools are needed to evaluate on-console performance. At the start of our robotics program in 2006, we set-up a time- and quality-based evaluation program and aim to consolidate this data into a simple set of metrics for self-evaluation. Materials and methodsUsing our index procedure of robot-assisted radical prostatectomy (RARP), we prospectively collected data on 2,215 cases over 10 years from 6 faculty surgeons and 94 trainees (43 urologic oncology fellows and 51 urology residents). The steps of the operation were divided into 11 consistent steps, and the metrics included time to completion and quality using a 6-level grading system. Time metrics were consolidated into quartiles for benchmarking. ResultsThe median times for trainees to complete each step were 15% to 120% higher than those of the staff (P<0.001). Each step can be presented with quartile-based time metrics by pooled trainee and staff results. Steps performed by trainees were carefully chosen for a high success rate, and on our Likert-like scale were graded 4 to 5 in more than 95% of cases. There were no grade 0 (very poor) cases, and grades 1 (multiple technical errors) and 2 (could not be completed but without safety issues) were rare (<1%). ConclusionsRARP training can be evaluated with a time-based metric that allows a quartile-based comparison to a large experience of trainees and staff. As a trainee progress through a rotation, these benchmarks can assist in prioritizing the need for more attention to a basic step vs. progression to more advanced steps.

Quality-Based Conditional Processing in Multi-Biometrics: Application to Sensor Interoperability

As biometric technology is increasingly deployed, it will be common to replace parts of operational systems with newer designs. The cost and inconvenience of reacquiring enrolled users when a new vendor solution is incorporated makes this approach difficult and many applications will require to deal with information from different sources regularly. These interoperability problems can dramatically affect the performance of biometric systems and thus, they need to be overcome. Here, we describe and evaluate the ATVS-UAM fusion approach submitted to the quality-based evaluation of the 2007 BioSecure Multimodal Evaluation Campaign, whose aim was to compare fusion algorithms when biometric signals were generated using several biometric devices in mismatched conditions. Quality measures from the raw biometric data are available to allow system adjustment to changing quality conditions due to device changes. This system adjustment is referred to as quality-based conditional processing. The proposed fusion approach is based on linear logistic regression, in which fused scores tend to be log-likelihood-ratios. This allows the easy and efficient combination of matching scores from different devices assuming low dependence among modalities. In our system, quality information is used to switch between different system modules depending on the data source (the sensor in our case) and to reject channels with low quality data during the fusion. We compare our fusion approach to a set of rule-based fusion schemes over normalized scores. Results show that the proposed approach outperforms all the rule-based fusion schemes. We also show that with the quality-based channel rejection scheme, an overall improvement of 25% in the equal error rate is obtained.

Evaluating Medical Training Programs by the Quality of Care Delivered by Their Alumni

MEDICAL EDUCATION SERVES MANY GOALS, AND all of them are difficult to measure. For that reason, assertions that one medical school or residency program is better than another may have many different meanings. Nevertheless, most stakeholders, including prospective trainees, health systems, and patients, could be justified in expecting that graduates of good training programs generally take care of patients well, and that graduates of better training programs generally take care of patients better. The evaluation of medical education programs ought to keep this goal in sight. Because patient outcomes are already used to judge the performance of physicians and hospitals, a logical extension might be to evaluate training programs in part by the downstream outcomes of patients treated by their graduates. A key issue is whether patients have better outcomes if they receive care from physicians trained at top institutions. Although the institutional effect of a training site might not have as much predictive value as other physician characteristics, training pedigree might distinguish physicians, and it is easily observable. This idea has intuitive appeal, but also presents considerable challenges to its development and possible use. Several conceptual issues related to clinical quality-based evaluation of medical training must be considered, leading to a proposed research agenda.

The effects of a medical care utilization review program on back and neck injury claims.

A number of quality-based evaluation and treatment protocols have been developed and marketed for the management of work-related musculoskeletal problems. Yet, little is known about their effectiveness in improving patient outcomes. We evaluated one such approach adopted by the Department of Labor and Industries, which insures approximately two-thirds of the non-federal workforce in Washington State. The outcomes of back and neck injury claims (primarily sprains and strains) filed in the 2 months after the program was fully operational were compared with two comparable groups of claims from the same base population filed before the program's availability. There were no statistically significant differences between groups in the number of days of work loss, medical costs, and permanent partial disability awards granted during the 2 years after injury. The quality-based program used as an adjunct to claims management failed to improve outcomes.

Quality-based evaluation of multimedia synchronization protocols for distributed multimedia information systems

Distributed, networked multimedia information systems will be a critical component of technology-based information infrastructures in the future. We present an infrastructure for supporting multimedia applications. We discuss various characteristics of multimedia data and the effect of the network on the required quality of presentation for multimedia data. We present a suite of synchronization protocols to support the quality of presentation. The crux of these protocols is the scheduling of multimedia information for synchronized delivery, over broadband networks with limited resources, and is identified as an NP-hard problem. We introduce two parameters which can be used to measure the performance of end-to-end synchronization protocols in a network supporting distributed multimedia applications. We propose and implement several heuristic scheduling algorithms, and compare their performance. We deduce the appropriateness of these algorithms in different types of distributed multimedia environments.