Quality Assurance Framework Research Articles

Agile methodology in higher education quality assurance system for SDGs 4, 8 and 9 achievement: national experience

This paper is focused on considering agile methodology as an instrument to use in education quality assurance. We propose the Scrum method applicable for education quality assurance based on adapted Manifesto for Agile Education Quality Assurance and twelve principles behind it. The Scrum procedure is described and roles are distributed for two real-life cases of external and internal educational program quality evaluation. We illustrate that proposed Scrum procedure perfectly fits existing practices and can be used to enhance both external and internal quality assurance processes in higher education. We consider achievement of SDG 4 targets through proposed methodology as the necessary step to take in achieving SDGs 8 and 9. It is concluded that stakeholders feedback about their satisfaction by economic and innovative factors should be included in each sprint review procedure in proposed Scrum methodology. We discuss SDG 4 achieving within multilayered DIKW+DM hierarchy as a framework for education quality assurance that allow to join information processing, knowledge acquisition and corresponding decision-making algorithm.

A Framework for User-Configurable Data Quality Assurance of Electronic Patient Records.

Electronic Patient Records (EPRs) are valuable data resources for clinical and operational research. The heterogeneity of medical software coupled with the changing data formats and long lifespan of the patient datasets stored in EPRs results in data inconsistencies that hinder operational activities and increase personnel efforts for data lookup and cleaning. This study presents an approach for automated data quality reporting that was developed and tested within a real-world hospital setting at Royal Surrey County Hospital NHS Foundation Trust in 2020. 81 data quality tests configurable via spreadsheets were defined and executed to yield standardised human-readable reports in comma-separated value format. The data evaluation and reporting routines provided manyfold improvement over existing data quality reporting mechanisms.

A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study.

BackgroundThe global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the forefront as a promising solution for the rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. This study examines the opportunities and challenges afforded by the societal shift toward web-based testing and highlights an urgent need to establish a standard data quality assurance framework for online studies.ObjectiveThis study aims to develop and validate a new supervised online testing methodology, remote guided testing (RGT).MethodsA total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory, and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (n=41) or online using remote guided testing (n=44) and delivered using identical web-based platforms (Cambridge Neuropsychological Test Automated Battery, Inquisit, and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, and response times) and overall task performance measures.ResultsThe results indicated that, across all data quality and performance measures, RGT data was statistically-equivalent to in-person data collected in the lab (P>.40 for all comparisons). Moreover, RGT participants out-performed the lab group on measured verbal intelligence (P<.001), which could reflect test environment differences, including possible effects of mask-wearing on communication.ConclusionsThese data suggest that the RGT methodology could help ameliorate concerns regarding online data quality—particularly for studies involving high-risk or rare cohorts—and offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance.

Retrospective Review and Scenario Analysis for qPCR Quality Assurance.

Quantitative polymerase chain reaction (qPCR) is a molecular method used in laboratories for detection and quantification of DNA nucleotides. Standard curves and reference values are usually combined into the PCR amplification process to calculate initial amount of target DNA molecule in a testing sample. This study is a retrospective review to examine the performance of standard curves in a qPCR-based assay for the screening of a genetic disorder in laboratories. Three different scenarios were designed to replay the historical data generated from over 3,000 qPCR assays to evaluate how omission of standard curves would affect the overall screening results. The outcomes of all the scenarios concluded that including standard curves in qPCR assays had decreased the screening specificity and accuracy, resulting in more false positives and additional retests. This was particularly true in case the initial DNA molecules were at relatively low copy numbers. It strongly suggests that the implantation of qPCR assays in diagnostic procedures should be frequently retested and reviewed. More importantly, the strategies of retrospective review and scenario analysis presented here will provide a good framework for assay validation and periodic quality assurance in laboratory.

INTERNATIONAL POLICY AND PRACTICES FOR QUALITY ASSURANCE IN TEACHER EDUCATION THROUGH ACCREDITATION AND LICENSING: A LITERATURE REVIEW

Effectiveness of Education System is dependent upon teacher education. National Education Policy (2009-2015) specifies the Planning Commission’s Vision-2030’ focusing on change of mindset which exhibit commitment to a new set of societal goals.. In Pakistan, there is an immense need to trace teacher education development and reform in terms of the major questions that have driven the field and the sometimes competing ways these questions have been constructed, debated, and enacted in research, policy, and practice. To ensure better quality and productivity, accreditation and licensing for teacher educators in Pakistan is extremely necessary. The impact of teachers’ education on teacher learning, professional practice, and student learning is enormous. The present study is focused on analyzing the existing practices and inputs of accreditation and teacher licensing in Pakistan and worldwide with special reference to USA, Australia and Scotland. Moreover, the document analysis of UNESCO reports and guidelines has been done with critical lenses in order to provide ground for full length research. to inform designing Indigenous Framework for Quality Assurance in Teacher Education drawing upon International Perspectives on Policy and Practice. It will pave the way for introducing teacher licensing regime in Pakistan in order to establish uniform education system in Pakistan

Guidelines on Quality Assurance Framework of the Ministry of Higher Education: A Critical Analysis

Higher education is one of the most significant factors for the development of the nations and its quality assurance has changed into an important matter in higher education management and Afghan higher education is no exception. This Analytical-Descriptive research has been conducted in a “Critical Implementing Manner” based on “structural and tasks guidelines of capacity building programs”. On account of the effective legal and executive measures for quality assurance, there seem to be challenging on the way. The research finds out; legal challenges; lack of binding legal instruments, the existence of institutions with vague and parallel duties, lack of an independent monitoring body from the quality assurance process, lack of hearing complaints created in the process, and executive challenges; the existence of vague and general standards in the checklists, short term turnover of the checklists, a dependent combination of the assessing committees, lack of accurate need evaluating procedure for defining standards and drafting the checklists and finally lack institutionalized quality promoting culture are the reasons disturbing it to reach the targets for the quality assurance of the higher education in the country. Keywords: Afghanistan, Quality Assurance, Legal Challenges, Execution Challenges

Performance evaluation of a multinational data platform for critical care in Asia

Background: The value of medical registries strongly depends on the quality of the data collected. This must be objectively measured before large clinical databases can be promoted for observational research, quality improvement, and clinical trials. We aimed to evaluate the quality of a multinational intensive care unit (ICU) network of registries of critically ill patients established in seven Asian low- and middle-income countries (LMICs). Methods: The Critical Care Asia federated registry platform enables ICUs to collect clinical, outcome and process data for aggregate and unit-level analysis. The evaluation used the standardised criteria of the Directory of Clinical Databases (DoCDat) and a framework for data quality assurance in medical registries. Six reviewers assessed structure, coverage, reliability and validity of the ICU registry data. Case mix and process measures on patient episodes from June to December 2020 were analysed. Results: Data on 20,507 consecutive patient episodes from 97 ICUs in Afghanistan, Bangladesh, India, Malaysia, Nepal, Pakistan and Vietnam were included. The quality level achieved according to the ten prespecified DoCDat criteria was high (average score 3.4 out of 4) as was the structural and organizational performance -- comparable to ICU registries in high-income countries. Identified strengths were types of variables included, reliability of coding, data completeness and validation. Potential improvements included extension of national coverage, optimization of recruitment completeness validation in all centers and the use of interobserver reliability checks. Conclusions: The Critical Care Asia platform evaluates well using standardised frameworks for data quality and equally to registries in resource-rich settings.

Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data

Representativeness and quality of collected meteorological data impact accuracy and precision of climate, hydrological, and biogeochemical analyses and predictions. We developed a comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework, consisting of three major phases: Phase I—Preliminary data exploration, i.e., processing of raw datasets, with the challenging problems of time formatting and combining datasets of different lengths and different time intervals; Phase II—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme data; and Phase III—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The paper includes two use cases based on the time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado), and the Barro Colorado Island (BCI, Panama) meteorological station. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.

On Preserving Scientific Integrity for Climate Model Data in the HPC Era

Over the last 30 years, the Computational Science Graduate Fellowship (CSGF) program has played an integral role in preparing a large and diverse community of computational scientists to push the limits of high-performance computing (HPC). To celebrate the CSGF program’s enduring influence, I share my perspective from the climate modeling community, which has used HPC to better understand the earth’s climate system. While the benefits of HPC in climate science have been enormous, rapid computing advances have brought new challenges. One difficulty is quality assurance—ensuring that large and complex codes running on multiple platforms are correct. A second is mitigating the increasingly large data volumes. Here, I describe our software quality assurance framework and strategies to reduce climate data volumes. In these complementary efforts, our focus has been preserving the scientific integrity of the simulation output data, a priority shared across HPC model simulation disciplines.

The change of disciplinary practices as an effect of peer review in re-accreditation: the case of humanities in Croatia

ABSTRACT The efforts in establishing quality assurance schemes in Croatia have faced a relatively new task of evaluating their effect on multiple levels. The effects of institutional compliance with European and national quality assurance framework and introduction of higher education management approach tools for internal quality assurance are noticeable in the compliance parts of the re-accreditation reports. In contrast, analysis of open parts of re-accreditation reports in humanities has shown unexpected results. The reviewer teams’ recommendations are addressing positive disciplinary practices characteristic of the humanities and suggesting the improvements targeting the modifications of practices related to the cultural-cognitive aspect of academic discipline. Content analysis results outline that reviewers have detected institutional strengths related to teaching which correspond with traditional cultural-cognitive practices in humanities (soft-pure sciences) contrastively, recommendations for improvement are mostly related to research practices, which demonstrate characteristics of hard sciences.

Performance evaluation of a multinational data platform for critical care in Asia.

Background: The value of medical registries strongly depends on the quality of the data collected. This must be objectively measured before large clinical databases can be promoted for observational research, quality improvement, and clinical trials. We aimed to evaluate the quality of a multinational intensive care unit (ICU) network of registries of critically ill patients established in seven Asian low- and middle-income countries (LMICs). Methods: The Critical Care Asia federated registry platform enables ICUs to collect clinical, outcome and process data for aggregate and unit-level analysis. The evaluation used the standardised criteria of the Directory of Clinical Databases (DoCDat) and a framework for data quality assurance in medical registries. Six reviewers assessed structure, coverage, reliability and validity of the ICU registry data. Case mix and process measures on patient episodes from June to December 2020 were analysed. Results: Data on 20,507 consecutive patient episodes from 97 ICUs in Afghanistan, Bangladesh, India, Malaysia, Nepal, Pakistan and Vietnam were included. The quality level achieved according to the ten prespecified DoCDat criteria was high (average score 3.4 out of 4) as was the structural and organizational performance -- comparable to ICU registries in high-income countries. Identified strengths were types of variables included, reliability of coding, data completeness and validation. Potential improvements included extension of national coverage,optimization of recruitment completeness validation in all centers and the use of interobserver reliability checks. Conclusions: The Critical Care Asia platform evaluates well using standardised frameworks for data quality and equally to registries in resource-rich settings.

Comparison of Indian Quality Assurance Model and Accreditation Parameters of Higher Education with International Standards

Abstract: The globalization of higher education has become one of the most significant factors for the academic, social, and political promotion of a country. Quality human resources and knowledge workforce plays a vital role in the emerging environment and digital economy. Assessment and Accreditation (AA) of education ensures the quality of education and make the system more responsive to demand and accountability. This paper explores international quality assurance models and compares the significant quality parameters of higher education with the Indian accreditation system. India's accreditation bodies, National Assessment and Accreditation Council (NAAC) and National Board of Accreditation (NBA) maintain the quality of higher education in India which evaluates the institutional and programme standards respectively. The research mainly adopted generic quality parameters identified by the global accreditation agencies for the survey and feedback from the educational experts in higher education. The paper aims to propose a qualityassurance framework model that matches with global standards. Keywords: Quality Assurance, Higher education, Accreditation, Quality framework

In-situ point cloud fusion for layer-wise monitoring of additive manufacturing

Additive manufacturing (AM) has received an increasing attention in the manufacturing sector, owing to its high-level design freedom and enhanced capability to produce parts with complex geometries. With advances in AM technologies, the role of AM has been shifting from rapid prototyping to viable production-worthy manufacturing of functional parts. However, AM processes are highly inconsistent, and the lack of quality assurance significantly hampers the broader adoption of AM. Most existing techniques for AM online monitoring focus on the detection of conspicuous defects, such as under-fills and cracks. They are limited in their ability to detect layer surface variations induced by miniature process shifts. The objective of this study is to develop a new layer-wise monitoring framework for AM quality assurance based on in-situ point cloud fusion. Specifically, online 3D structured-light scanning is used to capture the surface morphology from each printed layer. The collected point cloud is partitioned, and the morphological patterns in local regions are delineated with a new affinity measure to evaluate the conformity to the reference. A deep cascade model is further introduced to leverage the local affinities for the identification of abnormal patterns on the printed layers. Finally, a statistical control chart is constructed for process monitoring and the identification of miniature shifts. Simulation and real-world case studies using the fused filament fabrication (FFF) process are conducted, and experimental results have demonstrated the effectiveness of the developed framework. It has a great potential to be implemented in diverse AM processes with a wide variety of materials for mission-critical applications.

Strengthening the competencies of policy makers for better use of data in public policy design1

Statistical literacy is one of the main areas of work of the Global Network of Institutions for Statistical Training (GIST) established in 2017. While the scope of statistical literacy initiatives will range greatly from those intended for school children and teachers to those aimed at media representatives or general public, one of the areas where a dedicated Task Team of the GIST set out to undertake a more detailed analysis was related to the core data competencies for policy makers. The adoption of the Sustainable Development Goals by UN member States has led to a growing awareness around the importance of timely, robust, quality and disaggregated data for informing public policies and decisions and providing a solid evidence to address a number of complex policy issues related to ensuring more equitable policy outcomes and more coherence decision-making across different dimensions of sustainable development and different levels of governance from global to national and local. This article presents the results of a survey conducted by the GIST Task Team on Statistical Literacy back in 2018 with the participation of policy makers from various UN Member States, reviews core data competencies for policy makers, presents the free, self-paced e-learning course developed by UN Institute for Training and Research (UNITAR), UN Statistics Division and UN Economic Commission for Africa (UNECA) with support from the Swiss Government and using UNITAR’s Quality Assurance Framework, and discusses the ongoing work of the GIST on the inventory of statistical literacy initiatives as a new product developed by the dedicated Task Team.

Data science training for official statistics: A new scientific paradigm of information and knowledge development in national statistical systems

The ability to incorporate new and Big Data sources and to benefit from emerging technologies such as Web Technologies, Remote Data Collection methods, User Experience Platforms, and Trusted Smart Statistics will become increasingly important in producing and disseminating official statistics. The skills and competencies required to automate, analyse, and optimize such complex systems are often not part of the traditional skill set of most National Statistical Offices. The adoption of these technologies requires new knowledge, methodologies and the upgrading of the quality assurance framework, technology, security, privacy, and legal matters. However, there are methodological challenges and discussions among scholars about the diverse methodical confinement and the wide array of skills and competencies considered relevant for those working with big data at NSOs. This paper develops a Data Science Model for Official Statistics (DSMOS), graphically summarizing the role of data science in statistical business processes. The model combines data science, existing scientific paradigms, and trusted smart statistics, and develops around a restricted number of constructs. We considered a combination of statistical engineering, data engineering, data analysis, software engineering and soft skills such as statistical thinking, statistical literacy and specific knowledge of official statistics and dissemination of official statistics products as key requirements of data science in official statistics. We then analyse and discuss the educational requirements of the proposed model, clarifying their contribution, interactions, and current and future importance in official statistics. The DSMOS was validated through a quantitative method, using a survey addressed to experts working at the European statistical systems. The empirical results show that the core competencies considered relevant for the DSMOS include acquisition and processing capabilities related to Statistics, high-frequency data, spatial data, Big Data, and microdata/nano-data, in addition to problem-solving skills, Spatio-temporal modelling, machine learning, programming with R and SAS software, Data visualisation using novel technologies, Data and statistical literacy, Ethics in Official Statistics, New data methodologies, New data quality tools, standards and frameworks for official statistics. Some disadvantages and vulnerabilities are also addressed in the paper.

Digital documentation of complications in visceral surgery: possibilities and evaluation of an instrument for quality management

Against the background of the growing economization of clinical medicine, in the last decades the topics of risk and complication management have also become more important in surgical disciplines. The standardization and reproducible documentation of outcome and complication data play a key role for valid quality control. In this article a digital system implemented at the surgical clinic of the Charité University Medicine in Berlin is analyzed with respect to its practicability for perioperative and postoperative monitoring of complications within the framework of quality assurance.

Quality Assurance Framework in Technical and Vocational Education and Training: A Comparative Study of Nigeria, Malaysia and UK

This study aims to compare the technical vocational education and training quality assurance framework of Nigeria, Malaysia and the United Kingdom. The study adopted a qualitative method document analysis to elicit information to compare quality assurance frameworks of Nigeria, Malaysia and the United Kingdom in the context of the technical vocational education and training systems. The study revealed current practices of quality assurance frameworks of Nigeria, Malaysia and the United Kingdom. The framework's emphasis on appropriately skilled workforce needed for socio-economic development and sets a benchmark for consistency to promote trust. The study also revealed similarities as a commitment to evidence-based decision making for continuous quality improvement while the difference in quality assurance frameworks of Nigeria and Malaysia is revealed based on the government-led approach and the United Kingdom operates based on a unitary approach. The study also revealed suitable quality assurance framework components as follows: integrated planning, integrated reviewing and management. This study discussed reforms needed of quality assurance framework in technical vocational education and training system and suggested that Nigerian government needed to encourage her technical vocational education and training system for the desired objectives through quality assurance framework.

Developing functional requirements for Temporary Housing by integrating Axiomatic Design with the 5 Gaps Model of Service Quality

Temporary Housing (TH) schemes are a controversial component of post-disaster recovery plans, and yet they offer a fundamental service to the homeless population. Their sustainability should be understood and addressed in terms of service quality for all clients, rather than as a matter of product engineering. Since the evaluation of service quality is different from that of goods, value in TH assistance should be measured according to how well it matches clients’ expectations. This paper adopts the 5 gaps model of service quality as a framework for TH quality assurance and advances that closing the current performance gap requires tackling issues in the briefing, design, project execution and conformance phases, as well as in communication. Against this background, engineering methods such as Axiomatic Design (AD) can effectively be exploited to reduce the gap between what people want and what they get, considering the needs and objectives from humanitarian actors. Results indicate that AD can reveal conflicts and potential for cooperation between the many “clients” of TH, via the joint analysis of their different needs, and the associated Functional Requirements (FRs) and illustrates via a post-factum analysis what mechanisms need to be in place to ensure better preparedness for future disasters.

Considerations for quality assurance of multiplex malaria antigen detection assays with large sample sets

Multiplex assays for malaria antigen detection can gather data from large sample sets, but considerations for the consistency and quality assurance (QA) of mass testing lack evaluation. We present a QA framework for a study occurring November 2019 to March 2020 involving 504 assay plates detecting four Plasmodium antigens: pan-Plasmodium aldolase and lactate dehydrogenase (LDH), histidine-rich protein 2 (HRP2), P. vivax LDH (PvLDH). Controls on each plate included buffer blank, antigen negative blood, and 4-point positive dilution curve. The blank and negative blood provided consistently low signal for all targets except for pAldolase, which showed variability. Positive curve signals decreased throughout the 5-month study duration but retained a coefficient of variation (CV) of < 5%, with the exception of HRP2 in month 5 (CV of 11%). Regression fittings for inter-plate control signals provided mean and standard deviations (SDs), and of 504 assay plates, 6 (1.2%) violated the acceptable deviation limits and were repeated. For the 40,272 human blood samples assayed in this study, of 161,088 potential data points (each sample × 4 antigens), 160,641 (99.7%) successfully passed quality checks. The QA framework presented here can be utilized to ensure quality of laboratory antigen detection for large sample sets.

An integrated framework for online news quality assurance

This paper introduced a synthesized theoretical framework of online news quality assurance. The framework includes conceptual models of quality evaluation, value assessment, and intervention. The framework also provides typologies of user activities, information agents, and the relationships among them. The framework is grounded in prior frameworks of information quality and the analysis of two cases of large-scale online news aggregators: Google News and Facebook News. The framework can be used as a knowledge source to guide the design and evaluation of quality assurance processes of online news providers and aggregator ecosystems.