ADMINISTERING ONLINE EXAMS FROM HESITANTLY TO INNOVATIVELY - A PERSONAL PERSPECTIVE THROUGH AN ACTION RESEARCH

In the midst of COVID-19, university campuses were shut down and faculty had to move their classes online. The abrupt change opened up many challenges. One of them was how to handle online exams. This paper recounted how one instructor had managed the exams online. The paper presents this experience from an action research perspective. At the core is the narrative that captures the exam design process, the tools used, and the proctoring setup. The results are based on the interpretation of the phenomenon through a lens of the unified theory of acceptance and use of technology (UTAUT). The insights reveal some qualitative evidence to support relevant factors in UTAUT

E-Learning as an Emerging Entrepreneurial Enterprise in Universities and Firms

With the inflow of an estimated $6 billion of venture capital over the past five years, E-learning is driven not only by many startup dot-com entrepreneurs but also big corporations, for-profit spin-off ventures, and big and small universities. All vie for a piece of a promising marketplace. Many universities entered the E-learning marketplace using non-profit models, leveraging their knowledge in the traditional classroom to the E-learning environment. Countless entrants and overwhelming numbers of services and products, coupled with market chaos, created confusion that makes it difficult to assess the E-learning industry. This paper identifies and presents four emerging models of E-learning in terms of enterprises, target market, relative advantages and challenges. We introduce a spatial visualization to differentiate among various E-learning models based on their educational orientations and resources. A comparison of the costs associated with E-learning from the perspectives of producers, consumers, and faculty is then presented. We conclude by discussing the lessons that can be learned from this industry\u27s evolution.

Strategy For Academic-Community Collaboration: Enabled And Supported By The Development Of An Open-Source Web Service

To cope with the challenges of economic turbulence in many small communities in U.S. and other parts of the world, this paper aims to propose an academic-community collaboration strategy to improve education, enhance workforce development, foster social community development, and facilitate economic development in a community. Based on the Design Science framework, the proposed academic-community collaboration strategy is presented based on the Asset-Based Community Development (ABCD) approach and value-chain analysis, and supported by our proposed open-source IT infrastructure, including a showcase of web service called Community Development Collaboration Service (CDCS). This web service functions as a central portal that identifies available services and resources, disseminate areas of needs, and then match the resources and the needs appropriately and efficiently within a community, with the support and promotion from local universities that the community can trust. Our preliminary survey findings suggest that most of the potential users find the overall content quality and perceived usefulness of the CDCS good or excellent. Implications, limitations and future improvement of the CDCS are presented in the paper

Evaluating Key Factors in Supplier Selection for Micro-Businesses: Implications for Buyer Satisfaction

Final quality of products/services starts with suppliers in the supply chain. Problems can occur if suppliers do not deliver the quantities requested in full, on time, or buyers select suppliers solely on the basis of lowest price. Supplier selection has been studied for large businesses but not for very small (micro) businesses. Therefore, a survey was administered to micro-businesses to determine: what factors are important to micro-businesses in selecting suppliers and how satisfied they are with their suppliers. Factors included Brand Name, Consistency, Cost/Lower Price, Loyalty, Quality, and Warranty. Results indicated that none of the factors were unimportant. However, buyer satisfaction was found to be dependent on Quality, Brand Name, and the Length of Time of the Buyer/Supplier Relationship. Additionally, it was concluded that quality, along with complete, on-time delivery are key to buyer satisfaction and may help suppliers achieve preferred status with micro-business buyers

The Contribution of Commitment Value in Internet Commerce: An Empirical Investigation

Exploring what makes Internet customers satisfied is perhaps one of the most important challenges facing customer relationship managers in this decade. It is important because prior studies suggest that happy customers make repeat purchases and develop brand loyalty. However, there is not enough accumulated knowledge to understand specifically the determinants of customer satisfaction in Internet commerce. To more accurately understand the determinants that may enhance a customer\u27s satisfaction with their Internet shopping experience, this study looks at the customer\u27s commitment value and examines its relationships with the customer\u27s satisfaction. Commitment value is defined as a total value perception from a buyer and is composed of three components: sociopsychological, economic, and product values. The results from this study show that the sociopsychological value (i.e., shopping enjoyment and convenience in purchasing) and the product value (i.e., product quality) contribute significantly to the attainment of customer satisfaction. The economic value (i.e., reduction of time spent in Internet shopping), however, has no significant positive impact on customer satisfaction. Explanations are presented along with the implications

HierarchyNet : learning to summarize source code with heterogeneous representations

Code representation is important to machine learning models in the code-related applications. Existing code summarization approaches primarily leverage Abstract Syntax Trees (ASTs) and sequential information from source code to generate code summaries while often overlooking the critical consideration of the interplay of dependencies among code elements and code hierarchy. However, effective summarization necessitates a holistic analysis of code snippets from three distinct aspects: lexical, syntactic, and semantic information. In this paper, we propose a novel code summarization approach utilizing Heterogeneous Code Representations (HCRs) and our specially designed HierarchyNet. HCRs adeptly capture essential code features at lexical, syntactic, and semantic levels within a hierarchical structure. HierarchyNet processes each layer of the HCR separately, employing a Heterogeneous Graph Transformer, a Tree-based CNN, and a Transformer Encoder. In addition, HierarchyNet demonstrates superior performance compared to fine-tuned pre-trained models, including CodeT5, and CodeBERT, as well as large language models that employ zero/few-shot settings, such as CodeLlama, StarCoder, and CodeGen. Implementation details can be found at https://github.com/FSoft-AI4Code/HierarchyNet

Gravitational Waves From Known Pulsars: Results From The Initial Detector Era

We present the results of searches for gravitational waves from a large selection of pulsars using data from the most recent science runs (S6, VSR2 and VSR4) of the initial generation of interferometric gravitational wave detectors LIGO (Laser Interferometric Gravitational-wave Observatory) and Virgo. We do not see evidence for gravitational wave emission from any of the targeted sources but produce upper limits on the emission amplitude. We highlight the results from seven young pulsars with large spin-down luminosities. We reach within a factor of five of the canonical spin-down limit for all seven of these, whilst for the Crab and Vela pulsars we further surpass their spin-down limits. We present new or updated limits for 172 other pulsars (including both young and millisecond pulsars). Now that the detectors are undergoing major upgrades, and, for completeness, we bring together all of the most up-to-date results from all pulsars searched for during the operations of the first-generation LIGO, Virgo and GEO600 detectors. This gives a total of 195 pulsars including the most recent results described in this paper.United States National Science FoundationScience and Technology Facilities Council of the United KingdomMax-Planck-SocietyState of Niedersachsen/GermanyAustralian Research CouncilInternational Science Linkages program of the Commonwealth of AustraliaCouncil of Scientific and Industrial Research of IndiaIstituto Nazionale di Fisica Nucleare of ItalySpanish Ministerio de Economia y CompetitividadConselleria d'Economia Hisenda i Innovacio of the Govern de les Illes BalearsNetherlands Organisation for Scientific ResearchPolish Ministry of Science and Higher EducationFOCUS Programme of Foundation for Polish ScienceRoyal SocietyScottish Funding CouncilScottish Universities Physics AllianceNational Aeronautics and Space AdministrationOTKA of HungaryLyon Institute of Origins (LIO)National Research Foundation of KoreaIndustry CanadaProvince of Ontario through the Ministry of Economic Development and InnovationNational Science and Engineering Research Council CanadaCarnegie TrustLeverhulme TrustDavid and Lucile Packard FoundationResearch CorporationAlfred P. Sloan FoundationAstronom

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator