Facilitating Online Learning via Zoom Breakout Room Technology : A Case of Pair Programming Involving Students with Learning Disabilities

2021 | Communications of the Association for Information Systems | Citations: 0

Authors: Li, Ling; Xu, Li Da; He, Yuming; He, Wu; Pribesh, Shana; Watson, Silvana; Major, Debra

Abstract: The coronavirus disease of 2019 (COVID-19) pandemic has required many educators ... Expand

Abstract: The coronavirus disease of 2019 (COVID-19) pandemic has required many educators to redesign how they deliver their courses. In this study, we develop innovative procedures and pedagogy to teach pair programming via Zoom breakout rooms in a cloud environment. We report six fundamental innovative teaching mechanisms and procedures: 1) strategically planning a course, 2) effectively managing teaching resources, 3) enhancing faculty responsiveness, 4) selecting reliable technology, 5) mandating online educator's training, and 6) accommodating students with learning disabilities. From teaching pair programming via Zoom breakout rooms, we have gained valuable experience in promoting collaborative, engaging, active, and problem-based learning activities in a cloud environment. Our results enrich our knowledge of delivering online education and contribute to pair programming literature in general.Ling Li is the Chair of the Department of Information Technology and Decision Sciences at Old Dominion University, USA. She is eminent scholar and university professor. She has published over 140 peerrefereed research papers in high-quality journals. Her research is motivated by theoretical and practical explanations of how organizations can best deploy their technology and supply chain strategies for competitive advantage. She serves as area editor, associate editor and editorial board member of several journals. systems. She examines systems of inequality for students at-risk; namely those who live in poverty, make residential moves, have disabilities, attend schools with fewer resources, take developmental education courses and live in less traditional family structures. Recently she has been engaged in research that spans multiple countries to determine if patterns stemming from systems of inequality are similar in varying contexts.Silvana M. R. Watson is a professor of special education at Old Dominion University. Her research interests focus on 1) promoting evidence-based practices for students with learning disabilities, attention deficit hyperactivity disorders, and English learners with and without disabilities; 2) teacher preparation; and 3) examining the nature of students' learning difficulties. Her has disseminated her work through presentations at international, national, and state professional conferences, peer-reviewed publications, book chapters, other academic publications, and consultations with educational agencies. She is one of the co-PIs of the National Science Foundation's grant awarded to Old Dominion to support the investigation of pair programming as a teaching method to support undergraduate students with learning disabilities taking instructional technology courses. She has been awarded a large grant from the U.S. Department of Education, Office of English Language Acquisition, to assess and instruct English learners with and without disabilities. Debra A. Major is a professor and eminent scholar in the College of Sciences at Old Dominion University, USA. Her professional specialty is industrial/organizational psychology. Her research focuses on barriers encountered by women and ethnic minorities pursuing educational and career pathways in STEM. She is especially interested in improving persistence and recently developed and validated instruments for assessing students' embeddedness in STEM majors and the broader university. Collapse

Topics: pair programming video conference cloud computing online learning system Visual Basic

Methods: design methodology survey

Multivariate data quality assessment based on rotated factor scores and confidence ellipsoids

2020 | Decision Support Systems | Citations: 0

Authors: Almeida, Fabrício Alves de; Leite, Rodrigo Reis; Gomes, Guilherme Ferreira; Gomes, José Henrique de Freitas; Paiva, Anderson Paulo de

Abstract: This study explores the nature of the correlation in data to estimate the data q ... Expand

Abstract: This study explores the nature of the correlation in data to estimate the data quality to be used in decision-making processes. The main contribution of this research is the introduction of a new multivariate method based on rotated factor scores by varimax strategy for the repeatability and reproducibility study to effectively identify possible data of poor quality leading to measurement errors. In addition, a new confidence ellipsoid-based decision support method is developed. The efficiency of the proposed method was demonstrated using the metallographic measurements of the geometric characteristics of the resistance spot welding process. To prove the efficiency of the proposed method, it was compared with other consolidated techniques such as the analysis of variance, weighted principal components method, and factor analysis without rotation. Thus, we verified that the proposed method performed better interpretation of the latent information, minimizing the dimensionality of the data, and separating the quality attributes analyzed by clusters. One response group was classified as acceptable, and the other as marginal. These results were verified by the confidence ellipsoids, in which the proposed method obeyed the Bonferroni bilateral limits, outlining the factors which demonstrated superior discriminatory power with non-overlapping ellipsoids avoiding the confounding and favoring the better data quality analysis for multicriteria decision-making. When compared with the other approaches, the proposed method demonstrated more reliable and robust results without such deficiencies as inversion of the groupings, neglection of the variance-covariance structure, and the variability attributed to the data within the measurement system. Collapse

Topics: data quality decision making decision support Visual Basic

Methods: parametric test ANOVA data transformation descriptive statistic trade-off analysis method

A Bibliometric Analysis of the HICSS Software Technology Track

2020 | HICSS | Citations: 0

Authors: Grønli, Tor-Morten; Majchrzak, Tim A; Kaindl, Hermann; Wien, TU

Abstract: The HICSS Software Technology track has a long tradition and many papers have be ... Expand

Abstract: The HICSS Software Technology track has a long tradition and many papers have been published as part of its history. Its impact in terms of citations, paper contributions, author share and community impact does not yet seem to have been investigated, though. In particular, software technology has evolved, and as it stands, it is of primary importance for mobile computing, the Internet-of-Things and Cyber-physical Systems. Hence, the development of these topics and the related impact of this track are of particular interest. In this paper, we present a bibliographic analysis as a first step towards such an investigation. We found that the history of the track is indeed noteworthy. Our results include finding a few extremely much cited papers, some curious tendencies, and a generally favourable outlook for HICSS. We found that indeed many papers in the history of this HICSS track addressed mobile technology and are highly cited. Together with providing insight into track, paper and author impact, we also raise questions worth of further investigation to understand the role of the HICSS Software Technology track and its impact on the academic field and society. Collapse

Topics: mobile system internet of things systems development spreadsheet Visual Basic

Methods: bibliometric analysis descriptive statistic co-citation analysis literature study

Scheduling Flexible Demand in Cloud Computing Spot Markets

2020 | Business & Information Systems Engineering | Citations: 0

Authors: Keller, Robert; Häfner, Lukas; Sachs, Thomas; Fridgen, Gilbert

Abstract: The rapid standardization and specialization of cloud computing services have le ... Expand

Abstract: The rapid standardization and specialization of cloud computing services have led to the development of cloud spot markets on which cloud service providers and customers can trade in near real-time. Frequent changes in demand and supply give rise to spot prices that vary throughout the day. Cloud customers often have temporal flexibility to execute their jobs before a specific deadline. In this paper, the authors apply real options analysis (ROA), which is an established valuation method designed to capture the flexibility of action under uncertainty. They adapt and compare multiple discrete-time approaches that enable cloud customers to quantify and exploit the monetary value of their short-term temporal flexibility. The paper contributes to the field by guaranteeing cloud job execution of variable-time requests in a single cloud spot market, whereas existing multi-market strategies may not fulfill requests when outbid. In a broad simulation of scenarios for the use of Amazon EC2 spot instances, the developed approaches exploit the existing savings potential up to 40 percent – a considerable extent. Moreover, the results demonstrate that ROA, which explicitly considers time-of-day-specific spot price patterns, outperforms traditional option pricing models and expectation optimization. Collapse

Topics: cloud computing price management real option decision support cloud computing provider

Methods: simulation stochastic model literature study two sample t-test with equal variance parametric test

Name it as you like it? Keeping pace with social media something

2018 | Electronic Markets | Citations: 1

Authors: Bühler, Julian; Bick, Markus

Abstract: Social media has emerged over the last decade and consequently has accompanying ... Expand

Abstract: Social media has emerged over the last decade and consequently has accompanying information systems (IS) research. In this paper, however, we argue that researchers cannot keep pace with the rapid changes this topic engenders. This claim is substantiated by a database built from 28,283 articles published in either top IS journals, i.e., ELMA, BISE, and all AIS basket journals, or IS conference proceedings, i.e., ICIS, ECIS, AMCIS, WI, HICSS, and PACIS. We derive a set of 13 keywords that have been used to describe what we call the ‘social media phenomenon’. The results are transformed into a four-phase model and a taxonomical categorization, which provides an exhaustive overview of social media terms and trends and reflects the main research issue facing academia: The fact that the versatile social media phenomenon in its current phase is dominated by just two terms—“social media” and “social network”—or imprecise “such-as-Facebook” analogies. Collapse

Topics: social media database system social network virtual world website

Methods: meta analysis literature sample computational algorithm synthesis design science

Business Value of the Internet of Things – A Project Portfolio Selection Approach

2018 | European Conference On Information Systems | Citations: 0

Authors: Fähnle, Annika; Püschel, Louis; Roeglinger, Maximilian; Stohr, Alexander

Abstract: The Internet of Things (IoT) counts among the most disruptive digital technolog ... Expand

Abstract: The Internet of Things (IoT) counts among the most disruptive digital technologies on the market. Despite the IoT's emerging nature, there is an increasing body of knowledge related to technological and business topics. Nevertheless, there is a lack of prescriptive knowledge that provides organizations with guidance on the economic valuation of investments in the IoT perspective. Such knowledge, however, is crucial for pursuing the organizational goal of long-term value maximization. Against this backdrop, we develop an economic decision model that helps organizations determine an optimal IoT project portfolio from a manufacturer's perspective and complies with the principles of project portfolio selection and value-based management. For our purposes, IoT project portfolios are compilations of projects that aim to implement IoT technology in an organization's production process, products, or infrastructure. Our decision model schedules IoT projects for multiple planning periods and considers monetary as well as monetized project effects. On this foundation, it determines the project sequence with the highest value contribution. To evaluate our decision model, we discussed its real-world fidelity and understandability with an industry expert renowned for its proficiency in IoT technology, implemented a software prototype, and demonstrated its applicability based on real-world data. Keywords: Internet of Things, economic valuation of IoT, value-based management, project portfolio management. Collapse

Topics: mobile system internet of things smart device organizational value Visual Basic

Methods: design artifact qualitative interview design science

Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods

2018 | Information Systems Journal | Citations: 0

Authors: Kock, Ned; Hadaya, Pierre

Abstract: Partial least squares-based structural equation modelling (PLS-SEM) is extensive ... Expand

Abstract: Partial least squares-based structural equation modelling (PLS-SEM) is extensively used in the field of information systems, as well as in many other fields where multivariate statistical methods are used. One of the most fundamental issues in PLS-SEM is that of minimum sample size estimation. The ‘10-times rule’ has been a favourite because of its simplicity of application, even though it tends to yield imprecise estimates. We propose two related methods, based on mathematical equations, as alternatives for minimum sample size estimation in PLS-SEM: the inverse square root method, and the gamma-exponential method. Based on three Monte Carlo experiments, we demonstrate that both methods are fairly accurate. The inverse square root method is particularly attractive in terms of its simplicity of application. © 2016 John Wiley & Sons Ltd Collapse

Topics: spreadsheet Visual Basic computer software accounting IT project

Methods: Monte Carlo simulation partial least squares path modeling partial least squares regression computational algorithm experiment

A decision support system for integrated container handling in a transshipment hub

2018 | Decision Support Systems | Citations: 4

Authors: Legato, Pasquale; Mazza, Rina Mary

Abstract: The productivity of a maritime container terminal can be improved through a mode ... Expand

Abstract: The productivity of a maritime container terminal can be improved through a model-driven decision support system (DSS) focused on a better integration among container handling operations occurring across the quay, transfer and yard areas. Integration is pursued to minimize the blocking, locking and other queuing phenomena which are unavoidable, especially when human-operated equipment is shared in a real environment subjected to several random events and activities. An integrated queuing network is proposed in this paper as the natural modeling paradigm for a DSS aimed to highlight and quantify the blocking, locking and other queuing phenomena experienced in real practice. After an in-depth discussion of the limitations of solving the queuing network model analytically, discrete-event simulation is adopted as solution method. Numerical examples referred to a case study for a real transshipment hub return reliable estimates for the above queuing phenomena. They illustrate how the queuing-based DSS may effectively support the operations manager in determining the proper operational policies and equipment management with respect to a proficient integration of container handling operations. Collapse

Topics: decision support system productivity Visual Basic Microsoft Windows

Methods: simulation experiment case study discrete event simulation goodness of fit statistical test

Short-term and Long-term Effects of Fear Appeals in Improving Compliance with Password Guidelines

2018 | Communications of the Association for Information Systems | Citations: 0

Authors: Mwagwabi, Florence; McGill, Tanya; Dixon, Mike

Abstract: Passwords are the most widely used method of authentication on the Internet, but ... Expand

Abstract: Passwords are the most widely used method of authentication on the Internet, but users find compliance with password guidelines difficult, and we know little about the long-term effects of attempts to improve compliance. In this paper, we extend the work of fear appeals use in the IS security domain to investigate their longer-term effects. We conducted a longitudinal experimental study to examine fear appeals’ long- and short-term effects. Using a model based on protection motivation theory (Rogers, 1983), we found that fear of threat, perceived password effectiveness, and password self-efficacy predicted compliance. We also found that neither perceived vulnerability to a security attack nor perceived severity of an attack influenced compliance. Providing persuasive communication improved compliance with password guidelines and resulted in significantly stronger passwords, but the effects on compliance intentions were only short term. This study extends our understanding of the factors that influence compliance with password guidelines and how we can modify them to improve compliance. We raise interesting questions about the role of fear in different IS security contexts. We also highlight the need for more research on the long-term impact of persuasive communication. Collapse

Topics: password IT security self efficacy behavioral intention IT security defense

Methods: experimental group survey parametric test ANOVA longitudinal research

Theories: protection motivation theory health belief model theory of reasoned action behavioral theory

Failure pattern-based ensembles applied to bankruptcy forecasting

2018 | Decision Support Systems | Citations: 0

Authors: du Jardin, Philippe

Abstract: Bankruptcy prediction models that rely on ensemble techniques have been studied ... Expand

Abstract: Bankruptcy prediction models that rely on ensemble techniques have been studied in depth over the last 20 years. Within most studies that have been performed on this topic, it appears that any ensemble-based model often achieves better results than those estimated with a single model designed using the base classifier of the ensemble, but it is not uncommon that the results of the former model do not outperform those of a single model when estimated with any other classifier. Indeed, an ensemble of decision trees is almost always more accurate than a single tree but not necessarily more than a neural network or a support vector machine. We know that the accuracy of an ensemble used to forecast firm bankruptcy is closely related to its ability to capture the variety of bankruptcy situations. But the fact that it may not be more efficient than a single model suggests that current techniques used to handle such a variety are not completely satisfactory. This is why we have looked for a method that makes it possible to better embody this diversity than current ones do. The technique proposed in this article relies on the quantification, using Kohonen maps, of temporal patterns that characterized the financial health of a set of companies, and on the use of an ensemble of incremental size maps to make forecasts. The results show that such models lead to better predictions than those that can be achieved with traditional methods. Collapse

Topics: database system Visual Basic

Methods: artificial neural network conceptual modelling discriminant analysis logistic regression support vector machine