Bringing Light into the Dark - Improving Students’ Black-Box Testing Competencies using Game-Design Elements

2023 | International Conference on Information Systems | Citations: 0

Authors: Jokisch, Christine; Hobert, Sebastian; Schumann, Matthias

Abstract: As software becomes increasingly complex, there is a growing need to enhance qu ... Expand

Abstract: As software becomes increasingly complex, there is a growing need to enhance quality assurance in software engineering. However, the lack of qualified human resources is a barrier to performing software testing activities in software companies. At the same time, software testing can be considered a tedious task and is often not done at the necessary level of detail, e.g., designing test cases. However, it is crucial for novice programmers and testers to acquire and improve their testing competencies, and to utilize testing techniques, e.g., black-box testing. Teaching software testing is often based on theoretical instructions, resulting in limited practical experience. As a result, students may not develop the necessary testing mindset, highlighting the need for more extensive software testing education. To address this issue, this paper utilizes a design science research approach to implement a gamified learning system that promotes black-box testing competencies with empirical insights from a field test. Collapse

Topics: online learning system usability perceived usefulness gamification web application

Methods: design artifact testing descriptive statistic correlation analysis design science survey

Theories: self determination theory cognitive load theory

INCREASING STUDENTS’ ENGAGEMENT: DESIGNING A GAMIFIED PEER FEEDBACK SYSTEM

2023 | European Conference On Information Systems | Citations: 0

Authors: Jokisch, Christine; Hobert, Sebastian; Schumann, Matthias

Abstract: Formative feedback is considered as one of the most effective interventions for ... Expand

Abstract: Formative feedback is considered as one of the most effective interventions for promoting students' development in learning processes. Nevertheless, providing formative feedback on assignments is time and resource-constrained, especially in large-scale lectures at universities. To address this issue, we developed a peer feedback system for exercises to support students' learning process at universities. The approach enables students to provide feedback to each other similarly to scientific peer review approaches, allowing students to become more reflective and acquire metacognitive skills while reducing lecturers' workload. However, the lack of motivation is a challenge in peer feedback approaches, as students perceive the process as additional effort. We use gamification to influence the emotional and cognitive state of students positively. Following a design science research approach, we developed and evaluated a web-based gamified peer feedback system after two build-evaluate cycles where game-design elements are used to promote students' learning process and engagement. Collapse

Topics: digital dashboard gamification perceived usefulness user interface usability

Methods: survey descriptive statistic design science correlation analysis design principle

Theories: self determination theory

Bridging the Gap: An Interview Study on Challenges in Software Testing and Educational Needs

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Jokisch, Christine; Schumann, Matthias

Abstract: As information systems become increasingly complex, software testing is being r ... Expand

Abstract: As information systems become increasingly complex, software testing is being recognized as a key element in this process. However, organizations continue to encounter challenges in effectively implementing and executing testing procedures, highlighting the persisting difficulty arising from a lack of knowledge and awareness. Thus, it is crucial to understand the challenges related to software testing to point out educational needs in software testing. To gain a comprehensive understanding of the current challenges related to software testing, this study conducted an empirical cross-sectional interview study with 23 experts. Additionally, a literature review was conducted to investigate if there are any discrepancies or similarities between the current challenges identified in academic research and industry, emphasizing relevant educational needs in software testing. The software testing life cycle was utilized as a framework to systematically present the results. Overall, this study provides insights into the challenges of software testing and current educational needs. Collapse

Topics: system quality software developer database system

Methods: qualitative interview literature study cross sectional research literature sample qualitative content analysis

Illuminating Smart City Solutions – A Taxonomy and Clusters

2023 | International Conference on Information Systems | Citations: 0

Authors: Jonas, Claudius; Schmitt, Kevin; Oberländer, Anna Maria; Ebel, Philipp

Abstract: With urban problems intensifying, Smart City solutions are recognized by resear ... Expand

Abstract: With urban problems intensifying, Smart City solutions are recognized by researchers and practitioners as one of the most promising solutions to make urban areas economically, environmentally, and socially sustainable. While many elements of Smart City solutions have been explored, existing works either treat Smart City solutions as technical black boxes or focus exclusively on Smart City solutions' technical or nontechnical characteristics. Therefore, to conceptualize the unique characteristics of Smart City solutions currently available, we developed a multi-layer taxonomy based on Smart City solution literature and a sample of 106 Smart City solutions. Moreover, we identified three clusters, each covering a typical combination of characteristics of Smart City solutions. We evaluated our findings by applying the Q-sort method. The results contribute to the descriptive knowledge of Smart City solutions as a first step for a theory for analyzing and enable researchers and practitioners to understand Smart City solutions more holistically. Collapse

Topics: smart city internet of things mobile system mobile application analytical information system

Methods: survey computational algorithm cluster analysis design process design methodology

Managing Misinformation within the Public Sector: Cases from the Global South

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Jonathan, Gideon Mekonnen; Watat, Josue Kuika

Abstract: The advances in digital technologies and improved digital literacy have provide ... Expand

Abstract: The advances in digital technologies and improved digital literacy have provided myriads of opportunities for societies. Particularly in the public sphere, improved digitalisation has meant better access to information for citizens, among others. Digital technologies, such as social media, have been proven invaluable in events such as a public health crisis such as COVID-19. However, the adoption of these technologies has also brought challenges related to misinformation, where publicly available information is manipulated and disseminated for purposes that are against the public interest. This paper presents an ongoing empirical study that attempts to explore the measures taken by the public sector to manage misinformation. The study, conducted in two developing countries, explores the immediate and long-term approaches to tackling misinformation. The implication of the expected results for research and practice are also presented. Collapse

Topics: misinformation pandemic social media digital platform digital transformation

Methods: literature study qualitative interview survey survey design partial least squares path modeling

Guest editorial digital platforms and transformational entrepreneurship

2023 | International Journal of Information Management | Citations: 0

Authors: Jones, Paul; Troise, Ciro; Schiuma, Giovanni

Abstract: This article provides a summary of the manuscripts included within the special i ... Expand

Abstract: This article provides a summary of the manuscripts included within the special issue entitled Digital platforms and transformational entrepreneurship. The concept of transformational entrepreneurship has emerged recently as a phenomenon to implement effective and efficient entrepreneurial behaviours. Currently, digital platforms offer opportunities for entrepreneurs and their ventures, to enable transformation entrepreneurship. Recent global crisis such as Covid-19 have accelerated this trend. This special issue explores this phenomenon and offers insights into best practice to enable effective digital transformational entrepreneurship. Collapse

Topics: digital platform entrepreneurship electronic commerce innovation management pandemic

Methods: personal interview

Theories: theory of affordance

Getting Your RPA Priorities Straight with Process Mining: The PLOST Framework

2023 | European Conference On Information Systems | Citations: 0

Authors: Jongeling, Hilde; Lu, Xixi; Beerepoot, Iris; Weerd, Inge van de; Reijers, Hajo

Abstract: Robotic Process Automation (RPA) has gained much attention both in industry and ... Expand

Abstract: Robotic Process Automation (RPA) has gained much attention both in industry and academia. One of the main challenges for a successful implementation of RPA is selecting which tasks should be automated. While different methods exist to identify RPA candidate tasks, they lack in providing objective evidence on why to automate that task. Such objective evidence can be gathered by applying process mining techniques to gain insights into the performance of a process and its tasks. Although this has multiple advantages, it can be time-consuming to analyze all potential processes. We conducted a literature review of existing methods to identify relevant criteria and method components, based on which we designed a framework for identifying and prioritizing suitable RPA candidate tasks: the Prioritized List of Suitable Tasks (PLOST) Framework. The framework includes both qualitative and quantitative assessment criteria and guides the analyst to focus on relevant processes before zooming in on the task level. It also takes into account a customized automation strategy. We conducted a case study to evaluate the applicability and effectiveness of the PLOST Framework and performed thinking-aloud sessions to evaluate its usability, practicality, and completeness. The results show that the framework is easy to apply and feasible. Collapse

Topics: process mining business intelligence organizational value usability digital dashboard

Methods: case study cognitive walkthrough qualitative interview design science literature study

Derivative Work in Open-license Platforms

2023 | International Conference on Information Systems | Citations: 0

Authors: Joo, Heejin; Maruping, Likoebe

Abstract: The emergence of derivative works in open-license platforms has sparked inquiri ... Expand

Abstract: The emergence of derivative works in open-license platforms has sparked inquiries regarding their impact on original works and the platform as a whole. While it is widely recognized that derivative works may compete with the original content, there are also arguments that they can augment traffic and engagement. This remains an open empirical question. We extend the conceptualization of derivative works to open-license platform environments and then explore the implications of such works. Our empirical analysis of original music videos and corresponding reaction videos on YouTube shows that derivative works are complementary to original works and to the platform ecosystem. The findings shed new light on both the complex impact of derivative videos in open-license environments -as well as its broader strategic significance for platform operators seeking sustainable long-term growth opportunities. Collapse

Topics: digital ecosystem YouTube application programming interface intellectual property business model

Methods: Granger causality longitudinal research theory development field study vector autoregression

Corporate Hierarchy and Organizational Learning: Member Turnover, Code Change, and Innovation in the Multiunit Firm

2023 | Organization Science | Citations: 0

Authors: Joseph, John; Rhee, Luke; Wilson, Alex James

Abstract: This study examines how recombinant innovation is affected by member turnover an ... Expand

Abstract: This study examines how recombinant innovation is affected by member turnover and organizational learning within a corporate hierarchy. Prior work has overlooked the role of organizational structure in organizational learning, focusing instead on the knowledge provided by individual new hires or on the disruption caused by individual departures. We address this gap by applying March’s [March JG (1991) Exploration and exploitation in organizational learning. Organ. Sci. 2(1):71–87.] mutual learning model to a corporate hierarchy. In doing so, we theorize how the contributions of corporate staff to socializing new employees and to learning from the organizational code may differ from those of the organization’s subunit members. Empirically, we examine the learning effects of aggregate corporate and subunit arrivals and departures on novel recombinant innovation by subunits. Using 24 years of Motorola company directories, we construct membership turnover measures for corporate and subunit employees and exploit patent data to capture recombinant innovation. Our results suggest that, whereas the influx of new ideas through arrivals may be critical, breaking the pattern of inertial behavior through departures is more important for recombinant innovation. Corporate departures matter most for recombinant innovation, a result that reflects not only corporate staff’s slower individual learning from the organizational code but also its ability to update that code more quickly. In supplementary analyses, we find different effects for technical and nontechnical staff and internal and external arrivals, as well as demonstrate the mutual learning mechanism using internal corporate documents to capture code change. Our study has strong implications for theories of organizational learning, strategic human capital, organization design, and innovation. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2022.1618. Collapse

Topics: innovation management organization learning IT personell turnover global navigation satellite system communication service infrastructure

Methods: theory development statistical hypothesis test regression analysis method post-hoc analysis longitudinal research

LiMS-Net: A Lightweight Multi-Scale CNN for COVID-19 Detection from Chest CT Scans

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Joshi, Amogh Manoj; Nayak, Deepak Ranjan; Das, Dibyasundar; Zhang, Yudong

Abstract: Recent years have witnessed a rise in employing deep learning methods, especiall ... Expand

Abstract: Recent years have witnessed a rise in employing deep learning methods, especially convolutional neural networks (CNNs) for detection of COVID-19 cases using chest CT scans. Most of the state-of-the-art models demand a huge amount of parameters which often suffer from overfitting in the presence of limited training samples such as chest CT data and thereby, reducing the detection performance. To handle these issues, in this paper, a lightweight multi-scale CNN called LiMS-Net is proposed. The LiMS-Net contains two feature learning blocks where, in each block, filters of different sizes are applied in parallel to derive multi-scale features from the suspicious regions and an additional filter is subsequently employed to capture discriminant features. The model has only 2.53M parameters and therefore, requires low computational cost and memory space when compared to pretrained CNN architectures. Comprehensive experiments are carried out using a publicly available COVID-19 CT dataset and the results demonstrate that the proposed model achieves higher performance than many pretrained CNN models and state-of-the-art methods even in the presence of limited CT data. Our model achieves an accuracy of 92.11% and an F1-score of 92.59% for detection of COVID-19 from CT scans. Further, the results on a relatively larger CT dataset indicate the effectiveness of the proposed model. Collapse

Topics: covid 19

Methods: computed tomography ImageNet ablation analysis experiment machine learning