Know the Knowledge of Your Students: A Flexible Analytics Tool for Student Exercises

2023 | DESRIST | Citations: 0

Authors: Aguirre Reid, Sören; Kammer, Frank; Schüller, Daria; Siepermann, Markus; Wölfer, Jonas

Abstract: Intelligent tutoring systems (ITS) have the power to influence lecturers’ practi ... Expand

Abstract: Intelligent tutoring systems (ITS) have the power to influence lecturers’ practices in the classroom and to improve students’ learning. Many ITS provide standardized analytical methods to evaluate classroom performance or the results of the exercises. But they lack more sophisticated, flexible and individual analyses. This paper presents an e-learning Analytics Tool (EAT) for an ITS that provides a dashboard with key figures and a flexible analytics board (FAB). This enables lecturers to analyze students’ performance in detail and identify misconceptions. For instance, the FAB allows us to classify student solutions, reveal conceptual errors in exercises, and analyze each part of an exercise. By this, common mistakes can be identified, and tailored feedback can be given to the students. Following the design science approach, the platform is designed in a general way so that it can be used for different types of exercises (e.g., Math, Excel, SQL). To assess the artifact, we conducted group interviews with German University lecturers from various courses. The results show that lecturers require a good overview of the submitted student solutions to provide timely feedback. They also appreciate the flexible analytics tool for detailed analyses of student solutions to understand student mistakes better. The employed architecture allows general analyses of exercises and the content of students’ solutions. In addition, the EAT is not bound to a specific kind of exercise, but can cope with different kinds like SQL and Excel. Collapse

Topics: digital dashboard structured query language database system online learning system perceived usefulness

Methods: group interview design science design artifact survey qualitative interview

Digital Transformation of Public Sector Manual Procurement and Socioeconomic Development: A Developing Country Case Study

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Agbeko, Michael; Effah, John; Boateng, Richard

Abstract: Digital transformation in the public sector offers opportunities for developing ... Expand

Abstract: Digital transformation in the public sector offers opportunities for developing countries to address socioeconomic development challenges related to citizen wellbeing. While countries in the developed world digitally transform their public sector procurement for socioeconomic development, many in the developing world are yet to do so. Existing information systems research on digital procurement in developing countries has focused more on adoption, strategy, and design. Little is known about how manual procurement practices are digitally transformed in the public sector of developing countries for socioeconomic development. This study employs interpretive case study as a methodology and activity theory as analytical lens to investigate how manual procurement activities in the public sector get digitally transformed and its effect on socioeconomic development in a developing country context. The findings have implications for research, practice, and policy.The developed procurement platform (GHANEPS) has two parts. These modules allow the performance of various procurement activities on the system. The PDW on the other hand is the database that stores information on all procurement activities and is supposed to be connected to external ERP systems, other data repositories, and business intelligence systems. The project manager observed in one of the training sessions that Our inability to successfully train and bring on board all public sector institutions is as a result of the COVID-19 emergence and other challenges in the public sector. This has delayed the training sessions. This means that the government effort to enhance the country's socioeconomic development within the medium term is going to be affected. Collapse

Topics: procurement management digital transformation digital platform Python structured query language

Methods: qualitative interview case study field study

Theories: activity theory

The Role of Followers and Followees in the Adoption of Innovations

2023 | HICSS | Citations: 0

Authors: Atlas, M.; Gavious, A.; Ravid, G.

Abstract: An online social network is a key platform through which innovation diffuses. T ... Expand

Abstract: An online social network is a key platform through which innovation diffuses. To learn about innovativeness, we simultaneously investigate two Twitter networks, the relationships network, following-follower relationships, and the activity network, the flow of tweets. Specifically, the innovativeness relations to the networks' indegree and outdegree, the volume of platform use, and the profile's age. The more active and central the user, the earlier the adoption. Innovativeness increases with the number of followers only when at least several of them adopt the innovation. Surprisingly, having more followees is linked to later engagement with the innovation. This association is mediated by the number of adopters' followees. Those who created a Twitter profile later are also more likely to adopt innovations later. This study is novel in distinguishing between the two networks and analyzing their interactions. Its contribution lies in identifying the innovativeness of users in an online social network platform diffusion. Collapse

Topics: Twitter mindfulness social network innovation management user acceptance

Methods: descriptive statistic regression analysis method

Designing a Digital Marketing Analytics Operations Platform using Action Design Research

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Babu, Xavier; Motiwalla, Luvai

Abstract: Digital environment has transformed the work environment of marketing firms. Tr ... Expand

Abstract: Digital environment has transformed the work environment of marketing firms. Traditional marketing processes are repetitive, lack coordination, and are not dynamic or data-driven. To compete effectively in the digital world, marketing firms need a digital marketing analytics operations platform (DMAOP) optimized for data analytics, workflow, team coordination, and quick decision-making. We developed a DMAOP using a design science research model known as ADR. DMAOP uses data analytics leading to marketing decisions that create value with intelligent robotic processes assisting marketing practitioners in executing marketing actions. DMAOP is customized to a user's skill level, supporting marketing functions, advanced analytics, preserving privacy, and episodic reporting for users without technical skills. This study contributes to descriptive knowledge problem space by identifying the key aspects of DMAO. It also contributes to the "elaborated ADR" model with a new cycle, "personalization". Finally, it contributes to prescriptive knowledge and DMAOP instantiation with design science for digital platforms. Collapse

Topics: marketing management usability personalization marketing intelligence distributed computing

Methods: design science case study action design research design artifact design principle

Human-machine collaboration for feature selection and integration to improve congestive Heart failure risk prediction

2023 | Decision Support Systems | Citations: 0

Authors: Ben-Assuli, Ofir; Heart, Tsipi; Klempfner, Robert; Padman, Rema

Abstract: The issue of harnessing machine learning (ML) algorithms for the prediction of a ... Expand

Abstract: The issue of harnessing machine learning (ML) algorithms for the prediction of adverse medical events is important considering the prevalence of vast repositories of patient-level medical data, and the quest to reduce healthcare costs while elevating the quality of care. Of particular interest is identifying a set of features that can better predict the risk of unplanned readmissions of chronically ill patients within 30 days post discharge, among them patients with Congestive Heart Failure (CHF). While numerous studies have employed ML algorithms to identify sets of significant features, only a handful have compared features extracted by various methods, and even fewer have compared the predictive power of feature sets selected by human experts to those selected by ML. Hence, this research aimed to elicit a comprehensive feature set selected by four ML algorithms and compare its predictive performance to that of a feature set selected by experts. We then evaluated a merged list of the two feature sets, constructing a human-machine collaborative set to predict the likelihood of 30-day unplanned readmission of CHF patients using data on 10,763 CHF patients hospitalized during the years 2010–2017. Our models achieved Area under the ROC Curve (AUC) above 0.8 and an Accuracy of ~0.89, comparable to the best models in the extant literature. Moreover, the Human-Machine Collaborative model significantly outperformed (best AUC 0.836) other human-only selected models as well as the machine-selected set. This study contributes to a better understanding of the power of using ML for patient risk stratification with special attention to the benefits of human-machine collaboration, even when these two entities work separately or in parallel, for improved clinical decision making. Collapse

Topics: healthcare data decision making big data missing data data warehouse

Methods: machine learning computational algorithm XGBoost descriptive statistic random forest classification

Exploring the value of IoT data as an enabler of the transformation towards servitization: an action design research approach

2023 | European Journal of Information Systems | Citations: 0

Authors: Chen, Kuan-Lin; Lassen, Astrid; Li, Chen; Møller, Charles

Abstract: Servitization is a well-recognised phenomenon in the manufacturing industry. Bus ... Expand

Abstract: Servitization is a well-recognised phenomenon in the manufacturing industry. Business potentials are demonstrated mainly from the marketing perspective on servitization. However, increased digitalisation makes servitization interesting to other research areas. This paper applies the resource-based view (RBV) to argue how to value the data and explore its potential and impact on servitization. We examine the evolving role of information technology (IT), particularly of the Internet of Things (IoT), and the role of data in the servitization journey. This research is based on a longitudinal study of a product-oriented manufacturing company’s transformation towards servitization. The engagement with the company also includes the development of an IT platform that consolidates IoT and enterprise data, which enables managers to explore new data-based insights. Our goal is to investigate the organisation and in particular cross-functional effects of data-based insights and their impact on supporting strategic decision-making. The action design research (ADR) approach is applied to unfold the servitizing activities inside the organisation and extract the lesson learned into the joint domains of servitization and information systems research. First, we argued that exploring the value of data is becoming a more complex process. Rather than having one design perspective, technical concerns, business considerations, and operational purpose must be aligned to frame the value of data to support decision-making. Second, we discuss the emerging managerial implications, especially the role of IT in the transformation. A cross-functional team is a prerequisite to exploring complex transformation projects. Thus, managers must recognise the problematic situation and bootstrap the available organisational resources. Finally, we provide empirical evidence on how scholars and practitioners can address mutual interests by applying the ADR approach to a transformation project. In summary, servitizing a product-centric manufacturing firm to have a digital services business model is a transformation involving complex social and organisational relations. This study advocates resource-based analysis as a lens and demonstrates how IT and data as heterogeneous and imperfectly mobile resources create value for a product-oriented manufacturing company. However, a critical question remains on how to manage the expanding operational condition of a servitizing organisation and its business system to sustain its competitive advantage and win the digital market. Collapse

Topics: mobile system internet of things enterprise information system enterprise resource planning smart device

Methods: action design research experiment qualitative interview longitudinal research design artifact

Theories: resource based view of the firm

Mining Health Informatics Job Advertisements: Insights for Higher Education Programs and Job Seekers

2023 | HICSS | Citations: 0

Authors: Elnoshokaty, A.; Al-Ramahi, M.; El-Gayar, O.; Wahbeh, A.; Nasralah, T.

Abstract: This paper used web scraping and data mining to analyze 831 health informatics ... Expand

Abstract: This paper used web scraping and data mining to analyze 831 health informatics job advertisements on indeed.com. Results showed that 87% of jobs explicitly required a college degree in a related field, 41% of jobs preferred a graduate degree, while 29% preferred or required professional certification. The analysis showed that preferred skills were analytics problem solving, communication skills, oral communication, interpersonal skills, project management, statistics, and critical thinking. The analysis also showed that college degrees, certifications, and the above-mentioned skill set are in high demand for working in the field of health informatics, especially in states with large populations and strong economies. Our results inform curriculum development of health informatics programs in higher education, which helps map knowledge units across the curricula to bridge the skills gap and meet employers' expectations. At the same time, the results help job seekers familiarize themselves with what employers seek in a successful candidate. Collapse

Topics: health information system Indeed.com online labor market problem solving structured query language

Methods: qualitative interview natural language processing machine learning literature study survey

Perceived Social Norms, Token Rewards, and Cooperation in Decentralized Autonomous Organizations (DAOs)

2023 | International Conference on Information Systems | Citations: 0

Authors: Dong, Sichen; Hu, Daning; Chau, Michael

Abstract: Decentralized autonomous organizations (DAOs) offer a novel paradigm, fostering ... Expand

Abstract: Decentralized autonomous organizations (DAOs) offer a novel paradigm, fostering members' decentralized cooperation towards collective goals. Central to this are token rewards, aligning individuals' interests with DAO's collective goals to enhance cooperation. We introduce a theoretical model proposing that DAO members' perceived social norms impact the effectiveness of this token-based interest alignment mechanism by influencing members' tendencies to hold tokens, subsequently affecting their cooperative behaviors. By analyzing data collected from the prominent social DAO, Steem, our empirical findings validated this proposition. Our study stands at the forefront of elucidating the complex interplay between economic incentives and social motivations in DAOs, particularly the interest alignment mechanism. Moreover, based on the basic rationales of profit-sharing arrangements in traditional organizations, we transpose this understanding to the context of DAOs, offering a nuanced articulation of the interest alignment mechanism, which is absent in the current DAO literature. Collapse

Topics: social norm blockchain structured query language application programming interface social media

Methods: theory development economic model experiment

Theories: economic theory

Establishing a Gamified Programming Practice Environment with Immediate Feedback

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fu, JenRuei; Hsu, Chiung-Wen

Abstract: Feedback serves a key role of closing the gap between students' current underst ... Expand

Abstract: Feedback serves a key role of closing the gap between students' current understanding and desired learning. However, it is difficult for students to obtain feedback on homework corrections in a timely manner. With the guidance of self-determination theory, this research integrated gamified elements and immediate feedback feature in students' practice assignments and develops a highly motivating SQL programming practice exercise that is not limited by time and space, allowing exploration and trial-anderror process surroundings. The system completely records the content of each activity process and problem-solving so as to provide teachers with after-the-fact review and serve as a reference for classroom teaching. We provide students with an engaging but meaningful learning experience in gamified scenarios. From the perspective of learning gamification, this research explores how gamification elements in the learning process affect students' learning engagement and learning outcomes. Collapse

Topics: gamification user interface usability enterprise architecture structured query language

Methods: survey design artifact

Theories: self determination theory

They Work with Data and Do Some Science: How Identity Conflict Turns Data Professionals away from Data Science

2023 | International Conference on Information Systems | Citations: 0

Authors: Rosa, Marta; Aikath, Devdeep; Mayer, Anne

Abstract: Data science is widely perceived as an attractive, lucrative, and prestigious e ... Expand

Abstract: Data science is widely perceived as an attractive, lucrative, and prestigious emerging occupation. Research so far has focused on understanding data scientists' practices and identity work associated with establishing and legitimizing this new occupation. This work, however, is not sufficient to explain a phenomenon we observed whereby professionals rejected the opportunity to adopt this new occupational identity. To understand why professionals may not want to be labeled data scientists, we analyzed 43 interviews with data professionals at an educational measurement company in the U.S. Despite a clear steer from management towards the data science label, many interviewees stuck to their established professional identities. In our preliminary findings, we use the literature on identity conflict as a lens to make sense of our observations. By identifying three types of conflicts: 1) task conflict, 2) role conflict, 3) tool conflict, we begin to explain what turns professionals away from data science. Collapse

Topics: database system structured query language Tableau software programming language relational database

Methods: qualitative interview grounded theory machine learning personal interview qualitative coding