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Meetings are ubiquitous at work. Therefore, understanding what makes meetings effective (or not) is important. Entitativity (i.e., the “group-ness” of a meeting) may theoretically explain when some meetings are effective. That is, when meeting participants perceive a high enough level of group-ness in their meeting, then they begin to enact the processes to create a successful meeting and experience the outcomes of a successful meeting. The authors propose a model connecting the characteristics of successful face-to-face (FtF) meetings to entitativity and extrapolate this model to online meetings. Specifically, the authors interpret well-researched characteristics and practices of meetings (e.g., using an agenda and meeting punctuality) to be examples of well-established entitativity antecedents (e.g., creating similarity of goals and establishing meeting boundaries). That is, using an agenda creates effective meetings because it focuses members’ attention on common goals. Therefore, entitativity may be an explanatory mechanism for successful meetings. The authors examine the unique challenges of online meetings, which are growing in number. The authors note that entitativity may be harder to establish in online meetings making successful online meetings more difficult. Characteristics of online meetings (e.g., focusing on the few shared documents which may focus members on goals) that may promote success. The authors propose further theoretical work as well as suggest strategies that can be used to increase entitativity in FtF and online meetings.

This study examines the relative efficacy of groups in both virtual and traditional face-to-face courses, as well as differences in group dynamics between the two delivery methods. We surveyed students in online and traditional classroom sections of the same intermediate-level cost accounting course about their perceptions of group processes, general satisfaction with group work, learning outcomes, and group communications. Traditional classroom students were more positive about their group processes and learning outcomes than were online students. They also were more likely to agree that the learning benefits of group work outweighed the costs, (e.g., uneven and inefficient work distribution.) Our findings suggest that instructors who use groups in online courses should specifically consider the potentially negative effects of such factors as workload imbalances when designing group learning activities so that learning objectives are not adversely affected.

This study investigates a perceived student performance disparity between traditional synchronous and web-based asynchronous course delivery. Synchronous classes meet face-to-face or online with scheduled meeting times and the ability to directly monitor class attendance and participation. Asynchronous classes are 100% online, requiring no face-to-face or online live sessions. This study identifies student attributes associated with performance differences in the two delivery modes. The authors examine data from over 15,000 students who took introductory financial and managerial accounting classes at a large state university. The authors analyze student demographic and class performance data. Controlling for instructor and year effects, the authors find a statistically significant lower DFW rate (better performance) in the synchronous introductory accounting classes compared to the asynchronous ones. Using these findings, the authors revised scheduling and advising protocols to improve student success likelihood in the asynchronous sections. This study provides two insights applicable to many accounting departments. First, the results suggest that empirically exploring student performance implications may be warranted as the number of web-based asynchronous class offerings grow. Additionally, the study provides an example of working within the limitations of existing registration policies and systems to translate the result of the analysis into improved advising and scheduling approaches.

The chapter presents the implementation of ethics education via challenge-based learning (CBL) in three European settings. At TU Eindhoven (the Netherlands), a mandatory first-year User, Society, and Enterprise course on the ethics and history of technology offers a CBL alternative on ethics and data analytics in collaboration with internal student and research teams. The University of Lübeck (Germany) initiated the project CREATE – Challenge-based Learning for Robotics Students by Engaging Start-Ups in Technology Ethics, which enables 60 students in Robotics and Autonomous Systems to integrate ethical and societal considerations into technological development processes, in cooperation with start-ups from a local accelerator. In Spain, CBI-Fusion Point brings together 40 students from business and law (ESADE), engineering and technology (Polytechnic University of Catalonia), and design (IED Barcelona Design University) for an innovation course focused on the application of CERN-developed technologies to real-world problems. The chapter documents the process of setting up three CBL courses that engage students with grand societal topics which require the integration of ethical concerns from the design stage of technological development. The authors also reflect on the challenges of teaching ethics via CBL and the lessons they learned by delivering experiential learning activities rooted in real-life challenges and contexts marked by high epistemic uncertainty. The contribution reflects the transition to remote teaching and presents strategies employed to enhance online communication and collaboration. The chapter thus provides guidance for instructors interested in teaching ethics via CBL and recommends further lines for action and research.

Faced with the existential threat of COVID-19, the College of Business Administration (CBA) at Princess Nourah Bint Abdulrahman University (PNU) decided to work toward the dual goals to achieve accreditation and an effective social and educational response to the pandemic. CBA’s quality improvement process was implemented synergistically with Seligman’s (2011) PERMA well-being model, namely positive emotions, engagement, relationship, meaning, and accomplishment/achievement. The case study methodology, which was based on direct observations, faculty and students’ interviews, surveys, feedback, documents, and archival data records, allowed to capture the context and lived reality of all the participants in QAA processes. Results showed that quality improvement was facilitated through three domains: (1) governance and academic leadership, (2) teaching and learning, and (3) digitalization and technology. Within each domain, specific programs, activities, human resources, and networks were enabled through a framework based on the PERMA well-being model. As a result of this hybrid QAA well-being implementation process, CBA achieved NCAAA accreditation for its offered programs, while experiencing high levels of well-being and commitment to teaching and learning by the staff members and students. The description of CBA’s accreditation journey might be insightful for other higher education institutions (HEIs).

Prior to the spring 2020, education in the United States looked very similar to how it had always looked … students attended brick-and-mortar schools, used technology in their classrooms and homes to supplement their learning, and relied on the support of teachers as needed or wanted. Parents, for their part, were involved in the traditional supportive roles of checking over homework, monitoring attendance, and providing encouragement as warranted, and worked to balance this role with professional and community obligations and responsibilities. The COVID-19 pandemic swept across the globe, and parents as well as teachers were suddenly thrust into different and less familiar roles, as teaching and learning transitioned to a virtual experience. In examining this transition, a team consisting of researchers from Florida and North Carolina sought to determine the effectiveness of the parent roles in schooling from the educator perspective. In this chapter, the findings of this study are explored and analyzed, with recommendations made for research moving forward in this area.

This Chapter is all about communication and the ways we are now able to reach out to others around the world from our personal computers or mobile devices, which were never available before. One might initially consider this section more in line with productivity tools instead of those impacting the digital humanities. I will, however, demonstrate that it is through these tools that the field is expanding, offering interesting ways in which scholars can communicate ideas with one another, share thoughts, research, and collaborate. Additionally, it is through the use of these tools that our ideas are being shared with students and interestingly how students are, in turn, reciprocating our efforts. The chapter focuses on video broadcasting tools, audio conferencing, audiocasting, and collaboration applications, offering examples of how they can be used in a classroom setting.

This chapter focuses on techniques and technologies to aid groups in making decisions, with an emphasis on computer-based support. Many office workers regularly meet colleagues and clients in virtual meetings using videoconferencing platforms, which enable participants to carry out tasks in a manner similar to a face-to-face meeting. The development of computer-based platforms to facilitate group tasks can be traced back to the 1960s, and while they support group communication, they do not directly support group decision making. In this chapter we distinguish four technologies developed to provide support to group decisions, clustered into two main traditions. Technologies in the task-oriented tradition are mainly concerned with enabling participants to complete tasks to solve the group's decision problem via computer-supported communications. Group Decision Support Systems and social software technologies comprise the task-oriented tradition. Alternately, in the model-driven tradition, participants use computers to build and use a model that acts as a referent to communicate, mostly verbally, about the group's decision problem. System modeling and decision-modeling technologies constitute the model-driven tradition. This chapter sketches the history and guiding ideas of both traditions, and describes their associated technologies. The chapter concludes with questioning if increased availability of online tools will lead to increased use of group decision support technologies, and the differential impact of communication support versus decision support.

Introduction: With the proliferation and amalgamation of technology and the emergence of artificial intelligence and the internet of things, society is now facing a rapid explosion in big data. However, this explosion needs to be handled with care. Ethically managing big data is of great importance. If left unmanageable, it can create a bubble of data waste and not help society achieve human well-being, sustainable economic growth, and development.

Purpose: This chapter aims to understand different perspectives of big data. One philosophy of big data is defined by its volume and versatility, with an annual increase of 40% per annum. The other view represents its capability in dealing with multiple global issues fuelling innovation. This chapter will also offer insight into various ways to deal with societal problems, provide solutions to achieve economic growth, and aid vulnerable sections via sustainable development goals (SDGs).

Methodology: This chapter attempts to lay out a review of literature related to big data. It examines the implication that the big data pool potentially influences ideas and policies to achieve SDGs. Also, different techniques associated with collecting big data and an assortment of significant data sources are analysed in the context of achieving sustainable economic development and growth.

Findings: This chapter presents a list of challenges linked with big data analytics in governance and achievement of SDG. Different ways to deal with the challenges in using big data will also be addressed.