Agile global software development (AGSD) is an increasingly prevalent software development strategy, as organizations hope to realize the benefits of accessing a larger resource pool of skilled labor, at a potentially reduced cost, while at the same time delivering value incrementally and iteratively. However, the distributed nature of AGSD creates geographic, temporal, socio-cultural distances that challenge collaboration between project stakeholders. The Cloud Computing (CC) service models of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are similar to the aspirant qualities of AGSD as they provide services that are globally accessible, efficient, and stable, with lower predictable operating costs that scale to meet the computational demand. This study focused on the 12 agile principles upon which all agile methodologies are based, therein potentially increasing the potential for the findings to be generalized. Domestication Theory was used to assist in understanding how cloud technologies were appropriated in support of AGSD. The research strategy took the form of case study research. The findings suggest that some of the challenges in applying the agile principles in AGSD may be overcome by using CC.

The authors present the results of a study conducted at a comprehensive, urban, coeducational, land-grant university. A quasi-experimental design was chosen for this study to compare student performance in two different classroom environments, traditional versus flipped. The study spanned 3 years, beginning fall 2012 through spring 2015. The participants included 433 declared business majors who self-enrolled in several sections of the Management Information Systems course during the study. The results of the current study mirrored those of previous works as the instructional method impacted students’ final grade. Thus, reporting that the flipped classroom approach offers flexibility with no loss of performance when compared to traditional lecture-based environments.

Aim/Purpose: This paper aims to describe how various Kanban elements can help alleviate two prominent types of challenges, communication and collaboration in Global Software Development (GSD). Background: Iterative and Lean development methodologies like Kanban have gained significance in the software development industry, both in the co-located and globally distributed contexts. However, little is known on how such methodologies can help mitigate various challenges in that occur in a globally distributed software development context. Methodology: The study was conducted using a single-case study based on a general inductive approach to analysis and theory development. Through the literature review, collaboration and communication challenges that GSD teams face were identified. Data collected through semi-structured interviews was then inductively analyzed to describe how the case-study teams employed various Kanban elements to mitigate communication and collaboration challenges they face during GSD. Findings: The study found that some Kanban elements, when properly employed, can help alleviate collaboration and communication challenges that occur within GSD teams. These relate to Inclusion Criteria, Reverse Items, Kanban Board, Policies, Avatars, and Backlog. Contribution: The paper contributes to knowledge by proposing two simple concept maps that detail the specific types of communication and collaboration challenges which can be alleviated by the aforementioned Kanban elements in GSD. Recommendations for Practitioners: This paper is relevant to GSD teams who are seeking ways to enhance their team collaboration and communication as these are the most important elements that contribute to GSD project success. It is recommended that relevant Kanban elements be used to that effect, depending on the challenges that they aim to alleviate. Future Research: Future research can investigate the same research questions (or similar ones) using a quantitative approach.

Aim/Purpose: Executive doctoral programs in higher education are under-researched. Scholars, administers, and students should be aware of all common delivery methods for higher education graduate programs. Background This paper provides a review and analysis of executive doctoral higher education programs in the United States. Methodology: Executive higher education doctoral programs analyzed utilizing a qualitative demographic market-based analysis approach. Contribution: This review of executive higher education doctoral programs provides one of the first investigations of this segment of the higher education degree market. Findings: There are twelve programs in the United States offering executive higher education degrees, though there are less aggressively marketed programs described as executive-style higher education doctoral programs that could serve students with similar needs. Recommendations for Practitioners: Successful executive higher education doctoral programs require faculty that have both theoretical knowledge and practical experience in higher education. As appropriate, these programs should include tenure-line, clinical-track, and adjunct faculty who have cabinet level experience in higher education. Recommendation for Researchers: Researchers should begin to investigate more closely the small but growing population of executive doctoral degree programs in higher education. Impact on Society: Institutions willing to offer executive degrees in higher education will provide training specifically for those faculty who are one step from an executive position within the higher education sector. Society will be impacted by having someone that is trained in the area who also has real world experience. Future Research: Case studies of students enrolled in executive higher education programs and research documenting university-employer goals for these programs would enhance our understanding of this branch of the higher education degree market.

Aim/Purpose: This paper describes and information system for the maintenance and management of municipal lighting systems that also serves as a decision support tool for reducing power consumption on urban lighting. Background: Many municipalities are financially constrained and unable to invest in improving their lighting infrastructure. We propose a very efficient and inexpensive way to set up the database and provide city leaders with tools to improve their system efficiently. Methodology: An information database for the data management and an Integer Programming model for deriving the optimal investment plan. Contribution: This paper contributes to the fields of urban economics and sustainability. Findings: Informing management and workers about the status of the system and how to optimize it will reward the city with considerable savings and improve the service quality. Recommendations for Practitioners: The application of this model, even in a small scale such as a neighborhood can improve citizen’s quality of life without a heavy burden on the city budget. Recommendation for Researchers: There is a growing need for cost-effective means to improve urban management. Innovative ideas that meet these goals should be researched and developed. Impact on Society: First, it allows reduction in carbon emissions and light pollution by reducing power consumption and over-luminous lighting levels. Second, financially constrained municipalities can manage their systems at a very low cost. Future Research: A full scale application is needed in order to evaluate the city-wide benefits of the system.

Aim/Purpose: To monitor Sustainability Development Goals (SDG) established by the United Nations through the hierarchical architecture of informing systems Background: The paper discusses the case of Poland and its Gdansk region Contribution: The solution combines the big-picture of civilization with small-picture of a nation, regions, cities, and firms Findings: The presented solution can be implemented if the political will can be secured. Recommendations for Practitioners: Take the main idea of this paper and adapt to your local case. Recommendation for Researchers: Develop some prototypes of presented informing systems and test in your local environment Impact on Society: The success of the sustainability of globalizing society can be secured if the coherent informing systems can be applied to the planning, monitoring, and implementation of the UN's universal SDG. Future Research: Work on the modeling of costs and benefits of the presented solution.

Aim/Purpose: The aim and purpose of this study is to understand why there is a dearth of faculty of color ascending to senior levels of leadership in higher education institutions, and to identify strategies to increase the representation of faculty of color in university senior administrative positions. Background: There is a lack of faculty of color in senior level academic administrative position in the United States. Although there is clear evidence that faculty of color have not been promoted to senior level positions at the same rate as their White colleagues, besides racism there has been little evidence regarding the cause of such disparities. This is becoming an issue of increased importance as the student bodies of most U.S. higher educational institutions are becoming increasingly more inclusive of people of various racial and ethnic backgrounds. Methodology: Qualitative interviews were used Contribution: This study adds to the research and information made previously available regarding the status of non-White higher educational members in the U.S. by contributing insights from faculty of color who have encountered and are currently encountering forms of discrimination within various institutions. These additions include personal experiences and suggestions regarding the barriers to diversification and implications of the lack of diversity at higher educational institutions. Given the few diverse administrative or executive leaders in service today in higher education, these personal insights provide seldom-heard perspectives for both scholars and practitioners in the field of higher education. Findings: Limited diversity among faculty at higher educational institutions correlates with persistent underrepresentation and difficulty in finding candidates for leadership positions who are diverse, highly experienced, and highly ranked. This lack of diversity among leaders has negative implications like reduced access to mentorship, scholarship, and other promotional and networking opportunities for other faculty of color. While it is true that representation of faculty of color at certain U.S. colleges and programs has shown slight improvements in the last decade, nationwide statistics still demonstrate the persistence of this issue. Participants perceived that the White boys club found to some extent in nearly all higher educational institutions, consistently offers greater recognition, attention, and support for those who most resemble the norm and creates an adverse environment for minorities. However, in these findings and interviews, certain solutions for breaking through such barriers are revealed, suggesting progress is possible and gaining momentum at institutions nationwide. Recommendations for Practitioners: To recruit and sustain diverse members of the academic community, institutions should prioritize policies and procedures which allocate a fair share of responsibilities between faculty members and ensure equity in all forms of compensation. In addition, institutional leaders should foster a climate of mutual respect and understanding between members of the educational community to increase confidence of people of color and allow for fresh perspectives and creativity to flourish. Where policies for diversification exist but are not being applied, leaders have the responsibility to enforce and set the example for other members of the organization. Assimilation of diverse members occurs when leaders create an inclusive environment for various cultures and advocate for social and promotional opportunities for all members of the organization. Recommendations for Researchers: Significant research remains on understanding barriers to the preparation of faculty of color for leadership in higher education. While this research has provided first-hand qualitative perspectives from faculties of color, additional quantitative study is necessary to understand what significant differences in underrepresentation exist by race and ethnicity. Further research is also needed on the compound effects of race and gender due to the historic underrepresentation of women in leadership positions. At the institutional and departmental level, the study validates the need to look at both the implicit and explicit enforcement of policies regarding diversity in the workplace. Future Research: Higher education researchers may extend the findings of this study to explore how faculty of color have ascended to specific leadership roles within the academy such as department chair, academic dean, provost, and president.

Aim/Purpose: To understand readiness of students for learning in online environments across different age groups. Background: Online learners today are diverse in age due to increasing adult/mature students who continue their higher education while they are working. Understanding the influence of the learners’ age on their online learning experience is limited. Methodology: A survey methodology approach was followed. A sample of one thousand nine hundred and twenty surveys were used. Correlation analysis was performed. Contribution: The study contributes by adding to the limited body of knowledge in this area and adds to the dimensions of the Online Learning Readiness Survey additional dimensions such as usefulness, tendency, anxiety, and attitudes. Findings: Older students have more confidence than younger ones in computer proficiency and learning skills. They are more motivated, show better attitudes and are less anxious. Recommendations for Practitioners: Practitioners should consider preferences that allow students to configure the learning approach to their age. These preferences should be tied to the dimensions of the online learning readiness survey (OLRS). Recommendations for Researchers: More empirical research is required using OLRS for online learning environments. OLRS factors are strong and can predict student readiness and performance. These are opportunities for artificial intelligence in the support of technology-mediated tools for learning.

Aim/Purpose: In the United States, the Centers for Disease Control and Prevention (CDC) tracks the disease activity using data collected from medical practice's on a weekly basis. Collection of data by CDC from medical practices on a weekly basis leads to a lag time of approximately 2 weeks before any viable action can be planned. The 2-week delay problem was addressed in the study by creating machine learning models to predict flu outbreak. Background: The 2-week delay problem was addressed in the study by correlation of the flu trends identified from Twitter data and official flu data from the Centers for Disease Control and Prevention (CDC) in combination with creating a machine learning model using both data sources to predict flu outbreak. Methodology: A quantitative correlational study was performed using a quasi-experimental design. Flu trends from the CDC portal and tweets with mention of flu and influenza from the state of Georgia were used over a period of 22 weeks from December 29, 2019 to May 30, 2020 for this study. Contribution: This research contributed to the body of knowledge by using a simple bag-of-word method for sentiment analysis followed by the combination of CDC and Twitter data to generate a flu prediction model with higher accuracy than using CDC data only. Findings: The study found that (a) there is no correlation between official flu data from CDC and tweets with mention of flu and (b) there is an improvement in the performance of a flu forecasting model based on a machine learning algorithm using both official flu data from CDC and tweets with mention of flu. Recommendations for Practitioners: In this study, it was found that there was no correlation between the official flu data from the CDC and the count of tweets with mention of flu, which is why tweets alone should be used with caution to predict a flu out-break. Based on the findings of this study, social media data can be used as an additional variable to improve the accuracy of flu prediction models. It is also found that fourth order polynomial and support vector regression models offered the best accuracy of flu prediction models. Recommendations for Researchers: Open-source data, such as Twitter feed, can be mined for useful intelligence benefiting society. Machine learning-based prediction models can be improved by adding open-source data to the primary data set. Impact on Society: Key implication of this study for practitioners in the field were to use social media postings to identify neighborhoods and geographic locations affected by seasonal outbreak, such as influenza, which would help reduce the spread of the disease and ultimately lead to containment. Based on the findings of this study, social media data will help health authorities in detecting seasonal outbreaks earlier than just using official CDC channels of disease and illness reporting from physicians and labs thus, empowering health officials to plan their responses swiftly and allocate their resources optimally for the most affected areas. Future Research: A future researcher could use more complex deep learning algorithms, such as Artificial Neural Networks and Recurrent Neural Networks, to evaluate the accuracy of flu outbreak prediction models as compared to the regression models used in this study. A future researcher could apply other sentiment analysis techniques, such as natural language processing and deep learning techniques, to identify context-sensitive emotion, concept extraction, and sarcasm detection for the identification of self-reporting flu tweets. A future researcher could expand the scope by continuously collecting tweets on a public cloud and applying big data applications, such as Hadoop and MapReduce, to perform predictions using several months of historical data or even years for a larger geographical area.

Aim/Purpose: The purpose of this paper is to address the issue of gaps in students’ knowledge at the time they enter a comprehensive Information Systems cap-stone course. This problem of knowledge gaps was exacerbated by the forced remote learning and isolation caused by the COVID-19 pandemic. The aim was to find a technique that would identify and fill those gaps. Ideally, the method would also reinforce the students’ interpersonal soft skills. Background: Many universities have a capstone course where students may apply their knowledge from the curriculum to a project, and they are evaluated on their retention of knowledge from the core classes. Over the past two years, students have experienced course interruptions and modifications due to the pandemic, resulting in learning gaps on topics covered in the core courses. Depending on the project’s scope and curriculum, this may prevent students from conversing on many essential concepts during the capstone course. By requiring students to create “Teach Back” tutorials on materials from their core courses, faculty may ensure that the key concepts are discussed multiple times within the curriculum. Methodology: We present a case study to identify key concepts and compare cohort results before and after implementation. Contribution: A process for identifying potential knowledge gaps is identified, and a method to repeatedly expose students to concepts is introduced. Findings: There were improvements to the overall capstone scores after the tutorial implementation. While many factors influence changes in scores across cohorts, the initial findings are promising, supporting the concept that teaching back helps to close knowledge gaps. Recommendations for Practitioners: Faculty should collaborate to identify knowledge areas that need to be rein-forced later in their students’ academic careers. Teaching back essential concepts that may not be prioritized in implementing a capstone project ensures a repeated exposure to the identified concepts. Recommendations for Researchers: There needs to be a priority to teach students to be lifelong learners and to teach the skills needed to share their knowledge with future coworkers. There needs to be more research into a pedagogy that builds these essential soft skills within our curriculum. Finally, research into alumni feedback on course topics and pedagogy is needed. Impact on Society: Introducing pedagogy that improves both knowledge and soft skills, this re-search looks to build individuals who will learn independently and be able to communicate with and improve others. Future Research: There needs to be additional research to study the changes in technical knowledge before and after Teach Back, the consequences of elective sequencing, the consideration of elective versus required courses, and the use of Teach Back to capture student knowledge gained from completing diverse electives prior to the capstone course.

Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.

Aim/Purpose. Business schools need to design, develop and deliver courses that are relevant to business problem-solving. Current pedagogies do not often provide the insight – or experience – necessary to close the gap between theory and practice. Background. The paper describes an initiative to design, develop and deliver courses in business-technology problem-solving that thoroughly immerses students in the actual world of business. Methodology. The methodology included case-based analysis where actual cases where selected to model problem-solving scenarios. Contribution. Several courses are developed that immerse students into actual problem-solving experiences. Findings The courses will be delivered to business students to assess the impact of immersive/experiential learning. Recommendations for Practitioners. Additional courses should be informed by actual cases; the commitment to relevance should be expanded. Recommendations for Researchers. Ongoing research to measure the impact of immersive/experiential learning is recommended. Impact on Society. Business schools should rethink the content of their courses and the pedagogies that have dominated business schools for many decades. Future Research. Additional research will include more courses and additional immersive/experiential pedagogies.