An Agile Approach to Doctoral Research and Dissertations

1. An Agile Approach to Doctoral Research and Dissertations Doctor of Professional Studies in Computing Class of 2016 Seidenberg School of Computer Science and Information Systems Pace University, White Plains, NY Student/Faculty Research Day, May 2, 2014

2. Abstract This research sets out to: • compare traditional, or “non-agile” doctoral programs and their respective dissertation processes with an Agile professional studies doctoral program. • compare and contrast the core differences of the two program types. • summarize enrollment and completion rates from various private, public, and online institutions • conclude with a summary and ideas for future work.

3. Introduction / Background Why is Doctoral Research Important? • Although there are inherent differences, traditionally, university-led research programs devote a percentage of resources to the attainment of a doctoral-level degree, which affords both student and university with what can be considered leading-edge research. This research thus becomes a vital and continuous source of funding for universities due to the reputation gained of discovering, sharing, and creating real-world solutions(measured via various metrics such as student enrollment, graduation and retention rates, reputation, endowment, number of patents, et al) What are the drivers of value? • Given the breadth, depth, and successes of ongoing doctoral-level research programs, interest has arisen in discovering a better understanding as to which components in these respective research programs are responsible for the tremendous value that continues to be attributed to university-led doctoral research. Do results vary based on non-agile vs. Agile research and dissertation processes? • In this study, we examined the historical make-up of non-agile doctoral-level research programs with a focus on U.S. universities that offer degrees in information technology, information systems, computer science and engineering, and computational and computing disciplines such as informatics and information theory. • The common framework and practices in these programs were discussed and analyzed. The researchers then compared and contrasted these non-agile programs which employ a top-down, approach of directed research from theory to applications, with those programs that adopt an Agile-based approach.

4. Applying Agile Values to a Doctoral Program An Agile approach to doctoral research and dissertations can be compared to Agile values in software development Using Agile values can allow students to: • Complete their dissertations • Complete their dissertations sooner • Maintain a sustainable pace during research and dissertation writing The important Agile principles for a research and dissertation process include: • Early and continuous delivery of valuable product • Welcoming changed requirements, even late in development • Delivering working product frequently, from a couple of weeks to a couple of months, with a preference for the shorter timescale • Measuring progress primarily through useful deliverables • Using Agile processes for sustainable development, enabling sponsors, developers, and users to maintain a constant pace indefinitely • Valuing simplicity as the art of maximizing the amount of work not done.

5. Research Methodology • The DPS 2016 cohort comprised of 14 doctoral students authored and conducted the study. • The authors operated on the Agile practice of “frequent delivery of quality product” by setting up a framework for the study paper and matrices, which were filled in as drafts of sections were completed. • Authors made phone calls and sent emails to Universities and searched websites to find program descriptions and statistics for Computer Science and Information Technology doctoral programs.

6. Research Focus Research was focused on answering these questions for public, private, and on-line doctoral programs: • The number of applicants • The number of acceptances • The number of students who have passed the written qualifying exam • The number of students who have passed the oral qualifying exam • The number of graduates • The length of time that it took these students to complete their studies • The number of students leaving the program ABD (All But Dissertation) • If this could be broken down by gender, and race • And if possible, by year The authors built matrices and statistics tables as results were provided, and all authors were asked for their input on the conclusions.

7. Programs researched for this study Private • Indiana University – School of Informatics and Computing • Stanford University – Engineering Computer Science • Pace University – Doctor of Professional Studies in Computing Public • Penn State University – College of Information Science and Technology • University of Virginia – Computer Science and Engineering • University of California, Los Angeles – Computer Science • Virginia Tech – Computer Science and Information Technology • City College of New York - Engineering • George Mason University – Information Technology and Computational Sciences • Rutgers University – Computer and Information Science Online • University of Phoenix – not specified • Nova Southeastern – not specified • Walden University – not specified • Capella University – Information Technology • Edinburgh University – Science and Engineering

8. Results - Non-agile versus Agile Research Program Characteristics

9. Results- Non-agile versus Agile Research and Dissertation Process (1 of 2)

10. Results- Non-agile versus Agile Research and Dissertation Process (2 of 2)

11. Results- Approaches to the Dissertation Process The typical research process in a non-agile approach consists of the following steps: • Planning the Study • Literature Review • Study Implementation and Data Gathering • Analysis and Interpretation • Reporting The typical research process in an Agile approach that consists of the following steps: • Begin with the problem • Research defines the goals • Divide into sub-problems • Create Hypothesis as proposed solutions to the problem • Look for data directed by your hypothesis, collect and organize • Interpret the meaning of the data, resolve the problem, or create new ones • Start back at [1]

12. Percentage vs. Years to Completion for Multiple Disciplines and Pace DPS • Data shows a higher level of completion for Pace DPS students in the first three to five years of study, while some of the other programs do not show their students completing until the six to eight year mark. • While Pace DPS students tend to complete their degree earlier as compared to traditional programs, the Pace faculty are always trying new methods to improve the completion rate and the dissertation quality

13. Key Conclusions • We found that because the Pace DPS program leverages professional experience in the program, this enables quicker completion whereas non-agile programs spend anywhere from three to five years preparing students with basic coursework before they even begin the dissertation process. • When speaking with several of the traditional institutions, we also found that they seek and attract a much different type of doctoral candidate. Most institutions would not allow students to have careers or full time jobs, required residential status, and required students to teach during their program. • Moreover, the dissertation process was mostly self-guided, instead of a true collaborative work as it is in the Agile research and dissertation process.

14. Future Work • Survey tool sent to all DPS students (alumni and current) asking them about their satisfaction with the program, if they would suggest the program to other perspective students, and suggestions for possible improvement of the DPS program. • Additional research around graduation and attrition statistics. Due to the lack of response from many of the researched institutions, it was difficult to obtain a consistent set of statistics across the boardfrom public, private, and online institutions.

15. Author List - DPS Class of 2016 • Gilbert Alipui • Claude Asamoah • Richard Barilla • Leigh Anne Clevenger • Alecia Copeland • Sam Elnagdy • Hugh Eng • Michael Holmes • SaravananJayaraman • Kevin Khan • Steven Lindo • Javid Maghsoudi • Mantie Reid • Michael Salé

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