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    Dakota State University
   
 
  Nov 21, 2017
 
 
    
Graduate Catalog 2017-2018

Information Systems, D.Sc.


Program Description

The Doctor of Science (DSc) in Information Systems is designed to prepare individuals for careers in research, teaching and corporate employment. This program emphasizes applied scholarship, focusing on multi-disciplinary research projects with a strong emphasis on the productive application of information systems and information technology to organizations and their management. The program supports a thriving and sustained applied research program that meets the research needs of the State of South Dakota, the university, and its graduate students. The degree program is intended to produce graduates with a commanding knowledge of information systems and of applications and research in information systems. Graduates of the program will be qualified to pursue careers in:

  • teaching and research within an academic setting.
  • applied research within a corporate setting or government agency.
  • industry, particularly in data-intensive industries such as the banking and finance industry in the state, or within other data-intensive corporations.

Program Completion

The program can be completed on a full-time or part-time basis, with classes offered in three academic terms: fall, spring, and summer. Full-time students with a master’s degree in information systems should be able to complete this program in 3 years. The program must be completed within 7 years of the semester of their admission. Students who do not meet the academic requirements for admission may be required to complete up to 12 additional hours of foundational coursework.

Admission Requirements Specific to the DSc in Information Systems

Dakota State University seeks highly motivated individuals with education and professional credentials that will enable them to be successful doctoral students. Students who do not meet the academic requirements for admission may be required to take up to 12 additional hours of foundational coursework.

DSc Admission Requirements

  1. Baccalaureate degree from an institution of higher education with full regional accreditation for that degree. International students must have an undergraduate (bachelor’s) degree that is the equivalent to a four-year undergraduate degree in the U.S. Students who enter the program with graduate coursework in disciplines related to information systems may have to complete some master-level information requirements. Students who enter the program without a master’s degree in information systems or related field and without an undergraduate background in information systems will be required to complete a series of foundational courses.
  2. Minimum undergraduate grade point average of 3.0 on a 4.0 scale (or equivalent on an alternative grading system).
  3. Essential knowledge in both business fundamentals and information systems. This knowledge includes the following:
    • that they can analyze organizational systems and take appropriate action with particular business structures, particularly overcoming resistance to change;
    • organizations, and the role of IT professionals in developing, acquiring and managing IS;
    • systems including, setting a direction for information resources, managing technology resources, and managing the information systems function; (Windows and UNIX);
    • ability to use spreadsheets for computations and analysis;
    • understanding of the principles of programming and the ability to program.

The knowledge requirement can be met in a variety of ways, including: an undergraduate degree in MIS; specific undergraduate or graduate coursework that covers required knowledge; appropriate, verifiable IS/IT or management experience. Students using experience to meet the knowledge requirements may be required to demonstrate competency in the subject. Students who have not had appropriate coursework or acceptable experience to meet the knowledge requirements will be admitted to the program if they meet the other minimum requirements. However, these students will be required to meet the knowledge requirement by satisfactory completion of specified knowledge support courses as part of their program of study.

Entry-Level Knowledge Requirements

Students who enter the program with graduate coursework in disciplines related to information systems may have to complete some foundational and masters-level information systems requirements. Students who enter the program without a master’s degree in information systems or related field and without an undergraduate background in information systems will be required to complete a series of foundational courses prior to being admitted to the program in addition to the 27 credits in information systems at the master’s degree level. Foundational courses include:

Program Faculty:

Richard Christoph, Dorine Bennett, Omar El-Gayar, Steve Graham, Tom Halverson, Stephen Krebsbach, Jun Liu, Insu Park, Josh Pauli, Wayne Pauli, Ronghua Shan, Kevin Streff, Daniel Talley

Program Requirements

The program can be completed on a full-time or part-time basis, with classes offered in three academic terms: fall, spring, and summer. Overall, the program requirements for the DSc in Information Systems include a total of 88 semester credit hours:

  • 63 credit hours of graduate coursework:
    • 27 credit hours of master’s level information systems which may be waived for students with an MSIS degree
    • 9 credit hours of research methods
    • 27 credit hours of research specialization including research seminars, and core and electives courses
  • Comprehensive examination
  • Qualifying portfolio
  • 25 credit hours of dissertation

Courses supporting the DSc Program


The doctoral curriculum assumes that a student enters the program with a master’s degree in information systems or a related field. Students who enter the program without a master’s degree in information systems (MSIS) or a related field will be required to complete up to 27 credits at the master’s degree level: 18 credits in information systems core courses and 9 credits of elective coursework in one of the five specializations currently offered by DSU. Students who enter the program with graduate coursework in related disciplines may have to complete some of these requirements.

Information Systems Masters Specialization (9 cr. hrs)


Students must choose one of the five specializations below to complete.

General


Students select one course from the Application Development Specialization, one course from the Network Administration & Security Specialization and one course from the Data Management Specialization to obtain the General Specialization.

General Specialization - Application Development

Select one course from the Application Development Specialization list below.

General Specialization - Network Administration & Security

Select one course from the Network Administration & Security Specialization list below.

General Specialization - Data Management

Select one course from the Data Management Specialization list below.

Research Specializations (27 cr. hrs.)


The curriculum includes three research specializations. The specializations each include 27 credit hours:

  • 3 required courses (9 credits)
  • 6 seminar courses (6 credits total at 1 credit each, taken each semester in which the student is enrolled)
  • 4 elective courses (12 credits)

The required and elective courses within each specialization are intended to provide a coherent body of knowledge in support of the student’s research agenda/career plans. The research seminars are intended to acquaint students with contemporary information systems research issues.

Specialization 1: Analytics and Decision Support


Specialization 2: Healthcare Information Systems


Specialization 3: Information Assurance and Computer Security


Research Seminar Courses (6 cr. hrs.)


Students complete a total of six credit hours of the research seminar topics course (INFS 890 ) for one credit, each time they register until all six credits are successfully completed. The seminar is to allow students in the DSc (IS) program to report, present and discuss research articles on specific topics in their areas of specialization as well as their own research, and thus provide a solid foundation for their dissertation. Students are encouraged to enroll in INFS 890  sections immediately at the beginning of the program and continue enrolling for one seminar course in the subsequent semesters (including summer) until all the six seminar course requirements are completed. This will enable them to get a broader perspective on different research topics, while also improving their presentation abilities and completing the requirements of the DSc program in a timely manner.

Specialization Electives: Select four (12 cr.) courses


Select four (12 cr.) courses from the specialized list of electives below based on students elected specialization.

Research Methods Courses (9 cr. hrs.)


The research methods courses are designed to provide students with a basic background in information systems research as well as a strong foundation in information systems research methodology, including quantitative, qualitative and design research methods.

Dissertation (25 cr. hrs.)


Students complete 25 credits of dissertation work (INFS 898D ).

Course Grades


Course Grades are used as an indirect measure of student attainment of specific program goals and objectives. DSU guidelines require students to maintain a 3.0 GPA in the program, receive no grades below a C, and have no more than 2 grades of a C. If you do not maintain the required “B” average you will be placed on academic probation and given the opportunity to raise your GPA to 3.0 within the next nine credit hours. If you do not raise your GPA to 3.0 you will be suspended from the program. If you receive more than 6 credits of “C” or any grade lower than a “C” you will be suspended from the program. You may appeal the suspension. If students have questions regarding grading, they should review the Satisfactory Progression Guidelines or speak with their advisor.

Assessment/Evaluation Activities


The D.Sc. program committee and a student’s research advisory committee will evaluate the student’s progress using these three evaluation methods: comprehensive examination, qualifying portfolio, original research and dissertation defense.

  • Comprehensive Examination
  • Portfolio
  • Dissertation

D.Sc. Comp Exam Guidelines


DSc Comprehensive Examination Guidelines

The objective of the DSc comprehensive examination is to assess the student’s knowledge of information systems literature, particularly in their area of specialization and as well as their understanding of information systems research methods and ability to conduct research and evaluate research results. The comprehensive exam is a significant milestone towards determining the students’ readiness to undertake independent research.
The comprehensive examination will consist of the following components:

  1. Written comprehensive course exam
  2. Oral comprehensive course exam

Prerequisites

  • Students should have completed the MSIS core or equivalent courses.
  • Students should have completed the coursework in the following research specialization:
  1. Analytics and Decision Support
    INFS 838 : Decision Support and Knowledge Management Research (3 credits)
  2. Information Assurance and Computer Security
    INFS 848 : Information Assurance and Computer Security Research
  3. Healthcare Information Systems
    INFS 868 : Health Informatics Research
  • Students should have completed 9 credits of research methodology coursework, as follows:
  1. INFS 805 : Design Research Methods
  2. INFS 810 : Qualitative Research Methods
  3. INFS 815 : Quantitative Research Methods
  • Students should have completed 3 credits of research seminar (INFS 890 ).

Written comprehensive course exam

Structure

The written comprehensive course exam will consist of 4 sections, each worth 100 points (total points: 400), based on the 1 research specialization course and 3 research methodology courses mentioned in the comprehensive exam prerequisites. Each section may contain multiple questions. The exam on each section will test the readiness of the students to undertake independent research and thus may be significantly different than the corresponding course exam. The examination will be open book, open notes. Students will have the flexibility of distributing their time and effort on each section during the overall test period. Email or other such mechanism will be used for sending and receiving the exam.

Timeline

Students must schedule their written comprehensive course exam no earlier than the semester in which they will be completing the prerequisites for the comprehensive exam. The written comprehensive course exam will be held twice a year. It will be scheduled on the weekend following the finals week for the Fall and Spring semesters, starting on Friday at 5:00 p.m. and due on the following Monday at 8:00 a.m. No written comprehensive course exam will be scheduled in the summer semester. The results of the written comprehensive course exam will be provided to the students in 3 weeks following the exam.

Evaluation

The written comprehensive course exam will be evaluated by an examination committee. Students will be given a pass/fail grade on each section. Students passing all the sections of this exam would be considered as an overall pass in the written comprehensive course exam. If a student fails one or more sections, he/she may re-take the exam for that section in the following semester or when it is offered the next time. There will be a maximum of 2 attempts for appearing for the exam for each section. Failing to successfully pass each of the sections (with a maximum of 2 attempts per section) will result in not advancing towards the DSc degree.

Oral comprehensive course exam

Structure

The oral comprehensive course exam complements the written component of the exam. The comprehensive exam committee members will ask questions based on the student’s coursework on research methodology and research specialization and may ask the student to comment on their answers in the written comprehensive exam.

Timeline

The exam will be held within two weeks from completing the written comprehensive exam. The Office of Graduate Studies and Research in conjunction with the exam committee will schedule the exam for individual students.

Evaluation

The oral comprehensive course exam will be evaluated by the comprehensive examination committee based on the student’s fundamental and applied knowledge about the issues covered in the research methodology and research specialization courses. Students will be given a pass/fail grade for this component. Failing to successfully pass these components (with a maximum of 2 attempts per component) will result in not advancing towards the DSc degree.

Overall Evaluation

Students passing both components of the comprehensive exam will be considered as an overall pass. There will be a maximum of 2 attempts for any of the components.

DSc Research Seminar


DSc Research Seminar Guidelines

The objective of the research seminar topics course (INFS 890 ) is to allow students in the DSc (IS) program to report, present and discuss research articles on specific topics in their areas of specialization as well as their own research, and thus provide a solid foundation for their dissertation. This seminar will be open for all interested faculty and students who wish to attend and participate in the discussions.

Prerequisites

None

Structure

Each research seminar topics course will be of 1 credit hour with S (satisfactory) / U (unsatisfactory) grade, counting towards the DSc (IS) program requirements. Students will be required to complete 6 research seminar topic courses with an S (satisfactory) grade in each of these courses in order to meet the DSc (IS) program requirements. Students must have completed at least 3 credit hours of research seminar topics courses before attempting the DSc comprehensive examination. Also, students must have completed the requirement of 6 credit hours of research seminar topics courses before scheduling their final dissertation defense. The procedural details of the research seminar would be as follows. Each section of INFS 890  would have a faculty supervisor assigned for each semester. The supervisor would be responsible for the logistics of the course, such as providing a potential reading list, coordinating student presentations, managing discussion forums, and grading. Each section of the course would consist of students’ presentations on different, but possibly related topics. The nature of the presentations in each section may differ and will be decided by the faculty supervisor. Students may be asked to present their own research (either work-in progress or based on a recent conference or journal publication) or a comprehensive literature review on a topic of their interest highlighting contemporary research issues. Alternatively, a list of key articles in a particular area may be provided and students will be asked to present articles from this reading list. Other articles may be included for presentation upon discussion with the faculty supervisor. These research seminars will provide an excellent opportunity for students to get feedback from their peers and faculty. To successfully complete each research seminar course, each student would be required to submit a written report based on the presentations conducted in that section of the course. Other related details such as focus/format of presentations, length of presentations, format/length of written report, will be provided by the faculty supervisor in each section of the course.

Presentations would be conducted synchronously for both on-campus and off-campus students through use of appropriate distance learning technologies. Presentations may be recorded and made publicly available for later reference. Asynchronous discussions on presentation topics may be enabled using discussion forums or wikis or related technologies.

Timeline

Students are encouraged to enroll in INFS 890  sections immediately at their beginning of the program and continue enrolling for one seminar course in the subsequent semesters (including summer) until all the six seminar course requirements are completed. This will enable them to get a broader perspective on different research topics, while also improving their presentation abilities and completing the requirements of the DSc program in a timely manner.

Evaluation

Each student would be evaluated by the faculty supervisor and provided an S (satisfactory) or U (unsatisfactory) grade at the end of the semester. Sections with a U (unsatisfactory) grade will not count for completion of the DSc (IS) program requirements. Key criteria for grading would include student presentation abilities (key points coverage, research perspectives on the topic, presentation skills), and student participation through in class discussions and/or discussion forums, in addition to any other criteria set by the individual faculty in charge.

DSc Portfolio Guidelines


The objective of the DSc portfolio is to provide a structured way for students enrolled in the DSc (IS) program to demonstrate their abilities to perform research, teaching, and service related activities that can hold them in good stead in their post-doctoral careers.

Prerequisites
None

Structure of the DSc Portfolio

Research will be the primary focus area of the DSc portfolio with either service or teaching as a secondary focus area. The final deliverable of the portfolio should include a summary report comprising of two main sections: (1) research, (2) teaching, or service. Each section should contain two main subsections. First sub-section should depict the philosophy/perspective of the student towards that area. For example, research philosophy should include the student’s research interests, research methodologies adopted, how his work fits within his areas of interest, his/her vision for next few years, and so forth. Second sub-section should summarize the student’s work and  contribution in that area. The summary report should also have two appendices, namely A for research, and B for teaching or service. The appendices should contain evidential information and documents related to the work described in the three sections of the summary report. These documents should be referred to at appropriate places in the main summary report, rather than merely attaching a stack of documents as appendices. The contents of each section would be specific to the student’s work in the relevant area, namely, research, teaching, or service. The evaluation rubric provides a list of potential activities and their evaluation that may serve as a guideline to begin work in each of these areas is provided. Students may engage in other related activities as part of their portfolios upon approval of their dissertation committee members.

Timeline

Students enrolled in the DSc (IS) program are expected to begin work on building the portfolio from their first semester into the program. As part of this effort, they should continually document and summarize their research, teaching, and service related activities during their tenure in the doctoral program. Students must submit the completed DSc portfolio at least one semester before the intended final dissertation defense. The dissertation committee will provide feedback within a month of submission of the portfolio. The portfolio must be approved by the committee in order to attempt the final dissertation defense. This will allow adequate time for review, performing additional activities recommended (if any), and final approval from the committee.

Evaluation

The dissertation committee, chaired by the dissertation chair, will jointly decide if the DSc portfolio requirements have been satisfactorily met. If the portfolio is not approved by the committee members, students will need to revise and resubmit the portfolio after addressing the recommendations provided by the committee members. The overall grade for the portfolio will be given based on the following guidelines.

  • Meet expectations: Meets expectations on research and any one of teaching or service.
  • Needs improvement: Fail to meet expectations requirements

Requirements and evaluation guidelines for each of the three focus areas are given below.

Research

This category will be graded based on the following guidelines.

  • Meet expectations: Meets expectations on at least 2 of the research artifact categories
  • Needs improvement: Fail to meet expectations requirements
    Research artifacts Meet expectations
    Refereed journal publications
    • 1
    Refereed national or international conference/workshop papers
    • 2 papers with at least 1 paper in the following conferences: ICIS, WITS, AMCIS, HICSS, DSI, AAAI
    • Student must be the first author on at least 1 paper
    Refereed book chapters
    • 1
    Refereed extended abstracts/posters /demonstrations/regional conference papers/doctoral consortium papers
    • 2
    • Student must be the first or second author on the research artifacts

Teaching

This category will be graded based on the following guidelines.

  • Meet expectations: Meets expectations on at least 1 of the teaching artifact categories
  • Needs improvement: Fail to meet expectations requirement
    Teaching artifacts Meet expectations
    Instruct graduate or undergraduate IS related courses
    • Instructor for 1 course
    Teaching assistant for graduate or undergraduate IS related courses
    • Teaching assistant for at least 1 course
    Refereed teaching cases
    • 1

Service

This category will be graded based on the following guidelines.

  • Meet expectations: Meets expectations on at least 1 of the service artifact categories
  • Needs improvement: Fail to meet expectations requirements
    Service artifacts Meet expectations
    Reviewer for refereed journals
    • 1
    Reviewer for refereed conference/workshop papers
    • 2 papers with at least 1 paper for the following conferences: ICIS, WITS, AMCIS, HICSS, DSI, AAAI
    Reviewer for refereed book chapters
    • 1
    Reviewer for extended abstracts/posters/demonstrations/regional conference papers/doctoral consortium papers
    • 2
    Volunteer in organizing an academic gathering (conference, workshop, etc.)
    • 1

DSc Dissertation Guidelines


DSc Dissertation Guidelines

The objective of the DSc dissertation is to assess the student’s knowledge of information systems literature, particularly in their area of specialization and their ability to successfully conduct independent research in information systems.
The dissertation requirement will consist of the following components:

  1. Dissertation proposal report and presentation
  2. Final dissertation report and presentation

I. Structure of the Dissertation Committee

Students should form a dissertation committee as early on in the program as possible. Please refer to DSU Guidelines on “Dissertation/Thesis/Project Committees” regarding detailed requirements of a dissertation committee. As part of the dissertation committee, the student must also select the dissertation chair or co-chairs, who will be the primary guide(s) during the dissertation process.

II. General Guidelines and Requirements

  • A total of 25 dissertation credit hours are required for meeting the program requirements. Students may take dissertation credits anytime during their tenure as doctoral students with the approval of their academic advisor or dissertation committee chair or co-chairs. However, students should not exceed maximum credit hours per semester as outlined in the DSU Guidelines on “Graduate Enrollment Status and Course Load”.
  • Students who have completed the 25 dissertation credit hours, but have not yet successfully defended their dissertation will need to register for additional dissertation credits every semester until they graduate from the program.
  • Upon forming the dissertation committee, the student must first work on formulating a dissertation proposal to be submitted and presented for approval as outlined in Section III (Dissertation Proposal) in this document.
  • Students are expected to demonstrate the ability to conduct independent research during the dissertation process. This includes taking self-initiative in leveraging and carefully managing available resources such as library, committee members’ knowledge and expertise, in addition to managing their own time and efforts.
  • Students are responsible for managing the expectations of the dissertation committee members. To facilitate this process, it is suggested that the student take the initiative in developing and following a feasible and mutually agreed upon communication plan between himself/herself and the committee members. Depending on the role of the dissertation member, the communication plan may be unique for each member. Following is a recommended reading regarding how to manage the dissertation process: Davis, G. B., & Parker, C. A. (1997). Writing the Doctoral Dissertation: A Systematic Approach (2nd ed.). Hauppauge, New York: Barron’s Educational Series, (ISBN: 978-0812098006).
  • Please review DSU Policies 01-20-00 on “Research-Based Data Collection and Release Policy” and 04-03-00 on “Use of Human Subjects in Research at DSU”. Compliance with these policies is critical, and must be done BEFORE any data is collected. As mentioned in the policies, any student using human studies must clear their research through DSU’s Institutional Review Board (IRB). In addition, prior to any data collection, you must also take the online training program for researchers by the Collaborative Institutional Training Initiative (CITI). Failure to comply with DSU Policies 01-20-00 and 04-03-00, and to take the online program mentioned above will have serious consequences including jeopardizing the student’s degree.
  • Students are encouraged to attend doctoral consortiums (at least one), in order to be able to present their research, gain feedback, interact with peers and faculty from other institutions, and gain some visibility. Most of the conferences in the field of IS (including AMCIS and ICIS) conduct such consortiums on an annual basis.
  • Students are required to ensure that their dissertation is free of grammatical errors and meets academic English language writing standards. See, for example, “Academic Writing for Graduate Students”, 2nd edition, (2004) by Swales and Feak.
  • A generic guide to writing dissertations is available online, this guide provides descriptive guidelines on writing social science oriented dissertations. A similar procedure may be adapted for design science oriented dissertations. The classic article published in MIS Quarterly by Hevner, March, Park, and Ram (2004) provides a framework for such research. Additionally, detailed guidelines and evaluation metrics for the dissertation are provided in Section IV (Final Dissertation). Students should refer to these guidelines and evaluation metrics throughout the dissertation writing process. They should also consult with their dissertation committee to discuss how each of the main requirements can be met.

III. Dissertation Proposal (Report and Presentation)

Structure

The dissertation proposal is an integral part of the overall dissertation process. It is expected that students begin working on their dissertation proposal early on in their tenure as doctoral students. Students should work closely with their dissertation committee chair and other committee members in formulating the dissertation proposal.
The dissertation proposal report should contain a detailed description of the specific dissertation project the student intends to undertake. The proposal should identify a significant problem in the field of research, clearly formulate the research question(s)/problem(s), summarize the current knowledge in the form of a thorough review of relevant literature, present proposed/developed IT artifact(s) (system design, research model, etc.), justify and explain the research methodology/validation mechanism to be adopted, describe the expected results and practical contributions, and clearly present the future research plan/steps and timeline.

Report Format:

The dissertation proposal report should not exceed 15 pages, and should meet the following formatting requirements: 1.5 line spacing, Times New Roman font, font size 12, APA style formatted references and citations (select APA 6th style in EndNote).
While all proposal reports are expected to have an introduction and a literature review section, the rest of the sections may vary depending on the nature of your proposal and the requirements of your committee.

For design science oriented dissertation proposals, the proposal report may consist of the following sections:

  • Introduction
  • Literature review
  • Theory and artifact design
  • Implementation and validation methods
  • Expected results, contributions and discussion
  • Future research plan and timeline

For social science oriented proposals, the proposal report may consist of the following sections:

  • Introduction
  • Literature review
  • Proposed research model
  • Research methodology/design
  • Expected results, contributions and discussion
  • Future research plan and timeline

Presentation Format:

The dissertation proposal presentation will consist of the student giving a 30 minute public presentation (briefing the dissertation proposal) to the dissertation committee, followed by 30 minute question-answer period (10 minute public QA+20 minute committee QA). The dissertation committee will ask questions during and/or after the student’s presentation based on the dissertation proposal. Presentations would be conducted synchronously for both on-campus and off-campus students through use of appropriate distance learning technologies.

Timeline

Students may work on formulating the idea, writing the dissertation proposal, seeking and incorporating feedback from their dissertation committee members anytime during their tenure as doctoral students. However, students must propose a dissertation proposal defense date only after successfully completing all sections of the DSc Comprehensive Exam. A minimum of two weeks’ notice is required for scheduling the dissertation proposal presentation/defense. Students are responsible to ensure availability of all committee members on the proposed proposal presentation (defense) date. Students must formally submit their dissertation proposal report to their dissertation committee members at least 1 week prior to their proposed dissertation proposal presentation.

Evaluation

The dissertation proposal (report and presentation) will be evaluated by the student’s dissertation committee. Students will be given an overall pass/fail grade for the dissertation proposal (report and presentation). Failing to successfully defend the dissertation proposal in a maximum of 2 attempts will result in not advancing towards the DSc degree.
In addition to the overall quality of writing and presentation, the dissertation proposal will be evaluated based on the following key criteria:

  • Problem statement
    • Is the problem statement clearly defined?
    • Is the research problem well motivated? Does the author include supporting data/references to show the importance of the problem?
    • Is the research problem interesting and current? Are there recent publications addressing the general research area?
  • Literature review
    • Is the literature review comprehensive and complete?
    • Does it include obvious and highly relevant references?
    • Does the literature review include current and latest developments in the area?
    • Is the literature review well organized? Does the author use tables or other artifacts to categorize or summarize the literature review?
  • Research Model/IT Artifact
    • Is the research model/IT artifact clearly articulated and described?
    • Does the research model/IT artifact have a sound theoretical base?
    • Is the research model/IT artifact logically derived from theory and past literature?
  • Methodology
    • Is the methodology clearly described?
    • Does the methodology section includes relevant details regarding experiment/survey/case study design and instruments/interview protocols if employing quantitative and qualitative research methods?
    • Does the proposal include appropriate validation mechanism suited to the research problem under consideration, if employing design science research methods?
  • Originality and Impact - The following points clarify the nature of an original contribution.
    • Something that has not been done, found, known, proved, said, or seen before that results from:
      • Asking or identifying new questions, topics, or areas of exploration
      • Applying new ideas, methods, approaches, or analyses to an old question, problem, issue, idea, source, thinker, or text
      • Developing or applying new theories, theorems, theoretical descriptions, or theoretical frameworks
      • Inventing, developing, or applying new methods, approaches, computations, techniques, or technologies
      • Creating, finding, or using new data, data sets, archives, information, materials, or sources
      • Applying old ideas, methods, approaches, or analyses, to new data, material, or sources
      • Developing or applying new analyses, analytic approaches, frameworks, techniques, models, or statistical procedures
      • Coming up with new ideas, connections, inferences, insights, interpretations, observations, perspectives
      • Producing new conclusions, answers, findings, or proofs
    • Is publishable
    • Adds to knowledge
    • Changes the way people think
    • Moves the field forward/advances the state of the art

IV. Final Dissertation (Report and Defense)

Structure

The final dissertation report and defense are the culmination of the student’s research effort. The report serves as permanent record and documentation of the student’s research effort while the proposal assesses the student’s ability to present and defend their research contributions. Students should work closely with their dissertation committee chair and other committee members throughout the dissertation process.
The final dissertation report follows the general structure described earlier for the dissertation proposal report (See Dissertation Proposal above). In addition to providing a detailed description of the specific dissertation project, the final dissertation report include a detailed account of research findings, discussion of the findings, theoretical and practical contributions, and clearly present the future research plan/steps and timeline.

Report Format:
The final dissertation report has no page limit. The dissertation format must be based off of the D.Sc. Dissertation Template MS Word document available in the Portal under D.Sc. Forms and Documents (see “Dissertation Template”). It is important that you use APA style for formatting references and citations (select APA 6th style in EndNote).

_________________________________________

1 Adopted from Lovitts, B. E. (2007). Making the Implicit Explicit: Creating Performance Expectations for the Dissertation. Stylus Publishing, LLC., Virginia, USA. (pp.191-195).

Presentation Format:
The final dissertation defense is an open ended public presentation, in which the student presents the findings of their research. The dissertation committee and the public may ask questions during and/or after the student’s presentation based on the material presented and the final dissertation report. Presentations would be conducted synchronously for both on-campus and off-campus students through use of appropriate distance learning technologies.

Timeline

  • Students should submit an “Application for Graduation” by the census date of the semester of their intended graduation as outlined in the DSU Guidelines on “Application for Graduation”.
  • The dissertation committee requires four weeks to review the final draft. Within the four-week timeframe, committee members will submit comments to the candidate and notify the dissertation chair or co-chairs about the student’s readiness to defend.
  • The dissertation committee chair/s will work through comments with the candidate and inform the candidate of the readiness to defend.
  • Once permission is provided, candidate needs to confirm a defense date (within 2 weeks after permission is given) and notify the Office of Graduate Studies and Research of the proposed final defense date. The final defense date must meet the deadlines for final defense date for the corresponding semester (10/31 for Fall semester, and 3/31 for Spring semester) set by the Office of Graduate Studies and Research. Students are responsible to ensure availability of all committee members on the proposed defense date. A minimum of two weeks’ notice is required.
  • Students must submit the approved dissertation to the Office of Graduate Studies and Research by the final dissertation submission deadline (11/30 for Fall semester, and 4/30 for Spring semester).
  • Students must allow enough time for the dissertation review, revisions, and final defense scheduling during the semester they plan to graduate. It is recommended that they decide on a tentative dissertation defense date as early as possible in the semester they plan to graduate.

Evaluation

Following the public presentation, the dissertation committee will evaluate the dissertation based on the metrics/guidelines mentioned in Section VI (Dissertation Evaluation Guidelines), which extend upon the dissertation proposal evaluation guidelines mentioned in Section III (Dissertation Proposal). It is recommended that students use these guidelines/evaluation metrics keeping in the mind the following suggestions:

  1. It is recommended that students use the rubric/evaluation guidelines throughout the dissertation process to help develop a dissertation of outstanding quality.
  2. Note that not all the metrics mentioned in the rubric apply to every dissertation. The student, in consultation with the dissertation chair, should identify relevant metrics from the rubric to help guide evaluate and improve the quality of their dissertation.
  3. Design science oriented dissertations use the format discussed in Table 1, while social science oriented dissertations should use the format discussed in Table 2.
  4. For design science oriented dissertations, the theory section of the design science dissertation rubric evaluates the theoretical basis and design of the artifact, while the method section of the rubric evaluates the implementation and validation of the artifact. The results and analysis section evaluates the outcome and analysis of the IT artifact validation process.

V. References

Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75-105.

VI. D.Sc. Dissertation Evaluation Guidelines2

Table 1. The components of a design science oriented dissertation and their characteristics at different quality levels

Components Quality Levels
Outstanding Very Good Acceptable Unacceptable
Introduction
  • Well written.
  • Captivating.
  • Provides motivation and establishes the importance of the problem and places it in context.
  • Presents a very clear and concise statement of the problem, results, conclusions, and contributions.
  • Lays out the plan for the dissertation.
  • Writing is good.
  • Motivates the work but does it less well and is not captivating.
  • Clearly describes what the problem is and why it is important.
  • Starts with the big picture and narrows it down to the point being made.
  • Indicates what the contributions are.
  • Not well written (has missing components).
  • The ideas seem to be there.
  • Is narrower in scope.
  • Problem is not stated.
  • Includes a lot of extraneous material.
Literature
Review
  • Complete, comprehensive, up to date, organized, and coherent.
  • Has nice logical structure.
  • Provides a critical look at the problem
  • Supports the statement of the problem and the statement of the contribution.
  • Puts the work in context of what has been and being done.
  • Shows a good understanding of the state of the art.
  • Discriminates between important an un-important papers.
  • Identifies gaps in the literature.
  • States limitations of previous work.
  • Simplifies and discusses very complex papers.
  • Summarizes and ties together all the different methods people have been employing, using a common notion.
  • Provides detailed examples of existing methods.
  • Is a contribution in and of itself.
  • Educates the reader.
  • Written at the appropriate level of depth with the appropriate amount of references.
  • Good enough.
  • Pretty comprehensive, but may be missing a few important works.
  • Shows that there are holes in the literature with respect to the problem.
  • Inadequate or missing.
  • Does not provide a context for or relate to what the student is doing.
  • Omits a lot of important material.
  • Cites work that the student has not read.
  • Plagiarizes articles.
Theory
  • Creative, insightful, elegant, and significant.
  • Conceived and presented logically and correctly.
  • Takes theory beyond the literature.
  • Develops a new theory.
  • Is or provides mathematically correct foundation for the research.
  • Appropriate, complete, and correct.
  • Build on existing theory.
  • Ties the project together.
  • Defines where the theory works and where does it not.
  • Presents a lot of theory that is never used.
  • Assumes away all the difficulties.
  • Omitted.
  • Does not understand or justify the theory.
  • Uses theory inappropriately.
Methods
  • Provides a comprehensive description.
  • Has a simple, complete, elegant approach.
  • Exhausts all possibilities.
  • Combines theory and methods.
  • Has a balanced use of theory, experiments, and simulations.
  • Uses existing theory to develop methods for useful applications.
  • Seizes new tools and applies them to the problem.
  • Demonstrates things through examples or simulations.
  • Compares chosen method against existing methods.
  • Discusses its advantages and disadvantages.
  • Identifies why the student chose the method.
  • States all the assumptions.
  • Indicates the range of parameters over which the method will work.
  • Tests hypotheses experimentally or with simulations.
  • Precise and complete enough so others can replicate.
  • States what the student is trying to establish and how he or she will go about it.
  • Sequential process- does all combinations randomly.
  • May require major corrections.
  • Shoddy.
  • Lacks clear scientific deductive thinking.
  • Does not identify what is being measured or why.
  • Just a bunch of simulations.
  • Makes improper generalizations.
Results/data
analysis
  • Well written.
  • Clear, simple, and appropriate presentation of unambiguous results, contributions, applications, limitations, and impact.
  • Insightful.
  • Very repeatable.
  • Measurements have high degree of precision.
  • Documentation supports the precision, accuracy, and reliability of the results.
  • Has statistically and observably significant usable results.
  • Results, including unexpected results, match or support the theory.
  • Graphically displays carefully selected variables and results.
  • Draws proper conclusions and makes proper inferences.
  • Theory and results correspond.
  • Provides an explanation for the correspondence.
  • Sufficient.
  • Measurements, theory, and analysis align.
  • Does not justify the claim it works better than something else.
  • Needs major revisions.
  • Data are inaccurate, fudged, or falsified.
  • Selectively presents only supporting data.
  • Has lots of tables but no analysis or discussion of the contribution.
  • Provides evidence that it works only one little narrow situation.
  • Student does not understand the results.
  • Draws conclusions based on very little data.
Discussion
and conclusion
  • Short summary that brings out major points and ties back to the introduction.
  • Contains lucid insights.
  • Places work within the context of the field.
  • Identifies contributions and applications as well as limitations and shortcomings.
  • Anticipates criticism.
  • Discusses future directions.
  • Good summary of results.
  • Clearly states contributions, possible applications, and future directions.
  • Not well done.
  • Provides some considerations for future work based on shortcomings of current work.

2 Adopted from Lovitts, B. E. (2007). Making the Implicit Explicit: Creating Performance Expectations for the Dissertation. Stylus Publishing, LLC., Virginia, USA. (pp.191-195).


Table 2. The components of a social science oriented dissertation and their characteristics at different quality levels

Components Quality Levels
Outstanding Very Good Acceptable Unacceptable
Introduction
  • Short, focused, creative, and very synthetic.
  • Has a hook.
  • States the problem and shows why it is interesting and important.
  • Explains the significance of the study.
  • Introduces the literature review.
  • Sets the context.
  • Locates the project on what has been done before.
  • Lays out a thesis and an organizational structure.
  • Provides a preview and a road map of where the research is going and what is in the coming chapters.
  • Well written, but less eloquent.
  • Poses a clear research question.
  • Expresses clarity of purpose.
  • Focuses on the key issues.
  • Is good, solid but not surprising.
  • Workmanlike.
  • Reasonably clear and focused.
  • Has a marginal hook but is not exciting.
  • Conveys what the research is about.
  • Shows understanding of the topic.
  • Provides an inking of the theoretical and methodological approach.
  • May leave something out but does not say anything
  • Nor grounded in anything.
  • Very defensive.
  • Tone is very politicized.
  • Takes inappropriate stances.
  • Goes off on incomprehensible tangents.
Literature
Review
  • Demonstrates a grounded understanding of the literature.
  • Provides reasons for looking at the literature differently.
  • Draws on literature in a convincing and supple way.
  • Brings together and summarizes a broad body of material and makes meaningful distinctions without being exhaustive.
  • Knows what needs to be cited and what does not.
  • Analysis is organized around themes.
  • Is succinct.
  • Indicates the significance of the research.
  • Provides a meaningful summary of the literature.
  • Includes both classic and recent citations.
  • Is not a laundry list of “Smith said this” and “Jones said that”.
  • Demonstrates a nuanced understanding of the literature.Takes a body of the material and leans it toward a particular direction.
  • Brings various intellectual resources to bear on the topic.
  • Builds a case for the research and for the hypotheses.
  • Is ill conceived or seems wrong.
  • Not analytical, integrated, or synthesized
  • A stacked annotation, “This person said this” and “This person said that”
  • Just regurgitates material.
  • Confusing.
  • Not clear why some literature is being cited and other literature is not.
  • Omits people who have done the same thing the student is doing.
  • Has not looked at commonly understood bodies of relevant literature.
  • Cites articles that are out of date.
  • Misinterprets the literature.
  • Misquotes major theorists.
  • Shows lack of understanding of the literature and where their research fits in the field.
Theory
  • Provides a good, logical, sensible, coherent argument.
  • Clearly indicates understanding of the major perspective.
  • Shows up in the introduction, literature review, and in the substantive parts of the dissertation.
  • Is in student’s own language.
  • Relates to other traditions and other ideas.
  • Evaluates a specific problem through a theoretical lens.
  • Evaluates different theories.
  • Sees multiple levels and multiple relationships.
  • Links observations to theory.
  • Uses conceptual ideas in a creative way.
  • Synthesizes theories.
  • Develops or creates theories
—-
  • Is weakly understood.
  • Does not specify assumptions.
  • Shows slippage between the conceptual apparatus and the problem.
  • No theory.
  • Completely unclear.
  • Ideas, theory, and material are not aligned.
Methods
  • Appropriate, clever, original, thorough.
  • Very well done.
  • Has basic validity.
  • Exhibits good judgment about what needs to be said and what can go in an appendix.
  • Connects questions and theory with methods.
  • Does something that ordinarily cannot be done.
  • Uses a novel method or multiple methods (triangulation).
  • Uses cutting-edge statistical techniques.
  • More workmanlike.
  • Does not provide lengthy definitions of techniques already in the literature.
  • Use of a different technique might have been more appropriate or made it more interesting.
  • Appropriate, competent.
  • No fatal flaws.
  • A rubber-stamped use of a textbook method.
  • Appropriate foe the problem.
  • Has basic validity.
  • Sample is large enough but barely.
  • Uses a very unusual group that does not represent the average.
  • Yields a reasonably accurate answer.
  • A different method might have been better.
  • Fatally flawed.
  • Mismatch between method and problem.
  • Does not seem to understand the method.
  • Uses method improperly.
  • The operationalization is inappropriate.
  • No clear relationships between hypotheses and variables.
  • Variables do not capture the concept.
  • No variance in one of the major variables.
  • Measures are not valid or reliable.
  • Statistical techniques are inappropriate or poorly explained.
Results/data analysis
  • Appropriate.
  • Uses advanced techniques.
  • Interprets data properly.
  • Sees complex patterns in the data.
  • Does a high level, iterative analysis of the data.
  • Uses tables, figures, charts, and maps to display the data cleverly.
  • Makes clear links between the conceptual apparatus and results.
  • Highlights the most important, original, and significant contributions.
  • Goes beyond supporting the argument and disproves common theories.
  • Data rich.
  • Provides plausible arguments.
  • Sees interrelations that are not obvious.
  • Has rich illustrations.
  • Analysis are well executed but not sophisticated or substantial.
  • Data are not rich.
  • Does not have enough substance.
  • Is not clear that the data are really evidence of the concepts.
  • Findings are null.
  • Provides too much information.
  • Loses significant and important findings in the midst of endless discussions of insignificant ones.
  • Includes every regression equations.
  • Marginal analysis of the data.
  • Student does not know why he or she uses the technique.
  • Uses advanced technique but sees nothing in the data.
  • Has obvious misinterpretations of the data.
  • Shows every iteration of the model, but cannot discern what is important.
  • Mindless presentation of the data without interpretation.
  • Uses graphic displays to create misleading perceptions.
  • Evidence does not support the argument.
  • Results do not follow from the analysis and are interpreted incorrectly.
  • Oversells or over- generalizes the results.
Discussion
and conclusion
  • Briefly summarizes what was done and reaches into new areas and different ways of seeing things.
  • Ties the whole study together.
  • Shows that the questions, methods, analyses, and findings are consistent.
  • Connects to the theoretical puzzles or debates they started with and takes them to another level.
  • Underscores the findings.
  • Discusses what is interesting and surprising about the results.
  • Recognizes the study’s strengths, weaknesses, and limitations.
  • Sees the big picture significance of the work.
  • Speculates on an provides an astute discussion of future directions.
  • Has implications for the subfield, sociology, or social science.
  • Discusses what is now known that was not known before.
  • Shows the limits of the research.
  • Indicates where future research might improve upon what was done.
  • Proposes logical follow-on research.
  • Focuses on very specific findings and neglects to bring out the general implications.
  • Restates what was already been said.
  • Summarizes rather than analyzes.
  • Overstates the results.
  • Does not see or generalize the big picture.
  • Indicates that further research is necessary but does not provide specifics.
  • Just a summary
  • No conclusions.
  • Takes a section out of the introduction and puts it in the conclusion.
  • Oversells the results.

DSc Oral & Written Comp Exam Preparation Tips


The comprehensive exam is designed to test your ability to conduct research. As opposed to the testing in individual courses, where only knowledge of the topics covered in a specific course is tested, the comprehensive exam is designed to test your ability to apply concepts learned across different courses to help develop and investigate Information Systems research questions and objectives.

  1. Start preparing for the comprehensive exam at least 2 months in advance.
  2. While the exam itself is open book, it is best to prepare for the exam assuming it is closed book. Given the length of the exam, you really would not have time on the day of the exam to refer to any books or notes.
  3. It can help if you prepare in advance 3 mini proposals in an information systems research area of interest to you, one using design research, another using quantitative research methods, and the third using qualitative research methods. This can help build your understanding of methodology as well as the research process to use for dissertation research, which is the focus of the comprehensive exam.
  4. Review latest IS research in your area of interest and be prepared to cite latest developments in your area of research from leading IS journals such as MISQ, JAIS, ISR, JMIS, DSS, ACM Transactions, IEEE Transactions etc.
  5. Be prepared to present a clear understanding of the theoretical basis of your research proposals (all 3) as well as potential contributions to theory and practice of such research.
  6. Develop an in-depth understanding of all 3 methodologies such that you can explain any methodological concept in the context of the area of your interest.

D.Sc. in IS Course Rotation


Knowledge Requirements


Required only of students who do not meet specific admission knowledge requirements.

Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 601 Information Systems X X   X X   X   X X
INFS 605 Information Systems Programming X     X     X     X
INFS 608 Applied Statistics X     X     X     X
INFS 614 An Introduction to Research X     X     X     X

Master's-Level Information Systems Core Courses


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 720 Systems Analysis & Design X X   X X   X   X X
INFS 724 Project and Change Management X X   X X   X   X X
INFS 730 Web Application Development   X X   X X   X X  
INFS 750 IT Infrastructure, Technology and Network Management   X X   X X   X X  
INFS 760 Enterprise Modeling, and Data Management X   X X   X X   X X
INFS 780 Information Technology Strategy and Policy   X X   X X   X X  

Master's Level Information Systems Electives (select one of five specializations)


Application Development


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 732 Emerging Technologies and Issues X     X     X     X
INFS 734 Multi-tiered and Service-Oriented Architectures   X     X     X    
INFS 736 Technology for Mobile Devices     X     X     X  

Network Administration & Security


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 752 Advanced Network Technology & Management     X     X     X  
INFS 754 Network Security and Intrusion Detection X     X     X     X
INFS 756 Cloud Computing and Network Services X     X     X     X

Data Management


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 762 Data Warehousing & Data Mining X   X X   X X   X X
INFS 764 Information Retrieval X     X     X     X
INFS 766 Advanced Database   X     X     X    

Healthcare Information Systems


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
HIMS 701 Foundations in Healthcare Information X     X     X     X
HIMS 742 Health Informatics, Information Systems, and Technology   X     X     X    
HIMS 744 Data Analytics in Healthcare     X     X     X  

General


Students select one course from the Application Development Specialization, one course from the Network Administration & Security Specialization and one course from the Data Management Specialization to obtain the General Specialization.

General Specialization - Application Development Rotation

Select one course from the Application Development Specialization list below.

ourse # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 732 Emerging Technologies & Issues X     X     X     X
INFS 734 Multi-tiered & Service-Oriented Architectures   X     X     X    
INFS 736 Technology for Mobile Devices     X     X     X  
General Specialization - Network Administration & Security Rotation


Select one course from the Network Administration & Security Specialization list below.

Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 752 Advanced Network Technology & Management     X     X     X  
INFS 754 Network Security and Intrusion Detection X     X     X     X
INFS 756 Cloud Computing and Network Services X     X     X     X
General Specialization - Data Management Rotation

Select one course from the Data Management Specialization list below.

Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 762 Data Warehousing & Data Mining X   X X   X X   X X
INFS 764 Information Retrieval X     X     X     X
INFS 766 Advanced Database   X     X     X    

Doctoral-Level Research Methods


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 805 Design Research Methods X     X     X     X
INFS 810 Qualitative Research Methods X     X     X     X
INFS 815 Quantitative Research Methods   X     X     X    

Doctoral-Level Research Specializations


Analytics and Decision Support


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFS 830 Decision Support Systems X     X     X     X
INFS 834 Knowledge Management   X     X     X    
INFS 838 Decision Support/Knowledge Mgmt Research   X     X     X    
INFS 890 Research Seminar Topics X X X X X X X X X X

Healthcare Information Systems


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
HIMS 744 Data Analytics in Healthcare     X     X     X  
INFS 820 Current Issues in Health Informatics   X     X     X    
INFS 868 Health Informatics Research   X     X     X    
INFS 890 Research Seminar Topics X X X X X X X X X X

Information Assurance and Computer Security


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFA 701 Principles of Information Assurance     X     X     X  
INFA 713 Managing Security Risks X     X     X     X
INFS 848 Info Assurance/Computer Security Research   X     X     X    
INFS 890 Research Seminar Topics X X X X X X X X X X

Specialization Electives: Choose 4 (12 cr.) courses


Choose four (12 credits) courses below from the appropriate electives list based on students chosen specialization.

Analytics and Decision Support Electives


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFA 713 Managing Security Risks X     X     X     X
INFS 762 Data Warehousing & Data Mining X   X X   X X   X X
INFS 764 Information Retrieval X     X     X     X
INFS 766 Advanced Database   X     X     X    
INFS 768

Predictive Analytics for Decision Making

X     X     X     X
INFS 770

Advanced Data Mining Applications

  X     X     X    

Healthcare Information Systems Electives


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
HIMS 746 Health Information Lifecycle Governance X     X     X     X
HIMS 747 Leadership and Management for Health Informatics X     X     X     X
HIMS 748 Research Design in Health Informatics   X     X     X    
INFA 713 Managing Security Risks X     X     X     X
INFA 715 Data Privacy   X     X     X    
INFS 762 Data Warehousing & Data Mining X   X X   X X   X X
INFS 764 Information Retrieval X     X     X     X
INFS 766 Advanced Database   X     X     X    
INFS 830 Decision Support Systems X     X     X     X
INFS 834 Knowledge Management   X     X     X    

Information Assurance and Computer Security Electives


Course # Course Title FA
17
SP
18
SU
18
FA
18
SP
19
SU
19
FA
19
SP
20
SU
20
FA
20
INFA 715 Data Privacy   X     X     X    
INFA 721 Computer Forensics   X     X     X    
INFA 723 Cryptography   X     X     X    
INFA 745 Compliance and Audit   X     X     X    
INFA 751 Wireless Security X     X     X     X
INFS 830 Decision Support Systems X     X     X     X
INFS 834 Knowledge Management   X     X     X