Course Information

Catalog Description

Student Learning Objectives

...From Prior Courses

Appropriate references and resources include those associated with prerequisite coursework and electives taken. Those sources—books, articles, assignments, projects, notes—reflect the knowledge and skills participants bring to this course and use to address course projects.

...Project Specific

Readings and resources applicable for this semester depend on the characteristics of chosen projects. The project selection and definition process incluees identifying readings and resources that correspond with those projects as well as the backgrounds of those working on the projects.

...General Recommendations

The following recommendations are applicable to projects typical of a computer science senior experience and to students who are entering computing professions.

• The Five Dysfunctions of a Team by Patric M. Lencioni, Jossey-Bass (2002)
  
• ACM Code of Ethics and Professional Conduct by ACM, acm.org (2021)
  
• Computational Thinking by Peter J. Denning and Matti Tedre, MIT Press (2019)
  
• Clean Craftsmanship by Robert C. Martin, Addison-Wesley (2022) [ISBN 9780136915713]
  
• Software Engineering Code of Ethics and Professional Practice by IEEE-CS/ACM, ieee.org (1999)
  
• The Pragmatic Programmer (20th Anniversary Edition) by David Thomas & Andrew Hunt, Pragmatic Bookshelf (2019)
  
• Where Research Begins: Choosing a Research Project That Matters to You by Thomas S. Mullaney & Christopher Rea, University of Chicago Press (2022) [ISBN: 9780136915713]
  (Recommended for Research Projects)
  

In an ideal world, the knowledge and practices of computer science would be objective. However, much of knowledge is subjective and representative of a small set of privileged voices. In this course we will draw on works and experiences of a diverse group of students, practitioners, and advocates. Even so, limits will still exist on this diversity. I acknowledge that it is possible that there may be overt and covert biases in material because of the lens through which it was created. Integrating a diverse set of experiences is important for a more comprehensive understanding of CS. I would like to discuss issues of inclusion and diversity in the computing professions as part of the course from time to time.

Furthermore, I would like to create a learning environment that supports diversity (of thoughts, perspectives, backgrounds, and experiences) and honors your identities (gender, class, sexual orientation, religion, ability, nationality, ethnicity, background, …). To help accomplish this:

• Please let me know your preferred name and set of pronouns if any, especially if this differs from what appears in your official MSU Denver records.
• If you feel like your performance in the class is being affected by your experiences outside of class, please don’t hesitate to talk with me. I want to be a resource for you. You can also submit anonymous feedback (via Moodle). If you prefer to speak with someone outside of the course, MSU Denver’s Campus Support Programs web page is a useful resource.
• I am continually in the process of learning and discovering diverse perspectives and identities. If I or a classmate says or writes something that makes you feel uncomfortable, please talk to me about it.
• As a participant in discussions, you also should strive to help include others and to honor the diversity of your classmates.

Preparation & Participation

You are expected to prepare for and to participate in all class activities and discussions both during and outside of the classroom. Participation in class activities and discussions is mandatory and constitutes part of the overall assessment of performance in the course.

Significant information is disseminated during class sessions or via the course websites. You are strongly encouraged to take notes and review them. You are responsible for knowing this information whether or not you attended the sessions and accessed the websites.

Successful computing practice is rarely, if ever, a solitary endeavor. Collaboration is a norm. As in the work environment, individual performance may be recognized but the entire team is judged by the team’s collective performance. Utilization of collaborative skills and practices is expected and comprises part of the assessment. The collective performance of a group comprises part of each individual’s grade.

Class Session Attendance

If you are not present...

• you are not contributing to the collaborative learning environment and the experiences of other participants.
• your team is missing a vital team member.
• your instructor is unable to provide real-time mentoring.
• your instructor is unable to assess your performance and credit your contribution to the learning environment and as a collaborative member of the team.

The team remains accountable whether you are there or not so please plan to attend. Please contact your instructor directly concerning special circumstances or needs for assistance.

Project teamwork requires meeting with your team members at times outside of the in-class time. While class time will be available for teamworking, it will not be sufficient. You must be willing and able to dedicate significant additional time outside of class to be successful.

Grading

The final course grade is determined based on the successful completion of assessments, detailed in class sessions and on the course websites, and computed by combining scores. These include active contribution to the group and class learning environments and outcomes associated with activities and projects. Peer evaluations of contributions are elicited in the team context.

Course letter grades are determined by the following conversion of achieved scores to letters.

      90%  ≤  A
      80%  ≤  B  <  90%
      70%  ≤  C  <  80%
      68%  ≤  C− <  70%
      60%  ≤  D  <  68%
              F  <  60%

Activities, assignments, and projects afford the opportunity to practice applying the concepts, to enhance understanding, and to demonstrate knowledge and the ability to apply it. During the course, students will:

• Consider potential projects and their feasibilities
• Create and deliver a project proposal
• Determine and justify an appropriate plan to achieve success in their chosen project
• Define appropriate procedures, practices, and techniques for their project
• Determine and justify deliverables that the project team will provide
• Develop and maintain appropriate project plans
• Provide periodic reports on project status
• Follow the project's model, procedures, practices, and techniques
• Provide periodic self-assessments of their practices (including successes and areas for improvement)
• Deliver completed project artifacts that satisfy their stakeholders

CS Senior Experience Project Specifications

• Computer science knowledge as an integral component
• Computational artifact deliverables demonstrate the application of a synthesis of knowledge and skills developed throughout a CS program
• Group-based project work
• Oral and written presentation deliverables addressing:
  • well-defined objectives
  • analyses of legal, social, and ethical impacts of proposed objectives
  • a priori estimates of feasibility
  • plans to achieve the objectives
  • comparisons of estimates and plans with actual metrics and experiences
  • evaluation of results

Project Assessment

Projects will be assessed with respect to criteria that include effective application of computer science knowledge (concepts, tools, techniques, practices) and communication with stakeholders (both internal and external).

Reflections

Significant learning can result from reflecting on one's own experiences.

"Reflections" shared with the instructor describe personal insights and observations resulting from self-reflection on the associated experiences.

Deliverables

Text-only documentation should be plain (unformatted) text using ASCII or UTF-8 encodings. Only open file formats should be used for other file types. Specifically unacceptable file formats include proprietary formats, such as (but limited to): Microsoft Word, Apple Pages, Microsoft PowerPoint, Apple Keynote, Rich Text Format (RTF). A deliverable submitted in an incorrect format is equivalent to no submission.

If you are unsure about the acceptability of a file format, please check with your instructor well before submission.

Collaboration & Citation of Sources

Collaboration, teamwork, and consultation of work by others are the norms in the computing community.

Collaborative activity is required for successful completion of this course. In particular, collaboration is regarded as an essential aspect of learning computer science and being a computing professional. Collaboration and discussion with fellow students, instructors, and university resources (such as the Writing Center) are strongly encouraged. You are expected to learn the course content and work on assignments and projects in collaboration with other course participants.

That said, in order to provide fair and meaningful assessment for grading, you must make your own submissions and report your individual effort for assessment, whether or not the outcome resulted from collaborative effort.

Note that you are expected to compose and submit a personal reflection for collaborative and individual efforts.

Team deliverables are expected to be a joint effort involving all team members. An overall evaluation will be made for each deliverable that reflects the quality of product. An individual grade for each team member will be assigned for each deliverable. This individual grade may reflect a combination of instructor and peer evaluations. You will be expected to assess each team member's contribution, including your own.

• In every submission, you must credit the people with whom you worked or consulted.
• If you consult any sources (people or works), your submission must explicitly reference those sources and indicate where and how they apply.
• If you include direct quotations or derivatives (text, graphics, program code, etc.), your submission must include explicit citations that identify the sources.

Academic Dishonesty

Turning in work that includes quotations or derivatives (text, graphics, program code, etc.) without corresponding citations, does not properly cite references, or does not credit collaborators will be treated as an act of academic dishonesty. It is your responsibliity to ensure that you have properly vetted and cited all sources.

N.B. Online aggregators, search engines, and text generators may not properly attribute content. Responsibility for appropriate attribution resides with you, not those service providers.

Incidents of suspected dishonesty will be reported to the Chair of the department and the Dean of the college. Consequences may include a score of 0 on the assignment, a grade of "F" for the course, academic probation, or dismissal from the institution. This is a very serious matter and should not be taken lightly. If you have any uncertainty or concerns, please discuss them with your instructor or your advisor.

Official Information

Official policies applicable to all courses may be accessed at https://msudenver.edu/cs/policies

MSU Denver Academic Calendar: http://www.msudenver.edu/events/academic/
Additional official dates and deadlines, including the last dates to withdraw and holidays

MSU Denver Student Rights and Responsibilities: https://catalog.msudenver.edu/content.php?catoid=43&navoid=3176