Course Syllabus

SDEV 355 - Agile Programming Methodologies

Fall 2020 (Item #5651)

Course Information

Instructor Information

Course Description

Students use Scrum, an agile framework for completing complex projects, to develop software and deliver business value to clients.

This is a team project-based class. You will participate in a quarter long team project and strengthen your software development and Agile skills, culminating in a real-world project that will become part of your professional portfolio. The project will be made up of two-week sprints, each culminating in a product demo (sprint review).

The course will meet via Zoom two days a week. Participating in these meetings is critical, since much of the course is team-based. If you are unable to attend a class session, be sure to notify your team beforehand, and touch base with them afterward.

Course Outcomes

Agile technical practices include testing, integration, refactoring, and pair programming. Scrum practices involve stand ups, product backlogs, user stories, sprints, and retrospectives. At the end of the course, the student will be able to:

  1. Identify the roles in a Scrum team.
  2. Conduct Scrum events, including stands ups, sprint planning, sprint reviews, and retrospectives.
  3. Create and refine Scrum artifacts, including a Working Agreement, Product Backlog, and Sprint Backlogs.
  4. Apply agile team practices such as daily scrum meetings, sprint planning, continuous integration, and kanban.
  5. Initiate and foster a client relationship with ongoing communication throughout the project life cycle.
  6. Understand the difference between various Agile approaches to software development.
  7. Prepare and present a professional portfolio and elevator pitch.
  8. Articulate the difference between Agile and the traditional waterfall approach to software development.

Program and Campus Learning Outcomes

Course Resources

Required Textbooks

Recommended Reading

Canvas

All assignments, supplementary materials, the course schedule, due dates, and updates to this syllabus will be posted to the course web site in Canvas at https://egator.greenriver.edu/

Check the course web site and your @mail.greenriver.edu email account daily for important announcements.

If you have any questions about the course, reading, or the homework, please post them to Canvas Discussions. This will enable you to get an answer to your questions more quickly, and also help classmates who might have the same question. If you see a question in the Discussions that you think you can answer, please do so! 

If you have questions of a personal nature, such as regarding a specific grade or scheduling an appointment, then either email me or visit me during office hours.

Tutors

There are tutors available both at Auburn Center and the main campus (Holman Library) for all IT Software Development classes. View the Tutoring Schedule

Tutoring Protocols

Student Portal

my.greenriver.edu contains information and links for important student resources.

LinkedIn Learning

LinkedIn Learning provides a wide range of technical video tutorials, and is free to Green River students.

Course Policies

Late Work

All assignments are posted well in advance, so be sure to get an early start! Late assignments will be accepted up to one week after the due date, and will receive 50% credit.

Team Contribution

All team members are expected to contribute their fair share to the class project. In most cases, everyone will receive the same project points. However, in the rare case that a team member does not adequately contribute to the team effort, their grade will be adjusted accordingly. An individual grade for a sprint may be different from the team grade, based on peer evaluations, GitHub commits, and instructor discretion.

To avoid any lost points, all students should strive to be productive and contributing team members.


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Academic Integrity and Collaboration

Plagiarism occurs when you knowingly submit someone else's work (ideas, words, code) as your own. Plagiarism is an act of intentional deception that is not only dishonest, it robs you of the most important product of education - the actual learning. Should I suspect that you have plagiarized, I will talk with you one-on-one and ask you to prove the work in question is your own. 

You may use AI tools for learning or research, but you are responsible for verifying the accuracy of any AI-generated information. All submitted work must be your own. AI-generated submissions will be considered academic dishonesty.

The purpose of this restriction is to ensure that students develop a fundamental understanding of technical concepts and problem-solving skills.

Software Development and Data Analytics are skills that demands active engagement, critical thinking, and hands-on practice. By prohibiting the use of AI text generators, we aim to promote a genuine learning experience where students grapple with challenges, debugging issues, and algorithmic thinking on their own. This approach encourages the development of analytical skills, creativity, and the ability to translate conceptual knowledge into practical solutions.

Furthermore, fostering a learning environment that relies solely on individual effort and peer collaboration prepares students for real-world scenarios where coding proficiency is essential. While tools like ChatGPT have their place in certain applications, this course aims to lay a strong foundation in skills that students can build upon throughout their academic and professional journeys.

Students are encouraged to seek assistance from the instructor, tutors, and peers, as well as to utilize the provided course materials and resources to enhance their understanding and overcome challenges. Embracing the learning process, persevering through difficulties, and honing problem-solving abilities are key objectives of this course, and refraining from the use of AI text generators supports the achievement of these goals.

If your work is not your own, you will receive a failing grade of zero on the assignment. If your work continues to be plagiarized during the quarter, you will receive a failing grade for the course.

Grading

Grading in this course consists of your demonstrated competency and professionalism. If you have any questions or concerns about a course grade, talk to the instructor within two weeks of receiving the grade.

Grades will be converted according to the following scale:

Decimal %
4.0 95
3.9 94
3.8 93
3.7 92
3.6 91
3.5 90
3.4 89
3.3 88
3.2 87
3.1 86
Decimal %
3.0 85
2.9 84
2.8 83
2.7 82
2.6 81
2.5 80
2.4 79
2.3 78
2.2 77
2.1 76
2.0 75
Decimal %
1.9 74
1.8 73
1.7 72
1.6 71
1.5 70
1.4 69
1.3 68
1.2 67
1.1 66
1.0 65
0.0 <65