Course Syllabus
Contact Information
Dr. Kim has PhDs in Public Administration and Business Administration. She has over 20 years of teaching experience and enjoys teaching. Her recent teaching interests are data analytics, database management, and health informatics. Her research areas include health informatics using data analytics, health disparity, and knowledge management. She especially enjoys working with data. A few of her recent publications appear in reputable journals such as health informatics, information science, and knowledge management journals.
Course Details
For a list of course activities, scroll to the bottom of this page.
Course Prerequisites
No pre-requisite required
Course Materials
No textbooks are required for this course.
Software Requirements
Hardware Requirements
- Windows Operating System preferred because examples will be demonstrated on Windows.
- Must have administrator privileges to install software if you use your office computer.
- Computing power:
- Recommended 8GB RAM or higher.
- Recommended processor is 2.3 Hz, but minimum 1.8 --- your machine will be slow or can crash while running R.
Grades
Breakdown
| Activity | Description | Percentage |
|---|---|---|
| Hands-On Assignments | These assignments will require you to apply the learning in the module, and they will act as an assessment of your mastery of the content of the module. | 58% |
| Quizzes | These quizzes will act as a check that you understand the basic concepts presented in the instructional videos and other provided resources. | 18% |
| Final Project | Throughout the semester, you will work on a real-world database project. Pieces of the project will be turned in throughout the course, and the final product will be turned in at the end of the course. Each piece submitted will be worth 25 points, while the final submission will be worth 100 points. | 24% |
| Total | 100% |
Scale
| Percentage | Letter Grade | Description |
|---|---|---|
| 90–100% | A | Exceptional performance, exemplary work on all aspects of the assignment. |
| 80–89% | B | Work of good quality on all requirements of the assignment and high quality on some aspects. |
| 70–79% | C | Marginal work that does not meet standards in one or more aspects of the assignment. |
| 60–69% | D | Unsatisfactory work that exhibits multiple problems in meeting requirements of the assignment. |
| Below 60% | F | Failure to meet minimal requirements. |
Note: The Graduate College considers a grade of “D” to be a failing grade in terms of graduate degree credit.
Course Components
Module Overviews
Each module will have an overview page, which will include:
- a brief description of the topics of the module to help you know what to focus on and how it ties to other topics in the course,
- learning objectives to help you know what you are working toward throughout the module,
- and a to do list to help you manage your time.
Resources
You will be provided with instructional videos to give you the foundational knowledge needed to complete the activities and assessments in the module successfully. You may also need to review websites and articles.
Concept Check Quizzes
After reviewing the module resources, you will have a chance to practice your knowledge in a concept check quiz.
Live Sessions
Every other week, there will be Live Sessions on Wednesdays from 7:30 PM - 9 PM Central Time. These will include some lecture materials, examples, and opportunities for interaction and collaborative learning. If you are not able to attend live, please watch the recording later.
Hands-On Assignments
Each week, you will have a hands-on assignment in which you will have to create and/or manipulate databases using the knowledge you gained during the module. The results of this assignment will help you and your instructor assess your level of mastery over the content of the module.
Project Work
Throughout the course, you will work on a real-world project of your own choosing. You will submit work toward that project at a few touch points throughout the course, and then you will submit the final product during the last week. This project should show comprehensive mastery and growth.
Extra Credit Opportunities
Students can earn extra credits for the following conditions:
- Students can answer questions from peers on Canvas. If your answer significantly enhances the learning of the class, the instructor will email you with the extra credit. The credit usually ranges between 2 and 5 points.
Course Policies
Communication
There is no such thing as perfect communication, especially when dealing with complicated topics like this one. As such, it is natural to have questions. If you have any questions or concerns, you can use one or more of the following methods.
- It is strongly encouraged to use the discussion board on Canvas because the instructor checks the discussion board as frequently as she can. Also, some students are too shy to ask questions, and your posting on the discussion board will benefit other students.
- Students can email on Canvas if they prefer.
- If you need the instructor to see your code on the screen, you can email the instructor for a zoom meeting request, but it may take one or two days since the instructor has other obligations.
- Students are not allowed to post a code or an answer. If it happens, the instructor will delete the posting.
Feedback
Most assignments will be returned in a one-week turnaround time.
Assignment Submission & Late Work Policy
- All assignments should be submitted via Canvas. No assignment will be accepted via email.
- No assignment should be submitted on the comment box as the instructor will not know.
- Late work will NOT be accepted unless there is an unforeseen medical problem or immediate family passing. A detailed explanation for an unforeseen problem should be included in the extension request. If you are granted to submit late for an assignment, it is your responsibility to indicate the week and the name of the assignment.
- You will need to use the screen capture function (Fn + Alt + PrintScrn) or (shift +
windows + s) or other ways to screenshot for your submissions and paste the screenshot into a document. More specific guidelines will be provided in the lecture notes. All assignments should be in screenshot. - The screenshots with readable font size should include the code and the output in one page.
- Submissions must not be zipped.
- Any submission failing to follow these guidelines will be returned
Plagiarism
Plagiarism is the most common form of academic misconduct at OU. There is basically no college-level assignment that can be satisfactorily completed by copying. OU's basic assumption about writing is that all written assignments show the student's own understanding in the student's own words. That means all writing assignments, in class or out, are assumed to be composed entirely of words generated (not simply found) by the student, except where words written by someone else are specifically marked as such with proper citation. Including other people's words in your paper is helpful when you do it honestly and correctly. When you don't, it's plagiarism.
For more information about plagiarism, watch this video and then take this short course offered by University Libraries.
University Academic Policies and Student Support
Access the University Academic Policies Document.
Course Summary:
| Date | Details | Due |
|---|---|---|