Policies
Attendance/Participation Expectationsβ
- You are expected to attend and participate in all class activities.
- When you're not able to attend the class for any circumstances, you are expected to notify me in advance.
- You are responsible for catching up on any missed material.
- When absence reoccurs, you may be asked to provide documentation regarding the absence reasoning.
- You are responsible for maintaining a line of communication with me regarding your performance.
- You're encouraged to help your classmates via the channel.
- this may count towards extra credit points when your grade needs it.
- If you're not sure if your help would be considered cheating/plagiarism, reach out and ask.
Communication protocolsβ
- I will post weekly announcements on Canvas (make sure itβs connected to your email)
- For assignment-related questions please ask you questions on the MS Teams channel and engage with your fellow classmates.
- You're also encouraged to participate and answer any questions your fellow classmates may post on the board or on Canvas. (this counts towards extra credit points)
- When posting a question about your code, you must include:
- what you are trying to do
- what have you already tried
- code snippet
- a Screenshot may be acceptable. However, something we can copy-paste would be greatly appreciated (GitHub Gist or code sandbox)
- For grading-related questions, please email the TA and copy me on the communication.
- Please note
IT3049C
in the email subject.
- Please note
- For any email communication with me or the TA, make sure to:
- Send it FROM your School UC email.
- Send it TO my School UC email :) yahya.gilany@uc.edu.
- Please review my Service Level Agreement for more (important) info about when to expect a response.
Course Evaluationβ
The School of Information Technology requires that each course is evaluated each time it is taught. The School uses a confidential web-based system, CoursEval, for these evaluations. At the beginning of finals week,you will receive an email from the School Head, with βCoursEvalβ as the topic. There is a link on that email that takes you directly to the evaluation. The online system is anonymous. I will receive only a summary report of combined data after final grades have been submitted.
As an instructor, I greatly value your input regarding the strengths and areas for improvement of this course. Your feedback is essential for me to continually improve instruction and provide for quality student learning and outcomes.
Late or Missing Policyβ
- Quizzes will not be accepted (and will not be available) once the due date has passed.
- Late work grade will be deducted 10% per day. (~3/20 points every late day)
- No Exception or additional extensions will be given except for the two University-approved situations:
- Accommodations requested and verified in advance from the Office of Disability Services.
- Religious holidays, when I am notified of them in advance.
Assignment Submission Workflow and Expectationsβ
-
Accept the GitHub Classroom assignment
- this will copy the starter files for the assignment to a repository named as
<assignment name>-<your github username>
- this will copy the starter files for the assignment to a repository named as
-
Clone down the project to your computer.
-
start modifying/writing your code to satisfy the assignment requirements.
-
Make sure you commit your code frequently and use a descriptive commit messages.
- the best practice here is to commit at the end of every complete thought. (i.e.
modified the user class to validate the age input
,updated the self assessment in the README file
)
- the best practice here is to commit at the end of every complete thought. (i.e.
-
Once you're done with the assignment, confirm that you've updated the self evaluation and added any notes or reflections you had.
-
Copy the Repository link and submit to Canvas.
Remember to: make sure your code is on GitHub and you didn't just commit it locally.
Use of AIβ
- Artificial intelligence (AI) language models, such as ChatGPT may only be used if the assignment calls for it and with proper citation. If you are in doubt as to whether you are using AI language models appropriately in this course, I encourage you to discuss your situation with me.
- Examples of citing AI language models are available at: libguides.umn.edu and montclair.edu
- You are responsible for fact checking statements composed by AI language models as they can hallucinate incorrect answers