Course Policies :: 67-443
Fall 2024
This page contains information on policies specific to the 67-443 course and applicable only for the Fall 2024 semester. For general Information Systems program policies, please choose the Department Policies link below. This section contains material on:
Grading
Lectures and Zoom
Labs
Xcode
Readings
Questions & Slack
Policy on Use of Generative AIs
Laptops & Phones
Special Accommodations
Concern for Students
Diversity and Inclusion
Educational Research
Faculty & Office Hours
TA Information
Grades in this course are determined by student performance in four areas: a course project (worth 53% total), intermediate sprint deliverables (worth 17% overall), nine weekly labs beginning in week two (worth 20% total) and attendance, short in-class assignments, and quizzes (periodically; worth 10% total). Any grading curves, if deemed necessary, will be applied only to the final course score and not to individual assignments.
Note that this a primarily a project-based course and that more half your grade comes from the final project evaluation and the intermediate sprint deliverables. Even in that, 75% of the project grade comes from the faculty and TA evaluation of the final state of the project. If indeed "the proof of the pudding is in the eating," then for this class the proof of your learning comes in large measure from the quality of the application you and your team are able to develop.
We will be putting you on teams of three (or in one or two cases, teams of four if the total number of students is not evenly divisible by three) to work on the app. You are allowed to pick partners and if you all mutually agree, we will assign you as a team. If you do not submit a choice for a partner by 4pm on September 5th, we will assign you partners.
To help ensure you are making regular progress on your project, each week after the course project kicks off, your team is required to have a 15-minute "stand-up" check-in with your supervising TA on Mondays and every other week have a 20-30 minute check-in with your assigned alumni mentor (around the halfway point of the sprint). Failure to complete these check-ins in a timely fashion will result in a penalty of 1 percent off the final course grade for the first missed/late meeting, 2 points for the second, 4 for the third, 8 for the fourth, and continuing to double after that. Because of the limited time for these meetings, anyone who is 2 or more minutes late for any meeting will be considered absent. Finally, copies of all deliverables need to be submitted to the mentors as well as the faculty and TAs.
Note that in order to deter team members from becoming "free riders", we will be conducting peer reviews at the end of the semester in addition to TAs providing weekly reports on individual contributions. If there is evidence of free riding behavior, a student may have to meet with Prof. H to discuss remediation. If the behavior continues, the faculty reserve the right to lower an individual's grade on the team project by up to 3 letter grades, depending on the severity and duration of the free riding behavior.
Exams and other individual assignments are designed to be completed by individuals without the assistance of other, unassigned CMU students or other outside developers. The IS department has made a separate statement regarding the honesty and integrity policy in this course and students need to review this policy as soon as possible. The IS program considers academic integrity to be of great importance, we actively scan for cheating policy violations and will take swift and appropriate measures against those who fail to abide by these standards.
We will have small in-class assignments to do on a periodic basis. These assignments will not be announced in class beforehand; since regular attendance is the norm, this should not be an issue. (FYI: attendance is taken until 5 minutes after class starts. After that time a student is considered absent. Students have two excused absences before any grade penalty is applied.) A major purpose of these in-class assignments is for both students and faculty to be certain that key concepts are understood and can be applied to basic problems. There will be no make-up for missed in-class assignments but you can be excused with prior permission.
A final note on etiquette and attendance: please avoid stepping out of class or leaving early. If there is an emergency and you cannot avoid leaving the classroom for a moment, go and come back discreetly, with a minimum of disruption to others. If exiting during class becomes a habit for a student, he/she may be docked points for attendance.
Regrades: Any questions or concerns about grading must be directed to the TA supervising your team for resolution before it can be taken to the professor. An entire statement regarding regrading for IS courses in general can be found in the department policies section and will be implemented here. Do not labor under the mistaken impression that you somehow special and therefore are exempt from this policy! If (and only if) you have followed the policy and are unhappy with the way the TA has handled your matter, you are welcome to take your case to the faculty. The faculty will want the TA's input before making a final decision (to be sure that we are fully informed when making the final decision), however, so any attempt to bypass the TA will be futile. If you attempt to do an end-run through the process, you will be sent back to discuss the matter with the TA. In the interest of fairness to all, we also reserve the right to lower grades further if we believe the TAs have been too generous in grading the assignment in question. (This has happened in the past so be forewarned.)
Attendance is taken at each lecture. Please check in with the TA at the start of lecture and make sure your attendance is registered. Also, please note that if you leave early without permission, we reserve the right to un-mark your attendance for the day. As noted earlier, everyone is given two free absences to help cover life events like time-off for interviews, or personal matters, or illnesses such as flu, colds, and the like. We will not be using Zoom this semester, barring unusual circumstances or a return of the pandemic; the one exception to this is the lecture on November 26, just prior to Thanksgiving, which will be on zoom and recorded for those who might be traveling for the holiday.
To help students master the material covered in class, we will have a series of hands-on lab assignments for students to complete, starting in week 2. All labs are graded on a credit/no credit basis, depending on whether students completed the lab. Half credit can be given at the discretion of the TAs for labs that are more than half complete but less than fully finished. There are 11 labs in total and students must complete any 9 of them for full lab credit.
Lab sessions are run by TAs and/or faculty Tuesday, Wednesday, and Thursday evenings from 7pm-8:50pm. There are a total of 11 labs for the course -- completing any 9 will give the student full lab credit. Students are allowed to complete lab work on their own (unlike 67-272, you do not have to complete the assignment during your assigned section) and have it checked off later by TAs, but all check-offs must be complete by 8:45pm on the date the lab is due. To not overwhelm TAs in labs, you must get your lab signed off during the session you were slated to attend or reach out to the lab TA (listed below) if you need an extension.
We do expect labs to be completed by the end of the lab session, but we know that sometimes life throws a curve at us all and that deadline might be hard to meet for a given week. To work around that, each student has 2 "extension coupons" that will allow them to complete the lab and get it checked off by a TA on the Sunday the lab is due, rather than the lab session. If you have used your two extension coupons, then you will have to do a make-up lab as there are absolutely no additional coupons that will be issued. The TA supervising labs (see below) will handle late check-offs students.
Apple is planning on making a change to iOS 18 this fall and with that change will come changes to both Swift and Xcode. For the first half of this class, we will be using Xcode 15.x - many labs and class examples will use these. If you move to Xcode 16 early, you may have difficulties with the labs and problems running code examples and getting help from TAs. At some point, we will transition to this new platform, but students are strongly encouraged to wait on this transition and not to automatically upgrade their version of Xcode (or let MacOS do it for you); doing so is entirely at the student's risk. You have been warned.
There are no assigned books this semester because the most up-to-date documentation is on the web. However, Apple has a number of free iBooks to help developers and you will probably find it advantageous to get a copy of these for yourself as references:
Students are strongly encouraged to ask questions during class. The material can be tricky at times and we expect questions to be asked during the lecture. Odds are that if you have a question, someone else is wondering the same thing; if no one asks then the mystery remains a mystery. In a few cases in the past, the question is on a more obscure technical point that interests very few in the class -- in those cases Prof. H may choose to defer and answer the questioner after class so that the rest of the students are not bored or confused, but the question will be answered.
In addition, this semester we will be using Slack to consolidate a lot of communication and help bridge the gaps between in-person and remote students. The class slack workspace is https://67443-F24.slack.com/ and each of you will be invited to join. Each project team will have their own channel and we are going to ask that you keep team-related communications on that channel so everyone is connected, there's a clear communication record, and your supervisor can monitor your progress. Any announcements will go on the #general channel (please read, but do not post to this channel), other lecture-related activities such as polls or instructions will in in the #lectures channel, and there will be a #labs channel to help facilitate communications between lab instructors and students. (Posts from students welcomed on #lectures and #labs.)
For the record, Professor Heimann is only half-Klingon. Hence, you can safely ask questions in class or during office hours without being worried about him 'killing you where you stand for asking your question.'
Policy on Use of Generative AIs
To develop good mobile applications, you would need to have a good understanding of the software and what it’s supposed to do; and most apps for this class is built on thousands or tens of thousands of lines of code. But at this stage, most generative AIs can only handle around 4000 characters. This will increase eventually, but only so much, since the cost of training/running this AI increases along with it. As a result, generative AI is perfect to handle small scripts and methods, but cannot handle an entire software platform or write a complex app from scratch.
For these reasons and others discussed in class, the use of any AI in class or lab exercises is prohibited, except when explicitly stated in the assignment; there will be assignments where you will be explicitly told to use a generative AI like ChatGPT or Bard, and in those cases you should do so. In cases where you are instructed in class or in lab to use an AI, the prompt needs to be included. Sometimes we provide the exact prompt, but in later exercises we will not give an exact prompt; in any case, document the prompt used as a comment in the file.
For the course project, the use of a generative AI like ChatGPT or Bard is allowed, but their use must be appropriately acknowledged and cited. For instance, if you generated a file such as a model or controller or test file through an AI, you should first edit it for accuracy (see warning below), and then document your work with a note such as “This code was generated through ChatGPT and edited for accuracy.” In addition, you must provide the exact prompt used to generate the code. Paraphrasing or quoting smaller samples of AI generated content must be appropriately acknowledged and cited, following the guidelines established by the APA Style Guide. These acknowledgements should recorded using comments in the file(s) where they occur. In addition, the project README should have a list of files where an AI was used in part or in whole.
Additionally, please be aware that tools like ChatGPT and Bard will sometimes provide code that is primative and/or in need of refactoring. Since your final project is being evaluated for code clarity and style, using an AI to generate the code without reviewing and/or editing that code risks losing points in the final project evaluation. Ultimately, you are responsible for the code that you turn in.
It is each student’s responsibility to assess the validity and applicability of any AI output that is submitted. You may not earn full credit if inaccurate or invalid information is found in your work. Deviations from the guidelines given above will be considered violations of CMU’s academic integrity policy. Note that expectations for “plagiarism, cheating, and acceptable assistance” on student work may vary across your courses and instructors. Please email or slack Prof. H and/or your supervising TA if you have questions regarding what is permissible and not for a particular assignment.
This semester involves regular use of technology during class – both for in-person and remote students. Research has shown that divided attention is detrimental to learning, so I encourage you to close any windows not directly related to what we are doing while you are in class. Please turn off your phone notifications and limit other likely sources of technology disruption, so you can fully engage with the material, each other, and me. This will create a better learning environment for everyone.
If you have a disability and have an accommodations letter from the Disability Resources office, I encourage you to discuss your accommodations and needs with me as early in the semester as possible. I will work with you to ensure that accommodations are provided as appropriate. If you suspect that you may have a disability and would benefit from accommodations but are not yet registered with the Office of Disability Resources, I encourage you to contact them at access@andrew.cmu.edu.
All of us benefit from support during times of struggle. You are not alone. There are many helpful resources available on campus and an important part of the college experience is learning how to ask for help. Asking for support sooner rather than later is often helpful.
If you or anyone you know experiences any academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support. Counseling and Psychological Services (CaPS) is here to help: call 412-268-2922 and visit their website at http://www.cmu.edu/counseling/. Consider reaching out to a friend, faculty, or family member you trust for help getting connected to the support that can help.
Every individual must be treated with respect. The ways we are diverse are many and are fundamental to building and maintaining an equitable and inclusive campus community. These include but are not limited to: race, color, national origin, sex, disability, age, sexual orientation, gender identity, religion, creed, ancestry, belief, veteran status, or genetic information. In this course we will work to promote diversity, equity and inclusion not only because it is necessary for excellence and innovation, but because it is just. Therefore, while we are imperfect, we all need to fully commit to work, both inside and outside of our classrooms to increase our commitment to build and sustain a campus community that embraces these core values.
Educational Research to Improve Course
For this class, I am conducting research on student outcomes. This research will involve your work in this course. You will not be asked to do anything above and beyond the normal learning activities and assignments that are part of this course. You are free not to participate in this research, and your participation will have no influence on your grade for this course or your academic career at CMU. If you do not wish to participate or if you are under 18 years of age, please send an email to Chad Hershock (hershock@cmu.edu) with your name and course number. Participants will not receive any compensation. The data collected as part of this research may include student grades. All analyses of data from participants’ coursework will be conducted after the course is over and final grades are submitted. The Eberly Center may provide support on this research project regarding data analysis and interpretation. The Eberly Center for Teaching Excellence & Educational Innovation is located on the CMU-Pittsburgh Campus and its mission is to support the professional development of all CMU instructors regarding teaching and learning. To minimize the risk of breach of confidentiality, the Eberly Center will never have access to data from this course containing your personal identifiers. All data will be analyzed in de-identified form and presented in the aggregate, without any personal identifiers. If you have questions pertaining to your rights as a research participant, or to report concerns to this study, please contact Chad Hershock (hershock@cmu.edu).
I maintain office hours that are run strictly on a first come, first served basis. However, I am available for appointments on other days and welcome students to stop in at other times without an appointment; if I am busy with something else at the moment then we will set up an appointment to talk at a more convenient time, either in-person or remote via Zoom. Contact information is listed below:
- Professor Heimann
- Office: Hamburg 3001
- Phone: 8-8211 (warning: I only answer this phone when I recognize the number)
- Hours: In-person on Tuesdays and Thursdays from 4:00pm to 5:30pm, starting 9/3. Remote hours may be available by request on Wednesdays from 12pm to 3pm.
- Life Hours: In-person on Thursdays from 12:30-1:30pm. Open discussion of any life issues students are interested in that is not course related. We will hold these in my office in Hamburg 3001.
- Best means of contact is via direct message on Slack, email to profh@cmu.edu also works, but maybe not as quickly.
Please note that office hours are subject to change due to faculty meetings and the like.
Each team will be assigned a TA and that person will become your primary TA, but all our TAs are talented, work as a team, and can help out as needed. If you have a grading concern regarding the sprint deliverables, please talk with your assigned TA first.
In terms of labs, any questions or concerns about labs can be directed at Om Patel or can be posted on the labs channel on the course Slack.
The instructor reserves the right to make modifications to the materials in this syllabus during the term as circumstances warrant.