Description
NMD 100 Introduction to New Media is an exploration into the history, concepts, and modern practices of emerging technologies, considering the beneficial and detrimental consequences of their adoption Topics include telling stories in animation, video, and hypertext; designing user experiences; making web and mobile apps; creating new music, games, and virtual environments; and ethics of the Internet age.
In addition to surveying the broader history of new media technologies and social impact, this year’s course features a special focus on the most disruptive technology of the present day, namely generative artificial intelligence like ChatGPT and DALL-E. In the first half of the semester, students will write, code, and create media using familiar digital tools; in the second half, they will perform the same tasks using generative AI. The results of performing tasks with pre- and post-ChatGPT approaches will be analyzed and shared with the larger educational community..
Disclaimer
In order to best accommodate student projects and shifting technologies, the format, schedule or content for this course may be modified. In addition, student input may alter the content and direction of our work. In such case, changes will be made directly to this online syllabus, with in-class announcements.
NMD 100 Course goals
- Basic familiarity with the general history, impact, and ethics of new media.
- Basic familiarity with the theoretical underpinnings and practical management of personal computers.
- Beginner-level practice with applications for producing creative new media works in several genres.
- Production of an online portfolio for new media creative works.
- Familiarity with the New Media curriculum.
NMD 100 student learning outcomes
- Students should be able to offer one or more definitions of new
media and explain the differences between one-to-one, one-to-many, and
many-to-many communications media. - Student should be able to analyze and respond thoughtfully and critically to writing about developments in new media.
- Student should have a general grasp of the broad history of new
media and a more nuanced understanding of recent developments such as
the evolution of physical computing and the Internet. - Students should be able to ascertain and articulate the positive and negative impacts of different technologies on our world.
- Students should be able to explain how disruptive technologies of the past and present have affected different stakeholders.
- Student should understand fundamental properties of computers,
including the nature of binary code, memory, programming languages, and
input/output devices and formats. Students should also understand the
fundamental architecture of the Internet, including client-server and
peer-to-peer models. - Students should know how to manage files on their computers,
organize projects with complex components, share assets efficiently with
others. - Students should know the appropriate applications and file formats
for building works in different digital media, from animation to video
to websites. - Students should have some hands on experience with entry-level
software for producing and editing genres of creative expression such as
images, audio, video, and/or code. - Students should have created a website stocked with sample creative
and written work from the class that can document their future progress
through the major and eventually serve as a public portfolio. - Students should understand the fundamental structure of the New Media curriculum and their options for the major and minor.
Class
- Estabrooke 130, Mondays and Wednesdays 3:30-4:45 pm
- Remote–if needed via Zoom
- 3 credit hours
- There are no lab hours for this course
Instructor Office hours
- Sign up in advance at the instructor’s Google Calendar for these slots:
- Wednesdays 1-2pm in 337 Ferland Hall or
- Thursdays 1-2pm via Zoom
Teaching Assistant Office hours
- Thursdays 11:30am-3:30 in the New Media Focus Ring lab (127 Boardman) or Computer Science lab (138 Boardman).
Materials
- You can find most course materials and submit tasks and quizzes on the course website at UMaineNewMedia.net/nmd100. You MUST be logged in to see all class content.
- Register for the class website during the first class using your @maine.edu email (all others deleted for security)
- Login at UMaineNewMedia.net/nmd200/wp-login.php.
- Your own FREE (DO NOT sign up for the PAID version) WordPress.com account/NMD Portfolio for drafting, revising and publishing your writing. You will later be migrating this content to your own professional portfolio.
- You will receive an email invite to the course Slack workplace, where you can have synchronous or asynchronous conversations and submit exit tickets.
Symbols
- 📖 Reading
- 🍿 Movie
- 👨🏫 Instructor presentation
- 👆 Individual exercise
- 🤝 Team exercise
- 🗣 Discussion
- 🎟 Exit ticket
- ☑️ Quiz
- 👤 Human-only Task (homework)
- 🤖 AI-aided Task (homework)
- ℹ️ Information resource
This course is designed to help students and the broader public compare the experience of creating text, code, and media with chatbots and other AI assistants versus creating without AI help. While essays, images, and other projects that students create will not be shared outside the class, their writing reflecting on the experience will be shared in anonymized form with the research team working with the course. This team will analyze these reflections and possibly publish any useful conclusions in an academic journal.
Student privacy will be safeguarded according to UMaine’s research policies, and no student data will be kept in the long term or used for any other purpose. Nevertheless students in this course may choose to opt out from this study by alerting the instructor, ideally during the first week of the course.
Every pair of weeks will include similar tasks performed first without AI and then with AI. Because the point of the study is to compare tasks accomplished with versus without AI, it’s important that students not use AI to complete tasks in the first week of each pair, and conversely that they do use AI to complete tasks in the second. Note that this rule applies to reflective feedback as well as tasks; for example, students may use ChatGPT to convert notes to prose for feedback on assignments in the second week of each pair, but not in the first. Quizzes, however, should be taken without ChatGPT due to its tendency to fabricate answers.
To ward off student anxiety about the potential downsides of using or not using AI, grading of the actual tasks will be focused on effort rather than execution (see the Grading tab).
Professor
- Jon Ippolito, Professor of New Media
- 227 Boardman Hall
- Zoom / Slack
- Send direct message on Slack for fast and private response
- email: jippolito @ [university domain]
Teaching Assistant
- Sean Lopez
- Interdisciplinary Studies PhD candidate
- Drop-in hours Thursdays 11:30am-3:30 in the New Media Focus Ring lab (127 Boardman) or via Zoom
- Send direct message on Slack for fast and private response
- email: sean.lopez @ [university domain]
Grading criteria
Avoid missing any quizzes or assignments. Any missed work = 0, and that can really bring down your grade and give a poor reflection of the overall quality of your work.
Make up work: Life happens, and sometimes it’s more important than school. For these occasions, you will have up to 2 “freebies,” which are opportunities to turn in late work, without an excuse. You can apply these to quizzes and exit tickets but not tasks. Do not use these unless you have a serious issues–save them for when you might need them.
Apart from these exceptions, tasks will be penalized 10 points for every week late. We will accept no late work after 27 November.
- 50% Weekly tasks and feedback
Because this is a pilot course employing an experimental technology, you will be judged primarily on the effort you put into your project. Every task will get a grade out of 100 determined by a rubric. For AI-generated work, you may earn a high grade even if your results are not excellent but you reflect thoughtfully and in detail on the process. Grades will appear in comments after your post. For every task, you will post a text or media file at the link provided in the weekly schedule on this website. - 20% Weekly quizzes
These are 1 attempt “open book” random quizzes. These will help you prepare for discussion and can raise your grade (or lower it if you skip or fail). - 20% Lecture participation and exit tickets
Class participation will include attendance, questions and comments during lecture, and helpful feedback to classmates on Slack. If you are shy, reach out via Slack, and do ask us for ways to help you chime in. For example, giving tech assistance to fellow students during class can make up for a lack of class comments. - 10% Periodic surveys
Complete these along with your tasks to get participation credit for these. They’re linked from each task description and have questions like:- “In what ways was this assignment successful for you?”
- “In what ways was this assignment challenging?”
- “How would you compare the experience of applying AI to this task versus accomplishing a comparable task without AI?”
Final
There will be no final exam if your quiz average is 80 or above. Final exam will cover any quiz questions from previous quizzes and will be given at the instructor’s discretion.
The class may select best final projects for showing during mid-year student showcase.
Grading scale
It is easy to earn a B in this class with consistent effort, it is also easy to fail the class if you miss classes/labs, miss making up work, just do the bare minimum, or do not work consistently. My goal—and that of your classmates— is to help you earn the best grade you can.
- A Outstanding work that goes above and beyond class requirements, generous contribution to improvement of your own and other student work, robust contribution to class and peers.
- B Very good work fulfilling ALL class requirements, clear contribution to improvement of your own and other student work, robust contribution to class and peers
- C Satisfactory work without much improvement from initial class assignments, minimal contribution to class or peers; ie this is the grade for just “doing most of the work in a mediocre fashion”
- D Just getting most of the work done, but without much learning, contribution or improvement. Many missing assignments, low or missing quizzes, poor projects.
- F No evidence of learning from posted work, projects or quizzes; substantial missing or failing work.
Credit toward the New Media Major
Although passing is a 60 (D-), you must earn a 70 (C-) or higher for this course to qualify toward a New Media major.
Numerical scale
0-59 F
60-62 D-
63-66 D
67-69 D+
70-72 C-
73-76 C
77-79 C+
80-82 B-
83-86 B
87-89 B+
90-92 A-
93-96 A
97-99 A+
Completing work
My main expectations for the class are that you do the work as best you can and keep up. Even partial work is better than no work or late work, since you will get a few choices of projects to revise. While quality is important, it is more important to keep up, and perhaps revise or drop any low grades. Assignments have clear logged due dates on the class website, and you will lose points for unexcused late work. I will also factor in unexpected individual circumstances where needed..
Attendance
Factored into your grade–see above. For medical, family or school events, you may request to do make up work at my discretion.
Talk to me beforehand if you know you’ll have to miss time in class. I will work with you as best I can to support you if I see evidence of responsibility and effort.
Behavior
Encourage diversity of thoughtful viewpoints. This means telling your truth and doing so in ways that are constructive and supportive. Respect professor, guests, and classmates with clear attention and engagement, and give thoughtful, genuine feedback designed to encourage growth.
Equipment
Have your computer and/or whatever you need to enable you to work during every class. Phones will NOT be sufficient for class work.
If conditions are safe, you may make use of the various equipment and labs on campus, including IMRC, Focus Ring/Still Water, SCIS labs and any other available resource you need.
Personal constraints
See me if you have an especially difficult personal constraint–such as your own illness, or children or parents you need to care for. I may not be able to help, but I can probably direct you to someone who can. Students with disabilities can also go directly to Services for Students with Disabilities (581-2319). I do not hold any personal circumstance against you in terms of grading (though I cannot credit you for work not done) and will work with you to achieve your best work.
Don’t wait until these constraints affect your class work, however. Try to alert me to any impending or disruptive issues before and as they happen, so I can do my best to get you the support you need (and have paid for) to get over those common life challenges.
Register to Vote
Voting is one of the key powers you have to shape your future. Don’t give away your power.
For information about voting–how to vote, how to register, absentee ballots, see https://umaine.edu/studentlife/uvote/
UMaine Policies
Academic Honesty Statement:
Academic honesty is very important. It is dishonest to cheat on exams, to copy term papers, to submit papers written by another person, to fake experimental results, or to copy or reword parts of books or articles into your own papers without appropriately citing the source. Students committing or aiding in any of these violations may be given failing grades for an assignment or for an entire course, at the discretion of the instructor. In addition to any academic action taken by an instructor, these violations are also subject to action under the University of Maine Student Conduct Code. The maximum possible sanction under the student conduct code is dismissal from the University. Please see the University of Maine System’s Academic Integrity Policy listed in the Board Policy Manual as Policy 314: https://www.maine.edu/board-of-trustees/policy-manual/section-314
Note: See the AI in the Classroom tab for special considerations unique to this course.
Students Accessibility Services Statement
If you have a disability for which you may be requesting an accommodation, please contact Student Accessibility Services, 121 East Annex, 581.2319, as early as possible in the term. Students who have already been approved for accommodations by SAS and have a current accommodation letter should meet with me (the instructor of the course) privately as soon as possible.
Course Schedule Disclaimer
In the event of an extended disruption of normal classroom activities (due to COVID-19 or other long-term disruptions), the format for this course may be modified to enable its completion within its programmed time frame. In that event, you will be provided an addendum to the syllabus that will supersede this version.
Observance of Religious Holidays/Events:
The University of Maine recognizes that when students are observing significant religious holidays, some may be unable to attend classes or labs, study, take tests, or work on other assignments. If they provide adequate notice (at least one week and longer if at all possible), these students are allowed to make up course requirements as long as this effort does not create an unreasonable burden upon the instructor, department or University. At the discretion of the instructor, such coursework could be due before or after the examination or assignment. No adverse or prejudicial effects shall result to a student’s grade for the examination, study, or course requirement on the day of religious observance. The student shall not be marked absent from the class due to observing a significant religious holiday. In the case of an internship or clinical, students should refer to the applicable policy in place by the employer or site.
Sexual Violence Policy
Sexual Discrimination Reporting
The University of Maine is committed to making campus a safe place for students. Because of this commitment, if you tell a faculty or staff member who is deemed a “responsible employee” about an experience of sexual assault, sexual harassment, stalking, relationship abuse (dating violence and domestic violence), sexual misconduct or any form of gender discrimination involving members of the campus, they are required to report this information to Title IX Student Services or the Office of Equal Opportunity.
If you want to talk in confidence to someone about an experience of sexualdiscrimination, please contact these resources:
- For confidential resources on campus: Counseling Center: 207-581-1392 or Cutler Health Center: at 207-581-4000.
- For confidential resources off campus: Rape Response Services: 1-800-871-7741 or Partners for Peace: 1-800-863-9909.
- Other resources: The resources listed below can offer support but may have to report the incident to others who can help:
- For support services on campus: Title IX Student Services: 207-581-1406, Office of Community Standards: 207-581-1406, University of Maine Police: 207-581-4040 or 911.
Additional Policies
• Student Conduct Expectations
• Classroom Civility
• Inclusive and Non-sexist Language
• Copyright Notice for Materials Accessible through the Course Website
• Contingency Plans in the Event of an Epidemic