Syllabus – Information Systems Innovation with AI

MIS3536 – Section 1

Spring 2026

Instructor:

Jeremy Shafer (jeremy@temple.edu)

Physical Office: 209D Speakman Hall

Phone: (484) 440-9108

Profile: https://community.mis.temple.edu/jshafer

Office Hours:

2:30 – 3:30pm Mondays
2:30 – 3:30pm Wednesdays
Other times by appointment
Office hours are in effect 1/12/2026 through 4/27/2026
Email: jeremy.shafer@temple.edu (Please be specific in your email
communication with me, kindly include your name, course, and
section for a faster reply)

Class Locations and Time:

Section 1: 10:00am – 11:20am, Monday, Wednesday – In Person – Speakman 12

Prerequisites:

None

Course Description:

This course provides the knowledge and skills to leverage emerging and
innovative information technology to create business opportunities for both
new entrepreneurial ventures and traditional firms. As we move into the
AI/digital world, the ways by which companies create value is fundamentally
shifting from products to experiences. The rapid convergence to digital
technology provides new opportunities to offer novel products and services
that did not exist before. In this course, students will be asked to think
how entrepreneurs and companies produce radically new and innovative
products and services in the increasingly digital world.

The course focuses on how organizations can design novel and desirable
products and services with a focus on leading edge technologies. Through
applied projects, student teams will learn how to evaluate and apply new
innovative technologies to create new digital experiences, products, and
services.

Course Objectives:

1. Define and explain fundamental AI and ML concepts.

2. Understand the role of AI/ML in various business domains.

3. Identify opportunities for AI/ML integration in business processes.

4. Evaluate ethical and social implications of AI/ML in business.

5. Apply AI/ML algorithms to real-world business scenarios.

6. Communicate AI/ML concepts and solutions to a general audience. What are
the Strengths, Weaknesses, Opportunities, and Risks of a solution?

Required Textbook:

None. Selected readings and/or viewing will be assigned.

Students may be required to purchase access to
“ChatGPT Plus”, “ExcelGPT”, or similar. Out-of-pocket cost to students
should not exceed $20.00.

How the course will be taught:

This course has three phases. Each phase lasts roughly 5 weeks. The first
phase overviews the technical origins of AI, and AI as it existed prior to
November 30, 2022 when OpenAI publicly released ChatGPT.

The second phase focuses on the “modern era” of AI with an emphasis on Large
Language Models (LLMs).

The third phase challenges students to innovatively and apply AI to a modern
work environment.

In all three phases, reading/listening assignments and guest speakers will
be used to promote discussions concerning the appropriate use of AI.

Evaluation and Grading:

Items

Item	Percentage
Attendance	5%
Participation (3)	10%
Quizzes (6)	10%
Assignments (6)	10%
Exam 1	10%
Exam 2	15%
Final	20%
Class Project	20%

Scale

94 – 100	A	73 – 76.99	C
90 – 93.99	A-	70 – 72.99	C-
87 – 89.99	B+	67 – 69.99	D+
83 – 86.99	B	63 – 66.99	D
80 – 82.99	B-	60 – 62.99	D-
77 – 79.99	C+	Below 60	F

Attendance:

Attendance is essential.

Attendance will be tracked and account for a portion of the student’s grade.

If a student does miss class, it is the student’s responsibility to catch up
on any related material. While every student is encouraged to use office
hours to gain a better understanding of class material, office hours are NOT
for helping students catch up on material they missed because they were
absent.

Students are allowed to miss up to 4 classes without penalty. After these
four “grace” absences, a student attendance grade will drop in 5-point
increments for each unexcused absence. While 4 class absences are allowed
without penalty, 0 class absences are expected. That is, the general
expectation of the instructor is that students will be present for every
class.

Absences will not be excused lightly and/or without documentation.

Attendance and participation are inherently intertwined. Although an absence
may be excused, opportunities for participation cannot always be replicated
and student participation grades may reflect this.

Participation:

Participation is essential.

Constructive conversation in the classroom is an important form of
participation. When called on, respond to the instructor’s questions
thoughtfully and constructively. Your instructor will ask students to
discuss one or more topics as a group and then share relevant discussion
notes with the whole class. It’s important to be both a contributor to those
conversations and, on occasion, the spokesperson for the group.

Participation takes other forms as well. It is, in part, contributing to
class discussions. It is also “following along” and doing various forms of
setup work and preparation outside of class as directed by the instructor.
Finally, in the last phase of the semester, participation is measured
largely by each student’s project team contributions. Students who abandon
their efforts to contribute to the class project are not participating in
the class.

Because the nature of participation changes throughout the semester,
participation grades are broken down into 3 separate gradable units. The
final participation grade will be the average of these three units.

Regular attendance is essential for participation; frequent absences may
result in a reduced participation grade.

Participation grades are assigned at the sole discretion of the instructor.

Quizzes:

There will be 6 quizzes to be taken outside of class, on canvas. Quizzes
exist to reinforce key concepts and to help the students prepare for exams.
Students are allowed unlimited quiz attempts/retakes up until the quiz due
date. Roughly 3 days after the quiz due date, a “study” version of the quiz
will become available to the students on canvas.

Any collusion among students to save or share quiz and/or exam materials
will result in disciplinary action.

Exams:

There will be three exams: two midterm exams and final exam.

The final exam is comprehensive and taken during finals week.

There will be no impromptu (‘pop’) quizzes or exams.

Students can expect that roughly10% of their mid-term exam questions will be
directly repeated from quizzes taken earlier in the semester.

Students can also expect that 10% or more of final
exam questions will be related to

content delivered by guest speakers

.

Assignments:

There will be 6 assignments. All assignments should be submitted via Canvas
before the due date. They are to be done individually and should represent
your own work.

#	Assignment
1	Excel Literacy
2	Decision Trees
3	Managing Bias
4	Web Development
5	Leveraging AI to support Cybersecurity (AICyber)
6	Secure the AI (SecureAI)

Late Assignment Policy:

All assignments and activities are graded on a 100-point scale. If an
assignment is turned in on or before its due date, it is on time.
Assignments turned in later are automatically assigned a 20-point penalty,
no matter what the reason.

Assignments may not be turned in more than three days late

. These assignments get a grade of zero.

For the assignment to be considered “on time,” you must attach all necessary
files specified in the assignment instructions by the due date. If
additional/revised/corrected documents are received after the due date, then
the 20-point penalty will be applied to the assignment.

Project:

The instructor will assign an end-of-semester project. Students will work in
groups to describe a current industry, demonstrate the application of AI to
that industry, and discuss the strengths, opportunities, weaknesses and
threats introduced by their innovation.

Students will be required to present their work to the class in the last
full week of the semester. Additional details regarding the project will be
announced later in the semester.

Students on the same project team typically receive the same project grade.
However, in cases where students do not sufficiently contribute to the
success of their project team, the instructor reserves the right to decrease
an individual student’s participation grade appropriately.

Withdrawal from project participation or abandonment of project
responsibilities toward teammates is not acceptable.

Disability Disclosure Statement:

Any student who has a need for accommodation based on the impact of a
documented disability, including special accommodations for access to
technology resources and electronic instructional materials required for the
course, should contact the instructor privately to discuss the specific
situation by the end of the second week of classes or as soon as practical.
Students should contact Disability Resources and Services (DRS) at
215-204-1280 in 100 Ritter Annex to learn more about the available
resources. The instructor will work with DRS to coordinate reasonable
accommodation for all students with documented disabilities.

Academic Integrity:

The MIS Department has a zero-tolerance policy for any type
of academic dishonesty in the classroom.

Academic dishonesty refers to any form of cheating, plagiarism, or other
unethical practices in academic settings. This includes, but is not limited
to, the following:

A. Plagiarism includes, but is not limited to, the use, by paraphrase or
direct quotation, of the published or unpublished work of another person
without full and clear acknowledgment. It also includes the unacknowledged
use of materials prepared by another person or agency engaged in the selling
or distribution of term papers or other academic materials.

B. Cheating includes, but is not limited to: (1) use of any unauthorized
assistance in taking quizzes, tests, or examinations; (2) use of sources
beyond those authorized by the instructor in writing papers, preparing
reports, solving problems, or carrying out other assignments; (3) the
acquisition, without permission, of tests or other academic material
belonging to a member of the university faculty or staff; (4) engaging in
any behavior specifically prohibited by a faculty member in the course
syllabus, assignment, or class discussion; (5) or otherwise engaging in
behavior that gives the Student an unfair academic advantage including, but
not limited to, fabrication of data or sources, resubmitting work already
submitted for another academic requirement without prior authorization, or
other similar behavior.

C. Facilitating, procuring, or encouraging another person to engage in
plagiarism or cheating.

To be clear, the following are unacceptable:

Copying material directly from the Internet (or another source)
without a proper citation crediting the author.
Posting material to the Internet so that it can be used by other
students who are violating this academic integrity policy (i.e.
posting exam material or assignment material to Course Hero).
Turning in an assignment from a previous semester as if it were
your own and created during the current semester.
Having someone else complete your assignment and submitting it as
if it were your own.
Fraudulently updating the attendance record.
Use of assignments completed in one class as any part of a project
assigned in another class.
Sharing/copying any graded assignment.
Use of any unauthorized information during an examination.
Any attempt to deliberately interfere with the technology used in
this class (e.g. the class servers), or to electronically
impersonate a student other than yourself, or to knowingly share
your credentials with another student.

In cases of cheating where multiple parties are involved, all parties will
be held equally responsible. Under this
zero-tolerance policy, any student found violating the academic integrity
policy will immediately receive a final grade of “F” for the course and a
formal complaint will immediately be filed with Office of Student Conduct
and Community Standards. This incident will be listed on your permanent
academic record. As part of my formal complaint, I will petition to have you
expelled from the university. I will not discuss the penalty for violating
this policy; I will simply direct you to this paragraph in the class
syllabus.

As outlined in the university’s Withdrawal from Classes policy (policy no.
02.10.14), once a student has been informed that academic misconduct is
suspected, the student may not drop or withdraw from the course during the
investigation and adjudication process except where the drop or withdrawal
is approved for exceptional circumstances. Details about the Department of
Student Conduct, and related policies and procedures, can be found here:

https://studentconduct.temple.edu/

Student and Faculty Academic Rights and Responsibilities:

The University has adopted a policy on Student and Faculty Academic Rights
and Responsibilities (Policy # 03.70.02) which can be accessed through the
following link:

http://policies.temple.edu/getdoc.asp?policy_no=03.70.02

Class recordings:

Class meetings will not be recorded.

Getting Help:

Students who need assistance can email the instructor, visit the instructor
during office hours, or contact the ITA. Please be specific in your email
communication with the instructor, kindly include your name, course, and
section for a faster reply.