Course Syllabus

MDST 2000

Professor Siva Vaidhyanathan

Email: siva@virginia.edu (Please see below for email policy. I prefer to be contacted through Canvas messaging for course matters).

Tuesdays and Thursdays, 11 a.m. to 12:15 p.m.

Nau 101

 

Office hours: Wednesdays 1 p.m. to 2 p.m. and by appointment in Wilson 209

 

 

From the intimate to the mundane, most aspects of our lives—how we learn, love, work, and play—take place within media. Taking a global perspective, this survey course covers what it means to live in, rather than with, media. The course focuses on lived experience—how people who use smartphones, the internet, and television sets make sense of their digital environment—to investigate the broader role of media in society and everyday life.

Introduction to Media Studies uses relatable examples and case studies from around the world to illustrate the foundational theories, concepts, and methods of media studies. 

 

The course is structured around eight core themes: 

• How media inform and inspire our daily activities; 
• How we live our lives in the public eye; 
• How we make distinctions between real and fake; 
• How we seek and express love; 
• How we use media to effect change; 
• How we create media and shared narratives; 
• How we seek to create well-being and flourishing within media. 
• How we use media to strengthen or weaken democracy
• How we think about changing technologies in our lives.

 

By highlighting diverse voices and radically embracing the everyday and mundane aspects of media life, this course encourages students to find new ways to think, talk, and write about media.

 

Learning objectives

By completing this course students will:

• Understand and describe the breadth of the field of media studies.

• Understand and explain how humans shape media ecosystems and how media ecosystems shape human behavior and interactions.

• Understand and be able to explain the relationship between media and democracy.

• Understand and be able to explain the various theories of technology in society.

Policies

1. Attendance

Attendance in lecture is essential for success in the course, as many of the exam questions will be based on the lecture material. Attendance in discussion sections is mandatory and will be taken through submission of the weekly reading reaction in-class writing assignments. 

2. Assignment processes and submission

Each exam will be a series of multiple-choice questions to be done within a specific amount of time on Canvas. Each in-section writing assignment will be done with pen and paper (with exceptions for accommodations), photographed, and then submitted via the Canvas phone app. I expect every assignment to be completed by the deadline. Students will have ample time to start and complete the exams on their own time. In-section writing must be submitted to Canvas during the discussion-section meeting time. 

3. Honor

I expect every student to conform to the UVA honor code. For information on how accusations of honor violations are considered, please see this FAQ:

 

4. Generative artificial intelligence use

Generative artificial intelligence tools—software that creates new text, images, computer code, audio, video, and other content—have become widely available. Well-known examples include ChatGPT for text and DALL•E for images. This policy governs all such tools, including those released during our semester together. You may not use generative AI tools on assignments in this course. If you choose to use generative AI tools in violation of this policy (or in another class that permits them), please remember that they are typically trained on limited datasets that may be out of date. Additionally, generative AI datasets are trained on pre-existing material, including copyrighted material; therefore, relying on a generative AI tool may result in plagiarism or copyright violations. Finally, keep in mind that the goal of generative AI tools is to produce content that seems to have been produced by a human, not to produce accurate or reliable content; therefore, relying on a generative AI tool may result in your submission of inaccurate content. It is your responsibility—not the tool’s—to assure the quality, integrity, and accuracy of work you submit in any college course. If you use generative AI tools to complete assignments in this course, in ways that I have not explicitly authorized, I will submit a complaint to the Honor Committee. Please act with integrity, for the sake of both your personal character and your academic record.

 

5. Communication

For questions about course content, procedures, and grading, please contact your teaching assistant first. The teaching assistant will decide if an issue is appropriate to bring to my attention so the teaching assistant and I can discuss the issue together. Please do not write to me first. I will only refer the question to your teaching assistant. However, if you wish to discuss something from the course in greater depth, as a subject to explore, then by all means do visit my office hours to discuss it with me. It would be a joy and a pleasure to converse about the ideas and issues of this course with you. Also, if you are interested in Media Studies as a major or work in media as a career, then please do come to my office hours. If you cannot make my office hours because of a course conflict, please arrange for a separate meeting time via email. If you want to contact me please use the Canvas messaging system, not my UVA email.

Assignments and grading

There will be 10 in-section writing assignments to be done on paper and submitted as a photograph to Canvas. Each of them will be worth 10 points. There will be four take-home, multiple-choice exams during the semester worth 20 points each. There will be a comprehensive final exam that will be worth 40 points. The final grade will be based on the percentage earned of 200 possible points. 

(Note: For second through the final exams each question will be worth one point, not two. There will be twice as many questions and I will give you twice the time to complete the exam.)

You may drop two of the ten in-section writing assignments, leaving 80 possible points for the writing and 120 points for the exams. 

If you complete all of 10 the writing assignments successfully, you may add one of them back as extra credit.

There is a 10 percent deduction for each day the exam is late. 

 

Grading scale:

A+	100
A	95
A-	90
B+	87
B	83
B-	80
C+	77
C	73
C-	70
D+	67
D	63
D-	60
F	0

 

Books

Broussard Meredith. 2023. More Than a Glitch : Confronting Race Gender and Ability Bias in Tech. Cambridge Massachusetts: MIT Press.

Deuze Mark. 2023. Life in Media : A Global Introduction to Media Studies. Cambridge: MIT Press.

Jankowicz Nina. 2022. How to Be a Woman Online : Surviving Abuse and Harassment and How to Fight Back. London: Bloomsbury Academic.

 

Class schedule

Week 1 January 16 Introduction NO DISCUSSION SECTION MEETINGS

Watch "What is Media Studies? Key concepts explained!" on YouTube. 

Week 2 January 23 and 25 NO LECTURE MEETING ON TUESDAY, JANUARY 23

Why do we study media?
No reading. 

 

Week 3 January 30 and February 1

How do we study media?
Read Deuze,  Chapter 1
First reaction writing in discussion section

Week 4 February 6 and 8

What are media?
Read Deuze, Chapter 2
Second reaction writing in discussion section

Week 5 February 13 and 15

Media as surveillance
Read Deuze, Chapter 3

Read Vaidhyanathan, "The Rise of the Cryptopticon."
Third reaction writing in discussion section.
First exam due Monday, February 19 at 11:59 p.m.

 

Week 6 February 20 and 22

Read Deuze, Chapter 4
Fourth reaction writing in discussion section.

Week 7 February 27 and 29 NO LECTURE MEETING ON THURSDAY, FEBRUARY 29 NO DISCUSSION SECTION MEETINGS


No Reading,

Watch "Postmodernism explained for beginners! Jean Baudrillard Simulacra and Hyperreality explained" on YouTube.

Watch The Matrix (1999)

Week 8 Spring Break

Week 9 March 12 and 14
Read Deuze, Chapter 5

NO REACTION PAPER DUE THIS WEEK

Week 10 March 19 and 21 
Read Deuze, Chapter 6
Fifth reaction paper in discussion section


Week 11 March 26 and 28
Read Deuze,  Chapter 7
Sixth reaction paper in discussion section.

Second exam due Thursday, March 28

 

Week 12 April 2 and 4 VIRTUAL LECTURES THIS WEEK 
Read Deuze, Chapter 8

Listen to episode of Hard Fork podcast with Jonathan Haidt.

Read "End the Cell-phone-based childhood" by Jonathan Haidt in The Atlantic.

Read "The Great Rewiring" in Nature.

Listen to Siva's audio lecture for Tuesday.
https://virginia.zoom.us/rec/play/yHvGzBfMTnSI8mEfnpBjpZ-ywD96trQlPQ1vtYpfc_qWVIqCkp94aIw0olZF2fgr2iHgXKxNALhqB1Zw.1IScVS9bFnNMHl5M

Passcode: !a92qde$

Listen to Siva's lecture for Thursday.

Seventh reaction paper in discussion section.

Week 13 April 9 and 11 VIRTUAL LECTURE THURSDAY, APRIL 11

Listen to recorded audio lecture for Thursday. 

Read Jankowicz, How to Be a Woman Online : Surviving Abuse and Harassment and How to Fight Back. Entire book.
Eighth reaction paper in discussion section.


 

Week 14 April 16 and 18 VIRTUAL LECTURES FOR TUESDAY, APRIL 16 AND THURSDAY, APRIL 18
Read Broussard, Introduction through Chapter 6

Listen to the audio lecture for Tuesday and Thursday.

Watch "Generative AI in a Nutshell - how to survive and thrive in the age of AI" on YouTube.

 

Watch "AI vs Machine Learning" on YouTube. 

Ninth reaction paper in discussion section.

 

 

Week 15 April 23 and 25

Third exam due Thursday, April 25Read Broussard, through end.

Watch "ChatGPT: 30 Year History | How AI Learned to Talk" on YouTube. 

Watch Professor Rafael Alvarado on generative AI and language models.

Watch "CS Professor Sounds Alarm on AI and Programmers"on YouTube. 

Tenth reaction in discussion section.

Week 16 April 30 NO DISCUSSION SECTIONS 

Watch Her

No reading.
Fourth exam due Thursday, April 30

 

Comprehensive final exam due Thursday, May 9