Skip to main content

WCWP 10B: The Writing Course B

Intermediate Academic Argumentation

The purpose of the Warren Writing sequence is to enable undergraduate students, through intensive practice, to read and write academic arguments in preparation for their work in various academic disciplines. Warren Writing 10B is required of all Warren College students who have completed WCWP 10A.

Prerequisite: Completion of WCWP 10A with a passing letter grade. Open to Warren College students only. (Letter grade only.)

Summer Session Instructor and Topic assignments

Summer Session 1

Section CRN Day Time Location Instructor Topic
A00 83923 TTh 800-1050 EBU3B 1124 Jeff Gagnon TBA
B00 83924 TTh 1100-150 EBU3B 1124 Ryan Rosenberg Education
C00 83925 TTh 200-450 WSAC 132 Ari Garvin Disney


Summer Session 2

Section CRN Day Time Location Instructor Topic
A00 84289 MW 200-450 WSAC 132 Ryan Rosenberg Education
B00 84290 TTh 800-1050 WSAC 132 Brie Iatarola Food
C00 84291 MW 1100-150 EBU3B 1124 Sarah Savage Big Data


See topic descriptions below.

Spring 2022 Topics and Schedule

Last Updated: 3/3/22

Spring 2022 Course Topics

Starting in 2022, we have returned to WCWP's historic practice of running multiple instructor-designed course topics for WCWP 10B. Each of the below courses were developed by experienced instructors who have at least two years of experience teaching in our program. We hope that by offering more variety, students and instructors alike will have an opportunity to work with curriculum that is engaging and exciting to them.

While course themes may differ, the overall structure, learning objectives, and required work remain consistant across all WCWP 10B sections. 

Big Data, AI, and Issues of Justice
Data science is everywhere, and its proponents advocate its uses in nearly every field and industry, from political advertising to the criminal justice system. In this class we will read writers who have begun to scrutinize the belief systems, methods, and practices involved with applications of “big data,” algorithms, and AI, and the ways that algorithms create or reproduce unjust forms of discrimination and systemic inequality.

Education, Equity, and Meritocracy
Education is often described as the great equalizer. But does everyone have the same access? In this class, students will think critically about the educational system (from early childhood education to grading and standardized testing) to examine the ways in which the ideology of meritocracy justifies, excuses, and perpetuates inequality.

Disney Animation & Ideology
In this course, we will be using critical reading skills to analyze Disney’s animated properties as well as their corporate culture to determine the promises and contradictions of Disney’s proposed ideologies and cultural ideals.

Food Justice
This course will examine various problems with America’s food production and delivery system and trace their roots to some of the underlying contradictions in our society. We will look at how those problems affect families, food workers, the quality of food that we eat, and the environment, which impacts the sustainability of our global food supply.

Media, Technology, & Popular Culture Ethics
This course will concentrate on developing argumentative and analytical skills with a featured focus on the growing influence and use of technology and popular culture texts, including but not limited to film, televised productions, music videos, and digital gaming.

Voting & Suffrage in a Representative Democracy
This course will examine the notion of justice and fairness in the right to vote and examine the tensions that exist between expanding voting rights and suppression of the vote. Who has access to the vote is a struggle that was both an issue in the past and is still one that exists today.

Spring 2022 Topic Schedule

On the Schedule of Classes, Professor Jeff Gagnon is listed as the instructor of record for all sections. However, sections are actually taught by our WCWP instructional body. To find the instructor or topic of a specific section, please reference the section number (e.g. 001) or CRN (e.g. 062558). There may be differences between what is listed below and what is listed on the Schedule of Classes, but the following is considered the most up-to-date version of the schedule.

*Please note only instructor Haleema Welji is approved to teach a 20-limit section. All other sections are capped at 15 students. 

Section CRN Days Time Location Instructor Topic
1 76286 MW 1100 - 1220 WSAC 132 Mike Gainey Disney
2 76287 MW 1230 - 150 WSAC 132 Mike Gainey Disney
3 76288 MW 200 - 320 WSAC 132 Mike Gainey Disney
4 76289 MW 330 - 450 WSAC 132 Paula Santa Rosa Disney
5 76290 MW 500 - 620 WSAC 132 Paula Santa Rosa Disney
7 76292 MW 1100 - 1220 WSAC 138 Nikki Cox Education
8 76293 MW 1230 - 150 WSAC 138 Nikki Cox Education
9 76294 MW 200 - 320 WSAC 138 Nikki Cox Education
10 76295 MW 330 - 450 WSAC 138 Nikki Cox Education
11 76296 MW 1100 - 1220 EBU3B 1113 Ari Garvin Disney
12 76297 MW 1230 - 150 EBU3B 1113 Ari Garvin Disney
13 76298 MW 200 - 320 EBU3B 1113 Ryan Rosenberg Education
14 76299 MW 330 - 450 EBU3B 1113 Ryan Rosenberg Education
15 76300 MW 1100 - 1220 Remote Kellie Miller Media
16 76301 MW 1230 - 150 Remote Kellie Miller Media
17 76302 MW 200 - 320 EBU3B 1124 Brie Iatarola Food
19 76304 TR 800 - 920 EBU3B 1124 Sarah Savage Big Data
20 76305 TR 930 - 1150 EBU3B 1124 Sarah Savage Big Data
21 76306 TR 1100 - 1220 EBU3B 1124 Sarah Savage Big Data
22 76307 TR 1230 - 150 EBU3B 1124 Sarah Savage Big Data
23 76308 TR 200 - 320 EBU3B 1124 Jasmine Tocki Big Data
24 76309 TR 330 - 450 EBU3B 1124 Jasmine Tocki Big Data
25 76310 TR 500 - 620 EBU3B 1124 Jasmine Tocki Big Data
26 76311 TR 630 - 750 EBU3B 1124 Jasmine Tocki Big Data
31 76316 TR 200 - 320 WSAC 132 Sarah Stembridge Disney
32 76317 TR 330 - 450 WSAC 132 Sarah Stembridge Disney
33 76318 TR 1230 - 150 WSAC 138 Haleema Welji* Education
34 76319 TR 200 - 320 WSAC 138 Eric Johnson Voting
35 76320 TR 330 - 450 WSAC 138 Eric Johnson Voting
36 76321 TR 500 - 620 WSAC 138 Eric Johnson Voting
38 76323 TR 930 - 1150 Remote Sherry Boulter Voting
39 76324 TR 1100 - 1220 Remote Sherry Boulter Voting
40 76325 TR 1230 - 150 Remote Sherry Boulter Voting
41 76326 TR 200 - 320 Remote Teresa Zimmerman-Liu Food
42 76327 TR 330 - 450 Remote Teresa Zimmerman-Liu Food

10B Principles of Writing and Communication

In Warren Writing, we have some important principles of writing and communication that we hope to teach in our classes. They are:

  • Good writing starts with good ideas. Write as if you have something to say, instead of as if you have to say something.
  • Good writing means learning to develop your voice. Using big words or perfect commas does not make you sound smarter or more “scholarly.” Great communication is all about using the right words, the right style, and the right syntax, for the right audience in the right situation.
  • Writing is a social activity. Human beings are social animals. Good writing means considering the needs, attitudes, and knowledge of your audiences.
  • Good ideas come with practice and process. Writing is a process. There is no one-size-fits-all process for everyone. Keep working until you find processes that work for you.
  • Give credit where credit is due. Give credit to the writers or thinkers that inspire your own ideas. And they should do the same for you.

Good writing is interconnected to critical thinking and critical reading. Therefore, we have some principles of reading and critical thinking that we hope to teach in our classes:

  • Justice matters. Our college’s namesake, former Chief Justice Earl Warren, inspires our course topics, themes, and questions. As members of a democractic society, we must learn how to decipher what is just, what is fair, and what is right. Our lives depend on it.
  • The Warren Analytical “Toolbox”: Analyzing readings, texts, and issues requires different tools for the job. We will teach you theoretical tools that you can apply to the cultural issues we will learn about.
  • Critical thinking matters. Critical thinking comes from learning to ask tough questions, listening to those whose opinions differ from our own, and practicing self-reflection.
  • History matters. We can look to the past to understand the present and shape the future.

The strategies we hope to teach in this course represent meaningful communicative tools that can help students grow and contribute to the world around them. 

Learning Outcomes

  • Apply critical thinking and reading strategies to a variety of sources that explore the ethical and justice-related causes and effects of data science
  • Define terms such as justice and structural racism and analyze ideologies, course texts, and social movements promoting and opposing these issues in the field of data science
  • Propose a solution to injustices in the field of data science
  • Compose clear claims/thesis statements for different genres and purposes
  • Select evidence/supporting details from course materials in support of their own ideas
  • Demonstrate knowledge of effective writing strategies, including the use of context, reasoning, evidence, analysis of evidence, and use of alternative perspectives (counter arguments)
  • Summarize, paraphrase, quote, and cite course materials appropriately
  • Practice clear writing using strategies such as paragraphing, actor-action, and old-to-new sentence structure