Students will design and lead discussions about our readings. We will have 8 readings, and each discussion is worth 5 points, for a total of 40 points. Students will be divided into teams, and grades are assigned to the entire team. At the end of the semester, students will provide a peer review of those on their team, and that peer review is worth 8 points. Thus, the total point value of all these activities is 48 points (meaning that these activities account for 48% of your grade).

Learning is not the accumulation of facts or the "banking" of knowledge. It is a social process that happens best in communities. People tend to learn best in face-to-face situations when they can talk to one another and collaborate. Recognizing these facts is particularly important given that Large Language Models (LLMs), centralized corporate social media platforms, and online courses are increasingly discouraging these kinds of interactions.

This course is not a place where a professor delivers knowledge to students. It is a place where a professor works alongside students to build conversations about our readings and to design activities that allow us to actively engage with ideas. There are times when the professor has to make decisions and guide the conversation, but there are also times where students in this class will do the guiding and even some of the teaching.

During a typical week, you will be assigned a reading. I will distribute paper copies, and students are required to keep copies of those readings in the binder they have for this class. All students are responsible for reading each assigned reading, annotating that reading, and taking detailed notes. Remember that unit tests are open note, and you will only be able to consult your binder during tests. So, the work you do to prepare each week will help you develop materials that will be useful on those tests.

During our Tuesday class, we will conduct a workshop, during which groups plan Thursday's class, and you may use computers (but not phones) to do that planning. During our Thursday class, we will conduct the discussion that we planned during Tuesday's workshop. The only computers permitted during the Thursday class are those used to deliver slide presentations.

Students will be divided into four teams at the beginning of the semester, and those teams will remain the same throughout the semester. For each reading, teams will be assigned a specific task, and you will work on that task during the Tuesday workshop. Groups will rotate amongst tasks each week.

Task Descriptions

There are four teams, each with distinct tasks for each reading. All teams should plan to develop materials that students can add to their binders.

Those tasks are as follows:

Summary and Analysis of the Reading Team
This team is tasked with summarizing and analyzing the reading. This means developing slides that will be delivered to the rest of the class at the beginning of our discussion and designing a handout for the class. This team will need to do additional research about the reading and to know the reading in as much detail as possible. They should aim to be as expert in the reading as possible.

This team may not use any AI/LLM tools at any stage of the process.

The Summary and Analysis team will want to answer questions such as (this list is not exhaustive):

• Who wrote this piece, and what are their credentials?
• What disciplines do/does the author/authors or work in?
• Where was it published? What kind of publication is it?
• When was it published?
• What is the argument?
• How is the argument constructed? What are its pieces, and how do those pieces fit together?
• What kind of evidence is used to support the argument?
• Who are the likely target audiences for the argument?
• What is the significance of the argument?
• What are some counter arguments or responses to the argument?
• How does the argument fit with other things we have read or discussed in class?

Related Research Team
The pieces we read will cite other writing and will sometimes even directly link to other work. This team is responsible for following those links, citations, and footnotes and then providing some summaries of those sources. Like the Summary and Analysis team, they will deliver a slide presentation about their work and will develop a handout. This team will not be able to summarize every source cited or linked, so they will need to strategize which sources deserve the most attention.

The Related Research team will want to answer questions such as (this list is not exhaustive):

• What kinds of research does the piece cite, and why?
• What patterns do you see in those citations and/or links to other sources?
• What are the reasons for citing or linking to these sources?
• What are the most important articles, essays, videos, etc. referenced in the reading? Why are they important?

This team may use AI/LLM tools. However, if they choose to do so they will need to provide a written document that explains, in detail, which tools they used, why they chose to use them, and how they used them. That document must be no shorter than 350 words and in addition to this write-up must also provide detailed examples of how the tool was used (prompts and responses, any human edits made to the responses, etc.)

Discussion Facilitation and Activity Design Team
This team is tasked with facilitating a discussion of the reading and designing exercises for our in-class session. This means developing questions prior to our Thursday session to spark discussion, and it might also mean seeking out supplemental materials that could help keep that conversation going. This team must also be actively engaged during the Summary and Analysis and Related Research presentations, and it will likely require working with those teams during the Tuesday workshop. During the Thursday session, this group is in charge of ensuring that all students are involved in the discussion and activities, and they may design the session however they see fit. This could mean posing specific questions to individual students, creating break-out groups, or any number of other strategies.

This team's goal is to build an effective and useful way of engaging with the reading. The class session should be a learning experience for all involved. In other words, the goal here is not just to direct questions at the Summary and Analysis team but to use our precious classroom time (we only get 2.5 hours per week) as a learning space for all involved.

In addition to conducting a discussion about the text, this team will need to design some kind of activity for the group. This team will have access to two texts as they consider the kinds of activities they might want to design: The Pocket Instructor: Writing and The Pocket Instructor: Literature. Paper copies of these texts will be available during class.

This team may not use any AI/LLM tools at any stage of the process.

Writing Test Questions Team
Our unit exams will be comprised of short answer questions. These are questions that can be answered in 4-5 sentences, and they must go beyond reporting on the content of the reading. The team in charge of writing test questions will have to design questions that they think would be effective ways of getting students to demonstrate not only that they understand the reading but also that they are able to apply the concepts in the reading. Remember that tests in this course are open-note. This is why it is important that questions not mere asks students to explain the content of the reading. Our tests are not about memorizing content or explaining what we read. That kind of work happens in our notes. Test questions will have to ask students to explain the significance of concepts, to compare arguments and ideas to one another, and to apply concepts and ideas described in the reading.

This team must develop at least 5 short answer questions related to the reading, and teams can and should develop as many questions as possible. Those questions will be shared with the rest of the class, and they will be potential questions on the unit test.

This team may use AI/LLM tools. However, if they choose to do so they will need to provide a written document that explains, in detail, which tools they used, why they chose to use them, and how they used them. That document must be no shorter than 350 words and in addition to this write-up must also provide detailed examples of how the tool was used (prompts and responses, any human edits made to the responses, etc.)

We will have four lab sessions during the semester, one during our "How not to automate everything" unit and three during our "How to pay attention" unit. Students will receive a handout with details of the lab session when they arrive in class, and lab reports will be handed in to Professor Brown before students leave class that day. Students must be present in class to complete the lab report.

At the end of each of our two units, we will have a test during which students can consult their binder devoted to this class. Each exam is worth 15 points. Exams cover readings, labs, discussions, and anything else covered in class. Exams will be composed of student-written exam questions in addition to questions written by Professor Brown.

There is one extra credit opportunity in this class, and it is worth up to 5 points.

Students can read a book of their choosing and meet with Professor Brown for a one-hour discussion. That discussion will be about the book itself, but it will also be a discussion of your experience of reading the book in its entirety. When did you read? Where did you read? What was difficult, challenging, or rewarding about the experience? Given our discussions of attention in this class as well as media reports about the struggles of many college students to read entire books, the goal of this assignment is to provide you with space to read a book start to finish and to reflect on the book as well as on your own capacity for the deep attention often required for this kind of activity.

Students may choose the book they would like to read for this extra credit assignment, or Professor Brown can recommend a book based on the student's interests. The book has to be approved by Professor Brown by September 30. For this extra credit opportunity, the use of AI/LLM technology is not allowed