Attendance and participation
This class is structured as a seminar, which means much of the content is discussion we have about either (1) the material we read before the class session, or (2) the content of the writing we intend to do. So, attending class synchronously is the best way to experience this content.
The active part of the class sessions will be recorded (i.e.,
discussions of material, but not working on assignments). The
recordings of each class session will then be available on the
Canvas coursesite.
If you attend class synchronously, you just need to participate in the discussion as much as you can.
However, life happens, so if you can't attend class synchronously, please still do the following:
- If discussion questions are due
- submit your own discussion questions
- read through posted discussion questions from other people
- reply to the attendance assignment for that session that you submitted your discussion questions and read through the other ones posted.
- Watch the recording from the active part of class and reply to the attendance assignment for that session that you watched the recording from class. This is of course on the honor system. Be honest. It's good for you.
In-text commenting
In-text commenting is very useful, especially interactive commenting where you can respond to other people's comments and engage in a discussion over the content. However, even just seeing other people's comments on content you also had thoughts about can help refine your own understanding of that content. That's why we’ll be doing in-text commenting for each session's reading(s).
Ideally, this kind of in-text commenting will allow you to specify and better explain your own thoughts for the discussion points you'll create for each session's reading(s).
We'll currently be using Perusall (linked through the Canvas coursesite) as a tool for in-text commenting. You'll be responsible for generating at least two comments (either directly on the content or in response to others' comments) for each session.
Late in-text commenting will be accepted for partial credit, according to Persuall's "linearly-declining" credit rubric. (So, the later you submit after the deadline, the less credit you get.)
- 2 points: On-time submission of 2 (or more) in-text comments
- 1 points: On-time submission of 1 in-text comment
- 0-2 points: Late submission of 1 or more in-text comments
- 0 points: Otherwise :(
Leading discussion
Even though discussions are a group activity, the discussion leader has spent a little extra effort going through the reading selection and identifying the aspects of the reading that are the main points and/or tricky things to understand. Discussion leaders are expected to prepare slides that include key figures, excerpts, or conceptual points. These slides will be used during the group discussion.
Importantly, this does not mean the slides include every detail of the reading. Instead, the slides provide guideposts to start off discussion, and may include the discussion leader's own thoughts on a particular aspect.
Note: If you forget to prepare slides for the class session you lead, you are still responsible for submitting slides and you may submit them late for partial credit.
Discussion slides are due at the beginning of the class session.
Late submissions are accepted until 1pm PST the Friday of Week 10. Please contact the professor if you submit late discussion lead slides, to make sure you receive credit for them.
- 1 to 10 points: On-time submission based on overall quality
- 1 to 5 points: Late submission based on overall quality
- 0 points: Otherwise :(
Weekly writing exercises
This class will have weekly writing exercises. These exercises are writing summaries that are meant to act as mini literature reviews synthesizing the relevant aspects of prior work on a particular topic. You’ll often find these literature syntheses in the background section of published articles or conference papers. Importantly, these summaries are not just regurgitating a chunk of previous work, but rather pulling out and organizing content from previous content according to a specific goal. We'll practice doing this every week.
Writing summaries will typically be 150 words or less, and due the following class session.
Late submissions are accepted until 1pm PST the Friday of Week 10. Please contact the professor if you submit a late writing exercise, to make sure you receive credit for it.
- 1 to 10 points: On-time submission, based on overall quality
- 1 to 5 points: Late submission, based on overall quality
- 0 points: Otherwise :(
Final project: Mini lit review
The final project for this class will have you write a mini literature review for a set of three or more articles of your choosing, with the idea that you're organizing content from these articles according to a specific goal. A goal can include the methods used (e.g., Bayesian models), the area of acquisition modeled (e.g., syntactic islands), or the empirical motivation for a model (e.g., children’s cognitive processing limitations), among other possibilities.
The final mini literature review will be 150-350 words.
In Week 9, you will select the papers and goal of your mini lit review and later give a brief presentation (around 5 minutes) to the class highlighting the main ideas in the papers you selected.
The mini lit review will be due the Monday of Finals week.
Your final writing project will be graded as follows:
- Identifying a set of papers and literature review goal
- 5 points: On-time submission
- 3 points: Late submission
- 0 points: Otherwise :(
- Brief slides presentation of mini lit review main ideas
- 1 to 5 points: On-time submission, based on overall quality
- 1 to 3 points: Late submission, based on overall quality
- 0 points: Otherwise :(
-
Final mini lit review
- 1 to 20 points: On-time submission, based on overall quality
- [12 points] Content: Goal (2 pts), Synthesis from papers (10 pts)
- [8 points] Style: Word choice (2 pts), Sentence structure (3 pts),
Citations of papers in main text (1 pt), Reference section (1 pt),
Within length limit (1 pt)
- 1 to 10 points: Late submission, based on overall quality
- [6 points] Content: Goal (1 pt), Synthesis from papers (5 pts)
- [4 points] Style: Word choice (1 pt), Sentence structure (1.5 pts),
Citations of papers in main text (0.5 pts), Reference section (0.5 pts),
Within length limit (0.5 pts)
- 0 points: Otherwise :(
- 1 to 20 points: On-time submission, based on overall quality
Using AI
In particular, AI is a tool, just like a pencil or a computer. AI can be a valuable tool for drafting content and fine-tuning content that's already been produced, but it definitely isn't a replacement for critical thinking and decision-making. You are always responsible for the ideas, claims, and arguments in your work.
For example, if you provide minimum-effort prompts, you'll likely get low-quality results. You'll need to refine your prompts to get better outcomes. This will take time and practice, as well as your own knowledge of the content.
AI output should be treated with healthy skepticism. Assume what the system generates is likely to be incomplete, misleading, or wrong in some way unless you already understand the topic well enough to evaluate it and verify it using trusted sources. In practice, AI tends to be most useful for topics you already understand reasonably well.
Use your best judgment to determine if/where/when to use this tool. It doesn't always make your life easier and/or better (but sometimes it really does).
Academic dishonesty
Academic dishonesty includes cheating on any assignment, having someone else complete an assignment for you (or doing this for someone else), copying someone else's assignment, and any activity in which you represent someone else's work as your own.
If you are caught being academically dishonest, you will receive a 0 for the assignment and you will be reported for academic dishonesty at the very least. Additional action may be taken, depending on the nature of the incident. Please see the information about academic integrity here, and more about what it means to be academically dishonest.
watched content asynchronously.