In-class writing exercises
Every class session will begin with a brief in-class
writing exercise. These exercises are meant to help
you practice and hone your ability to write clearly,
concisely, and appropriately for your intended
audience. You will work on these individually at the
beginning of class for the designated time, and submit
them via Canvas EEE by the designated time in
class.
Submissions are accepted as on-time through 11:59pm PST
the day the in-class exercise is due.
Late submissions are accepted until 11:59pm PST the
Friday of Week 10. Please email the
professor if you submit a late writing
exercise, to make sure you receive credit for it.
- 5 points: On-time submission where you put in a good effort
- 3 points: Late submission where you put in a good effort
- 0 points: Otherwise :(
Attendance
Being "present" in class has several benefits:
- You hear additional information relevant for the in-class exercises and the assignments you're working on.
- You have a chance to ask the professor and your classmates for help on things you're currently stuck on.
- You have dedicated time to make progress on your assignments.
When the class is offered remotely (either only remotely or in a
hybrid format), the following policy applies because life can interfere sometimes:
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 weren't able to attend class in real time, please do the following to receive partial attendance credit (1 pt):
- look over the in-class exercise for the day
- post your own reply to the in-class exercise
- like any in-class exercise replies you thought were good
- watch the linked recording of the active part of the class session
- and then reply to that session's attendance assignment with a
message like "I did the
in-class exercise and watched the recording"
Latex exercises
These exercises are designed for you to practice formatting and typesetting using the Latex software available through overleaf. There are several throughout the quarter, with time in class to work on them. Late submissions are accepted through 11:59pm PST the day the latex exercise is due.
- 5 points: On-time submission with no serious mistakes
- 4 points: Late submission with no serious mistakes
- 3 points: On-time submission with serious mistakes
- 2 points: Late submission with serious mistakes
- 0 points: Otherwise :(
Peer review
Peer review (the primary form of feedback we get in science) is an important component of scientific
writing -- both receiving peer reviews and generating
helpful peer reviews. For every abstract draft you
generate, there will be a peer review component --
this means you need to have a draft of your abstract
ready for review at the appropriate time, and you need
to generate helpful peer reviews. In this class, that
means having your draft ready the day we're doing peer
reviews in class, and generating peer reviews for your classmates to use when revising their
abstracts.
Note: Informative peer reviews generally start with an overall
comment about the quality of the draft, and then
separate sections for major comments (general
issues/observations, suggestions for organization,
etc.) and minor
comments (specific questions/observations about one part, typos, etc.).
While on-time peer reviews are the most useful to the people whose drafts you're reviewing,
you can still receive late credit for
peer reviews you complete after the deadline. This is because writing peer reviews
is a useful skill to practice.
- 5 points: On-time submission where you put in a good effort
- 3 points: On-time submission where
there's still enough there to peer review OR
late submission where you put in a good effort - 0 points: Otherwise :(
- 5 points: On-time peer review where you put in a good
effort
(or your assigned draft wasn't available) - 3 points: Late submission where you put in a good effort
- 0 points: Otherwise :(
Revised abstract drafts
Once you have your peer reviews, you will then try to
incorporate that feedback into a revised abstract
draft. Revised draft submissions are accepted as
on-time at the beginning of class
the day the revised abstract is due, with late
submissions accepted through 11:59pm PST the day the
revised abstract is due). Because these are still drafts, they're graded
primarily on your effort to incorporate the comments.
Your revised draft should highlight (color-code
usually) the parts of your draft that you updated based on
your peer reviews.
Note: Even if you didn't receive peer reviews
(which can happen if you submitted your draft late), you can still revise your draft
just by looking it over yourself again with fresh eyes.
- 5 points: On-time submission where you put in a good
effort
and highlighted the parts you updated - 4 points: Late submission where you put in a good effort
and highlighted the parts you updated - 3 points: On-time submission where
your effort was not-so-good
and/or you didn't highlight what you updated - 2 points: Late submission where
your effort was not-so-good
and/or you didn't highlight what you updated - 0 points: Otherwise :(
Midterms: Re-revised abstracts
Twice during the quarter, you'll submit a re-revised abstract. This will build off one of the revised abstract drafts you've already submitted, incorporating your growing knowledge about how to write well about language science (and also allowing you to experience the iterative cycle of revision involved in science writing). These serve in place of midterms, and will be graded more stringently according to the rubric below. Late submissions will be accepted through 11:59pm PST the day the re-revised abstract is due for a 10% penalty (-10 points off the top). For submissions after this time, please make arrangements with the professor to receive late credit.
- First paragraph:
- Context for main question & main question itself (10 pts)
- Methods to answer question (5 pts)
- Results summary (10 pts)
- Other paragraphs:
- Relevant background (by other people) (10 pts)
- Specific details about your approach & analysis (10 pts)
- Specific details about your results (10 pts)
- Interpretation of results (10 pts)
- Connection to larger context of language science and/or future
extensions
(10 pts)
- Style:
- Lexical choice (5 pts)
- Sentence structure (10 pts)
- Tailored to intended audience (5 pts)
- Within abstract length limit & obeying formatting guidelines (5 pts)
Final abstract
Your final abstract will be generated based on a paper or project we haven't spent time on in class, and will be one you choose yourself. You'll draw on your science writing skills to generate a draft, incorporate feedback from peer reviews, and produce a final abstract targeted to a specific audience. Late submissions will be accepted through 11:59pm PST the day the final abstract is due for a 10% penalty (-10 points off the top). For submissions after this time, please make arrangements with the professor to receive late credit
Extra credit
Extra credit can be earned on a per-assignment basis by helping answer your classmates' questions, using the discussion thread on the message board dedicated to questions about class assignments.
If someone helps you on your assignment, please indicate who it was and how they helped you as a comment when you turn your assignment in.
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.
For instance, 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.
In terms of content, assume what the system generates is probably wrong, unless you already know the answer and can verify with trusted sources. It works best for topics you deeply understand. This is why tailoring your prompts can be very helpful.
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.