Syllabus

BCSC 259: Syllabus

Fall 2023

Time & Location

Mon/Wed 4:50pm - 6:05pm
Hylan 201

Personnel

Instructor: Chigusa Kurumada
Office: Meliora 304
Email:
Office Hours: 3:30-4:30 on Weds

Teaching Assistants

Lillian Ravikoff (lravikof@u.rochester.edu)
Seth Cutler (scutler3@u.rochester.edu)

About This Class

In the beginning, we are little bundles of flesh that cry when we are uncomfortable - and that’s just about the extent of our communicative skills! But within a few short years, typically developing children are fully participating members of the language community. This is remarkable, because human language is an incredibly complex system. In this course, we ask the question: How do we acquire a system of such incredible complexity in such a short period of time? We will consider the steps children take along the path to learning language, including how they learn about sounds, words, higher-level sentence structure, and how to communicate effectively. We will also explore factors within the child and the child’s environment that make this remarkable feat possible.

Learning Objectives

Students in this class will

  1. gain knowledge about the importance of language in the overall cognitive development in early developmental stages.
  2. learn different levels of linguistic representations (e.g., phonology, semantics, syntax, pragmatics) and how they interact with each other in children’s language development.
  3. develop basic abilities to conduct a psycholinguistic study by forming a hypothesis, designing a task, and collecting and analyzing data.

Course Materials

For our readings, we will be drawing from a combination of textbook chapters and journal articles posted to Blackboard.

Optional textbook: Hoff, E. (2014). Language Development (5th Edition). Belmont, CA: Cengage.
You are not required to buy this book. As needed, I will post an electronic copy of relevant chapter on Blackboard.
There will be a copy of the textbook on Course Reserve in Rush Rhees.

I will be using Blackboard quite a bit this semester. Lectures, required readings, in-class quizzes, homework assignments, your grades for individual assignments will all be there. As such, I expect you to check Blackboard at least once before each class to view important announcements.

Course Requirements

  1. Three Exams (50% of your total grade): Our exams are open-book: you can bring your textbook, notes, and handouts.
    • The exams will be a combination of multiple-choice, short-answer, and essay questions. Exam questions will be based on readings, lectures, in-class videos, and class assignments.
    • Your total grade/score will be the average of the highest scores from 2 of the 3 exams. Each will count as 25%. (This means that if you are unlucky and get a really low score on one of the exams, it will not count!) If you are happy with the first two exams, you can skip the last one.
    • There will be NO MAKE-UP EXAMS except for University-sanctioned reasons. If you are unable to take an exam because of a University-sanctioned reason, you must take the exam PRIOR to the scheduled date. This must be requested at least 2 weeks in advance. In case of documented medical or family emergency, a make-up exam will be arranged after the original date.
  2. Final class project (25% of your grade)
    For the class project, you will team up with 1-2 other classmates and conduct an online experiment and data analysis using a crowdsourcing platform. You will summarize your findings in 1) a short written report and 2) a 10 minute presentation.
    • Final class presentation (15%)
    • Final project write up (individual submission) (10%)
  3. Assignments (25% of your grade): There will be 5 in-class quizzes (1 point * 5 = 5% of your grade), and homework (5 points * 4 = 20% of your grade).
    In-class quizzes are scattered across the semester (dates are listed in the calendar p.5- 7 below) and to be completed in the classroom. Quizzes will become available at the beginning of the class. Each quiz has 5 questions and those who provided correct answers for more than 3 questions will get 1 point (= 1% of your total grade).
    Homework assignments must be submitted via Blackboard on the date specified on the calendar (below). Late assignments will be penalized 20% for each day late.
    • HW1 & 2: Answering questions about published research articles
      You will be reading and providing a concise summary of one published article for each HW assignment. This exercise will give you ideas about how a research article is organized, and we will ask you to use the same format in your final project report. Your assignments will be graded by the instructor.
    • HW3: CHILDES problem set
      In class we learn how to extract frequency and collocation information from a large database. In this HW assignment, we will ask you to actually make queries and extract information to complete a problem set in preparation for your actual final project.
    • HW4: Final project research proposal
      With your group members, you’ll discuss what research topic you want to address in the final project. You will write a brief research proposal stating a goal and a prediction to be tested with some hypothetical data.
  4. Attendance: Class attendance and participation are highly encouraged! Please come to class well-prepared, having done the assigned readings and any assigned homework. If you miss a class, you are responsible for any and all material discussed during that class - so be sure to get notes from friends, or to arrange a time to meet with me.
    It is, however, possible to take this class by viewing recorded videos and competing all the assignments/quizzes/exams and other extra credit assignments. Choose your own adventure (while paying close attention to all the announcements on BB in terms of instructions, due dates, and in-class activities.)

Course Expectations

As my students, I expect that you will complete all assignments and participate in the course through regular attendance and engagement in class discussion. I also expect you to respect yourself and your fellow students by only submitting work that is your own.

As your instructor, you can expect me to provide an engaging classroom environment, to promote a friendly, respectful atmosphere for discussion, and to provide ample opportunities for you to ask questions or receive help if you need it. You can also expect me to be open to your feedback throughout the course.

Resources For You

YOUR Teaching Team: Please take advantage of our office hours! I am also happy to help you with your questions on the discussion board or via email, but please respect our time and expect a 24hr email turnaround time on weekdays, and a 48hr one on weekends (that is, please don’t want until the last minute!). If you write with questions via email, make them as specific as you can - if you write something like “I didn’t understand Chapter 2”, it’s going to be very hard for us to know how to help you!

CENTER FOR EXCELLENCE IN TEACHING AND LEARNING: CETL offers learning support to students with all kinds of GPAs and academic records. They have study skills groups, tutors and workshops that you may find helpful. In this class, we respect and welcome students of all backgrounds and abilities, and I encourage you to talk to me about any concern or situation that affects your ability to successfully complete the course. If you require accommodations (e.g. extra time for exams), make sure that you contact me about them via CETL so that I can accommodate you appropriately.

Other Important Information

ACADEMIC HONESTY: Bottom line: don’t cheat, don’t plagiarize. Cases of suspected misconduct will not be evaluated directly by me, but will be referred to the College Board on Academic Honesty. I take this policy VERY seriously. If you unsure of something, please ask me - I am always happy to help you! You MUST complete the homework and quizzes independently. Our exams are open book. The use of books, notes, etc. during exams is permitted - the only things NOT allowed at your desk during an exam are a computer, a tablet, and a cellphone (including any watches and other wearable devices that can transmit information.)

INSTRUCTOR EVALUATION: I want this to be the best possible learning environment for you, and so I encourage you to comment at any time about how the class is going, what you would like to see more or less of, or anything else that would make this a more instructive and supportive environment for you. To this end, I will post class/instructor feedback surveys on Blackboard throughout the semester to find out how things are going - but I also encourage you to talk to me about any issues you’re having. I’m always happy to have visitors during my office hours!

College Credit Hour Policy: This course follows the College credit hour policy for fourcredit courses. This course meets two times weekly for three academic hours per week. The course also includes independent out-of-class assignments for an average of one academic hour per week. In this course, students will complete their homework assignments and brainstorming activities in preparation for their final class projects.

Guidelines for ethical and transparent AI use

With respect to our use of AI technologies in this course, I adopt a general policy of "Unless I Say No," meaning that students are encouraged to use generative AI when it is helpful, unless specifically prohibited for a particular assignment, activity, or other student work. In doing so, we follow the disclosure policy of “Citation and Description” (see an example below). If you have used AI to edit or modify your work product, please submit both an original and an edited version (see Example 2). Note that you will NOT be penalized for using generative AI technologies as long as you clearly and honestly disclose your use. Failure to do so may be considered a violation of academic policy. In case of doubt, I reserve the right to ask for more information or to ask you to reproduce the work product without using AI.

  • Citation + Description: Include a citation along with a sentence or two stating how generative AI was used in the student work.
    • Example 1: I generated this text, code, or image in part with ChatGPT-3.5. It was used to identify, calculate and interpret the correct Excel formula.
    • Example 2: I generated a draft of this text (attached) and used the browser version of DeepL to edit it. I incorporated the edits and added further edits to the submitted version.

Because all AI technologies are in their nascent stages, it's impossible for me to provide a finite list of do's and don'ts. I would like to invite you to explore their possibilities in creative ways, while being mindful of ethical concerns. I ask you to be transparent in your use and mindful of copyright and intellectual property regulations. Below are general considerations provided by the Simon School of Education. If you have any questions or concerns, please contact me directly.

  • Cautionary Note About Hallucination in Generative AI: Generative AI tools, while immensely powerful, sometimes generate outputs that are inaccurate, made up, or not reflective of reality. Students need to critically analyze AI-generated content and vet for factual errors and inconsistencies. Students remain accountable for the accuracy, integrity, and ethical use of the information in their work.
  • Data Privacy: Special care must be taken regarding data privacy. Using generative AI grants the use of the data to the AI tool. Data or documents that are copyrighted should not be uploaded into AI without permission from the copyright holder. Students remain accountable for the accuracy, integrity, and ethical use of the information in their work.
  • Data Bias: Special care must be taken regarding data bias. Some of the information provided via generative AI may be biased. Examples of bias include racial, gender, nationality, religion, etc. Students remain accountable for the accuracy, integrity, and ethical use of the information in their work.