Psych 245A: Assignments

Everyone is expected to contribute to the class discussion. To prepare for this, you should come up with at least two questions or observations about the assigned readings. This will ensure that you have something you are comfortable discussing in class. Before coming to class, be sure you can summarize the key points of all of the reading selections to be discussed that day. You should be able to follow the flow of logic. Keeping these questions in mind will help direct your reading:

• What is the theoretical or empirical issue being addressed?
• For theoretical selections, what are the key data points used as the foundation of the argument? Do you agree with them?
• For empirical studies, what is the method? Do you understand the figures in the paper? What do the figures represent? Are the overall conclusions supported by the data in the results section?
• What are the main results & implications of the paper? Keep in mind at least one set of data points or one figure that illustrates the main gist of the paper. How does this relate to other selections read that week, or in previous weeks? Most selections are chosen precisely because they are on the same topic as others during that week, though either from a different perspective or as an interesting extension to previous work. All of them aim to answer something about the "big picture" of language learning, so keep in mind what they're trying to tackle. Can you think of any extensions that might logically follow from the current results?
• Important: Don't get hung up on every little wrinkle. Much of this will be primary source language-learning literature, and it may have terminology you're unfamiliar with and background assumptions you don't share. Don't panic: this is what class discussion is for.

Each student is responsible for leading the discussion at least twice for a subset of articles covered during one week. Most likely there will be 3 discussion leads per student during the quarter, unless the class size is particularly large. Leading discussion requires preparation of a brief summary of the paper(s), which should include things like the key question(s) being addressed, the method of analysis/computational model description, the flow of logic, key figures or sets of data points, results, and implications for the language learning question being tackled. You don't have to go into every single detail (since we'll have all read the articles before class, of course), but you should include enough detail so we recall the gist of the articles for discussion. In addition, you should consider for discussion the relation between these articles and the larger question of human language learning, as well as how these articles relate to each other and other articles on the same topic (and sometimes across topics). You may choose to meet with one of the instructors prior to your presentation so we can discuss the readings and key theoretical concepts (we recommend at least one class session before if you'd like to discuss it with us).

In general, you will probably find it easiest to lead the discussion if you have the key points and figures available in a powerpoint presentation.

You will be graded on your successful completion of class discussions. For each class discussion you lead, your grade will include

• being prepared to lead the discussion (this will include either a powerpoint presentation, handout, or really fantastic knowledge you can easily reel off without notes - we don't recommend the last option unless you're very sure of the information)
• how well you lead the discussion - you certainly don't need to know everything, but you need to have thought about what the article's about so we can all try to figure out any problem areas together

If you do not lead class discussion satisfactorily, you will be asked to write a final paper that proposes a computational learning study. (You may of course choose to do one anyway for extra credit, even if you lead class discussion well.) The paper should aim to be concise (ideally between 4 - 6 pages, single-spaced). But if you need to make it longer to include the necessary information, that's fine.

You must include the following in your proposal:

• the question you are trying to address
• relevant previous work on this question
• the methodology you would use (specific algorithm, computational framework, etc.)
• possible results, and what implications each set of results would have for the question you are trying to address
• how the results would fit into the "big picture" of language acquisition (what question would it answer, would it answer it better than previous studies on this topic or address shortfalls of previous studies)

For the most part, each of the papers we read will be structured in this way. Use them as a model for how much detail to include in any one section of your proposed study (for instance, the review of previous work on the question of study). Since you are proposing a computational study rather than carrying it out, you obviously will not have results. However, your study was probably motivated by what you would expect to happen - so your discussion of possible results is very important. What are the implications for the different possible outcomes in your study? Make sure you also include any relevant citations, and a reference section at the end of your paper listing the citations in their full form. (Look to the articles we read for a sense of when to cite other research appropriately.)