V89.0046 - Lab in Human Cognition

Meeting Time/Place: Meyers 460 from 11:00AM-12:50 PM on Mondays and Wednesdays
Instructor: Todd M. Gureckis
Office: Meyer 280
Office Hours: Immediately After Class Monday or by appointment
Email: todd.gureckis@nyu.edu
Teaching Assistant: Jerad Fields (jaf453@nyu.edu), 275 Meyer Suite, office hours: by appointment.
Writing Instructor: Zach Udko (zudko@earthlink.net), office hours: by appt.

Course Description

This course provides hands-on experience with the standard experimental tools used in cognitive psychology research. Students run experiments, collect and analyze data, write research reports, and design and run a new experiment as a final project. Additionally, students read and analyze a number of additional research papers in order to gain a broader perspective on experimental approaches to human cognition. Content areas include memory, categorization, attention, learning, automaticity, and visual perception. Occasional lectures introduce new skills that apply not only in analyzing, communicating, and presenting scientific work, but more broadly (including lectures such as "How to give a good scientific presentation", "How to make an informative graph", "Statistical Thinking").

Laboratory Software

We will be using a combination of open-source tools for running experiments and performing statistical analyses. Thus, there is nothing to purchase! We will make use of Microsoft Excel and perhaps other tools (such as R) for data analysis **.

Readings:

There is no textbook for this course. However, the following may come in handy in writing your reports:

No readings from this book will be assigned, and much of the content, is available on-line via judicious Google searches. There will be other readings made available as PDF files or handouts in class.

Experiments

We will be collecting data for four experiments in class, using each other as experimental subjects. The data will be compiled, then analyzed in class and written up outside of class. The final project will involve proposing, implementing, running, and writing up an experiment.

Attendance

Attendance and participation in lectures and labs is essential. There are in-class tasks and assignments in most class periods that cannot be made up later. Attendance at in-class experimental data collection sessions is mandatory. Students who are absent during data collection will receive a 50% penalty on the lab report for that experiment, no exceptions.

Writing

Lab reports will be APA-style research reports. Specific assignments will be explained in handouts and discussed in class. Reports will be graded on the quality of the ideas and thinking, prose style, and on adherance to APA format. Lab Report 1 will be reviewed by the Writing Instructor prior to submission. For all other reports, the writing instructor will read and assign a grade that will count for 10% of the total grade for that lab.

Teams

For some (but not all) assignments, students will be assigned to work in teams. Teamwork is an important skill in successful research and in life. In scientific research, papers often include an acknowledgements section which details the contribution of each author. Each assignment completed in a team must include a similar statement of the specific contributions of each person.

Readings

To supplement the hands-on-skills developed in this course, we will read a number of real, life (sometimes cutting edge) research papers together. Some of the paper will focus on the different types of data available to experimental psychologist including fMRI, EEG, MEG, eyetracking, etc. There will be short assignments related to these papers, as well as in-class discussion and tours/demonstrations of some of NYU's equipment.

Grading

Grades will be weighed as follows:

There may be opportunities for small amounts of extra credit, such as for brief presentations to the class on various topics.

Academic Misconduct

All work that students turn in must be their own work. Group assignments, all work must have been done by the students on the team, and must include an acknowledgements section detailing the contribution of each team member. Any outside sources (articles, books, people) must be appropriately cited in written assignments. Turning in someone else's work as your own is unacceptable and will result in a failing grade. On the basis of past experience with intellectually lazy students, I have written an automated algorithm written in python that can detect examples of copying from electronic sources such as Wikipedia in submitted papers (yeah it is so easy to plagiarize even a computer script can do it!). More importantly, such behavior is academically dishonest and lazy. Submit only your own ideas and words, or there will be consequences to your academic career.

Research Ethics and Misconduct

Although the experiments performed in this class are for educational purposes, and therefore not covered by the usual informed consent regulations, we will try to treat the confidentiality of the data as if it were. Falsification of any data or analysis will result in a failing grade for the course. (Note that grades are not based in any way on getting statistical significance or any particular result!)

**Statistics Software

Note that part of the class will be learning to use R and excel software packages for data analysis. We will be teaching these skills in the class. However, if you find that you need extra assistance, the Bobst library provide statistical consultants who are familiar with these packages. According to their webpage:

Consultation will be available starting in Feb on the 6th floor in rooms 620 and 621* via e-mail (data.service@nyu.edu), telephone 212-998-3434, by appointment or on a walk-in basis. Staff and student consultants will offer free tutorials and workshops on a variety of statistical packages. Sign up for fall software tutorials on the library's classes page: http://www.library.nyu.edu/forms/research/classes.html


Class Schedule

Each class session may cover several of a variety of topics and tasks. The schedule below is guaranteed to change! Check back for updates

Date Description Slides from Today's Lecture
Jan. 20, 2010 Introductions, Why Study Human Cognition?

PDF Copy of Syllabus for printing
Pre-Course Survey - Please fill out and email to me (remember [lhc]!!)

Assigned Readings:

A recent feature on R in the NYTimes

Simon, H.A. (1998) "What is an 'explanation' of behavior" in Mind Readings: Introductory Selections on Cognitive Science [pdf].

pdf
Jan. 25, 2010 What makes a good experiment? Collect Data for Lab 1


Assigned Readings:

Tulving and Thomson (1973) "Encoding specificity and retrieval processes in episodic memory" Psychological Review 80 (5), 353-373. [pdf]

Mind Performance Hack (Chapter 1 - Memory), Particular pay attention to Hint #12 as it talks about encoding specificity principal which is part of Lab 1 [pdf]

pdf
Jan. 27, 2010 Introduction to Excel (Exercise 1)

handout for exercise 1 [pdf]

Feb. 1, 2010 Introduction to Excel continued (Exercise 2)

handout for exercise 2 [pdf]

pdf
Feb. 3, 2010 Begin Analysis of Exp. 1

lab 1 directions [pdf]
data for lab 1 [xls]

Feb. 3, 2010 How to write a academic paper/continue analysis of Exp. 1

handout from Zach on APA style [pdf]

Feb. 8, 2010 Continue analysis of Exp. 1 in Excel
Feb. 10, 2010 Stats Quiz/Intro to Signal Detection Theory
Feb. 15, 2010 No Class President's Day
Feb. 17, 2010 Final discussion of lab 1 write up/How to make a bar chart

lab 1 test materials [pdf]

*remember* lab 1 is not due Monday at noon (instead of friday)
Feb. 22, 2010 Lab 2: Stroop

lab 2 [zip]
lab 2 pdf [pdf]

Feb. 24, 2010 Lab 2: Stroop (continued)

lab 2 data [txt]

Mar 1, 2010 Lab 2: Stroop (continued)

**Reading**:

MacLeod and MacDonald (2000) "Inter-dimensional interference in the Stroop effect: uncovering the cognitive and neural anatomy of attention" Trends in Cognitive Sciences, 4(10), 383-391. [pdf]

Mar 3, 2010 Lab 2: Stroop (continued)

Mar 8, 2010 Lab 2: Stroop (continued)

Mar 10, 2010 Lab 2: Stroop (finish up)

lab 2 [lab 2 part 2]
lab 2 supp. pdf [supplimentary info on 2-way ANOVA]

Mar 15, 2010 spring break
Mar 17, 2010 Lab 2: Stroop (finish up)

lab 2 [lab 2 part 2]
lab 2 supp. pdf [supplimentary info on 2-way ANOVA]

Mar 22, 2010 Lab 2: Stroop (finish up)

reminder: lab 2 paper will be due monday 3/29 before class
Mar 24, 2010 Lab 3: Mental rotation - collect data

lab 3 [lab 3 proceedure]
lab 3 supp. pdf [lab 3 starting handout]

Mar 29, 2010 Lab 3: Mental rotation (cont.) - first stage analysis

lab 3 data [txt]

pdf
Mar 31, 2010 Lab 3: Mental rotation (cont.) - regression

lab 3 analysis [pdf]
lab 3 reading 1 [shepard]
lab 3 reading 2 [encyclopedia entry]
lab 3 reading 3 (bonus) [anderson's critic in psych review]

Apr 5, 2010 Lab 3: Mental rotation (cont.)

Apr 7, 2010 Lab 3: no class, meet with TA if you need last minute help on mental rotation lab

Apr 12, 2010 Begin working on final projects (assign groups, etc...)

Plan for final projects: pdf
Apr 14, 2010 Continue working on final projects

Today's Reading: Nisbett and Miyamoto - The influence of culture: holistic versus analytic perception.
Remember, everyone should turn in a short summary and their thoughts on the paper at the start of class (1-2 paragraphs). This will count towards your attendance.
Apr 19, 2010 Continue working on final projects

1. Meet to discuss plans
2. Power Analysis Chapter (for in class): [pdf].
3. Use the power.t.test() function to estimate the effect size you will need in order to find a significant difference between your two most important conditions.
Apr 21, 2010 Continue working on final projects

[exp]
Apr 26, 2010 Continue working on final projects

[exp 2]
Apr 28, 2010 Continue working on final projects

[exp 3]

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