Lab #2: Word Recognition


Posted Monday November 21st; due Thursday December 8th.


In the previous lab in this course you ran pre-prepared experiments. In this lab you will create a pair of simple experiments that have not been prepared for you in advance. The studies are relatively simple, but you will have more direct control over all stages of the creation of the experiments.

The objective of the lab is to design, implement and run two Lexical Decision experiments. The goal of the experiments is (i) to verify the existence of frequency effects in accessing lexical items, and (ii) to test for (semantic) priming effects in lexical access. Things that you should learn from the lab include:

• Researching and designing an experiment using a paradigm that is (possibly) novel to you
• Analyzing the parts of an experiment in sufficient detail to implement it in a computer program
• Stimulus creation for lexical access studies
• Preliminary analysis of simple reaction-time datasets
• Learning to use widely used experimental control software, most likely PsychoPy, or any other tool that serves your needs.

The Experiments

The Lexical Decision Task is one of the simplest and most widely used reaction time tasks in psycholinguistics. In the simplest visual version of this task, participants read words and non-words that appear one-at-a-time in the middle of a computer screen. The participant’s task is simply to respond “yes” as quickly as possible if a real word is presented (e.g. TABLE, DOG, ACRONYM), or to respond “no” as quickly as possible if a sequence of letters is presented that is not a word (e.g. GLUB, FENDLE, DERILIOUS). The Lexical Decision task has been used to demonstrate a variety of properties of lexical access, including frequency sensitivity and many kinds of priming effects. Your task in this lab is to design, implement and run two simple lexical decision studies, with the goal of testing:

  • Frequency sensitivity in lexical access (in other words, the fact that more frequent words are accessed faster than less frequent words).
  • Semantic priming in lexical access [or you could choose another priming design, if you prefer to try something more innovative]

You can implement the experiment using any software package that you prefer. But we recommend to use PsychoPy, a modern, flexible, cross-platform tool. You should aim to test and analyze results from at least 5 people. Beyond this, the details of the design of the studies are left largely to you. Although this leaves the choice of design relatively open, it does not mean that ‘anything goes’ – rather, it means that you are responsible for doing some research into what would be an appropriate way to design the experiment.

Although you should submit your own copy of the lab report, you are strongly encouraged to collaborate with other members of the class on this lab. Figuring things out together can be very useful, as long as it doesn’t mean that you fail to learn how to do something yourself.

Some Potentially Useful Resources

Using PsychoPy

Download PsychoPy here:

You should download the standalone version so you don’t need to install Python separately, but you may be prompted to download other updates. Also, on recent versions of MacOS X you may be prompted to install X11. This is a very easy procedure.

When you open PsychoPy, you may receive an error message, saying that your security settings do not allow you to run an app that you downloaded from the internet. You can easily go into System Preferences > Security & Privacy to override that block. Then PsychoPy should open without problems.

PsychoPy Basic Overview

  1. PsychoPy always opens to a routine called “trial”.
  2. You can add components to this routine, which appear in categories on the right of the main window. For a trial such as lexical decision, you will likely want several text components and a keyboard response component. Other possible stimulus components include sound files, movies, images, and shapes. Response components include mouse clicks, microphone recordings, and other on-screen selections.
  3. Click on a component to add it to your trial. Once selected, you can edit the start and stop time (in seconds), and details about the display. You can stagger components to overlap with each other, or present them with gaps in between.
  4. You can create separate routines for each part of an experiment, such as the instructions, practice trials, feedback, etc.
  5. To create multiple trials, you should insert a Loop in the flow section. For multiple trials, insert a loop surrounding the routine(s) you would like to repeat. This usually consists of a trial routine and possible feedback routine. If you have a variable you would like to change every repeat (usually your stimuli!), you should import stimuli from an Excel document. Create a document with a column for each variable item – items in the same row will be used in the same repetition (this is key for a priming task – the prime and target will go together in the experiment if they’re in the same row in Excel). To reference a variable item, use $[column header] and indicate that it should set every repeat (if applicable).
  6. To specify how you want to loop through your Excel document, change the “loopType.” You may want to go through the document sequentially, or perhaps a random order is preferred.

Creating a mini Lexical Decision task

These instructions show you how to generate a very rudimentary Lexical Decision task. You do not need to follow the exact parameters, timing etc. in your experiment. These are included only as a guide. [Thanks to Julia Buffinton for preparing these notes.]

  1. Generate your stimuli: create an Excel document with two columns, e.g., stim, corrAns. Insert the text you want to display in the stim column (words and nonwords) and the correct response in the corrAns column. The correct response should correspond to the keys you use to collect responses, e.g., make “f” the correct response for words and “j” the correct response for nonwords. Save the file. Keep the files for your experiment in a single folder.
  2. Open PsychoPy. Save your experiment in the same folder as your Excel spreadsheet.
  3. In the trial routine that is automatically generated, add a text item called fixation that consists only of a plus sign that starts at time 0 and lasts 1 second.
  4. Then, create another text component that starts at time 1.5 and has no specified duration (clear this field). Set the text to “$stim” (no quotes around it). Change it from ‘constant’ to ‘set every repeat.’
  5. Last, add a keyboard response component that starts at time 1.5 (no endpoint) and has the allowed keys ‘f’ and ‘j’ (in quotes), separated by commas. Make sure ‘Force end of routine’ and ‘Discard Previous’ are checked. Also check ‘Store correct,’ which will note the correct answer in the output file. When the Correct Answer field appears, type “$corrAns” (no quotes) to reference the correct answer you indicated in your stimuli spreadsheet.
  6. Then, click on Experiment > New Routine and name your new routine instructions.
  7. In this routine, add a text item that starts at time 0 and has no duration. In the text field, add instructions for the experiment and a note that participants should press the space bar when they are ready to start.
  8. Lastly, add a keyboard response for ‘space’ that begins at time 2 (so they actually read the instructions!) and has no duration. Make sure that it forces the end of routine.
  9. To put the instructions and trials together, go to the Flow section of the Builder. Click ‘Insert Routine’ and then instructions. Click the dot that appears before the trial routine to insert it first.
  10. To loop through trials, click ‘Insert Loop’ and then click on either side of the trial routine. Change the number of ‘nReps’ to 1 (this loops through your Excel spreadsheet only once) and then ‘Browse…’ for ‘Conditions’ to add your Excel document.
  11. Last, click Run! It may take a little while to compile if this is your first time running the experiment.
  12. You can always make this more sophisticated by adding a Routine indicating the end of the experiment or another loop with practice trials that gives feedback about responses, or by adding additional components of a routine in a priming design.

Running the Experiments

You should aim to test at least 5-6 participants in your experiments. This is many fewer than you would normally use, but it should be adequate for the purposes of this lab. Ask your classmates to participate — and offer yourself as a participant in their experiments! Normally, you would want to include only native speakers, of course, but for the purposes of this lab exercise, advanced non-native speakers will also suffice.

Make sure that your participants understand what they have to do before you begin the experiment, and that they have a rough idea of how long the experiment will take. Be consistent in giving them instructions on how to perform the task. You might consider giving your participants a few practice trials, to familiarize them with the procedure.

Analyzing the Results

In presenting the results of both studies, you should calculate average (mean) RTs for your different experimental conditions (e.g. high/low frequency, related/unrelated pairs). You should also include information about the variance associated with each average, e.g. Standard Error (Std. Err. = Std. Dev. / sq. root of number of participants).

You should probably also exclude from your analysis trials on which the participant gave an incorrect response. You may also consider excluding outlier trials (e.g. the most extreme RT values for each participant, or any trials above some cut-off value that is likely to indicate distraction or equipment problems rather than slow processing). In your write-up, you should describe what data was excluded, and why you chose to do this.

One question to consider: although you do not need to run statistical tests on the results of your studies, you should give an approximate indication of how great the difference between the means is in terms of numbers of standard errors. If the difference between the two means is less than the sum of the two standard errors, then it is unlikely that the difference would be significant (at the p < 0.05 level). If the difference between the means is less than 2 standard errors, you should give an estimate of how many more participants you would need to run in order to reach this level (explain your reasoning).

In writing-up the results of your studies, you should explain your choice of methods and stimuli. You do not need to write at great length, but you do need to be explicit. Take a look at other relevant literature for guidance in writing up details of methods, etc.