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Gorilla Academy

  • Welcome to Gorilla Academy
  • Attention
  • Overview of selective attention
  • Building the task
  • Creating the experiment
  • Analysing the data (attention)
  • Advanced analysis using R Studio & JASP
  • Language
  • Overview of speech perception
  • Creating the task and experiment
  • Analysing the data (language)
  • Advanced analysis using R Studio
  • Learning
  • Overview of learning
  • Creating the n-armed bandit task
  • Organising the data in Excel (learning)
  • Calculating learning rate and total score in R Studio
  • Data analysis in JASP
  • Social Influence
  • Overview on social influence
  • Creating the Rotten Tomatoes task
  • Are you more influenced by critics or fans?
  • Sustained Attention to Response Task (SART)
  • History of the SART with Prof Ian Robertson
  • Building the SART
  • Are there differences in sustained attention with age and dementia?
  • Advanced pre-processing and using ggstatsplot in R Studio

Gorilla Academy is a growing library of content, including:

  1. Short introductions to key topics in Psychology and Behavioural Science

  2. In-depth reviews of academic papers, including how to find what you need to replicate an experiment

  3. Step-by-step guides showing you how to build a range of different tasks (all tasks in Open Materials)

  4. FREE downloadable data for analysis

  5. Video lectures covering basic and advanced aspects of data organisation and analysis (including excel and R scripts)

Select a topic from the list and start your journey into Online Research Methods using Gorilla!

Overview of selective attention

The video underneath will guide you through the fundamental experiments and theories in the field of selective attention.

For more in-depth coverage of this topic I'd recommend a good cognitive psychology textbook. When researching this lecture, I used Cognitive Psychology: A student's handbook by Eysenck & Keane (2020)



Length(mins): 14:21

Creating Dalton & Fraenkel in Task Builder

In this video, I build a dichotic listening task in Gorilla Task Builder. In this task participants listen to an audio scene and respond using text buttons and text entry boxes.

This task was originally created by Dalton & Fraenkel (2012), you can read the full manuscript here.

You can also find the task on Gorilla Open Materials here.



Length(mins): 20:41

Creating Dalton & Fraenkel in Experiment Builder

In this video, I bring evertyhing together to create the full experiment in the Gorilla Experiment Builder. This includes going through the questionnaires, and using a randomiser to direct participants into one of four versions of the task.

This task was originally created by Dalton & Fraenkel (2012), you can read the full manuscript here.

You can also find the full experiment on Gorilla Open Materials here.



Length(mins): 14:31

Analysing Dalton & Fraenkel (2012) using Excel & JASP

In this video, I'll show you how to analyse the data. First, we'll use Mircosoft Excel and pivot tables to pre-process the data. Then we'll run a Chi Squared analysis in JASP.

You can download a copy of the data here. 

Length(mins): 16:04

Advanced data organisation and analysis using R Studio & JASP

In this video, I'll show you a more advanced approach for analysing your data. This includes using R Studio to fully pre-process the data, creating a more comprehensive data spreadsheet. We'll run a Chi Squared analysis in JASP and look at the effect of filtering participants that didn't pass the checks.

You can download a copy of the data here. 

You can download my R script here. 

Length(mins): 15:37

Overview of speech perception

This video will introduce the key problems, solutions, and models in speech perception. This includes an understanding of Motor Theory, TRACE, and Cohort models of speech perception.

For more in-depth coverage of this topic I'd recommend a good cognitive psychology textbook. When researching this lecture, I used Cognitive Psychology: A student's handbook by Eysenck & Keane (2020)



Length(mins): 20:16

Building Karas et al (2019) in Gorilla

In this video, I build a speech perception task in Gorilla Task Builder. In this task participants will either listen to an audio file or watch a video of someone saying a word with or without noise. Participants are instructed to type in what they heard. This task uses video zones and text entry boxes.

This task was originally created by Karas et al (2019), you can read the full manuscript here.

You can also find the task on Gorilla Open Materials here.



Length(mins): 29:04

Analysing accuracy data using an ANOVA

In this video, I'll show you how to analyse the data. First, we'll use Mircosoft Excel and pivot tables to pre-process the data. Then we'll run a repeated measures ANOVA in JASP.

You can download a copy of the data here. 

Length(mins): 13:24

Advanced analysis of accuracy using mixed effects models in R Studio

In this video, I'll show you a more advanced approach for analysing your data. This includes using R Studio to fully pre-process the data and run a generalised linear mixed effects model as in the original study.

Mixed effects models are a great tool to learn about. I don't have enough time to go into a lot of detail in this video so have a read of these useful links by Michael Clark and Coding Club.

You can download a copy of the data here.  You can download my R script here. 

Length(mins): 31:32

Learning: A computer science perspective

This video will introduce the three main learning types; Supervised, Unsupervised, and Reinforcement Learning. Here, I'll discuss the key differences between each type of learning and how each type of learning is engaged for different situations.

For more in-depth coverage of this topic I'd recommend a good cognitive psychology textbook. When researching this lecture, I used Cognitive Psychology: A student's handbook by Eysenck & Keane (2020)



Length(mins): 18:14



High Score

If participants wanted they could leave their initials and be placed on the Gorilla High Score Screen. Congratulations to the top 5 players!

Name Score
GW 5171
sb 5082
DG 4728
Vasili 4624
KA 4613

Building Behrens et al (2007) in Gorilla

In this video, I build an n-armed bandit task in Gorilla Task Builder. Participants will choose between a blue and green slot machine in order to win the most points. Each slot machine has a different probability of paying out, as well as a different number of points available. The probilities and points are driven by a spreadsheet. At the end of the video, I used a little bit of scripting to calcalate who's a winner and what the total score is.

This task was originally created by Behrens et al (2007), you can read the full manuscript here.

You can also find the task on Gorilla Open Materials here.

You can download an example of the excel task spreadsheet including formulas here. 

Length(mins): 27:48



High Score

If participants wanted they could leave their initials and be placed on the Gorilla High Score Screen. Congratulations to the top 5 players!

Name Score
GW 5171
sb 5082
DG 4728
Vasili 4624
KA 4613

Calculating learning in Excel

In this video, we'll use Mircosoft Excel and pivot tables to pre-process the data. This includes using Excel formulas to calculate new variables.

You can download a copy of the data here. 

Length(mins): 16:14



High Score

If participants wanted they could leave their initials and be placed on the Gorilla High Score Screen. Congratulations to the top 5 players!

Name Score
GW 5171
sb 5082
DG 4728
Vasili 4624
KA 4613

Calculating learning rate and total score in R Studio

In this video, we'll use the hBayesDM package in R Studio to calculate the learning rate for each participant. We'll also calculate scores for winning trials along with the total scores for stable and volatile periods.

If you're interested in learning more about computational modelling of beahaviour there are some great online resources including this page by Drs den Ouden and O'Reilly.

I would strongly recommend going to this page for a course run by Miriam Klein-Fl├╝gge, Jacqueline Scholl, Laurence Hunt, and Nils Kolling from Oxford University where they discuss modelling a variation of this exact task.

You can download a copy of the data here.  You can download my R script here. 

Length(mins): 10:51



High Score

If participants wanted they could leave their initials and be placed on the Gorilla High Score Screen. Congratulations to the top 5 players!

Name Score
GW 5171
sb 5082
DG 4728
Vasili 4624
KA 4613

Comparing behaviour in stable and volatile periods using JASP

In this video, we'll use paired T-tests, repeated measures ANOVAs, and correlations to explore this dataset. We'll also look at assumptions and how results change when you use the correct assumptions. All the analyses are conducted in JASP.

You can download a copy of the data here. 



Length(mins): 16:48



High Score

If participants wanted they could leave their initials and be placed on the Gorilla High Score Screen. Congratulations to the top 5 players!

Name Score
GW 5171
sb 5082
DG 4728
Vasili 4624
KA 4613

An overview of Social Influence

This video will introduce some of the different types of social influence, inlcuding: conformity, obedience, social learning, nudging, framing, and contagion.

In this lecture, I also made reference to the Stirling University's Nudge database. Click on this link to see lots of real world examples of nudging

For more in-depth coverage of this topic I'd recommend a good social psychology textbook. When researching this lecture, I used Social Psychology by Hogg & Vaughan (2017)



Length(mins): 21:35

Building a social influence task in Gorilla

In this video, I build a novel social influence task. Participants rated a series of movies using sliders, after which they learnt what the critics and audience thought and make a second rating. This video shows you how to use branching and embedded data, as well as a bit of scripting to change an attribute (move slider tip to participants previous rating).

Although there isn't a task out there like this, a lot of inspiration was drawn from De Martino et al (2017), you can read the full manuscript here.

You can also find the task on Gorilla Open Materials here.



Length(mins): 27:28

Analysing a social influence task in Gorilla

In this video, we filter the data in excel as an alternative approach to preprocessing the data. We analyse the data using T-tests, correlations, and linear mixed effects modelling. All the analyses are conducted in JASP.

You can download a copy of the data here. 



Length(mins): 27:07

History of the SART with Prof Ian Robertson

I was incredibly honoured to have one of my mentors and creator of the SART, Professor Ian Robertson, tell me all about Sustained Attention, the creation of the SART, and how to use this amazing tool effectively.

Professor Ian Robertson is Co-Director of the Global Brain Health Institute and Professor Emeritus at Trinity College Institute of Neuroscience

For more in-depth coverage of this topic I'd recommend a good cognitive psychology textbook. I've used Cognitive Psychology: A student's handbook by Eysenck & Keane (2020) in the past.

Prof Ian Robertson has also written a number of award winning books on this topic and others, including Mind Sculpture, The Winner Effect, The Stress Test and his newest book How Confidence Works is coming out in June 2021. You can find out more about Prof Ian Robertson and his works here.



Length(mins): 18:13

Building the Fixed and Random Sustained Attention to Response Tasks (SARTs) in Gorilla

In this video, I build the fixed and random Sustained Attention to Response Tasks as described in Robertson et al (1997).

Participants will see a series of digits (1-9) in a fixed or random order. Participants were required to respond whenever a number came on screen, unless it was a 3. Being able to snap out of a routine rhythmic patterns is a hallmark of sustained attention. Building this task required using different content types, encoding keyboard responses, using screen time limits, and different spreadsheet randomistion rules. There's even a bit of scripting to randomly change the size of the numbers on each trial.

You can also find the task on Gorilla Open Materials here.



Length(mins): 29:13

Analysing errors in SART performance across Young, Old, and MCI/Dementia

In this video, we pivot tables in excel to preprocessing the data. We also use filters in excel to diagnose some crazy values in our data. Later, we'll use correlations, a one way ANOVA, and a repeated measures ANOVA to address our hypotheses.

All the analyses are conducted in JASP.

You can download a copy of the data here. 

Length(mins): 25:57

Advanced pre-processing and analysis of the SART in R Studio

In this video, I'll show you how to preprocess your data in R Studio using some basic dplyr functions. In R Studio I was able to easily deal with the double tap problem mentioned here.

I'll also show you some simple and powerful analyses using ggstatsplot. It's a wonderful tool that covers pretty much every type of analysis, combining beautiful plots with detailed stats.

You can download a copy of the data here.  You can download my R script here. 

Length(mins): 12:44