Psychoinformatics : A complementary curriculum for the science of human behavior

June 11, 2014

Note: Edited on June 12, 2014 - At the suggestion of TY, I've changed the title and preamble to describe psychoinformatics as a complement to psychology (rather than an alternative, as was my original idea).

A few a weeks ago I made a ripple or two in the twittersphere with a previous post lamenting the lack of rigour in the psychological sciences. The post itself was inspired by the storm in a teapot known as #repligate, but got me thinking about broader issues - namely, the huge amount of statistical and computer skills I had to pick up (and am still picking up) in order to do my first research job properly. Critically, hardly any of this was taught while I was an undergrad - or if it was, it was not part of a mandatory curriculum. My feeling is that we could accelerate the discovery process by providing an undergraduate program that was designed to impart these skills.

So what I've done here is try to design a four-year undergraduate curriculum for the science of human behavior. It is heavy on lab work, stats and computer science, but could be offered as a complement to an existing psychology undergrad - but what to call it? Tal Yarkoni has already made some attempts to popularize a name : Psychoinformatics. Ideally, a psychoinformatics degree would attract students who are interested in understanding the patterns of human behavior but also have a keen interest in the tools necessary to study them. Optimally, graduates would be able to take part in industry and/or academic research immediately following college graduation.

So let me lay this on you. Be warned that this is a work in progress...and holler at me on twitter if you have any comments.

Year One
Term 1Term 2
Psych 1 - w/ LabPsych 2 - w/ Lab
Stats 1 - w/ R LabStats 2 - w/ R Lab
Philosophy - Critical Thinking/ReasoningProgramming 1 - Python/Ruby/Javascript
Reading 1 - The primary research articleReading 2 - The review paper

Year one begins with students being introduced to experimentation. The Psych and Stats courses are expected to work synergistically - with the data collected in Psych Lab being analyzed in Stats Lab. In this way, experimental designs are coupled with the appropriate statistical techniques, making the point that theory is only useful when you have a means to test it. These classes may be large but the lab sizes must be small enough that the students can have one-on-one help from an instructor. We will also introduce students to the jargon-laden hellscape of academic writing, by spending time reading primary research, and then review papers. Critically (pun intended) - we begin the degree with a course on logic and reasoning, and in the second term segue into the cold logic of talking to a machine.

Year Two
Term 1Term 2
Cognition LabMemory Lab
Programming 2 - DatabasesProgramming 3 - The Cloud (APIs etc)
Writing 1 - The Primary Research ArticleWriting 2 - The Review Paper

In year two, students refine their lab skills doing classic experiments on Cognition and Memory (they will use the programming and statistical skills they picked up in year one to implement these experiments). During this year, they will also learn how to store and search through data using databases, with an expectation that by Term 2 all collected data will be stored using these methods. Students will also be introduced to applications of the behavioral sciences : Economics and Marketing. Students will also be introduced to cloud computing, and will learn how to build and use APIs to interact with various web services. Importantly, they will begin writing their own research reports, as well as review papers.

Year Three
Term 1Term 2
Bioinformatics w/ LabBig Data w/ Lab
Stats 3 w/ LabStats 4 w/ Lab
Computational ModellingHistory of Psych
Writing 3 - The Grant (small)Writing 4 - The Grant (large)

In third year, students will start digging into more advanced analysis techniques. In Bioinformatics (coupled with Stats 3) they will be exposed to data sets that beg for more than just t-tests and correlations. Things like bayesian statistics, graph theory, and wavelet analysis are on the table here. In Big Data (coupled with Stats 4), students learn about the opportunities and challenges of learning of data sets accumulated through the use popular websites/social media - tracking and predicting individual behavior is the focus here (think netflix movie recommendations). However, we don't want to neglect the past - in History of Psych, students will study psychology through the years to get a perspective on what gets researched and why. This will tie in nicely with Writing 3 and 4, where students will learn how to write solid grants, starting with smaller scholarship/fellowship style grants in Term 1, and moving on to large grants intended at supporting entire laboratories.

Year Four
Term 1Term 2
Internship 1Internship 2
Current Issues 1Current Issues 2
Philosophy of ScienceCreative Writing - Science Fiction

In the final year of the program, students will spend a large portion (hence 3 courses instead of 4) of their time interning in either an industry or academic lab, and run their own research project which they might design with the help of a mentor. Deliverables from this course should be a primary research paper and a small grant, though ambitious students may attempt a review paper and/or large grant. They'll spend the rest of their time disucssing whatever is making waves in the field in Current Issues 1 and 2 - giving them a clear idea of what areas are most likely to get future funding. In Philosophy of Science, they'll have their faith tested in the scientific method. Lastly, they'll take a creative writing course in which they'll imagine the ways in which new technologies could change the world.

So that's it. I believe that this curriculum (or something close to it) would impart the skills necessary to design, implement, write-up, and fund experiments that will broaden our understanding of human behavior. Now all I need to do is score a faculty gig and start my own department...easy enough, right?

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