Oscar Olvera Astivia discovered the field of educational measurement during his undergraduate studies thanks to a multiple-choice midterm that left him wondering how to calculate the probability of passing under a specific set of circumstances. Following the spark of curiosity, Olvera Astivia has earned a PhD in measurement, evaluation and research methodology from the University of British Columbia and taught at the University of South Florida in the educational measurement and research program.

Now, Olvera Astivia is joining the University of Washington College of Education this fall as an assistant professor in education measurement and statistics.

Olvera Astivia works in quantitative methodology, a field that involves putting a magnifying glass on the methods used by researchers within the social sciences, education and quantitative methodology itself.

In the Q&A below, Olvera Astivia discusses his research agenda, what courses he’ll teach and how quantitative analysis can serve as a powerful tool for understanding and helping people.

What drew you to education?

Many years ago as an undergraduate student in Canada, I was double-checking my answers to a midterm test that was purely multiple-choice. I never liked submitting my exams early on the off-chance that I’d remember something, so I’d usually read and re-read the questions and try to come up with sensible reasons as to why different options could be correct. Eventually, I asked myself the question: “If I were to answer this test purely at random, I could calculate the probability of getting a passing mark. However, I am not answering these questions at random. I actually know things about what’s being asked, but I am uncertain about them. How could I calculate the probability of passing under this set of circumstances?” That question led to some serious internet searching until I found the field of Item Response Theory, which introduced me to the area of educational measurement and helped me choose this area to work on.

Describe your research agenda. What makes this work meaningful to you?

I did my graduate education at the same time as the Replication Crisis and the movement towards Open Science started to take form. By the time I was getting ready to defend my PhD dissertation, the evidence was too overwhelming to be ignored: research in the social sciences was in trouble. The realization that what were once considered well-established findings in education and psychology could be ... well ... not true made me wonder whether or not we, in the world of quantitative methodology, could also have our own overlooked host of issues. I believe this type of critical thinking is very important to quantitative researchers because our methods, techniques and recommendations help applied and empirical researchers analyze their data the best way they can in a variety of different areas. In a somewhat paradoxical way, I noticed that quantitative methodologists were tasked to evaluate the appropriateness of the methodology of other research ... but not our own. And if we are putting the magnifying glass on everybody else ... who is putting it on us? That’s what prompted me to study what I consider to be the two aspects of my research.

The workhorse of the modern quantitative methodologist is a series of computer-aided techniques collectively known as Monte Carlo simulations. If you are wondering, yes, the name does make reference to the famous Monte Carlo casinos because of its reliance on the computer’s ability to mimic randomness. We use Monte Carlo simulations in education, psychology and the social sciences to evaluate the robustness of our data-analytic approaches by creating a type of virtual world where the researcher controls the inputs and the computer generates the outputs. The first aspect of my research focuses on uncovering the hidden assumptions that researchers make when conducting simulations. To be more specific, I am interested in understanding how the (usually unacknowledged) mathematical properties of the algorithms used in these Monte Carlo simulations can impact the type of conclusions and recommendations we offer to applied researchers. I am also becoming very interested in the meta-scientific study of these simulations, which speaks more to the culture of quantitative research in education and the social sciences. Why do we do the kind of research that we do? What types of limitations does this research have? All are interesting questions that I don’t think always get the attention they deserve.  

The second aspect has to do with how statistical methodology is taught in education and the social sciences. Through my experience teaching, I have noticed that many of our textbooks and teaching materials make use of heuristics and rules of thumb that, although popular, are not necessarily understood from a more formal perspective. Since these recommendations are ubiquitous, I believe it is important to document the mathematical assumptions that these heuristics make so that we know when it is warranted to use them and when it doesn’t make sense. To sum it up, I’m in the business of asking simple questions which have long, technical answers.

What attracted you to UW College of Education?

Aside from UW being one of the top universities in the world and the prestigious ranking of the College of Education (CoE), I was immediately attracted to the unabated commitment that the CoE has towards equality, inclusion and the role that education plays in this. I immediately felt I wanted to be part of a college like this. Quantitative methodology is an area that can have negative connotations because of some of the implications people think it has (e.g. the idea that humans can be reduced to numbers). I don’t think that is the case and I believe the CoE offers a very unique environment where I can highlight how quantitative methods and data analysis are actually strong, powerful allies in the quest to better understand the human condition.

I also really like the Pacific Northwest! I lived all of my adult life in Vancouver, Canada, so I’m happy to be living in an area that is familiar to me and close to my friends and family in Canada.

What's a course you're particularly excited to teach?

I am particularly excited to teach my course “Introduction to Monte Carlo Simulations for the Social Sciences.” Something that became immediately apparent through my research into this field is that there is very little training offered for this technique with a focus on the social sciences. Most of us learn these methodologies “on the go” as we progress through our graduate studies. Courses do exist, but they are mostly geared towards students of statistics, mathematics or the natural sciences. It has always been surprising to me how there are so few opportunities to be trained in a technique as fundamental as this, which essentially constitutes the bedrock of our research. If this becomes a regularly-offered course, it could very well be the first (or one of the first) ones of its kind in North America, so I’m very happy to offer it!

Tell us about an education-related book or movie that has influenced you.

“Ivory Tower” was my first introduction to the complexities and challenges that the U.S. college education system faces and it is somewhat sad to see that most of the predictions made by this documentary in 2014 have become true. The major difference was that they became true much faster than the filmmakers themselves anticipated. 

As far as books go, I quite like “The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century” by statistician David Salsburg. This book traces the history of modern statistics and its major figures and helps contextualize why statistics has become so prominent in scientific research. It offers a perspective that I rarely see in the teaching and education of statistics: historical context. Who were these people? What kind of problems were they interested in? What was happening in the world that shaped statistical research? It’s written from a layperson’s perspective so anyone can read it and get something out of it!  

What's something that students and colleagues should know about you?

That they shouldn’t worry if I regularly reply to emails around 1 a.m. to 2 a.m. I’m not burning the candle at both ends, I just sleep very little. I’ve been like this since as long as I can remember so now it’s just become part of my routine.

Besides your work, what's something that you're passionate about?

I’m obsessed with all-things nerdy: pop-science stuff that has to do with outer space, physics, math, etc., sci-fi, Japanese anime, video games. The list goes on!

Story by Gabriela Tedeschi, marketing and communications student aide.


Dustin Wunderlich, Director of Marketing and Communications
206-543-1035, dwunder@uw.edu