Introducing the Research Skills Academy
The idea for the Research Skills Academy came from a series of conversations with co-founder and director Mark Galassi and three exceptional students in Santa Fe: Hajer Maaz, Ruben Hernandez O’Kelly, and Valentina Hussey.
In their conversations, they discovered there was a crucial missing link in preparing students to do research. There needed to be a program that would streamline students into higher education and other academic institutions by teaching them both hard and soft skills.
The students and Mark then formulated what a useful collection of skills and background knowledge would be for motivated high school students and ultra-motivated middle school students intrested in academic research. This group of skills became the course material for the Research Skills Academy.
We have some goals in mind for what students should pick up in this program: research skills, a habit of critical thinking, exposure to several different career paths, and how research enters into those paths.
The students had final say on the schedule, intentionally designing it to stimulate their age group and not be too exhausting for a high intensity summer program.
Students in the Research Skills Academy commit to about five and a half hours of work per day, four days a week, for three weeks. The specific durations mentioned below are just an approximation.
Each day starts with a tutorial lecture by a director of the program, Mark Galassi, Karina Higginson, or Albert Kerelis. Starting at 10 AM in our main time zone (US/Mountain time) and lasting about an hour, these lectures cover a wide range of topics, including workshop skills, soft skills, and theoretical discussions. The tutorials are often based on chapters in this book, but some are separate. To see a brief overview of the lessons, visit the appendix titled “Sample Syllabuses.”
Students then have a period of individual work on a long-term research question, or other areas of interest. In this period they are encouraged to invite collaboration from other students on the project they are forming in their mind. This is largely done using chat rooms and document sharing, and is a little over an hour long.
After a 45 minute lunch break, there is a 15 minute “scrum” meeting, guided by the Acadmey directors Karina Higginson and Albert Kerelis. In these meetings, students discuss and plan tasks with their peers and the senior members present so that their work is guided, efficient, and effective.
After the scrum it’s back to individual, or self-formed small group, work on a topic. This is intended to be focused on producing written results, and goes for about a hour.
The day ends with a career path lecture. Running about an hour and with 15 minutes for questions, scholars and professionals in very diverse areas speak about what careers in their respective field can look like, as well as current questions or issues in their field. The hope is to inspire students to think about potienetial careers, while also engaging their curiosity in potienital research questions. After this lecture, one more hour or so of independent work. The day will typically end around 3:45 PM.
What is Research?
For our purposes, research is not only scientific research that produces original results, such as experiments or data collections. Research is much more often the process of carefully studying a problem or an area of knowledge with the goal of understanding it clearly.
These two uses of the word “research” are linked, one acknowledges the new knowledge obtained while the other acknowledges the process of obtaining it. Original research is often a lengthy endeavor, and in the course of it a scholar will need to research many and varying academic fields that contribute to solving their question or problem.
A classic example of cross-field research is Albert Einstein’s path to formulating the theory of General Relativity. A key component in developing General Relativity was a field of mathematics called differential geometry. Einstein did not know much about it, so he asked his old friend the mathematician Marcel Grossmann to research whether an appropriate, non-Euclidean, geometry existed. Einstein’s biographer Abraham Pais [Pais1982] reports the story:
[…] he told Grossmann of his problems and asked him to please go to the library and see if there existed an appropriate geometry to handle such questions. The next day Grossmann returned (Einstein told me) and said that there indeed was such a geometry, Riemannian geometry. It is quite plausible that Grossmann needed to consult the literature since, as we have seen, his own field of research was removed from differential geometry.
Grossman and Einstein researched the existing state of mathematics surrounding the geometry of curved spaces. Grossman did traditional library research, which taught him of the existence of a new branch of mathematics. While not Einstein’s original research question, researching new areas of geometry was crucial in enabling Einstein’s original theory on Relativity.
As demonstrated, no research question is limited by it’s field. In any academic project you will need to research a variety of topics, and it is important that you get comfortable doing so with efficiency and precision.
What Students Should Produce in this Time
The general goal of each day is to produce some written work that demonstrates what a student has learned during their independent research time. What exactly that written product looks like can vary depending on the student’s inclinations and what makes sense for their project.
A simple approach could be to pick a topic in the morning, spend most of the afternoon doing research, and then taking the last 30 minutes of the day to write a position paper or research summary on it.
Alternatively, a student could put together a short lecture on their topic, add to a written product that spans multiple days of research, or write an experimental research proposal based on what they’ve learned.
The idea is not to have a rigid rubrick for what a student must complete, but to have each student get in the habit of synthesizing and communicating what they’ve learned in a way that makes sense for them and their project.
As a student you might find this independence daunting at first. We hope that you will find it to be what makes this experience remarkable.
The Slant of the Lectures
Below is the simple blurb we send to our lecturers when we ask them to present to the Research Skills Academy:
The purpose of lectures at the Research Skills Academy is to give students an overview of what careers look like in the speaker’s area of scholarship.
We also encourage speakers to include discussion of two aspects of their area: (a) “out of the box” thinking about it, which would demonstrate how it is different from what people imagine; (b) social justice ramifications and how a student can plan a career that improves their sector of the world.
But in the end it is entirely up to the lecturer – slides, fireside chat, …, any format they pick is good.
The lecturers are professionals in their field eager to share their insider knowledge with you. Ranging across many fields, these lectures are meant to inspire and inform not only in content, but also in style of presentation. You will have to give your own lecture at the end of the Academy, so take mental note of what styles of lectures work well for you, and which you might want to emulate.
Computing, Platforms, and Software Freedom
The Institute for Computing in Research is deeply rooted in software freedom, and its interns work entirely with free/open-source software (FOSS). The Research Skills Academy uses an entirely FOSS infrastructure, but does not require the use of a complete FOSS platform by students (although we do offer those tools).
While students aren’t required to use FOSS, some of the discussion in the Academy revolves around digital citizenship, vendor lock-in, and other areas in which software freedom plays a key role.
For our purposes computers will be used as a tool for communicating, researching, writing, visualizing information, and (quite rarely) examining source code and running it.
The two programs we will use beyond a web browser and office programs will be (a) a plotting program (for when we visualize data), (b) the Python language interpreter (for when we see what a computer program looks like), and (c) version control.
For plotting there are many tools available. We have prepared some information on is RAWGraphs. RAWGraphs works in any modern web browser, so it will be available to users of all platforms. You will find a tour of RAWGraphs in Appendix: logistical details.