In academia, a variety of people are required to teach students whether or not they have a background in teaching. There are many classes in which novice TAs and undergraduate course assistants are expected to lead both classroom discussions and one-on-one interactions with students with no prior experience. Often, this results in subpar instructional results such as explanations that students do not understand or the provision of answers themselves rather than explanations that help students learn. While rigorous teaching programs exist for instructional careers, these are not required or often feasible for TAs and tutors. A more lightweight teaching intervention is therefore needed for training TAs and tutors. Many universities have created TA training courses (e.g. CSE 599 at UCSD), but there is not yet a standard for such courses and a concrete set of teaching principles that are expected to be mastered.

The need for such interventions closely mirrors a problem I encountered as an educator prior to my experience as a graduate student. As a co-founder of Transform Tutoring, a company that provides one-on-one tutoring for high school students, I led the interview process for STEM tutors. Interviews were mock tutoring sessions wherein the candidate would play a tutor and the interviewer would play a student. I noticed that almost all candidates (mostly upper undergraduate or graduate students) simply explained a topic, or even solution to a question, from start to finish without engaging the student. Many candidates were clearly knowledgeable in their domain, and I predicted that if they were guided in effective teaching, the quality of their tutoring would improve drastically. I developed a required pre-interview reading for candidates which included an explanation and example of student-driven teaching--that is, allowing students to find the next step of a problem on their own rather than providing it to them. My student-driven teaching and learning guide yielded much better interviews, and illustrated to me the promise of lightweight teaching interventions. As a graduate student, I adapted this guide to create an Introduction to Python TA Training that has been used by the Cognitive Science department for training new TAs and tutors for our introductory programming course. I have run several TA trainings and am developing a TA training course that has concrete learning outcomes for TAs and tutors. As I develop these trainings along with teaching professors in my department, we will aim to answer the following questions:

RQ1: There are many well-established teaching principles in pedagogical literature. Which ones are suited to lightweight teaching interventions that could be effectively taught to TAs and tutors without prior teaching training?
RQ1: Which teaching principles taught via lightweight teaching interventions are most effective for improving student understanding?

By answering these questions, we hope to develop trainings that are both feasible to teach TAs and tutors and effective for improving student learning outcomes.