Program

Follow the Evidence: Improving STEM Learning for All
Susan Singer, Rollins College's Vice President for Academic Affairs and Provost and former Division Director in the Division of Undergraduate Education at NSF

Evidence for effective undergraduate STEM education abounds. Moving from evidence to practice at scale has been slow. Evidence of disparity in who succeeds in STEM abounds. Closing the gender, race, ethnicity, and socioeconomic status gaps has been slow. Developing and retaining high quality STEM graduates is contingent upon addressing both these challenges. This presentation will explore what we know about learning and understanding in STEM fields in the context of equity issues. Promising approaches to translating the research to widespread implementation in higher education will be emphasized.

(Dr. Singer bio)

Rethinking STEM Education in An Era of Convergence
John Brooks Slaughter, Professor of Education and Engineering at USC and former Director of NSF

The past few years have seen the gradual erasure of the borders separating the sub-disciplines within science and engineering. We are in an era of convergence in which these sub-disciplines are merging and commingling with one another and with the arts and humanities in ways that make it possible to develop solutions to complex problems that here-to-fore seemed intractable. This convergence of disparate fields offers new promise for STEM education.

(Dr. Slaughter bio)

We are all Data Scientists
Rob Gould, Academic Administrator, UCLA Department of Statistics and Vice-Chair of Undergraduate Studies and Director of Center for Teaching of Statistics

Merge data with computational thinking, and what do you get? Data Science.  We are constantly surrounded by data and we need to be thinking about how to infuse this into our courses in all STEM fields. In this talk, I'll show you a number of initiatives that are using data science to improve computational thinking in math and science at high school and collegiate levels.  I'll cover the promises of a data-literate society, and also discuss the challenges we face.

(Dr. Gould bio)

Equity: Selecting, Defending, and Inventing Inclusive Teaching Interventions 

Coleen Lewis, Dept. of Computer Science at Harvey Mudd

(Room: LSB 120)

As educators, we want to create equitable and inclusive classrooms where all of our students are successful. There are laundry lists of things we can do to achieve these goals and rarely time to put them all into practice. Anyone can find these lists laundry lists online, but likely only with the help of our peers can we select and customize these strategies for our context.

In this workshop, you will:

• learn from each other by brainstorming creative solutions to common challenges in creating equitable and inclusive classrooms, 
• sort through more than 100 tips for inclusive classrooms to identify actionable and impactful tips for your context, and 
• practice addressing common resistance to (or misunderstandings of) inclusive practices so that you can motivate and educate your colleagues.
• Come ready to problem solve, critique, discuss, and only very rarely listen to the workshop presenter.

(Dr. Lewis bio)

Problem Solving: Problem Structure and Analysis

David Quarfoot, Dept. of Mathematics at UC San Diego

(Room: LSB 118)

While there are numerous research lines related to problem solving in STEM disciplines, most of these occur "after the curtain has raised": that is, after a student encounters some task to work on. In this workshop, I focus on some "before the curtain" issues:

• Problem Structure: When we think of "good" problems, or problems that "facilitate problem solving", what features (e.g., novelty, cognitive sophistication, numerosity of steps, etc.) do they tend to have? What features do educators in specific fields hope to see in their problems (if the goal is to promote problem solving development) – and do these differ across fields? What major features have been identified in the literature, and how are they correlated in problems we currently use?
• Problem Analysis: How can we measure the amount of a feature present in some problem? For example, are educators able to judge the amount of creativity demanded by a problem? How about the number of solutions? Do students accurately report "difficulty" levels? Can a computer determine the novelty of a problem? Each of these settings (expert ratings, student self-reports, empirical calculations) offers its own challenges. In the case of expert ratings, we can use statistical techniques from the field of multi-rater inter-rater reliability to measure the level of agreement, and hence, of well-definition for problem features.

(Dr. Quarfoot bio)

Computational Thinking: Computing Across Domains

Leo Porter, Computer Science and Engineering Dept. at UC San Diego

(Room: Foley 210)

Computing has become nearly ubiquitous in our personal and professional lives. This has the potential to be a unifying factor across fields as a common knowledge we all share. In fact, many of us envision computing as an essential component throughout K-12 and higher education.

However, the realities are more complex. Although this workshop focuses on higher education, debate abounds about the curriculum in K-12 education and that curriculum heavily impacts what we can assume of our incoming students. Even within higher education, because each field often perceives different requirements from computing, we find a computing curriculum which is typically fractured across campus. For example, at some institutions, there are different introductory computing courses hosted by biology, chemistry, cognitive science, data science, engineering, and computer science departments.

This workshop has two goals. 1. Are our demands from computing truly so unique? Must the computing curriculum be fractured? To help inform these questions, we'll work in small groups based on discipline to determine what we want our students to be capable of doing with computing at both a program and course level. This discussion should help us better understand what we all have in common; and what we do not. 2. What can we learn from existing work in computing education research about how to teach computing? Specifically, we'll discuss how learning computing may be different than other fields, common challenges for students learning computing, and established best practices in teaching computing.

(Dr. Porter bio)

During lunch you will have the opportunity to start and continue conversations on problem solving, equity and computational thinking from the morning sessions, but this time related to your own discipline.  Guided by a table leader, you will discuss the most prevalent challenges and resolutions your discipline faces in promoting discipline-based education research, specifically around the three conference themes.

Clicking a title will take you to the corresponding abstract.

Equity

(Room: Seaver 101)

• Developing learner Identity in the science classroom community by Sissi Li, Chemistry and Biochemistry, Cal State University Fullerton
• Leading by Example: Creating Inclusive Classrooms by Erin-Kate Escobar (Center for Diversity) and Jennifer Weaver (Center for Teaching, Learning, & Outreach), Caltech
• Harnessing the Power of Language Diversity in Mathematics Classrooms by Bill Zahner, Mathematics, San Diego State University
• STEM Microaggressions: Words and Actions that Demoralize and Discourage Students by Darryl Yong, Mathematics, Harvey Mudd College
• Inquiry, Equity, and the Algebra Project by Robin Wilson, Mathematics, Cal Poly Pomona
• CAMPARE and Cal-Bridge: Two California Institutional Networks Increasing Diversity in Physics and Astronomy by Alex Rudolph, Physics and Astronomy, Cal Poly Pomona

Problem Solving

(Room: LSB 118)

• Research In The Classroom: Leveling the Playing Field by Mohamed Omar, Mathematics, Harvey Mudd College
• Monitoring, or Metacognition, is a Keystone to Problem-Solving Success by Jeff Phillips, Physics, Loyola Marymount University
• Integrating multiple perspectives on problem solving by Ed Price, Physics, Cal State University San Marcos
• Developing mathematical practices through Peer-Assisted Reflection by Daniel Reinholz, Mathematics, San Diego State University
• Perspectives on Problem Solving and Its Assessment by Qing Ryan, Physics, Cal Poly Pomona
• Problem Solving: Creativity and Relevance by Christina Deckard, Department of Defense

Computational Thinking

(Room: LSB 330)

• Different Flavors of Computing - Providing Context to a First Course in Computing by Chris Clark, Engineering, Harvey Mudd College
• A Framework for Models and Modeling to Unify Mathematicians and Biologists and Improve Student Learning by Kam Dahlquist, Biology, Loyola Marymount University
• Where do Mathematics and Statistics fit in to a World of Data Science? by Jo Hardin, Mathematics, Pomona College
• CS 1 Green:  An Introductory CS course with a Biology Theme by Ran Libeskind-Hadas, Computer Science, Harvey Mudd College
• Teaching Computational Thinking in Data Science with Open-Source Tools by Brian Granger, Physics, Cal Poly San Louis Obispo

Clicking a title will take you to the corresponding abstract.

• Achieve Scholars Program – Impacting Graduation and Retention Through Research by Everardo Barraza, Office of Undergraduate Research, Cal Poly Pomona 
• Sleep and Test Performance by Vincent Coletta, Physics, Loyola Marymount University
• Success and Barriers for Underrepresented Minorities in STEM by Nicole Duong, Psychology & Sociology, Cal Poly Pomona
• Using an Online Learning Platform to Enhance Student Success in a Mechanical Engineering Course by Juliana Fuqua, Psychology & Sociology, Cal Poly Pomona
• Transdisciplinary Scientific Collaboration Evaluation by Juliana Fuqua, Psychology & Sociology, Cal Poly Pomona
• Flipping the Large-Enrollment Introductory Physics Classroom by Chad Kishimoto, Physics & Biophysics, University of San Diego 
• Scaffold for Scientific Thinking in Non-Quantitative Classes by Bradley "Peanut" McCoy, Physics, Azusa Pacific University 
• CAMPARE and Cal-Bridge: Two California Institutional Networks Increasing Diversity in Physics and Astronomy by Alexander L. Rudolph, Physics and Astronomy, Cal Poly Pomona
• Values Affirmation: Empowering Minority Students in STEM Towards Academic Success by Viviane Seyranian, Psychology & Sociology, Cal Poly Pomona 
• Investigation of Team Based Learning For Teaching General Education Astronomy by Rick Sturdivant, Engineering and Computer Science, Azusa Pacific University 
• Designing a Richer Flipped Classroom Experience by Matthew Voigt, Math and Science Education, San Diego State University and UC San Diego

Equity (Room: Seaver 101)
Problem Solving (Room: LSB 118)
Computational Thinking (Room: LSB 330)

These three working groups provide a forum to develop ideas and coordinate work.  Participants will join others who share common interests to review the day, collaborate on new research projects and network with each other. Participants will be encouraged to continue the work beyond the conference and to prepare a submission for the conference proceedings.

Funding Opportunities in NSF's Education and Human Resources Directorate That Support Equity
Ron Buckmire, Professor of Mathematics at Occidental College and Lead Program Director for NSF’s Scholarship for Science, Technology, Engineering and Mathematics (S-STEM) 

(Room: Seaver 109)

This session will provide attendees with an overview of funding opportunities in the Directorate for Education and Human Resources at the National Science Foundation. In particular, there will be a focus on programs which can be used to support activities that broaden the participation by underrepresented students in STEM. Some of these programs include S-STEM, INCLUDES, ECR, IUSE, HBCU-UP among others. 

(Dr. Buckmire bio)

Getting Started in the Scholarship of Teaching and Learning
Jacqueline Dewar, Professor Emerita of Mathematics at Loyola Marymount University

(Room: LSB 331)

This interactive workshop will introduce participants to the scholarship of teaching and learning (SoTL) and help them begin to frame a question of their own to investigate. We will introduce a taxonomy of SoTL questions, provide examples of SoTL projects, and discuss methods for investigation. Participants will learn about types of evidence they might collect, human subjects requirements and venues for presenting or publishing their work.

(Dr. Dewar bio)