Tapia 2021 Workshop
This hands-on workshop is intended to provide faculty and graduate students teaching computer science (CS) courses an opportunity to modify their courses to better motivate and engage students via centering learning and equity in their courses’ assessment. Participants will learn about various assessment methods, explore their applications to various CS courses, and modify a syllabus or assignment for one of their courses based. The workshop will be supported with a workbook (guide) developed by the presenters so participants can continue to engage in their learning and course modification beyond the conclusion of the workshop. Participants will need to bring the syllabus and 1-2 assignments for the course they are interested in revising. Limited to 20 participants.
Introduction: Grading for learning (10 mins) During the first part of the workshop, we will discuss assessment from the assignment level to the course level and how it can align with learning and equity. We will outline key terms and discuss how assessment can encourage learning and support equity.
Proven Applications: Syllabus and assignment examples (20 min) Participants will practice applying the new terminology and theoretical grounding by studying examples of existing course syllabi and assignments.
Initial Course Modifying (10 min) Participants will begin to modify their courses to center learning and equity. During this time, participants should tackle one specific change—either at the course level (syllabus) or at the assignment level.
Peer feedback (10 min) Participants will share their course modifications with each other in small groups and provide feedback for areas of improvement.
Reflecting: Group Discussion (15 min) As a whole group, participants will reflect on their modifications, the feedback they received, and the questions they have for moving forward. Presenters will pose reflective exercises and answer participants’ questions.
Revisions and Next Steps (5 min) After hearing from their peers, participants will have the opportunity to revise their modifications and plan out their ‘next steps’.
Closing (5 min) Presenters will answer any final questions and share the workbook (guide) they have developed so participants can continue to engage in their learning and course modification beyond the conclusion of the workshop.
The workbook includes supplemental materials for the workshop and activities.
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Sarah Brown Dr. Sarah M Brown is an Assistant Professor of Computer Science at the University of Rhode Island and diretor of the Machine Learning for Sociotechnical Systems Lab. Previously she was a Postdoctoral Research Associate in the Data Science Initiative at Brown University and a Chancellor’s Postdoctoral Fellow in the Statistical AI Lab at University California, Berkeley. Dr. Brown earned her BS, MS and PhD in the Electrical and Computer Engineering Department at Northeastern University. Dr. Brown’s current research focuses on making AI more fair through interdisciplinary applied data science and system level interventions.
Dr. Brown’s qualifications in relation to the proposed workshop include formal pedagogical training and acquired teaching experiences of varying levels of formality. Dr. Brown has taught formal and informal computing workshops, and undergraduate and graduate courses. Dr. Brown has completed the Carpentries instructor Training and deeper study to certify as an Instructor Trainer. She also serves as chair of their Instructor Trainer Leadership Panel.
Victoria C. Chávez Victoria C. Chávez (they/she) is a proud Chapinx (Guatemalan) who was born and raised in Chicago, and now calls Rhode Island home. Victoria is an incoming student at Northwestern’s Joint PhD in Computer Science and Learning Sciences Program. Previously, they served as a Computer Science Lecturer in the Department of Computer Science and Statistics at The University of Rhode Island. Victoria has a Bachelor’s in Computer Science (CS) and Hispanic Studies and a Master’s on Urban Education Policy, focusing on CS Education.
Victoria’s qualifications as they pertain to the proposed workshop include pedagogical professional development, experience in formal and informal K-12 and undergraduate teaching, as well as adult learner teaching, and development and delivery of professional development for CS educators and teaching assistants. Victoria centers equity and accessibility in her own teaching and is consistently engaged in discourse of evidence-based pedagogical practices.