Teaching Machine Learning in the Context of Critical Quantitative Information Literacy

Bates College, is a small liberal arts postsecondary institution in the northeast United States. An information literacy course, Calling Bull, serves as an introductory data science class as well as a prerequisite-free quantitative literacy class. In this context, we spend a week discussing machine learning, with an emphasis on facial recognition algorithms. The emphasis is on the general algorithmic approach, critical inquiry of the process and careful interpretation of results presented in research or decision-making. This module relies on the use of open educational materials, discussion, and careful attention to issues of marginalization and algorithmic justice

Revealing Luz: Illuminating Our Identities Through Duoethnography

Hispanic Americans make up 15% of the current US workforce, but they only account for 7% of the STEM Education workforce [8]. One effective way to reach this population, particularly Latinas, is by providing stories and ethnographic biographies of successful Latinas they can relate to. It is important to note that Latinas have been earning PhDs in STEM disciplines outside of the US much longer than US-born Latinas have been earning them inside. Thus we offer the story of a mathematics educator, from Peru, Dr. Luz Antonia Mendizábal Gálvez de Rodriguez, a girl who was given a chance to be educated, and whose education opened doors for her and for those she influenced. She earned her PhD in Mathematics Education while raising eight children and working full time and later in life became the school superintendent in Lima, awarded a prestigious national award for her teaching and service. Through a narrative that is part biography and part duoethnography, we chronicle milestones in her journey and explore the intersections of her life with the lives of two other US-born mathematics educators, ourselves. We conclude with some thoughts on revising the storyline by presenting new narratives to empower our communities

The Case for Biocalculus: Design, Retention, and Student Performance

Calculus is one of the primary avenues for initial quantitative training of students in all science, technology, engineering, and mathematics fields, but life science students have been found to underperform in the traditional calculus setting. As a result, and because of perceived lack of its contribution to the understanding of biology, calculus is being actively cut from biology program requirements at many institutions. Here, we present an alternative: a model for learning mathematics that sees the partner disciplines as crucial to student success. We equip faculty with information to engage in dialogue within and between disciplinary departments involved in quantitative education. This includes presenting a process for interdisciplinary development and implementation of biology-oriented Calculus I courses at two institutions with different constituents, goals, and curricular constraints. When life science students enrolled in these redesigned calculus courses are compared with life science students enrolled in traditional calculus courses, students in the redesigned calculus courses learn calculus concepts and skills as well as their traditional course peers; however, the students in the redesigned courses experience more authentic life science applications and are more likely to stay and succeed in the course than their peers who are enrolled in traditional courses. Therefore, these redesigned calculus courses hold promise in helping life science undergraduate students attain Vision and Change recommended competencies

Can We Bridge the Gap? Mathematics and the Life Sciences, Part 1–Calculus-Based Modules, Programs, Curricula

This editorial serves as an introduction to Part 1 of the Special Issue Mathematics and the Life Sciences–a collection of articles showcasing ideas, examples, pedagogical frameworks, and curricular materials aiming to bridge the stubbornly persistent gap at the undergraduate level between the mathematical and the life sciences. The special issue features authors from public and private institutions of diverse types, sizes, and geographic locations: community colleges, liberal arts colleges, and research-oriented universities. We hope this special issue will serve as a resource to faculty who seek to make changes to their own course(s) or initiate curriculum reforms at their own schools. Part 1 focuses on educational initiatives that are appropriate for Calculus classes or require calculus as a prerequisite. Part 2 of the special issue features course materials and programs based on discrete mathematics, computational approaches, and statistics. Part 2 also includes articles on internship programs and co-curricular opportunities

Can We Bridge the Gap? Mathematics and the Life Sciences: Part 2–Discrete Models, Statistics, Co-Curricular Opportunities

This editorial serves as an introduction to Part 2 of the Special Issue Mathematics and the Life Sciences–a collection of articles showcasing ideas, examples, pedagogical frameworks, and curricular materials aiming to bridge the stubbornly persistent gap at the undergraduate level between the mathematical and the life sciences. The special issue features authors from public and private institutions of diverse types, sizes, and geographic locations: community colleges, liberal arts colleges, and research-oriented universities. We hope this special issue will serve as a resource to faculty who seek to make changes to their own course(s) or initiate curriculum reforms at their own schools. This Part 2 special issue features course materials and programs based on discrete mathematics, computational approaches, and statistics. It also includes articles on internship programs and co-curricular opportunities. Part 1 focuses on educational initiatives that are appropriate for calculus classes or require calculus as a prerequisite