ITEST Resources

What do high school students learn from a two-day datathon during which they tackle data to visualize the impact of biased data on healthcare decisions? How do they interact with their team of high school students, data scientists, clinicians, and teachers? What did we, the developers and leaders of the datathon, learn? How would we approach it differently next year? Our goal is to answer these questions plus share lessons learned. We will then divide the audience into teams to brainstorm ways to approach and solve some of the problems we experienced and hopefully recruit some audience members

This paper presents an empirical study of high school teachers’ perspectives on context-based learning about Artificial Intelligence (AI) and data science. Four teachers were interviewed after they had enacted a curriculum contextualized in healthcare. The data were coded for teachers’ perspectives on what students learned; on the kinds of tasks that engaged students; and on the challenges and needs in teaching and learning about these fields. While context-based learning has the potential to promote students’ career awareness and appreciation of AI and data science, future research needs to

Student engagement is a key predictor of academic achievement and is closely linked to career awareness, interest, and preparedness. Measuring student engagement during STEM learning is challenging for teachers, given the dynamic and ever-changing nature of these learning environments. Even when engagement data can be collected, leveraging this information to refine and personalise instruction requires significant experience and time. To address this, we are developing Scoutlier EngagEd, a digital teaching assistant that embeds in existing Learning Management Systems (LMS) to automatically and

There is a growing need in the United States for a workforce trained in quantum information science and technology (QIST), a disciplinary topic that is rarely addressed in precollege science, mathematics, and computer science curricula. University quantum physics and physics education researchers designed and initiated a 4-week, 12-h QIST professional development workshop for 𝑁=5⁢1 preservice and in-service secondary school science, mathematics, and computer science educators. A STEM integration framework guided the workshop structure, which incorporated a situated cognition model for learning

In Massachusetts, the Latino population increased by 475 percent between 1980 and 2017, marking a dramatic growth. This diverse ethnic community of Puerto Ricans, Dominicans, Salvadoreans, Colombians, Brazilians, and more also contains a wide range of cultures, immigration and migration experiences, languages, and socio-political backgrounds. However, there are numerous commonalities involving education. Recent research at the Mauricio Gastón Institute for Latino Community Development and Policy reveals that Latino students in Massachusetts are more likely to attend public schools, in

Quickly disseminating an innovative, timely afterschool program raises challenges, from recruitment and professional development to assessment, program fidelity, and quality. In this paper, we describe our experience as project developers, trainers, and researchers working with an afterschool network, Imagine Science, to disseminate a middle school club program about epidemic diseases and data. What we learned from working with this network may be useful to others who have created an afterschool science, technology, engineering, and mathematics (STEM) program they hope to spread widely

Learning to construct and make sense of time-series graphs is a key practice in middle school science. We describe a new, free educational tool called “Sonify” that enables students to extend their use of the Common Online Data Analysis Platform (CODAP) so that they can listen to graphs of scientific phenomena that change over time while they simultaneously examine these graphs visually. We report on how listening to graphs helps students attend to key elements, including slope, and how listening might help differentiate instruction. Sonify has special appeal to students who value learning

Epidemiology is the study of patterns of health and illness and how these are distributed in a given population. Combining elements of biology and medical science, sociology, environmental science, and statistics, it could be defined as the intersection of public health and data science. Epidemiology is increasingly relevant to modern life. Worldwide travel, human habitations encroaching on wild lands, and climate change are making epidemics ever more frequent. Meanwhile, political leaders in the US make controversial and often unsupported claims about the causes of chronic diseases. Yet

Scientific sensemaking is described in the context of studying a three-week, sixth-grade unit on the ecology and restoration of puffins living off the coast of Maine. Students engaged with a scientific adventure story, observed local bird species, used AI and webcam-facilitated tools, designed puffin burrows, and explored data sets about puffins. Students’ ideas were elicited through discussion of the challenges faced by scientists who restored the puffins; sharing observations of chick-rearing behaviors from a webcam; critiquing and revising classmates’ burrow designs; writing about bird

The study of Atlantic puffins among Maine middle-school science students provides a fascinating subject for integrating ecology, ornithology, and data practices. Atlantic puffins have made a remarkable comeback in Maine over the last 50 years under the leadership of ornithologist Stephen Kress and the National Audubon Society's Seabird Institute (Kress & Jackson, 2020). Studying the extent to which this seabird population has changed, and the reasons for these changes, is the focus of the Puffins curriculum project (Tumblehome, n.d.; NSF DRL-2241777). The curriculum combines a place-based