The importance and emergence of K-12 data science

LaMar, Tanya; Boaler, Jo

doi:10.1177/00317217211043627

Cited by 16 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One change idea that the mentor and teacher candidate explored was the use of an inquirybased activity process to engage student pre-existing knowledge to build new understanding. As part of the "Plan" for PDSA cycles, and based on Watson [45] and Lamar and Boaler [46], it was hypothesized that a data collection inquiry process would facilitate student engagement in inquiry-based activities such as those described by Anderson et al [47] and Engle and Conant [48]. It was also hypothesized that this type of engagement would improve learning of mathematics concepts that are typically taught procedurally at the high school level in the U.S. (for example, mathematical formulas and their proofs) [36].…”

Section: Resultsmentioning

confidence: 99%

Building Mathematics Learning through Inquiry Using Student-Generated Data: Lessons Learned from Plan-Do-Study-Act Cycles

Rakes,

Wesneski,

Laws

2023

Education Sciences

View full text Add to dashboard Cite

This paper describes how plan-do-study-act cycles engaged a classroom mentor teacher and student teacher in a professional collaboration that resulted in two inquiry activities for high-school geometry classes. The PDSA cycles were carried out in four high school geometry classes, each with 30 to 35 students, in a mid-Atlantic urban school district in the U.S. The four geometry classes were co-taught by the second and third authors of this paper. The data consisted of classroom documents (e.g., activity prompts, tasks), classroom observations, student feedback about activities, and monthly PDSA reports. The PDSA cycles had a direct effect on the professional learning of the teachers. The resultant classroom activities used a data collection approach to engaging students in inquiry to learn about trigonometry functions and density. Student learning behaviors were noticeably improved during these activities compared with traditional mathematics instruction. We concluded that the data collection sequence provided an accessible entry point for students to begin scientific inquiry in mathematics. The process opened the conceptual space for students to develop curiosity about mathematical phenomena and to explore their own research questions. The use of culturally relevant topics was especially compelling to students, and the open-ended nature of these exploratory activities allowed students to see mathematics through their own cultural lenses.

show abstract

Section: Resultsmentioning

confidence: 99%

Building Mathematics Learning through Inquiry Using Student-Generated Data: Lessons Learned from Plan-Do-Study-Act Cycles

Rakes,

Wesneski,

Laws

2023

Education Sciences

View full text Add to dashboard Cite

show abstract

“…In addition, a recent Dear Colleague Letter (NSF 22-071) asks for proposals for supplementary funding related to data science education. Given the relative abundance of data science-related work taking place in mathematics and computer science education contexts (LaMar & Boaler, 2021;Jiang et al, 2022;Wilkerson & Polman, 2020), this project addresses the need to develop and study data science approaches in discipline-specific ways, including in science education settings.…”

Section: Alignment With Nsf Prioritiesmentioning

confidence: 99%

CAREER: Rethinking How Middle and High School Students Analyze and Interpret Ecological Data

Rosenberg¹

2023

Preprint

View full text Add to dashboard Cite

There have been prominent and widespread calls for high school science students to work with data in more complex ways that better align with and support the work of professional scientists and engineers (Lee & Wilkerson, 2018; National Academies of Sciences, Engineering, and Medicine, 2019). This is part of the broader practice shift in science education research and standards and more data-intensive areas of study and work—and explorations of the roles of data science at the K-12 levels (Jiang et al., 2022; Wilkerson & Polman, 2020). Although teachers express the desire to do more with data in their science classrooms (Banilower et al., 2018; Rosenberg et al., 2022b), science teachers do not presently have a way to connect the work their students do with data to the science ideas they are working to help their students understand. The result is that students' work with data can be isolated from the sense-making students are doing about science. There is a need and an opportunity to provide science teachers with practical tools that are grounded in the framework of Bayesian data analytic methods that explicitly connect and weigh between initial ideas and empirical evidence. The specific opportunity for using Bayesian methods involves recent advances in informal statistical inference. This type of statistical inference considers how students not only interpret but also how they model data and make probabilistic generalizations from data. This opportunity is bolstered by current emphases on students’ investigations of phenomena as a locus of activity in science classrooms. This project advances middle and high school students' data modeling in ecological contexts by taking a Bayesian approach that is supported and studied as an informal statistical inference framework. It is instantiated through a unit, digital tool, and teacher professional development program for 15 middle grades and 15 high school educators that will be conducted in a way that emphasizes students' data analyses with phenomena of interest that relate to local context for teachers and students. Accordingly, the professional development program will begin with a two-day weekend program at the Great Smoky Mountains Institute at Tremont. A field experiment will compare the students' informal statistical inference capabilities by using qualitative analyses of written embedded assessments of students' probabilistic generalization from empirical data, and changes in the teachers’ confidence engaging their students will be assessed using validated surveys.

show abstract

“…It also shows an astonishing ignorance of mathematics by calling for de-emphasizing algebra and calculus in favour of data science. These points were articulated by the Stanford education professor Jo Boaler (LaMar and Boaler 2021; Boaler and Gould 2021). Such statements and many other aspects of the CMF proposal have been seriously analysed and debunked by the Stanford mathematician Brian Conrad in his blog ‘Public comments on the CMF’ (Conrad 2022; see also Freeman 2022).…”

Section: Penetration Of Sj In Educationmentioning

confidence: 99%

The Universalism of Mathematics and its Detractors: Relativism and Radical Equalitarianism Threaten STEM Disciplines in the US

Klainerman

2023

European Review

View full text Add to dashboard Cite

This is a modest personal attempt to understand the ideology behind the current antiscientific trends in STEM, and more specifically in mathematics. In simplified terms, these trends can be traced back to a growing imbalance between the old ideal of fairness based on individual merit and the increasingly predominant, unrealistic expectations of equality of outcomes in all areas of human activities. I draw on specific examples and various scientific studies to show how these trends undermine the teaching of science in the US and, increasingly, research in STEM disciplines.

show abstract

The importance and emergence of K-12 data science

Cited by 16 publications

References 18 publications

Building Mathematics Learning through Inquiry Using Student-Generated Data: Lessons Learned from Plan-Do-Study-Act Cycles

Building Mathematics Learning through Inquiry Using Student-Generated Data: Lessons Learned from Plan-Do-Study-Act Cycles

CAREER: Rethinking How Middle and High School Students Analyze and Interpret Ecological Data

The Universalism of Mathematics and its Detractors: Relativism and Radical Equalitarianism Threaten STEM Disciplines in the US

Contact Info

Product

Resources

About