Pre-service Teachers’ Evaluations of Ethics and Data Rights Across Individual, Communal, and Societal Layers

• In Event: Supporting Teachers to Engage in Meaningful Data Literacy and Data Science Practices Across Disciplines

Abstract

Objectives
The purpose of our study was to expose pre-service mathematics teachers to data science activities where they were required to grapple with ethical tensions between actors. By presenting data science and ethics activities as part of the mathematics pre-service curriculum, we hoped to signal that teaching data science draws from interdisciplinary knowledge that includes statistics, data, and society (Baumer et al., 2022). We ask, what data science ethical tensions do pre-service mathematics teachers identify, and how do their evaluations of data ethics vary across individual, community, and societal levels?

Theoretical Framing
We designed data science and ethics activities with respect to Lee et al.’s data constellations: that data are complex in part because they span multiple layers of social tools and processes (2021). We theorized that presenting data science dilemmas across individual, communal, and societal layers would encourage pre-service teachers to contend with ethical tensions and critically compare them at various grain sizes.

Methods
Our teaching experiment (Brown, 1992) encompassed a 75-minute data science and ethics lesson with 25 pre-service mathematics teachers. 22 teachers consented to participate and were audio and video recorded. After introductory framing, teachers worked in groups of 3-5 to identify ethical tensions from data in one of three scenarios, and determined which actors should be granted authority over data via policy and user rights:
Individual: determining an individual’s viability for a medical procedure with health and economic data;
Communal: whether data supported building a new parking structure at a university;
Societal: reconciling how social media data should influence decision making about teens
We describe ethical tensions as conflicts of interest between actors that may result from how they handle or interpret data. We analyzed the data using Lee and colleagues’ data constellations, looking for patterns of discussion among ethics and social layers (Creswell, 2014).

Results and Significance
Based on a previous iteration of this activity (Author, 2025), we hypothesized that teachers would find the fewest ethical tensions at the individual layer, because it is easier to empathize with individuals than a society. Our results contradict these findings (Figure 10.1). According to teachers, at the societal and communal levels, data ethics are outside of the individual users’ locus of control (e.g., companies using data for targeted advertisements). Thus, the public need stronger data rights to account for their lack of authority in corporate and political data-driven decision-making. At the individual level, data ethics can be determined on a case-by-case basis (e.g., did the patient make healthy choices?), which can surface reconcilable tensions between actors. In both iterations of this activity, we noticed that participants identified more ethical tensions and data rights’ issues in situations where they could actively participate. From this work, we suggest that teacher educators hold pre-service teachers accountable to data science ethics, but attend to the subject-matter of curricular activities as they determine what future teachers should learn.

Authors

• Victoria L. Delaney, San Diego State University

• Ryan Gabriel Aniceto, San Diego State University