Sage Journals: Discover world-class research

Abstract

Data ethics have emerged as an essential topic in education. Educators must know how to use data effectively and responsibly. This is a complex and systemic issue that involves bringing awareness to all stakeholders, building human capacity, modifying policy, and considering equitable solutions to data use. This article posits an initial framework that lays out responsible data use grounded in the concepts of transparency in and the consequences of the decision-making process, noting competing factors that influence decision making. Examples illustrate the complexity of ethical decision making and how it is manifested in practice. Suggestions on how to use the framework are posed.

Keywords

data ethics data literacy transparency consequences decision making

Get full access to this article

View all access options for this article.

References

Abedi

(2004). The No Child Left Behind Act and English language learners: Assessment and accountability issues. Educational Researcher, 33(1), 4–14.

Abedi

Herman

(2010). Assessing English language learners’ opportunity to learn mathematics: Issues and limitations. Teachers College Record, 11 2(3), 723–746.

Alwahaby

Cukurova

(2024). Navigating the ethical landscape of multimodal learning analytics: A guiding framework. In: Caballe

Casas-Roma

Conesa

(Eds.), Ethics in online AI-based systems: Risks and opportunities in current technological trends (pp. 25–53). Academic Press.

American Statistical Association. (2022). Ethical guidelines for statistical practice. https://www.amstat.org/docs/default-source/amstat-documents/ethicalguidelines.pdf?Status=Master&sfvrsn=bdeeafdd_6/

(2007). High-stakes testing and curricular control: A qualitative metasynthesis. Educational Researcher, 35(5), 258–267.

Beck

J. S.

(2023/2024, Dec./Jan.). Removing artificial barriers to licensure could ease the teacher shortage. Kappan, 105(4), 66–67. https://kappanonline.org/removing-artificial-barriers-to-teacher-licensure-beck/

Bell-Ellwanger

(2024, Jan./Feb.). Data that guides teaching and learning: A culture of data use ensures everyone has access to the information they need to help kids advance. Principal, 20–25.

Bergstrom

C. T.

West

J. D.

(2020). Calling bullshit: The art of skepticism in a data-driven world. Random House.

Bertrand

Marsh

J. A.

(2015). Teachers’ sensemaking of data and implications for equity. American Educational Research Journal, 52(5), 861–893.

10.

Bertrand

Marsh

J. A.

(2021). How data-driven reform can drive deficit thinking. Kappan, 102, 35–39.

11.

Blinder

(2015,Apr. 1). Atlanta educators convicted in school cheating scandal. New York Times. https://www.nytimes.com/2015/04/02/us/verdict-reached-in-atlanta-school-testing-trial.html

12.

Booher-Jennings

(2005). “Educational triage” and the Texas accountability system. American Educational Research Journal, 42(2), 231–268.

13.

Bowers

A. J.

Molle

Choi

Halverson

(2024, Jan./Feb.). Tracking the indicators of opportunity: Use data to measure the intangibles that can contribute to educational equity. Principal, 38–39.

14.

Bridgeman

Trapani

Attali

(2012). Comparison of human and machine scoring of essays: Differences by gender, ethnicity, and country. Applied Measurement in Education, 25(1), 27–40. https://doi.org/10.1080/08957347.2012.635502

15.

Brighouse

Ladd

H. F.

Loeb

Swift

(2018). Educational goods: Values, evidence, and decision-making. University of Chicago Press.

16.

Caraballo

(2022, Feb.). Remote learning accidentally introduced a new danger for LGBTQ students. Slate. https://slate.com/technology/2022/02/remote-learning-danger-lgbtq-students.html

17.

Cook

(2024, May 14). US schools leaked 32 million records in 2,691 data breaches since 2005. Comparitech. https://www.comparitech.com/blog/vpn-privacy/us-schools-data-breaches/

18.

Cronbach

L. J.

(1988). Five perspectives on validity argument. In Wainer

Braun

(Eds.), Test validity (pp. 3–17). Lawrence Erlbaum.

19.

D’Agostino

J. V.

Powers

S. J.

(2009). Predicting teacher performance with test scores and grade point average: A meta-analysis. American Educational Research Journal, 46(1), 146–182.

20.

Data Quality Campaign. (2014). Teacher data literacy: It’s about time. Author.

21.

Datnow

(2017). Opening or closing doors for students? Equity and data-driven decision making. https://research.acer.edu.au/cgi/viewcontent.cgi?article=1317&context=research_conference

22.

Datnow

Lockton

Weddle

(2021). When data use raises equity and ethical dilemmas in schools. In Mandinach

E. B.

Gummer

E. S.

(Eds.), The ethical use of data in education: Promoting responsible policies and practices (pp. 216–231). Teachers College Press.

23.

Datnow

Park

(2018). Opening or closing doors for students? Equity and data use in schools. Journal of Educational Change, 19(2), 131–152.

24.

Dieterle

Holland

Dede

(2021). The cyclical effects of ethical decisions involving big data and digital learning platforms. In Mandinach

E. B.

Gummer

E. S.

(Eds.), The ethical use of data in education: Promoting responsible policies and practices (pp. 198–215). Teachers College Press.

25.

D’Souza

(2024, Sept. 18). Even as Chat GPT becomes ubiquitous, A.I. pioneers warn of existential risks. EdSource News Brief. https://edsource.org/updates/even-as-chatgpt-becomes-ubiquitous-a-i-pioneers-warn-of-existential-risks

26.

Future of Privacy Forum. (n.d.). Resources. https://fpf.org/resources/

27.

Gay

(2018). Culturally responsive teaching: Theory, research, and practice (3rd ed.). Teachers College Press.

28.

Griese

T. G.

Wende

Bulut

Anderl

(2020). Introduction of data literacy in the undergraduate engineering curriculum. In 2020 IEEE Global Engineering Conference (EDUCON).

29.

Gummer

E. S.

Gibbs

N. P.

Dorn

(2021). The role of educator preparation programs to teach about the ethical use of data. In Mandinach

E. B.

Gummer

E. S.

(Eds.), The ethical use of data in education: Promoting responsible policies and practice (pp. 144–172). Teachers College Press.

30.

Halleck

(2019, March 12). Who’s been charged in the college admissions cheating scandal? Here’s the full list. New York Times. https://www.nytimes.com/2019/03/12/us/felicity-huffman-lori-loughlin-massimo-giannulli.html

31.

Hamilton

Halverson

Jackson

Mandinach

Supovitz

Wayman

(2009). Using student achievement data to support instructional decision making (NCEE 2009-4067). National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. https://ies.ed.gov/ncee/WWC/Docs/PracticeGuide/dddm_pg_092909.pdf

32.

Hargreaves

Braun

(2013). Data-driven improvement and accountability. https://nepc.colorado.edu/sites/default/files/pb-lb-ddia-policy.pdf

33.

Heafner

T. L.

Fitchett

P. G.

(2015). An opportunity to learn US history: What NAEP data suggest regarding the opportunity gap. The High School Journal, 98(3), 226–249.

34.

Heintzelman

S. C.

Bathon

J. M.

(2017). Caught on camera: Special education classrooms and video surveillance. International Journal of Education Policy & Leadership, 12(6), 1–16.

35.

Hibel

Penn

D. M.

(2020). Bad apples or bad orchards? An organizational analysis of educator cheating on standardized accountability tests. Sociology of Education, 93(4), 331–352. https://doi.org/10.1177/0038040720927

36.

Holmes

(2023, Oct.). The unintended consequences of artificial intelligence and education. Education International.

37.

Kahneman

(2011). Thinking fast and slow. Farrar, Straus, and Giroux.

38.

Khodaei

Abdelrazeq

Isenhardt

(2024). Towards categorizing ethical question in data literacy. Ing.grid, 1(2), 1–9. https://www.inggrid.org/article/id/3967/

39.

Labadze

Grigolia

Machaidze

(2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20(1), 56.

40.

Ladson-Billings

(1995). Toward a theory of culturally relevant pedagogy. American Educational Research Journal, 32(3), 465–491.

41.

Lasater

Bengston

Albiladi

W. S.

(2021). Data use for equity?: How data practices incite deficit thinking in schools. Studies in Educational Evaluation, 69(5), 1–10.

42.

Levinson

Fay

(2016). Dilemmas of education justice: Case and commentaries. Harvard Education Press.

43.

Mandinach

E. B.

(2025). Culturally responsive data literacy: An important construct for all educators. Rowman & Littlefield.

44.

Mandinach

E. B.

Cotto

(2021, Oct.). The case for including data privacy and data ethics in educator preparation programs. Future for Privacy Forum. https://studentprivacycompass.org/resource/case-data-privacy-ethics/

45.

Mandinach

E. B.

Gummer

E. S.

(2013). A systemic view of implementing data literacy into educator preparation. Educational Researcher, 42(1), 30–37.

46.

Mandinach

E. B.

Gummer

E. S.

(2016a). Data literacy for educators: Making it count in teacher preparation and practice. Teachers College Press.

47.

Mandinach

E. B.

Gummer

E. S.

(2016b). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366–376.

48.

Mandinach

E. B.

Gummer

E. S.

(Eds.). (2021a). The ethical use of data in education: Promoting responsible policies and practices. Teachers College Press.

49.

Mandinach

E. B.

Gummer

E. S.

(2021b). The landscape of data ethics in education: What counts as responsible data use. In Mandinach

E. B.

Gummer

E. S.

(Eds.), The ethical use of data in education: Promoting responsible policies and practice (pp. 35–55). Teachers College Press.

50.

Mandinach

E. B.

Jimerson

J. B.

(2021). The role of the district, school, and classroom to ensure ethical use of data: It’s more than just FERPA. In Mandinach

E. B.

Gummer

E. S.

(Eds.), The ethical use of data in education: Promoting responsible policies and practice (pp. 125–143). Teachers College Press.

51.

Mandinach

E. B.

Schildkamp

(2021). Misconceptions about data-based decision making in education: An exploration of the literature. Studies in Educational Evaluation, 69, 1–10.

52.

Mandinach

E. B.

Warner

Mundry

S. E.

(2019, Nov.). Using data to promote culturally responsive teaching (webinar). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Northeast & Islands.

53.

Martin

(2022a). Ethical theories and data analytics. In Martin

(Ed.), Ethics of data and analytics: Concepts and cases (pp. 51–56). CRC Press.

54.

Martin

(2022b). Transparency and accountability in data analytics. In Martin

(Ed.), Ethics of data and analytics: Concepts and cases (pp. 403–407). CRC Press.

55.

Messick

S. J.

(1989). Validity. In Linn

R. L.

(Ed.), Educational measurement (3rd ed.; pp. 13–103). Macmillian.

56.

National Association of State Directors of Teacher Education and Certification. (2023). Model code of ethics for educators (MCEE). https://www.nasdtec.net/page/MCEE_Doc

57.

National Forum on Education Statistics. (2010). Forum guide to data ethics (NFES 2010-801). U.S. Department of Education, National Center for Education Statistics. https://nces.ed.gov/pubs2010/2010801.pdf

58.

National Forum on Education Statistics. (2016). Forum guide to education data privacy (NFES 2016-096). U.S. Department of Education, National Center for Education Statistics. https://nces.ed.gov/pubs2016/NFES2016096.pdf

59.

New York Office of Information Technology Services. (2023, Sept. 27). State education department issues determination on biometric identifying technology in schools. https://www.nysed.gov/news/2023/state-education-department-issues-determination-biometric-identifying-technology-schools

60.

Nichols

S. L.

(2021). Educational policy contexts and the (un)ethical use of data. In Mandinach

E. B.

Gummer

E. S.

(Eds.), The ethical use of data in education: Promoting responsible policies and practices (pp. 81–97). Teachers College Press.

61.

Pane

Steiner

E. D.

Baird

M. D.

Hamilton

L. S.

(2015, Nov.). Continued progress: Promising evidence on personalized learning. Bill & Melinda Gates Foundation. https://www.rand.org/pubs/research_reports/RR1365.html

62.

Paris

(2012). Culturally sustaining pedagogy: A needed change in stance, terminology, and practice. Educational Researcher, 41(3), 93–97.

63.

Privacy Technical Assistance Center. (n.d.). Best practices for data destruction. U.S. Department of Education, Privacy Technical Assistance Center. https://studentprivacy.ed.gov/sites/default/files/resource_document/file/Best%20Practices%20for%20Data%20Destruction%20%282019-3-26%29.pdf

64.

Reich

J. A.

(2021). Power, positionality, and the ethic of care in qualitative research. Qualitative Sociology, 44(4), 575–581.

65.

Schermele

(2024, Mar. 28). Students used AI to create nude photos of their classmates. For some, arrests came next. USA Today. https://www.usatoday.com/story/news/education/2024/03/28/ai-nudes-generate-chaos-at-schools/72976869007/

66.

Schmidt

W. H.

Burroughs

N. A.

Zoido

Houang

R. T.

(2015). The role of schooling in perpetuating educational inequality: An international perspective. Educational Researcher, 44(7), 371–386.

67.

Seife

(2024, Jan. 4). The sins in academia only start with plagiarism. New York Times. https://www.nytimes.com/2024/01/04/opinion/plagiarism-academia-claudine-gay.html

68.

Singer

(2024, July 6). Students target teachers in group TikTok attack, shaking their school. New York Times. https://www.nytimes.com/2024/07/06/technology/tiktok-fake-teachers-pennsylvania.html

69.

Singer

Krolik

(2021, May 9). Online cheating charges upend Dartmouth Medical School. New York Times. https://www.nytimes.com/2021/05/09/technology/dartmouth-geisel-medical-cheating.html

70.

Stahl

W. M.

Karger

(2016). Student data privacy, digital learning, and special education: Challenges at the intersection of policy and practice. Journal of Special Education Leadership, 29(2), 79–88.

71.

Statewide Longitudinal Data Systems Program. (n.d.). About the SLDS Grant Program. https://nces.ed.gov/programs/slds/about_SLDS.asp

72.

Taibi

Fernandez-Sanz

Pospelova

Leon-Urrutia

Marjanovic

Splendore

Urbsiene

(2021). Developing data literacy competences at university: The experience of the Dedalus Project. In 2021 1st Conference on Online Teaching for Mobile Education (OT4ME) (pp. 112–113). IEEE. https://doi.org/10.1109/OT4ME53559.2021.9638912

73.

U. S. Department of Education. (2018). Office of the Chief Privacy Officer’s processing of Family and Educational Rights and Privacy Act complaints (ED-OIG/A09R0008). Office of Inspector General.

74.

Virginia Department of Education. (n.d.). Performance assessments and local alternative assessments. https://www.doe.virginia.gov/teaching-learning-assessment/student-assessment/virginia-sol-assessment-program/performance-assessments-local-alternative-assessments

75.

Wang

(2021). When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale. Studies in Educational Evaluation, 69, 1–9. https://doi.org/10.1016/j.stueduc.2020.100872

76.

Warner

(2021). Culturally responsive data literacy. WestEd, National Center for Systemic Improvement. https://ncsi-library.wested.org/resources/729

77.

Williamson

Molnar

Boninger

(2024). Time for a pause: Without effective public oversight, AI in schools will do more harm than good. National Education Policy Center. https://www.nepc.colorado.edu/sites/default/files/publications/PB%20Williamson_0.pdf

Shining Light on Ethical Uses of Data in Education: Emerging Importance

Abstract

Keywords

Get full access to this article

References