Applying a Responsible Innovation Framework in Developing an Equitable Early Alert System:

A Case Study




responsible innovation, retention, early alert systems, equity, students as partners, research paper


The anticipation, inclusion, responsiveness, and reflexivity (AIRR) framework (Stilgoe et al., 2013) is a novel framework that has helped those in science and technology fields shift their focus from products to the processes used to create those products. However, the framework has not been known to be applied to the development and implementation of data analytics in higher education. In a case study of creating an early-alert retention system at James Madison University, a working group of ~20 faculty, staff, and students creatively utilized the AIRR framework. The present study discusses how the AIRR framework was utilized to observe and enhance group processes, and the outcomes of those enhanced processes.


Beck, U. (2000). Risk society revisited: Theory, politics, and research programmes. In B. Adam., U. Beck, & J. Van Loon (Eds.), The risk society and beyond: Critical issues for social theory (pp. 211–229). Sage Publications.

Bensimon, E. M. (2005). Closing the achievement gap in higher education: An organizational learning perspective. New Directions for Higher Education, 131, 99–111.

Berendt, B., Littlejohn, A., & Blakemore, M. (2020). AI in education: Learner choice and fundamental rights. Learning, Media and Technology, 45(3), 312–324.

Bird, K. A., Castleman, B. L., Mabel, Z., & Song, Y. (2021). Bringing transparency to predictive analytics: A systematic comparison of predictive modeling methods in higher education. AERA Open, 7.

Broughan, C., & Prinsloo, P. (2020). (Re)centring students in learning analytics: In conversation with Paulo Freire. Assessment & Evaluation in Higher Education, 45(4), 617–628.

Brown McNair, T., Bensimon, E. M., & Malcom-Piqueux, L. (2020). From equity talk to equity walk: Expanding practitioner knowledge for racial justice in higher education. John Wiley & Sons.

Brown Wright, G. (2011). Student-centered learning in higher education. International Journal of Teaching and Learning in Higher Education, 23(3), 92–97.

Buckingham Shum, S., Ferguson, R., & Martinez-Maldonado, R. (2019). Human-centred learning analytics. Journal of Learning Analytics, 6(2), 1–9.

Carnevale, A. P., Rose, S. J., & Cheah, B. (2013). The college payoff: Education, occupations, lifetime earnings. Georgetown University Center on Education and the Workforce.

Casadevall, S. R. (2016). Improving the management of water multi-functionality through stakeholder involvement in decision-making processes. Utilities Policy, 43A, 71–81.

Creswell, J. W. (2014). A concise introduction to mixed methods research. SAGE.

Crosling, G., Heagney, M., & Thomas, L. (2009). Improving student retention in higher education. Australian Universities’ Review, 51(2), 9–18.

Culver, K. C., Harper, J., & Kezar, A. (2021). Design for equity in higher education. University of Southern California, Pullias Center for Higher Education.

Foster, E., & Siddle, R. (2020). The effectiveness of learning analytics for identifying at-risk students in higher education. Assessment & Evaluation in Higher Education, 45(6), 842–854.

Francis, P., Broughan, C., Foster, C., & Wilson, C. (2020). Thinking critically about learning analytics, student outcomes, and equity of attainment. Assessment & Evaluation in Higher Education, 45(6), 811–821.

Fulcher, K. H., & Prendergast, C. O. (2021). Improving student learning at scale: A how-to guide for higher education. Stylus Publishing.

Fulcher, K. H., Good., M. R., Coleman, C. M., & Smith, K. L. (2014, December). A simple model for learning improvement: Weigh pig, feed pig, weigh pig. (Occasional Paper No. 23). University of Illinois and Indiana University, National Institute for Learning Outcomes Assessment (NILOA).

Garcia, N. M., López, N., & Vélez, V. N. (2018). QuantCrit: Rectifying quantitative methods through critical race theory. Race Ethnicity and Education, 21(2), 149–157.

Garcia, P., Sutherland, T., Cifor, M., Chan, A. S., Klein, L., D’Ignazio, C., & Salehi, N. (2020). No: Critical refusal as feminist data practice. Companion of the 2020 ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW ’20) 17–21 October 2020, Virtual (pp. 199–202). ACM Press.

Gregory, A. (2007). Involving stakeholders in developing corporate brands: The communication dimension. Journal of Marketing Management, 23(1–2), 59–73.

Jayaprakash, S. M., Moody, E. W., Lauría, E. J., Regan, J. R., & Baron, J. D. (2014). Early alert of academically at-risk students: An open source analytics initiative. Journal of Learning Analytics, 1(1), 6–47.

Jiménez, D., & Glater, J. D. (2020). Student debt is a civil rights issue: The case for debt relief and higher education reform. Harvard Civil Rights–Civil Liberties Law Review, 55(1), 131–198.

Jones, K. M. L. (2019). Learning analytics and higher education: A proposed model for establishing informed consent mechanisms to promote student privacy and autonomy. International Journal of Educational Technology in Higher Education, 16, 24.

Kalsbeek, D. H. (2013). Framing retention for institutional improvement: A 4 Ps framework. New Directions for Higher Education, 2013(161), 5–14.

Kezar, A. (2019). Creating a diverse student success infrastructure: The key to catalyzing cultural change for today’s student. University of Southern California, Pullias Center for Higher Education.

Lang, C., Teasley, S., & Stamper, J. (2017). Building the learning analytics curriculum: Workshop. Proceedings of the 7th International Conference on Learning Analytics and Knowledge (LAK ’17), 13–17 March 2017, Vancouver, BC, Canada (pp. 520–521). ACM Press.

Montenegro, E., & Jankowski, N. A. (2020, January). A new decade for assessment: Embedding equity into assessment praxis (Occasional Paper No. 42). University of Illinois and Indiana University, National Institute for Learning Outcomes Assessment (NILOA).

National Center for Education Statistics. (2022, May). Undergraduate retention and graduation rates.,See%20Digest%20of%20Education%20Statistics%202021%2C%20table%20326.30.,fall%202019%20was%2061%20percent

Prinsloo, P., & Slade, S. (2014). Student data privacy and institutional accountability in an age of surveillance. In M. R. Menon, D. G. Terkla, & P. Gibbs (Eds.), Using data to improve higher education: Research, policy, and practice (pp. 197–214). SensePublishers Rotterdam.

Prinsloo, P., & Slade, S. (2018). Mapping responsible learning analytics: A critical proposal. In B. H. Kahn, J. R. Corbeil, & M. E. Corbeil (Eds.), Responsible analytics and data mining in education: Global perspectives on quality, support, and decision making (pp. 63–80). Routledge.

Reidenberg, J. R., & Schaub, F. (2018). Achieving big data privacy in education. Theory and Research in Education, 16(3), 263–279.

Sclater, N., Peasgood, A., & Mullan, J. (2016, April). Learning analytics in higher education: A review of UK and international practice. Jisc.

Seidman, A. (2012). Taking action: A retention formula and model for student success. In A. Seidman (Ed.), College student retention: Formula for student success, 2nd ed. (pp. 267–284). Rowman & Littlefield Publishers.

Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510–1529.

Spady, W. G. (1971). Dropouts from higher education: Toward an empirical model. Interchange, 2, 38–62.

Stilgoe, J., Owen, R., & Macnaghten, P. (2013). Developing a framework for responsible innovation. Research Policy, 42(9), 1568–1580.

Tamborini, C. R., Kim, C., & Sakamoto, A. (2015). Education and lifetime earnings in the United States. Demography, 52(4), 1383–1407.

Tampke, D. R. (2013). Developing, implementing, and assessing an early alert system. Journal of College Student Retention: Research, Theory & Practice, 14(4), 523–532.

Tinto, V. (1987). Leaving college: Rethinking the causes and cures of student attrition. University of Chicago Press.

Tinto, V. (2006). Research and practice of student retention: What next? Journal of College Student Retention: Research, Theory & Practice, 8(1), 1–19.

Watt, S. K., Mahatmya, D., Mohelabi, M, & Martin-Stanley II, C. R. (Eds.). (2022). The theory of being: Practices for transforming self and communities across difference. Stylus Publishing.

Westin, A. F. (1967). Legal safeguards to insure privacy in a computer society. Communications of the ACM, 10(9), 533–537.

Yin, R. K. (2014). Case study research: Design and methods (5th ed.). SAGE.




How to Cite

Patterson, C., York, E., Maxham, D., Molina, R., & Mabrey, P. (2023). Applying a Responsible Innovation Framework in Developing an Equitable Early Alert System:: A Case Study. Journal of Learning Analytics, 10(1), 24-36.



Special Section on Fairness, Equity, and Responsibility in Learning Analytics