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

Author:

Patterson ChrisORCID,York Emily,Maxham Danielle,Molina RudyORCID,Mabrey PaulORCID

Abstract

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.

Publisher

Society for Learning Analytics Research

Subject

Computer Science Applications,Education

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Explainable Artificial Intelligence for Academic Performance Prediction. An Experimental Study on the Impact of Accuracy and Simplicity of Decision Trees on Causability and Fairness Perceptions;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03

2. Toward Asset-based Instruction and Assessment in Artificial Intelligence in Education;International Journal of Artificial Intelligence in Education;2024-01-16

3. Debiasing Education Algorithms;International Journal of Artificial Intelligence in Education;2024-01-04

4. Fairness, Trust, Transparency, Equity, and Responsibility in Learning Analytics;Journal of Learning Analytics;2023-03-12

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