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Ethical by Design: Aligning LDT Student Outcomes with Responsible AI Use

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Title: Ethical by Design: Aligning LDT Student Outcomes with Responsible AI Use
Language: English
Authors: William Cain
Source: Educational Research: Theory and Practice. 2026 37(1):28-35.
Availability: Northern Rocky Mountain Educational Research Association. Web site: http://www.nrmera.org/educational-research-theory-practice/
Peer Reviewed: Y
Page Count: 8
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Ethics, Artificial Intelligence, Graduate Students, Learning Objectives, Technology Uses in Education
Geographic Terms: California, Massachusetts (Cambridge), Indiana, Pennsylvania, Connecticut, California (San Diego), Colorado (Denver)
ISSN: 2637-8965
Abstract: This paper examines the shared student learning outcomes (SLOs) of eight online graduate programs in Learning, Design, and Technology (LDT) and aligns them with generative AI-focused ethical principles derived from the Daniels Fund Ethics Initiative. This conceptual approach -- aligning thematically related or shared SLOs with a set of universal ethical principles in the context of generative AI use - demonstrates how ethical considerations can be integrated into LDT educational programs, ensuring that graduates are equipped to navigate the complexities of AI and emerging technologies responsibly. This paper is meant to demonstrate a research-based approach to developing ethical alignments for AU uses within LDT-program SLOs with the goal of fostering ethical, equitable, and sustainable professional practices in the field.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1505320
Database: ERIC
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  Availability: 0
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  Data: This paper examines the shared student learning outcomes (SLOs) of eight online graduate programs in Learning, Design, and Technology (LDT) and aligns them with generative AI-focused ethical principles derived from the Daniels Fund Ethics Initiative. This conceptual approach -- aligning thematically related or shared SLOs with a set of universal ethical principles in the context of generative AI use - demonstrates how ethical considerations can be integrated into LDT educational programs, ensuring that graduates are equipped to navigate the complexities of AI and emerging technologies responsibly. This paper is meant to demonstrate a research-based approach to developing ethical alignments for AU uses within LDT-program SLOs with the goal of fostering ethical, equitable, and sustainable professional practices in the field.
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