How can AI help us create more personalized and meaningful authentic student assessments? Are we ready to embrace AI not just as a tool but as a creative partner in our course design?
These questions were posed when we recently attended the EDUCAUSE Teaching and Learning Symposium, the main theme of which was Balancing Humanity and Technology AI in the Classroom.
Stephanie Speicher, a professor at Weber State University, presented a session entitled Authentic Assessment Meets AI: Fostering Human-Centric Pedagogies. Her session culminated with actionable takeaways and strategies for designing authentic assessments that foster human-centric pedagogies.
Professor Speicher shared two resources that can help instructors consider the role of artificial intelligence while planning assessments. Read on to learn more about Bloom’s Taxonomy guide, originally created by Oregon State University, and the AI/Assessment HUMAN framework.
Bloom’s Taxonomy Revisited
To help instructors reconsider course goals and student learning in the age of Generative AI (GAI), Bloom’s Taxonomy Revisited guide can be used as a reference to evaluate the current course activities and assessments and identify what changes may be needed with AI integration.
AI Authentic Assessment HUMAN Framework
The 5-step AI authentic assessment HUMAN framework can guide instructors in reflecting on real-world applications, engaging students authentically, and aligning assessments with learning objectives and emerging technologies.
Step 1- H: Defining HOLISTIC learning goals, considering
- Learning goals: What are the key knowledge, skills, or competencies gained?
- Authentic context: How can I embed AI in a scenario that mirrors real-world applications?
- Assessment type: What form will the assessment take, and how does it align with the learning goals?
Step 2- U: UTILIZE the right AI tool, considering
- AI capabilities: What specific AI functionalities (e.g., data analysis) are needed to support the authentic context?
- Available tools: Research potential AI tools based on functionalities, accessibility, and integration with your LMS.
- Ethical considerations: Are there any biases, data privacy practices, and alignment with NU’s values?
Step 3- M: Crafting MEANINGFUL experiences, considering
- Pre-assessment activities: What knowledge or skills do students need before interacting with AI?
- Interaction with AI: How students will engage with the AI tools (e.g., provide input data, interpret AI outputs)
- Formative feedback: How will I incorporate feedback on students’ interactions with AI (e.g., Instructor guidance, peer review)?
Step 4 – A: Assessing student learning, considering
- Assessment criteria: How will I evaluate student work beyond technical accuracy? Consider critical thinking, communication, and ethical issues.
- Rubrics and guidelines: Develop clear rubrics aligned with learning goals and assessment criteria.
- Debriefing and Reflection: Plan to discuss the AI’s role in the assessment, its limitations, and ethical implications. Encourage student reflection on their learning.
Step 5 – N: NAVIGATE ethical implications, considering
- What is AI’s role in the assessment, its limitations, and ethical implications?
- Does the authentic context include ethical considerations related to the use of AI?
- Data Privacy and Security: Be transparent about how student data is collected, used, and stored when using AI tools.
The HUMAN framework can guide you in creating AI-transformed authentic assessment methods for a more engaging and effective learning experience. The human-AI partnership not only enriches the learning process but also prepares students for a future where collaboration with AI is an essential skill (Speicher, 2024)
References
Advancing meaningful earning in the age of AI– Artificial intelligence tools– Faculty Support, Oregon State Ecampus, OSU Degrees Online. (n.d.). Ecampus.oregonstate.edu.
Speicher, S. (2024, February). 5 steps for human-AI authentic assessment design [Infographic].