Embedded Files
Assessment on BaiSE is both formative and participatory.
Educators contribute to a shared review ecosystem by:
Completing structured usability rubrics aligned with Issa & Isaias’s framework (2015)
Reflecting on real-world tool use through qualitative feedback forms
Engaging in dialogue with peers through discussion boards and in person professional development and real-world conversations
Rubric for User-Generated AI Tool Reviews
Rubric for User-Generated AI Tool Reviews
Feedback Questions for Impact on Learning and Teaching
Feedback Questions for Impact on Learning and Teaching
How does this review help me identify the most relevant and effective AI tools for my teaching practices?
How effectively does the AI tool integrate into my teaching workflow and reduce my cognitive load?
How has the AI tool enhanced my students’ learning outcomes and engagement?
What changes can I implement in my teaching practice based on feedback from the community and my own experience with AI tools?
Connecting the BaiSE Assessment Model to Canadian AI Curriculum
Connecting the BaiSE Assessment Model to Canadian AI Curriculum
Pan-Canadian Digital Competency Framework
Encourages educators to evaluate digital tools critically, emphasizing data literacy, AI awareness, and ethical technology use.
Artificial Intelligence in K-12 Education (AI4K12 Canada, 2023)
Promotes responsible AI implementation, requiring educators to assess AI tools based on transparency, fairness, and effectiveness.
Alignment with Global AI Standards and Best Practices
Alignment with Global AI Standards and Best Practices
BaiSE also reflects international standards for ethical AI use in education, ensuring global relevance.
UNESCO AI Competency Framework
Aligns with global AI ethics standards by ensuring AI tools are rigorously vetted and reviewed.
Promotes transparent, community-driven AI assessment, reinforcing ethical AI adoption.
Empowers educators to become critical AI evaluators and informed AI adopters.
Page updated
Report abuse