Strategies for Pedagogical Evaluation
Once a potential tool has been identified for use in courses or programs, faculty should evaluate the tool prior to implementation. Evaluating an artificial intelligence tool for use in a higher education course requires a systematic approach to ensure its effectiveness and suitability for the educational context. Here’s a step-by-step guide for evaluating such a tool:
- Define Learning Objectives: Determine how the AI tool can complement or enhance the achievement of course learning objectives.
- Trial and Pilot Testing: Conduct a trial or pilot test of the AI tool with a small group of students or colleagues. Gather feedback on its effectiveness and usability.
- Learning Analytics: Assess the tool’s ability to provide valuable learning analytics and insights for instructors and students. Analytics can help identify areas for improvement and measure learning outcomes.
- Feedback and Assessment: Collect feedback from students who used the AI tool and assess its impact on their learning experience and outcomes.
- Integration with Curriculum: Ensure the AI tool can be integrated seamlessly into the course curriculum without disrupting the overall flow of the course.
- Comparison with Traditional Methods: Compare the AI tool’s effectiveness with traditional teaching methods to gauge its added value.
- Support for Multimodal Learning: Verify if the AI tool supports multimodal learning, allowing students to engage with content using various formats, such as text, audio, video, and interactive elements.
- Long-Term Viability: Assess the long-term viability of the AI tool, considering its potential for future updates and scalability.
