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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Frontier model chatbots can help instructors create, improve, and use learning objectives.

Gregory J Crowther1, Merrill D Funk2, Kelly M Hennessey3

  • 1Life Sciences Department, Everett Community College, Everett, Washington, United States.

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Summary
This summary is machine-generated.

Advanced chatbots can assist in creating learning objectives (LOs) and assessment questions, but instructor oversight is crucial. While chatbots show promise in educational content generation, their outputs require careful review for full readiness.

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Area of Science:

  • Educational Technology
  • Artificial Intelligence in Education

Background:

  • Learning objectives (LOs) are fundamental to course design and curricular reform.
  • Generative artificial intelligence (AI) offers potential for streamlining educational content creation.

Purpose of the Study:

  • To evaluate the efficacy of leading chatbots (ChatGPT-4o, Claude 3.5 Sonnet, Gemini Advanced) in generating and refining learning objectives (LOs).
  • To assess chatbots' ability to create quality assessment questions aligned with LOs.
  • To explore the potential of AI in expediting the design of LOs and related curricular materials.

Main Methods:

  • Chatbots were tasked with creating LOs from course content, adjusting LOs to higher Bloom's Taxonomy levels, and generating assessment questions.
  • The study involved four undergraduate courses: Applied Exercise Physiology, Human Anatomy, Human Physiology, and Motor Learning.
  • Instructor ratings were used to evaluate chatbot outputs against established best practices and quality criteria.

Main Results:

  • Chatbots demonstrated a >70% success rate on most individual criteria for LO creation and assessment question generation.
  • However, chatbots struggled with specific criteria, such as providing appropriate context for LO actions and assigning correct Bloom's Taxonomy levels.
  • Overall, only 38.3% of chatbot-generated outputs fully met all criteria, highlighting the need for human oversight.

Conclusions:

  • Chatbots show significant potential to aid instructors in developing learning objectives and assessment questions, serving as valuable drafting tools.
  • Instructor oversight remains essential to ensure the accuracy, context, and pedagogical appropriateness of AI-generated educational content.
  • AI tools can expedite the creation of LOs and test question templates, improving efficiency in course design.