24 November 2024

AI Learning Centre Tasked with Enhancing MBA Syllabi via PowerFlow Sequential Prompt

How AI was used as an invaluable assistant for syllabus improvement.

The power of AI to assist in enhancing educational content is something educators are increasingly exploring. We recently experimented with an AI-driven approach to improve a course syllabus, focusing on streamlining content and enhancing clarity. This article details the process and the final outcome, offering insights into how AI can be harnessed to assist lecturers in elevating course materials.

This type of advanced work was done on UNIC's proprietary platform Accelerate, using PowerFlow's ability to perform tasks in sequential and parallel modes.

The Prompt and Its Purpose

To start, we provided the AI with a comprehensive prompt designed to create an improved version of an existing course syllabus. The course in question was a 2nd year MBA course and it involved multiple sections, including course information, description, objectives, learning outcomes, content, activities, assessment methods, required readings, academic journals, etc.

The key instructions in the prompt were:

  • Maintain specific formatting (e.g., bullet points instead of paragraphs, detailed weekly breakdowns).
  • Highlight suggestions and improvements.
  • Explain rationale behind suggestions and improvements after each section.
  • Generate course description based on the whole improved syllabus, not the original one.
  • Emphasize higher-order thinking skills based on Bloom's taxonomy.
  • Suggest 12 additional optional ideas for course content that might interest the lecturer (in a logical easy-to-learn progression for students)
  • Link learning activities with the course's learning outcomes.
  • Suggest additional ideas for Learning Activities, Teaching Methods, and Assessment methods.
  • Make sure each improvement in the Readings section is a book/textbook that exists.
  • Ensure gender-neutral language throughout.
  • Make sure up to 3 LOBs contribute to the UN PRIME SDGs.

The overall aim was to have the AI reformat, enrich, and organize the existing course syllabus to make it more engaging and educationally effective for students by way of suggesting possible improvements for the lecturer to choose from. Its goal is to be an assistant and a valuable resource.

The Process

The process involved feeding the AI each section of the prompt, allowing it to build a cohesive and improved syllabus from the ground up. Each part of the syllabus—from the course description to learning activities—was handled methodically. The prompt specified the format and content for each section, and the AI responded to each instruction step-by-step, providing suggestions to complement the lecturer's expertise.

List of all changes between the original syllabus and the improved one:

Course Description:

  • The original course description was revised to emphasize practical applications, clearer engagement, and the technological underpinnings of business process management (BPM).
  • The improved description highlighted specific skills students would gain, making it more compelling.

Course Objectives:

  • The AI replaced general verbs with higher-order verbs from Bloom's taxonomy, such as "innovate," "advocate," and "construct."
  • This shift focused on synthesis, evaluation, and strategic thinking, ensuring that objectives encouraged students to develop critical and higher-level skills.

Learning Outcomes:

  • The original learning outcomes were revised to enhance emphasis on comprehension, analysis, and application. Higher-order thinking verbs were used. Providing a more robust framework for evaluating student performance.
  • The AI ensured that the outcomes were consistent with the enhanced objectives.

Course Content:

  • The AI provided a detailed week-by-week breakdown of the course, whereas the original syllabus grouped some weeks together. Each week included specific topics with clear, concise descriptions, enhancing the structure of the learning progression.
  • Additionally, twelve optional topics were suggested, giving lecturers more flexibility to extend or personalize the course content.

Learning Activities and Teaching Methods:

  • The original syllabus contained standard activities such as lectures and case studies. The improved version introduced innovative learning activities, including workshops on emerging technologies, role-playing exercises, flipped classrooms, and peer review sessions.
  • These additions were designed to cater to different learning styles, increase student engagement, and make the course more interactive.

Assessment Methods:

  • The AI added new assessment methods, such as peer assessment, portfolio development, and oral presentations.
  • These were designed to foster reflective practices and provide a broader evaluation of student learning compared to the original syllabus, which relied more on traditional exams and case study analyses.

Required and Recommended Textbooks/Readings:

  • The AI curated a list of additional required and recommended readings, ensuring that only credible, existing sources were included.
  • This expanded the academic resources available to students, providing more comprehensive coverage of the topics.

Gender-Neutral Language:

  • The original syllabus contained instances of gender-specific language, which the AI revised to be gender-neutral, promoting inclusivity.

Formatting Changes:

  • The original syllabus used paragraphs for certain sections, which were changed to bullet points to improve readability.
  • Additionally, course information was organized into a structured table, making it more accessible to students.

Linking Activities with Learning Outcomes:

  • The improved syllabus included clearer links between learning activities and the course's learning outcomes, ensuring that each activity contributed directly to achieving the stated objectives.

Showcasing the Outcome

The resulting syllabus was enhanced to better support lecturers in delivering structured and engaging content:

  • Engagement: Updated objectives and learning outcomes were more action-oriented, emphasizing higher-order thinking skills, which encourages students to engage critically with the material.

  • Flexibility for Educators: The AI's suggestions for additional topics and teaching methods gave lecturers flexibility to tailor the course to their preferences and students' needs.

Conclusion

These changes collectively aimed to enhance the educational value of the course while providing lecturers with a range of tools to better engage their students. The AI's role was to suggest improvements that would complement the lecturer's expertise, making the course more effective and engaging without replacing the lecturer's crucial role.

Remember to always check AI outputs thoroughly, as human oversight lowers AI risk. For more information, contact AILC.

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