AI for Beginners Module Manuscript

Tools & Platforms

• Microsoft Word (manuscript development)

• LMS Integration (discussion boards, assignment submission)

• External Readings, Articles, and Multimedia (TechTarget, IBM, Fireship, YouTube)

Learning Objectives

By the end of this module, students were able to:

1. Explain the fundamental role of data in the field of AI.

2. Categorize diverse data sources applicable to AI.

3. Critically evaluate the role of databases in businesses.

4. Analyze emerging database technologies and trends.

5. Identify machine learning-based solutions to database performance challenges.

Instructional Design Highlights

• Curated Resources: Selected a balanced mix of textbook chapters, industry articles, and videos to give students both foundational and emerging perspectives on data in AI.

• Engaging Discussion Board: The Navigating Growth in Database Scaling discussion encouraged students to explore why businesses must adapt to growing data needs, identify challenges, and propose practical solutions. It also pushed them to connect with real-world experiences and emerging technologies, making the conversation relevant beyond the classroom.

• Applied Assignment: The Enhancing Database Performance with Machine Learning memo task asked students to step into the role of a tech company employee proposing solutions to performance issues. This professional-style activity required them to apply course concepts to realistic scenarios, fostering both critical thinking and workplace-ready communication skills.

• Scaffolded Design: The sequence - readings → discussion → application - ensured that students built knowledge, tested ideas collaboratively, and then synthesized learning into a concrete deliverable.

Assessment & Measurement

• Discussion Board: Assessed student ability to articulate challenges, propose solutions, and integrate peer feedback. Minimum word counts and guided prompts ensured depth of engagement.

• Memo Assignment: Evaluated based on clarity, professional tone, application of machine learning solutions, and connection to real-world database challenges.

• Learning Outcomes: Both assessments directly tied back to learning objectives, reinforcing critical thinking, emerging tech analysis, and solution design.