What caused the sudden 50% decrease in completion rates for Great Learning's Machine Learning Specialization program last month?

Introduction

The sudden 50% decrease in completion rates for Great Learning's Machine Learning Specialization program last month is a critical issue that demands immediate attention. This significant drop could have far-reaching implications for the program's success, student satisfaction, and the company's reputation in the e-learning space. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent change to the program structure or content. Has there been any significant update to the Machine Learning Specialization curriculum or platform in the past 1-2 months?

Why it matters: Recent changes could directly impact completion rates. Expected answer: Yes, there was a major curriculum update. Impact on approach: If confirmed, we'd focus on analyzing the changes and their effects on student engagement.

• Considering the magnitude of the decrease, I'm wondering if this affects all user segments equally. Do we see this 50% drop across all demographics, or is it more pronounced in specific groups?

Why it matters: Helps identify if the issue is universal or segment-specific. Expected answer: The drop is more significant among working professionals. Impact on approach: We'd investigate factors specific to this demographic, such as time constraints or course difficulty.

• Given the specialization nature of the program, I'm curious about the course progression. Has there been any change in how students move through the program or in the prerequisites for advanced modules?

Why it matters: Changes in course structure could affect student progress and motivation. Expected answer: No changes to progression, but stricter grading implemented. Impact on approach: We'd examine the impact of new grading policies on student persistence.

• Thinking about external factors, I'm considering market dynamics. Has there been any significant change in the competitive landscape for machine learning courses in the past month?

Why it matters: External competition could influence student commitment and completion rates. Expected answer: A major competitor launched a free ML course. Impact on approach: We'd analyze our value proposition and possibly adjust marketing strategies.