It looks like you've uploaded an image of a matrix-based problem from an online learning platform, likely involving Gaussian elimination or row reduction to solve a system of linear equations. The steps shown involve elementary row operations, and you're likely in Step 3, where you need to multiply row 3 by a scalar to get a leading 1 in the bottom-right corner.

Here’s what I can infer from the image:

• Step 1: The first row operation focused on getting a leading 1 in the second row, second column.
• Step 2: The next row operations were to obtain zeros in the first and third rows in the second column.
• Step 3: You're working on getting a leading 1 in the third row, last column (third row, third column).

It looks like you are supposed to multiply the third row by 3 to normalize the last element (from 27 to 1). This step will transform the matrix into row echelon form, allowing you to further simplify the system.

To proceed:

1. Multiply the entire third row by $\frac{1}{27}$.
2. After this operation, the last element of the third row will be 1, and the matrix should be close to or in reduced row echelon form.

Would you like a step-by-step breakdown of how to finish this? Let me know if you'd like more details.

Here are five follow-up questions based on this topic:

1. What is Gaussian elimination, and how does it help in solving systems of linear equations?
2. Can you explain the different types of elementary row operations?
3. How does one identify when a matrix is in row echelon form versus reduced row echelon form?
4. What do pivots represent in the context of Gaussian elimination?
5. How do you interpret the solution to a system of equations once the matrix is in reduced row echelon form?

Tip: Always ensure that each step in Gaussian elimination creates leading 1's (pivots) in descending rows and eliminates the necessary entries to simplify solving for each variable.