Educational Technology · Capella FlexPath

EDT-FPX5102B: Analyzing Data

The second course in the EDT-FPX5102 data sequence — moving from the collection strategy described in 5102A into actually analyzing student data to identify and address real educational problems.

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EDT-FPX5102B has Educational Technology FlexPath students analyze student data to identify and address educational problems. It's the analytical core of the EDT-FPX5102 sequence: where 5102A described the collection strategy, 5102B requires you to work with actual (or realistic) data, draw conclusions, and connect those conclusions to a concrete instructional problem — work that 5102C and 5102D then extend with tools and communication. This guide breaks down what the course typically requires and how academic support for EDT-FPX5102B fits into a self-paced course that still expects defensible data analysis.

Course Overview

Per the Capella catalog, this course has students "analyze student data to identify and address educational problems." The assessment typically requires you to work with a dataset (provided, simulated, or drawn from a practicum-style scenario), apply an appropriate analysis approach, and translate the findings into a specific, addressable educational problem statement.

Common Assessment Focus Areas

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Common Challenges in This Course

A common mistake is jumping straight to a recommended solution without first clearly demonstrating the data analysis that justifies it — most rubrics grade the analytical reasoning as much as the conclusion. Another frequent issue is identifying a problem too broadly ("students struggle with math") instead of a specific, data-supported issue that a targeted response could realistically address.

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EDT-FPX5102B FAQ

Do I need real student data for this course?

A realistic, anonymized, or simulated dataset is typically acceptable — check your course shell for the specific data source requirements.

How is this different from EDT-FPX5102A?

5102A describes the strategy for collecting data; 5102B requires you to actually analyze data and draw conclusions from it.

What analysis method should I use?

Choose an approach appropriate to your data type — trend analysis, subgroup comparison, or gap analysis are all common and acceptable as long as you justify the choice.

How specific does the educational problem need to be?

Specific enough that a targeted intervention could realistically address it — broad statements like "students need more support" are usually marked down.

What comes next in the sequence?

EDT-FPX5102C introduces specific technology tools for data collection, building on the analysis skills from this course.