The ability to become a data consumer is an art form which transcends professions. A vital aptitude in todays information age, Googles Chief Econ

Group Discussion: Step 3: Aggregate the Data

The ability to become a data consumer is an art form which transcends professions. A vital aptitude in today’s information age, Google’s Chief Economist Dr. Hal R. Varian commented, “The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades” (Dykes, 2016).

Step 3 of your Project further develops your ability to understand, process, and extract value from data. Also known as data aggregation, this step prompts you to pull together major findings and data points from multiple evaluation sources and culminate them into one complete programmatic story. This aggregate story will become your program’s source of truth, guiding initiatives, interventions, and teacher/family relationships.

In this Group Discussion Board, you and your group members aggregate the data from Connor Street’s evaluations. You look for comparisons, trends, and causal relationships to draw conclusions about the program’s strengths and opportunities for improvement. You also consider how stakeholders might perceive this information.

Reference: Dykes, B. (2016, March 31). Data storytelling: The essential data science skill everyone needs. Forbes. https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/#63d7604352ad 

To prepare

Examine the “Measuring What Matters” article, which details Step 3: Aggregating Data. Then, revisit the Week 5 and 6 Group Discussion Board in which each group member detailed his or her initial analysis. As you review each analysis, reflect on the key findings and insights that are both similar to and different from your own ideas.

By Day 5 of Week 7

Review the findings of your colleagues and address the following prompts:

1. Explain comparisons and trends that might exist among the key findings.

2. Explain which key findings might be in contrast with each other and why.

3. Explain how and/or why one key finding might be impacting (either positively or negatively) the successfulness of another data set.

4. Explain what might be the greatest strength of the program, as well as what might be the most important area for which the program needs to improve and why. 

5. Explain how these major findings might be perceived across stakeholder groups and why. 

Revisit this Discussion Board throughout Week 7 to collaborate with colleagues by responding to their posts. Work with colleagues to synthesizing the groups insights into one cohesive evaluation. which details the quality and effectiveness of the program. Note what you have learned and/or any insights you have gained as a result of the comments your colleagues made and the connections you have made with the Learning Resources.

Support your comments with in-text citations and references following the APA style guide.

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