Embedded Files
Back to model parts
This page pulls all relevant information from the different steps reflected in the site that directly influence Data Visuals and Collection in the Data Collaborative model. This page consolidates all information for Data Visualization. The focus of this section is on the Data Collaborative Partner facing Data Visuals and Collection. If you’re interested in how we tracked our own progress and quality of our team, please refer to the Internal Metrics page.
Here are a few quick links to the information provided below. (Click on the bolded area for where you would like to jump):
- Concepts: How are Data Visuals and Collection incorporated in the Data Collaborative model?
- People: Who is mainly responsible for Data Visuals and Collection?
- Capacity Building: What type of Capacity Building supports Data Visuals and Collection?
Operations: How are the Capacity Building initiatives created and maintained?
Click on the section you would like to jump to below:
Data Visuals and Collections as they relate to the Data Collaborative concept model are reflected in the routines that end in .3. The routines include:
- 1.3: Collect Student outcome data measuring Reading Success Pathway skills using a common assessment tool.
- 3.3: Create and implement data collection plan (and tool) to support fidelity of Evidence-Based Practices.
An important part to note when exploring the Concepts page around Routine 1.3 and 3.3 is to look at the scope and sequence. The Student Outcome data collection happens in intervals based on the designated windows described by the specific assessment(s) being used by the partner organization and when their program takes place — summer or school year. Implementation Data is informed based on the set goals in routines 2.2 and 3.2 and is continuously collected throughout the year.
Routine Quick Jump
Routine Quick Jump
Associated Routines
Associated Routines
The routines to the right will bring you the partner portal, which is a website designed for participating organizations. The site provides additional information on the routines and how they should be executed within the Data Collaborative community. It is important to note that this site is built for the perspective of a partner who is implementing the Data Collaborative model, not how to facilitate the Data Collaborative community like this site.
Different individuals throughout the Data Collaborative community are responsible for the Data Visuals and Collection. This section provides quick access to the core people in the process and provides additional clarity of what role and attributes they have when creating Data Visuals and Collection Tools.
Tyler Barnett
Tyler Barnett
Data Lead
Data Lead
- The Data Collaborative Team's Data Lead, Tyler Barnett, was the primary person responsible for the Data Visuals and Collection tools. His responsibilities included:
- DataFit
- Student Outcome Report
- Observation Tools
- Homebase
Exploring the bodies of work that the Data Lead was responsible for may provide additional clarity around the skill sets and attributes that were required to support the specific tools. The programs used in the Data Collaborative to support Data Visuals and Collections included:
- Google Data Studio
- Google Sheets
- Google Forms
The participating organizations in the Data Collaborative had three staff members that contributed specific strengths and roles to the overall aim of the Data Collaborative. Although the responsibilities varied for each organization, the role most closely associated with the Data Visuals and Collection cross section is the Data for Learning track. This track was associated with managing and organizing the Data Visuals and Collection tools and resources for their organization. The profile built, which can be found by clicking on the icon to the right, is the best representation of the desired characteristics the Data Collaborative sought to support the Data Visuals and Collection resources.
Core responsibilities to support Data Visuals and Collection included:
- Navigating DataFit
- Data entry of Observation Forms
- Creating customized graphs in Google Sheets or Excel
Learning
Learning
Data Leader
The Capacity Building provided around Data Visuals and Collection varied based on the different supports that were provided. The section below will go through the different Suite of Supports that exist in the Data Collaborative and will attempt to best direct you where to find additional context on Data Visuals and Collection.
Trainings
Trainings
There are a few different types of training, provided above, that support Data Visuals and Collection bodies of work. The naming convention of relevant trainings include:
- Observation Fidelity: These trainings focused on building the quality of data collection for teacher observations.
- Google Sheets: These trainings focused on developing participants’ capacity to use Google Sheets and Data Studio to manage and create data sets and visuals.
- Data Ladder of Inference: These training sessions focused on looking at data and the steps needed to ensure we are gaining our best insights from the data.
Coaching
Coaching
The Data Collaborative coaching agenda allowed for sessions to be dynamic while not missing critical focus areas. To ensure data analysis and collection was included, there was a dedicated section.
Step 2: Data was a permanent step on the monthly coaching sessions focused on reviewing data the partners had collected between the two sessions, as well as reviewing observations video to ensure and correct for the fidelity quality.
Technical Assistance
The Data Collaborative Team attempted to consolidate frequently asked questions that related to Data Visuals and Collection on the Partner Portal site. The areas where useful information may be found include:
- Google Forms
- DataFit
- Homebase
- Google Sheets
- Data Studio
Tools
The Tools and Resources created in the Data Collaborative were mostly opportunities to bridge the gap organizations’ need to depend on, understand and use data to improve student language and literacy outcomes. The tools that were specifically designed to substitute organizational capacity include:
- DataFit: An interactive data-dashboard that consolidated an organization's student outcomes and teacher practice observations.
- Observation Forms: A Google Form used to capture fidelity measurement of teacher practices in the classroom.
- Homebase: A backend data management Google Sheets workbook that hosted all of the organization's raw data.
- Student Outcome Report: A report generated in Data Studio that aggregated the results of an organization at the end of its program.
The operations required to generate the supports necessary for Data Visuals and Operations may be found in this section of the site. Based on your interest and curiosities you should be able to find the relevant information for the tools mentioned above in Capacity Building and what was required for the implementation of those resources.
Page updated
Report abuse