Job Posting: Research Officer, Peel District School Board

A posting is now open until July 18, 2018 for a Research Officer position at the Peel District School Board.  The position begins September 4, 2018.  This application is posted on applytoeducation.com (link at bottom of this pdf with more information) so to apply you will need to create an account first.

Click here for more information (link to apply at the bottom of the pdf)

The Peel District School Board (PDSB) is one of the largest school boards in Canada, with more than 150,000 students in over 250 schools. At PDSB, everything we do is designed to help all students achieve to the best of their ability. We have the incredible opportunity to inspire a smile in each student. Our collective, daily efforts make a positive difference in the lives of our students, their families and the world. Guided by our mission, vision and values, we build positive places for learning and working … together at http://www.peelschools.org We are currently accepting applications for a Research Officer.

Are you an experienced professional highly skilled in qualitative and quantitative research? Do you welcome the opportunity to draw on this expertise to support services and programs across the Peel District School Board? If so, take the next step in your successful career by joining our team.

Job Duties/Responsibilities and Details
Reporting to the Chief Research Officer, Research and Accountability, you will work both independently and as part of a team of education researchers in the design, implementation and interpretation of research and evaluation projects to support the board’s system-wide strategic goals, equity and diversity initiatives, and curriculum and instruction programs.

Being a Research Officer at the Peel District School Board means acting as a research and evaluation resource to support the use of data for planning and decision-making. This will include being responsible for consultation and development of assessments (curriculum, alternative programs, special education) as well as the evaluation of educational programs (equity, diversity, instruction, special education). The research
team and Board staff will also rely on your assessment of current educational trends, and on the literature reviews and environmental scans you can provide on topics of interest as they carry out their functions.

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School Board Researcher Network and Sharing Session

Over the past couple of years the Data User Group and Barrie Region MISA PNC have hosted a “Researcher Coffee Break” where school board employees with research, evaluation and data related roles can connect on a teleconference to discuss current issues, challenges or new approaches to common data sets.

Given the popularity of these periodic teleconferences, the Data User Group is collaborating with the Association of Educational Researchers of Ontario for a day of networking and sharing:feb-24-dug-aero-open-space-v2-image

Click here for the flyer which includes a link to the online registration.

 

 

 

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Community Data Models: A Look at their Development and Uses

In collaboration with the Barrie, Toronto and London MISA (Managing Information for Student Achievement) PNCs (Professional Network Centre) a Special Interest Group has been scheduled for:

  • Date: April 28th, 2015
  • Time: 1:00-3:30
  • Location: Toronto District School Board

This session will explore two existing community data models, the Social Risk Index (SRI) and the Learning Opportunities Index (LOI).  Topics of the session will include:

  • construction of the different models
  • examples of how the models are used in the context of a school board
  • comparison of the similarities and differences between the models.

The afternoon will wrap up with a general discussion of the Environics data that has been collaboratively purchased by the Barrie, London and Toronto PNCs.

Please click here to register for the event.  Additional details regarding the location is included at the end of the registration.

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New Resources: Qualitative Analysis in R

New to the R Resources page is the “Qualitative Analysis in R” pdf.   This resource, prepared by Greg Rousell, is an overview of getting started with qualitative data analysis in R using the RQDA package.  It walks the reader through Data Cleaning, Text Mining, Manual Thematic Coding, Auto-Coding Text, and Creating (exporting) a coded file and includes both screen shots and sample scripts for ease of reference.

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Community Data – Vulnerability indices and technical considerations

AERO has announced an upcoming Special Interest Group session “Working with Community Data Sets”.  
This free event will be of interest to those who want to learn more about the approaches and development of vulnerability indices and the practical, technical and utilization issues associated with this work.  The afternoon will feature:

  • three socio demographic models that are used by education researchers in Ontario;
  • discussion of issues related to the 2011 census;
  • presentation of R and QGIS tips and tricks when working with socio demographic data. 

If you are interested in attending or would like more information, send us a quick note and the registration information will be forwarded to you.

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R Summer Institute – Registration Open

Click here for a pdf of the flyer.

R Summer Institute Flyer3

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SAVE THE DATE! – SummR Series – June 23 and 24

The Toronto and Barrie Region MISA PNCs are sponsoring a two day R workshop on June 23 and 24.  A location in Toronto is in the process of being reserved for this event.

This two day workshop is an extension of the “Introduction to R – Towards Reproducible Research” workshops held earlier this school year. Along with an introductory session for those who are new to R (or requiring a refresher), we will also be exploring analysis of common data sets (EQAO, EDI, community level data) and data visualization techniques in R.  With two days to explore R, more time will be available to learn R in the context of your own data set.

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QGIS – Quick Start Tips

Here are a few quick references for getting started with QGIS.  All steps included are based on a 2.2.0 Valmiera installation of QGIS

Tips:

  • Install the “Table Manager” plugin to modify the attributes table (i.e. field names etc.)
  • Use the Field Calculator to create new fields and transform values from string to text.  this is useful when you only have to change 1 or 2 fields
  • Use a .csvt file to define the data types for each field in a large CSV file.  The .csvt file should only contain 1 row with “String” and “Integer” values used to represent each column in your .csv file.  The .csvt file should be in the same directory as your csv and will be used by QGIS when you join the data to a shape layer.

Managing Projections

Sometimes when you load a shape file the layers won’t line up.  When this occurs either the projection hasn’t been set or it is using a different coordinate system.  Making sure that the projections used for each layer and the project is important and often resolves this:

Checking the projection used for the project: In the lower right corner of the QGIS desktop there is a box labelled “Render”.  Immediately to the right of that there is a small spherical icon – click on this icon

  • In the “Coordinate reference systems of the world”:
    • Scroll down to “projections”
    • Select “NAD 83/UTM zone 17N”

Checking the projection used in each layer:

  • Right click on the layer
  • Click on “Set layer CRS”
  • Select the Projection of interest (in the case of southern Ontario, NAD 83 zone 17 is what I tend to use)
    • Repeat these three steps for each layer that is included in the project

Building a query (selecting by attributes)

Queries in QGIS use the same syntax as SQL:

    • Click on “Layer” in the top menu bar
      • Select “Query” (or CTRL F)
      • Create your query either by typing it directly into the “Provider specific filter expression” or by double clicking on the elements.  Queries usually take the form of “Field”  “Operator” “Value”.  For example  ID > 0

Joining Data (csv) to a shape file

    • Open your shape file (Layer>Add Vector)
    • Open your data file (Layer>Add Vector)
    • Open attribute of your shape file (right click on shape file> Open Attributes)
      • Confirm name of the primary key
      • Close attribute table
    • Open the properties of your shape file (right click on shape file> Properties)
      • Click on “Joins” tab
      • Click + button to add a join
      • Select the .csv file that is to be joined with the shape file
      • Confirm the Join field and Target fields are correct
      • Click on OK or Apply
      • Right click on the shape file and “Save As”

Spatial Joins

    • Open the polygon and point files
    • Click on “Vector” > “Data Management Tools” > “Join Attributes By Location”
      • The “Target Vector” is the shape file that you want the new data attached to (in this case a polygon file)
      • The “Join Layer” is the shape file with the attributes you want copied (in this case the points file)
      • Type in a filename and location for the new files that will be created
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R – Special Education Data Cleaning

Three new scripts have been added to the R resource section:

  • SpecEd_36_ISD_Coding.R
  • SpecEd_G9_ISD_Coding.R
  • SpecEd_OSSLT_FTE_ISD_Coding.R

These files have been developed to support the analysis of achievement or context by Special Education categories.

Each of the scripts takes your ISD file and:

  • recodes the Special Education IEP Types into a single column with each IEP Type labeled.
  • recodes the Special Education IEP Type into a single column by the Ministry categories of exceptionalities (http://www.edu.gov.on.ca/eng/general/elemsec/speced/guide/specedpartae.pdf page A18).
  • creates a new file with the two new recoded variables appended to all the ISD variables.
  • creates a new smaller file with fields of interest (this file is useful in constructing cohort data sets).
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Join us at OERS 2014…

If you are attending the 2014 Ontario Education Research Symposium be sure to stop by the Data User Group table that will be set up for the poster session. It will be a great opportunity to network and get feedback on the topics and issues you would like to see supported and promoted through the Data User Group.

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