Merging Large-Scale Assessment Data for Secondary Analysis: Experiences with EQAO’s Data


  •  Gul Shahzad Sarwar    
  •  Carlos Zerpa    
  •  Christina van Barneveld    
  •  Marielle Simon    
  •  Karieann Brinson    

Abstract

This paper is a narrative of our experience in analyzing and merging data files provided to us by the Education Quality and Accountability Office (EQAO). In the paper, we propose a scheme of merging data files by means of Structured Query Language (SQL, pronounced as “sequel”). Although, the narrative of our experiences using this merging scheme could have been extended to any number of data files, the aim of this work was to merge only three EQAO data files. Via this merge process, we were able to gain meaningful information and facilitate the analysis of EQAO data to answer our research questions. By using SQL queries, our approach was not only to analyze the available data files but also to construct a narrative about viewing and handling data contained in the files.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1927-5250
  • ISSN(Online): 1927-5269
  • Started: 2012
  • Frequency: bimonthly

Journal Metrics

h-index (March 2021): 37

i10-index (March 2021): 171

h5-index (2015-2019): 23

h5-median (2015-2019): 33

Learn more

Contact