Monday, June 6, 2011

Obtaining and Ensuring Good, Quality Data

Chapters 3 and 4 of Bernhardt’s book focus on the data being collected and the quality of the data being collected in the systems introduced in Chapter 2.

In chapter 3, Bernhardt talks about the specific types of data and focuses on demographic data, as well as the processes which occur within the school, and the perceptions of students, parents, staff, and others with regards to the learning environment. She then goes into a discussion of Input / Process / Output (IPO) and notes that there is a finite number of each of these elements within a learning organization (Bernhardt, 2008; p. 33). In order to understand the relationships between each of these three elements, data from all three groups must be gathered and analyzed. Bernhardt then launches into a discussion of the different types of analyses which can be done: Classroom Analyses, School Analyses, School District Analyses, and State / Federal Analyses.

Chapter 4 focuses on improving the quality of the data being entered into the systems. Bill Gates' quote in the beginning of this chapter sums up the use of data systems succinctly: The first rule of any technology used in business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency” (Bernhardt, 2008; p. 43). So while often times the focus is on automation, the more important focus is on internal organizational processes to collect and enter data into a system. Bernhardt then focuses on the common ways in which data quality can be compromised – often we think of data being compromised by input errors, but data can also be compromised by flawed processes. Bernhardt suggests that ensuring data quality can be done in a number of ways – by setting clear data definitions, but implementing proper procedures for data entry, and by assigning a data manager who “owns” the data and has responsibility to ensure that the data is “clean” (Bernardt, 2008; p. 46).

There is a tried and true phrase used in computer circles - “Garbage in / Garbage Out”. Effectively, this is what Bernhardt speaks about in Chapter 4 rang especially true for me as a project manager. The most difficult part of new system implementation was meeting with users and understanding the processes in place and trying to determine if any of the processes could be automated and/or improved. Breaking the system down into smaller pieces and assigning a “data czar” in each area was an important part of the process. Internal procedures are part of the process and automated systems can help by enforcing the defined rules. For example, if it is important to enter “M” or “F” for male or female, an automated system can either check input or provide a drop down box of options to enforce consistent data entry. There are many more examples similar to this one. Bernhardt's last piece of advice in this chapter is appropriate: “The data tools you use and data analyses you generate can only be as good as the data in them.” (Bernhardt, 2008; p. 55)

Bernhardt, V.L. (2008). Translating data into information to improve teaching and learning. Larchmont, NY: Eye On Education, Inc.

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