Are you a teacher who is Data Literate?

The question highlights the skills needed in developing data literacy as a teacher. Let us skills audit our data literacy to know where we are.

‘Data Literacy’ has become the buzzword and highlights all areas of teaching and learning.

Let’s do skills audit of data literacy to know where one stands as a data literate. The rubric provided is a self assessment tool to measure how data-wise a teacher is. A point to reinforce is that being a beginner, in reading data, means there are milestones to achieve and being an expert, in reading data, means the journey requires continuous updating and catching up.

The self explanatory rubric would provide the level of understanding in reading data. No matter at what level one is, reading data is a continuous and excruciating process as every question one poses could lead to more questions. The Answers derived from the data are milestones to achieve and adds more data to be analyzed further in the self pursuing journey of extracting information from numbers.

‘Data Literacy’ needs to have skills of locating data at various points of learning. For example, data could be located from the classroom by means of assessment (formative & summative), observations (formal & informal) and from projects, essays, and book scrutinies. Information could be derived from data base of past files & records. Collecting and analyzing data from those records and files could save time and provide valuable information about learners even before meeting them. It provides insight into the past learning journey and answers the question about the status of a learner. A lot of data could be accessed through tests that could help in grouping, planning intervention and forming support group.

Understanding of data is a skill that needs focus on reading all types of charts and graphs to compare, contrast and to use data in compiling and collating required information. Now many of the standardized tests provide detailed and individualized reports that contain various charts and graphs. A teacher should not only be able to read but should also be able to communicate their understanding through it.

Interpretation of data requires measuring right data from the whole database of numbers, charts and graphs. Planning application of steps to tackle an issue is an important skill in interpretation of data. Reading data and not to do anything about it, is a waste of derived information. To be able to detect gaps and solutions by posing right questions and filtering right data is the ultimate end of interpretation of data. All this will be more effective, if one could organize the available information into a presentable model or layout that would assist in not only planning but also in communicating to various educational bodies.

Using data, to make modifications to teaching,

requires a teacher to justify and take decisions based on the information derived from data. For example, planning an intervention for a number of pupils, a teacher has to provide evidence based on compiled data. Moreover, adapting or modifying curriculum based on the information available through data is another example of an evidence based academic practice.

Asking right questions is the first step in contact with data. Only when right questions are posed, one could find correct information from the data. For example, looking at data (final grade scores) if a teacher asks a question like: Who is scoring better among boys or girls, in a class, would lead to an information that would assist a teacher in the future planning.