Data Organization

All of the data has been gathered, and it's about time to start analyzing it. So, I've organized the data to get it ready for the analysis. Since my research involves a quantitative part and a qualitative part, there are two sets of data to organize. 

Quantitative: 

• The quantitative data was collected using a Google form. The responses were directed to a spreadsheet. 
• After all survey data had been collected, I changed all the Likert responses to a number (strongly agree = 5, strongly disagree = 1) and copied the responses into a Microsoft Excel spreadsheet. 
• I then set up formulas in the Excel spreadsheet to find the mean, median and mode for each question response. I've also labeled each question that needs to be converted because a negative response rather than a  positive one relates to alignment with the "desired" belief or practice. 
• The next step will be to create bar charts for each question to show the distribution of responses. 
• The question are also grouped into sections dealing with (a) technology beliefs, (b) perceptions of learner-centered instruction, (c) current practices regarding learner-centered instruction, and (d) barriers to creating technology-enhanced learner-centered classrooms. So, I will plan to calculate a mean for each person for each section as well. This will serve as an overall snapshot of that individual's beliefs and practices.

Qualitative: 

• The qualitative data was collected through interviews with each of the 11 science teachers. The interview data was recorded using the Easy Voice Recorder app on a Nexus 10 tablet. Notes were also taken on a printed form that included all the interview questions. Each recording was named "teachername interview". 
• The recordings were imported into an online transcription tool called Transcribe and transcribed by me. This took anywhere from 2 to around 6 hours per interview. Each transcription was named "teachername interview transcript".
• I then made a copy of each transcript so that I would always have a "clean" copy of the data. I read through each interview transcript copy (titled "teachername interview coded" and looked for various themes that I thought would be important in the analysis. I created another file called "Codes for Interviews" and listed each of the themes I've identified so far. I expect to modify this as I read back through the interviews a couple more times. Each theme has been assigned either a particular color of highlighting or a particular color of font. As a theme is identified in a transcript the highlighting or font color is changed to match the colors in the "Codes for Interviews" document. Here is an excerpt from this document:

Aware of problem with too much lecturing

Teacher as facilitator, guide

Teacher as motivator – make it interesting

Lack of maturity on part of students. Including cheating or misuse of technology.

• I then created documents for each of the sections discussed under the quantitative part including (a) technology beliefs, (b) perceptions of learner-centered instruction, (c) current practices regarding learner-centered instruction, and (d) barriers to creating technology-enhanced learner-centered classrooms. 
• The next step will be to cut and paste (with initials of teacher) the "coded" bits of the interview transcripts into these documents. This way I'll have a document for each teacher as well as documents for each of the areas of interest.

All of the files mentioned above will be stored in my Dropbox and also backed up to a flash drive.