Data Collection is Continuing

With Spring right around the corner our teachers are harnessing the extra daylight to keep pushing forward on their action research.  They are still modifying their data collection methods based on what they are learning in Jeffrey Glanz's "Action Research," a highly useful resource to any educator partaking in action research.

Pre-K Hallway-Ms. Kelly Bryant
This week, I've been working on refining the types of data that I will be collecting during my action research plan. Specifically, I have been working on defining the independent variable, Conscious Discipline, by specifying the elements of the intervention that I will be implementing. 

The independent variable will be the Conscious Discipline intervention, which includes elements of the program regarding student interactions and conflict resolution. The aspect of Conscious Discipline that will be implemented will be derived from the Assertiveness section of the program. Specifically from this section, I will be searching for:

1. Assertive Voices: tells the other child what to do instead of negative behavior, uses clear and direct speech, and uses a tone that says, "Just do it."
2. Proactive and Practiced Words and Phrases: "I don't like when you          , please   actvitity instead," "I'm sorry, I will    activitiy instead,"
3. Presence of Physical Response: Looking for whether the child was able to use words or react using hitting or physical altercation and whether or not the problem was able to be worked through.
4. Independent Action: were the children involved able to independently use problem solving skills to resolve a conflict or was teacher intervention required.
5. Special Needs vs. Non-Special Needs: were the students involved considered special needs students or not and was there a significant difference in data.

I hope to further refine these areas of my action research plan and will begin to work on planning how to organize and collect my raw data within the next few weeks.


1st Grade Hallway-Ms. Aprell Adams

Here comes the fun part! I am now at the stage of my research project where I begin to collect data. I am in the process of organizing my data sources in order to be able to clearly visualize my results. Having a variety of sources to collect data is beneficial when attempting to gather accurate data that will support my research questions. As I reflect on my research questions it seemed most useful to conduct observations, give surveys and norm-referenced tests to gather data for my action research project. Neither of these resources is powerful enough to stand alone, so by combining them I am confident I will collect a sufficient amount of data. Glanz states that observations are limited and should be rarely used as the sole means of collecting data. I am conscious of the biases that may exist with conducting observations and will consider my personal biases as I analyze the results. As I develop my survey questions Glanz suggests that the questions are related to the major purpose of the research project. I am fine tuning my questions to ensure they are both age appropriate and relevant to my topic. Having norm-referenced tests are valuable, but Glanz suggests that they are sometimes overused when trying to arrive at a decision about student achievement. Although test are easy to use and can give immediate data, I am aware that they are only a piece of the overall puzzle of the progress and growth of the students involved in the project. I am excited to combine all of my results from each data source and display and summarize my conclusions.

 3rd Grade Hallway-Ms. Stacey Seiler
his week the data analysis portion of our research got me thinking about how to code the responses to my questionnaire. The questionnaire that I created deals with student attitudes toward math class, and their own perceptions of the strength of their skills. At first I thought of this as qualitative data because I wasn’t understanding how I could turn opinions and feelings into numbers.
The Glanz text (p.141-143) helped me out greatly with how to code my survey data and turn it into a statistical analysis. The survey had three possible responses (strongly agree, agree, disagree). The most favorable response will be coded with a score of 3 points, the next favorable response will be awarded 2 points, and the least favorable response will be awarded a 1. There are 9 response items, therefore the most favorable score would be a 27 and the least favorable score would be a 9. From there I can analyze this data using descriptive statistics including percentage, mean, and standard deviation. I decided to use all three of these statistics because each of them make it a bit easier for the reader to interpret the findings. The mean shows the typical answer choice (in points). Unlike the mean, the standard deviation will show how much the choices differ per question. Lastly, the percentage will show the number of respondents who chose a particular answer choice.
Coding the survey was easier than I thought! It actually got me thinking about the connection to customer satisfaction surveys, and how that data is calculated. Though the data analysis portion seems complicated, I am finding that as we move piece by piece it is becoming clearer! 



4th Grade Hallway-Mrs. Jaime Lambrinos

Ms. Lambrinos is out of the office and will respond with her update as soon as she returns :)  

5th Grade Hallway-Mrs. Rebecca Young
After taking a few days to read through Glanz's "Action Research" I feel ready to actually create my first Likert scale and observation checklist. I am looking forward to using Survey Monkey to create my survey about attitudes towards healthy foods.  I have never used Survey Monkey before, but I have heard it is user friendly.