Presenting my data has been a constant struggle during my research. Do I want this to be understood by 2nd grade students? Or just teachers? Will I create a full presentation on it or just do a simple write up?
The main components will include:
4 Comments
Though I feel like my research has been ethical, it would have been nice to have done this week's blog at the beginning of the course just so that I would go through my research with an ethical perspective. I feel like now I have had to go back and double check that everything was truly ethical instead of just doing it from the start. Educational action research is a new concept to me so I appreciate being able to do these things in sequential order instead of backtracking. However, I feel like there are no areas of concern and I kept my research informed, private, and unbiased.
What primary concerns exist in ethics, validity and reliability in AR? How are you managing these concerns (or how will you) within your study?
I first looked at what are the ethics in research and found the following main ideas:
Though this number is low, there is still a variety of misconduct out there due to,”Institutional pressures, incentives, and constraints encourage people to commit misconduct, such as pressures to publish or obtain grants or contracts, career ambitions, the pursuit of profit or fame, poor supervision of students and trainees, and poor oversight of researchers (Resnik, 2016).” The ways that I am maintaining ethical research is through upholding informed consent and ensuring respect for potential and enrolled subjects (NIH, 2016). In my classroom among students and parents I strive to keep informed consent and respect for subjects at the forefront of my study. Since I am publicizing student work and achievements, it’s important that I have consent from each participant and their parent (CIRT). Sources: CIRT. Ethical Considerations. Retrieved from https://cirt.gcu.edu/research/developmentresources/tutorials/ethics NIH. 2016. Guiding Principles for Ethical Research. Retrieved from https://www.nih.gov/health-information/nih-clinical-research-trials-you/guiding-principles-ethical-research Resnik, D. 2016. What is Ethics in Research and Why is it Important? Retrieved from https://www.niehs.nih.gov/research/resources/bioethics/whatis/index.cfm After looking at other's blogs and their idea for sifting through data I gained a lot of new ideas. For one, I will put some into pie charts. At first I was going to do bar graphs and charts, but I feel like this doesn't represent the data as well, so instead I will focus on pie charts.
Since a lot of my data is observational and not statistical, I think I will come across some bumps in the road as I start to compile all the data. More importantly, I need to keep focused on the goal of my data collection and not get lost in it. Even before diving into it I forget what my guiding question is and start to lose sight of my end goal--- "Does Seesaw motivate student work and learning?" My data collection is fairly simple and explicit. I do not have to do much number crunching or statistical analysis. My data will show me patterns and trends.
For this question I went directly to Seesaw itself to see what can work and is useful for this program. It’s best collection of data is in qualitative forms. Students ability to keep a digital portfolio means they can do their own observations and teachers can keep a ongoing record of progress (McGrath, 2017). For this part of Seesaw I have wrote down observational notes of who shows an interest in using Seesaw and who doesn’t. For those who do not like it, I have kept track of reasons they don’t want to upload anything to Seesaw. This serves as a form of quantitative data. I can look at the number and ratio of students successfully using Seesaw. My data will also show which parents are actively involved with Seesaw. Parent involvement is a great feature of Seesaw because it lets parents who may not have the time or ability to see inside the classroom more than ever before (Teachers Talking Tech, 2017). Constine, J. 2016. How Seesaw accidentally became a teacher’s pet at 1/4 of US schools. Retrieved from https://techcrunch.com/2016/06/25/seesaw-education/ McGrath, C. 2017. Appsolutely! Using Seesaw for student portfolios and much more. Retrieved from http://learningandteaching-navitas.com/appsolutely-using-seesaw-student-portfolios-much/ Teachers Talking Tech. 2017. Seesaw. Podcast Week 8 Reflection Initially I thought that data mining would only be effective with a large pool of data-- there is no way my data this year will amount to that! Mariah also pointed out that factor, but after reading comments on her blog I realized that a small sample isn’t necessarily impossible. I also appreciated Virgil’s comment to also keep student behavior and attitudes in mind when collecting data because this dictates many factors. This will be especially helpful for my research as a lot of the data I am collecting isn’t tangible or numerical.
Josie gave great ideas for conducting surveys and made me think twice about the survey that I will give my students in the near future. I recently gave my parents a paper survey and it was challenging getting them to respond. I think I will look to survey monkey with my next parent survey to get more meaningful results. Data mining is the process used to explore and analyze large amounts of data. The researcher looks for patterns, relationships, and findings within the data. This can then be a predictor for future knowledge and inquiry. As stated in Statsoft, data mining "can guide decisions in conditions of limited certainty."
Data mining can occur in different forms. A few are:
My study will benefit from data mining because I will be able to use it as a predictor for future use. It will help me see patterns in the use of Seesaw. Was it effective? If so, with what demographics? If not, what pattern was consistent that may show the failures? I hope that data mining will do more than just show patterns, but will offer reasons for the why parts of the study happened the way they did. I hope to find answers within the data that can improve the experience for students next time it is used. Berson, A., Smith, S., and Thearling, K. An Overview of Data Mining Techniques. Retrieved from http://www.thearling.com/text/dmtechniques/dmtechniques.htm StatSoft. 2017. What is Data Mining? (Predictive Analytics, Big Data). Retrieved from http://www.statsoft.com/Textbook/Data-Mining-Techniques |
Author2nd Grade teacher at Keet Gooshi Heen in Sitka, Alaska Archives
December 2017
Categories |