So here is my little ugly duckling of a dissertation proposal, with data collection planned for this Fall. Wish me luck! Of course my hope is that it grows into a swan that helps push the field forward on theoretical, methodological, and practical levels, but, to be perfectly honest, I'll be glad even if it grows into a little larger ugly duck.
Tentative Title: The Influence of Peer Review on Writing Achievement and Individual Writing Self-Efficacy
Draft Abstract: This study will examine the influence of peer feedback and review on individual writing achievement and self-efficacy. Undergraduate first-year composition students will engage in normal instructional activities, using the Eli Review program in order to conduct peer feedback and review sessions. Using the data collected from surveys and through the web-based peer review system Eli Review, the influence of giving and receiving writing feedback in peer review groups on both individual writing achievement and individual self-efficacy will be modeled using a multilevel, social-network analysis methodology. The influence of other possible mediating variables also will be explored, including: the influence of the instructor; the influence of outside help such as roommates, family members, or use of the university writing center, and the individual’s prior achievement. This study will contribute to understanding the influence of peers in the writing peer feedback cycle as well as the ways in which writing achievement and self-efficacy are influenced.
Right now I am enrolled in CEP 956: Mind, Social Media, and Society taught by Dr. Christine Greenhow. We have assigned readings each week that we are to post a response to in our ANGEL discussion boards. This week being our 2nd week, I thought I might spice it up a bit and live-tweet my assigned reading using the hashtag #MSUepetReads. We are required to tweet twice per day for class using #MSUepet, so I thought this would be a fun way to differentiate the two practices. Plus, I didn’t know if my meta-cognitive tweeting might expose my cognition as lacking, so I didn’t want to poison #MSUepet with my humble ramblings.
Edutopia in collaboration with Facebook (2012, May). How to Create Social Media Guidelines for your School. http://on.fb.me/Jbs0eJ
Internet Safety Technical Task Force. (2009). Enhancing Child Safety and Online Technologies. Berkman Center for Internet & Society, Harvard University, Cambridge, MA http://cyber.law.harvard.edu/pubrelease/isttf/
Read the Executive summary and other sections you in which you are interested.
Overall, the readings were intriguing. I was familiar with both the Berkman Center’s report and the National Educational Technology Plan (which I’ve read nearly a dozen times now). I have to say that our governmental, business, and non-profits are truly exploring the implications of new media/technology in terms of what it means for learning, for teaching, and even for safety. What I noticed lacking was an attention to privacy concerns. After all, privacy is one of those rights enshrined in the constitution, as James P. Steyer noted in his NPR Fresh Air interview for his book Talking Back to Facebook. He noted that the folks over at CommonSense Media advocate for an “eraser” button for. He mentioned that kid-specific browsers have been found to have more cookies than more mainstream browsers intended for adults. The fact that we are trading our privacy for these fun, free, and even educational tools is a very real concern that I did not see adequately addressed in these documents.
In my live-tweetings of my readings (and how glad am I that my classmates joined into the live-tweeting fun!), I ended up with some interesting conversations around these documents (and my concern about the lack of attention to privacy issues). Here’s the Storify of this week’s #MSUepetReads:
Recently for my Introduction to Qualitative Methods course, I was asked to identify my own epistemological leanings, specifically in the context of how I design research studies. I thought it would be useful to post those musings here and check back in a bit to see if they still hold. As always, comments and criticisms are welcome:
The root of the word “science” is to “know.” My epistemological leanings, my understandings of how I “know,” are heavily influenced by my undergraduate training in the biological sciences. The scientist is trained not only in designing and executing experiments, but also in observing the natural world. Charles Darwin, a notable scientist surely, grounded his theory of evolution in what is technically a case study of the Galapagos Islands’ avian residents. Science and research need not be limited to one methodology, for there is much that we do not understand, and it would be foolish to think that one method alone was the sure path to knowledge. I situate myself in a place that is driven by questions and methods that are strongly grounded in theoretical frameworks. If there is an observable phenomenon that I have questions about, I consider those questions through the lens of a theoretical frame. I first consider what specific theories might predict about the phenomenon. Nonetheless, predicting outcomes is not the only way to do science or to have knowledge. I consider myself post-positivist in this sense. I habitually think in terms of theories making predictions, yet I recognize that not every human action is predictable. Learning and the study of education are complex and messy, and not every situation will fit in the theory-prediction box. As Erickson (1986) notes about school classrooms, “Interpretive researchers presume that microcultures will differ from one classroom to the next, no matter what degree of similarity in general demographic features obtains between the two rooms, which may be located literally next door or across the hall from one another (p. 128).” No matter how large the sample size or how robust the theory is, there will always remain a percentage of outcomes that remain unexplained. This ambiguity is where I find the entire “wild profusion (Lather, 2006)” so important. I earnestly reject the quantitative/qualitative divide while recognizing that my own personal research brain tends to work best in a more quantitative environment. That being said, I joke that I am a positivist with critical theorist (and even post-structuralist) leanings. I may feel most at home with a giant data set and a regression, but that does not mean that I don’t reject the dominant culture’s blind acceptance of the validity of these methods. As a former K12 classroom teacher, I have the lived experience of the ways in which statistics and data are used as a hegemonic tool, one that often was used even to disempower teachers and students. As Lather (2006) stated, “Profoundly interventionist in the history of the welfare state, statistics has served as a political tool in the theatre of persuasion in a way that maps onto the recognized needs of policymakers (p. 49).” I began teaching the year No Child Left Behind was enacted: I can’t think of a better example of political theater in which statistics played such a menacing part. Social science has no option of conducting research in a vacuum, and as a social scientist, I feel it is my responsibility to not only advance the field, but do it in a way that is ethical. My definition of ethical responsibility includes a responsibility to identify the ways in which my own privileges (as a middle-class person, as a white person, as an educated person, as a quantitative researcher, etc) inform my research.
Erickson, F. (1986). Qualitative research in education. In Merlin C. Wittrock (Ed.), Handbook of research in teaching (3rd ed., pp. 119-161). Washington, DC: American Educational Research Association.
Lather, P. (2006). Paradigm proliferation as a good thing to think with: teaching research in education as a wild profusion. International Journal of Qualitative Studies in Education, 19, 35-57. doi: 10.1080/09518390500450144