Encouragement is a big deal

The big deal with encouragement. 

This first quote stood out to me because I felt there was no other options in terms of assessments.  Yes we primarily “hunt for mistakes” when grading.  “When teachers see an upward of 100 students per day and are expected to assess the progress of each of them and then differentiate instruction… it is no wonder that standardized diagnostics become necessary” (page 67).  Doesn’t that happen with everything?  I felt my hands tied after reading this.  Yes, I do believe there must be an emphasis on “grading” and knowing what students can and can’t do (with the emphasis on can’t) because it helps a student learn from their mistakes and then learn to correct that mistake. 

I feel it is the nature of learning any new skill academic or interest-based.  Also, highlighting the strengths is just as necessary, but also depends on how and what is being measured.  A homework assignment is going to measure what the student knows, so it seems ordinary to know where their thinking needs improvement, just like any sport of student interest.  Sure, academic work looks different from extracurricular activities.  What if academic work was focused on positive outcomes and extracurricular activities would focus on the “needs improvement” skills.  Seems like there is not much a difference on how good measurement is achieved.   I think encouragement can help in any situation and is the key for succeeding in anything.

 

I think Maggie and Colby Steinburg would agree with the quote above.  They both found Lorena slipping away from academics and tried to find something positive to build skills.  This encourages her to become team player and to focus her energy on something attainable (college).  The connection from extracurricular activities and academics help become a “bridge” to success and skill building.  Their support is necessary for their success. 

From locating themes to analyzing them

Two weeks ago, you started developing codes for your data.  You probably started to see themes and patterns across the different kinds of data that you have.  These can be emergent (coming from your data) or a priori (emanating from your questions). 

List three themes that you see in your data, and choose one theme to describe and analyze.

Description answers the question "what is going on here?"

Analysis offers some possibilities as to how and why the pattern may be occurring.  

Both are based in data.  You can use direct quotes from interviews/surveys as data exemplars, but you never let data just hang there without analysis.  Here's an example:

Theme from my social justice teacher data: Professional Safety

Description: 

After being chastised by his principal for bringing in texts that addressed gender and sexuality, Daniel said:

“I toned down [the theory] and took out anything related to LGBT issues…I just feel like we are just being very superficial.  And so I wasn't into it as much.” 

 

Analysis:

For Daniel, teaching for social justice was an important part of his teaching identity.  However, he also knew that the school and community culture did not welcome discussion of these issues.  As a result, he "toned down" his pedagogy, which in turn made him less interested in teaching.  In order to feel professionally safe, he felt compromised in his teaching and his commitment to social justice.

Unlearning

One of the terms we use in teacher education is "unlearning."  What we mean by that is creating space for teacher candidates to unlearn what they thought they knew about teaching based on their experiences as students, or through what they thought teaching actually is.  In other words, to question what they think is true about students, the profession, and teachers.

 For example, when I started teaching at Aurora Alternative High School, I was appalled that some of my students would want to attend the local community college (never mind not go to college at all), as opposed to a state college.  I had to unlearn my assumptions that everybody who was going to be anybody in life was either a) a natural genius and didn't need to go to college or b) would go to a four year college.

What my students taught me--what I "unlearned"--is that "smart" looks different according to context.  I unlearned seeing my pregnant students as victims.  I unlearned that all graffiti was trashy.  I unlearned that smart meant being good at school.

Teacher research is all about unlearning: about questioning our assumptions and taking risks.  It is NOT about proving a particular hypothesis.  So what assumptions have you questioned about your students, teaching, or yourself during this process?  What new truths have you uncovered?  

Research Memo Option

Researcher choice this week.  Choose one of the following to guide your blog:

1. Write a memo on what you are discovering from your readings.  How does this literature inform what you have discovered so far in your own research?  What are some gaps in the research that your work may fill?

2. Write a research memo similar to two weeks ago, in which you synthesize this week's data in order to make meaning.  What new discoveries and questions have arisen?  What might you have to change (i.e., research questions, data collection practices) as a result?

Finding research on your topic

This week, we will be meeting in the library at the reference desk.  You will be looking for work that others have already done in your area of interest.  This will hopefully inform your practice and research, and maybe even give you new ideas on what to look for or questions to ask.  What is it that you already know about writing a literature review?

Now that you've been writing fieldnotes, and perhaps collecting other data, for a number of weeks now, what are some terms and phrases you might look for?  What is it that you want to see from other teachers and researchers to support you in exploring your questions?

Research Memo

Last week in class, we talked about the differences between fieldnotes and memos.  Fieldnotes consists of "raw" data, and are mostly descriptive.  Research memos, in contrast, are analytical and interpretive; i.e, they are an attempt to make sense of what you are seeing across your raw data.  Notice that I said "an attempt" here.  Leave yourself open to intuition and gut feelings here in these early stages of memo writing.

For this week's memo, look over your last week(s) of data collection.  What are some recurring themes and patterns as you review your fieldnotes and other data?  What new questions/surprises have arisen?  Write up a research memo that addresses these issues.

Acknowledging the Mess

"Hauling apart rhetoric and reframing and developing new ways forward is likely to be a variable, unstable, and messy process" (Cook, p. 281).

How comfortable are you with mess?  What might get messy in your research?  How will you handle this?