9.27 Research essays => form and focus

General patterns in presentation for writing studies research essays:  We used Robin Martin's study of relationships between teacher's written comments and student revisions as a model for what kinds of information writing studies researchers put in each section of a research essay.  Our analysis was as follows.

Introduction: identify the focus of the research, identify the research question and develop a discussion of the importance of the research; connect to other researchers + state how the current project is different, give a general description of the project + a general description of the findings

Literature review: discuss research studies that have the same focus, use the similar methods, develop important language or theories, or present findings important to your research study. Be sure to point out how your study brings something new to the findings and methods presented in the methods.

Presentation of your study:  This section (or several sections based on the sub-headings in Martin's study) should present an overview of what you did, your methods (including where you did your study, who your participants were, etc) and a presentation of your data.  If you do a case study or discourse analysis = clearly you will not present ALL your data.  Rather you will present the data relevant to the focus of your study.  If your study is a case study, an ethnographic study, an oral history or a study of literacy narratives or other kinds of data presented in stories = it may look more like a literary essay - and less like the presentation of the charts and data in this essay.  At the same time - the idea that you present "evidence" from the data you collected => and then state what it shows with respect to your research question = is the same.

Discussion of data.  The discussion of the data deepens and develops your exploration of what your data mean.  You may go back to your research question and make a series of points (using the data) to illustrate what your data has found.

Conclusions.  This section draws the discussion of data together by restating the main findings and pulling together and re-stating any generalizations that may come out of those findings.  It also points out any unanswered questions - or ideas for taking your study to the next level.  It might also - as in the Martin study - point out the limitations of your study design or data sets.

Working toward a do-able project with a focused research question.  You spent the rest of class working in small groups to tighten your focus and move in on your research question.  I asked the "listeners" in the group to ask the presenter questions about what they hope to find? where they expect to conduct their study?  what kind of data? what methods?  how they expect to analyze their data and so on. . .  from the wrap up at the end of class, this seemed as if it went fairly well. If you changed your ideas or re-focused your project => update your blog so I can respond to "where you are" with your project.  I will be replying to your blogs beginning Friday.

For next class:
Update Blog 7 (optional)
Blog 8: After you receive my comments to Blog 7 - do some more work on developing your research project.  List references, write to the prompts for 4 & 5 on "developing a research plan" => or develop writing useful for where ever you are in terms of developing your project.

Bring (or email me at the course email) a copy of an essay with teacher comments.  If you bring a print copy feel free to blank out your name.  I will make copies to distribute to the class

In class on Tuesday we will use your commented-on-essays as a data set.  You will work in groups to identify a research question and propose a project where you would study this data set for some purpose related to writing studies.

9.25 more on analysis and creating a research plan

Analysis.  You are making great progress on developing the basic moves and terminology you will use in writing analytic research for writing studies!   Good work.  The first part of today's class was about giving you a particular example of how one student (me) wrote her blog post for Blog 6.  We read the sample analysis (posted to the right) and talked about the strengths and weaknesses of the post.  First we identified what the Blog post required the writer to do, then you analyzed the post for whether and how it met the requests  made by the prompt.  You did a great job on this.  This class pretty much agreed on the author's strengths (presenting a rich, detailed list of names for what was happening in literacy narrative 3, posing some connections between what was going on in the literacy narrative and the categories she developed) and her weaknesses (the organization was difficult to follow until you figured it out, didn't set up the focus at the beginning) - and we discussed how the multiple questions posed at the end were in some ways a strength (gave the researcher lots of things to think about - lots of places to go with her research) and in some ways a weakness (didn't do what the prompt requested).

So good job on this.  You asked if you could go back and re-do your last blog - and of course I said yes.  I will be looking at blogs after Thursday - and have feedback for you before the end of the weekend.  You can re-do your post in one of several ways: re-write & re-post; add to the original; add comments about what you would do differently in a different colored font.  I will give points for the revised version taken together with the original.  Also - I suggested that if there are parts of analysis that you are still not understanding - write questions - and I will give you answers as part of your feedback.

Finding your focus for your research project.  We spent the next part of class doing some listing/freewriting for you to think about big ideas/general directions for your research project. You have your writing from class - and hopefully you will keep adding to it.

We then opened up the worksheet for developing a research plan - and talked a little about how to move from a broad idea (something about how technology is changing the way we write) to something "do-able" in terms of the research project for this course.

We talked through the first three steps - and your blog post for Thursday is to get started with doing some of the writing under these points.

Some things to think about as you narrow down your question:

• the focus has to connect to literacy studies (I can help with this angle - but talk to me early rather than later if you are worried about your connection)
• your paper will be 5-7 pages long (so your question needs a clear, tight focus)
• you will need to connect your data to what other researchers have written about your question (so you will need to be able to find research papers in writing studies relevant to your topic - again - I will help with this)
• you will need to collect observational data on your topic (or else clear with me that it will be a library project)

For next class:

Blog 6 (optional) revise/update in light of today's class discussion

Blog 7: do some writing to the points on the worksheet on developing a research question. You do not need to write to every point.  You do need to do sufficient writing to clearly identify a broad focus for your work.  The more you write into your idea - the more feedback I can give you.  

Read: Rhetoric of Teacher Comments on Student Writing  Robin Martin  This paper was written by a student researcher.  We will use it as an example of one kind of analysis that writing researchers do (it is not perfect - so you may see some things that you think should be done differently); and as a "model" for one way to write a research paper in writing studies.

Additional point:  The world is large enough and complicated enough  - and from a human perspective language flows through everything => so you should be able to choose something that truly interests you.  This is YOUR responsibility.  This project is a genuine opportunity to study something you are curious about.  Go for it.

Great class today - see you on Thursday.

9.20 What makes a joke funny & analyzing literacy narratives

We began by reviewing the features of funny shaggy dog stories that you identified last week (and in your analysis for today) - and then we ranked them.  They came out - in order of importance-  as follows.

1. Punchline
- audeince connection to the punchline in terms of familiarity (what they like) and understanding
- play on words

2. Development
- ridiculous use of terms in the punchline
- image/audience connection to the image + ridiculousness (surprise) of the characterization
- length (the longer the funnier)

3.  level of violence (and who wins = funnier when the "bad" guy/force wins)

When I summed up your preferences/predictions the table looked like this:
1 (the string 242 words) 6/4/-/-
2. (hollandiase 147 words) 1/1/8/2
3. (Ghandi) 64 words 1/3/1/7
4. (lawyer = 238 words) 4/4/3/1

These rankings suggest that length is a good predictor (though not the only factor) and that while violence and punchline seem to be factors - it can be hard to tell who will connect to what, and we don't have enough data to say for sure what makes these jokes funny.  At the same time, the length of the punchline & the number of plays on words in the punchline (the Ghandi joke has the most) doesn't necessarily seem to make a joke funnier = but the dialgog and characterization (associated with length) do seem to be a factor.

Good work on this - and I will be giving you feedback on blogs 4 & 5 as soon as I can - certainly before the end of the weekend.

Methods we have worked with so far:
visual/formal analysis (the puzzle) = useful for studying behaviors in interviews, digital writing - especially digital writing that includes images or that depends on spatial arrangement ot make meanings, learning spaces like classrooms or online sites,

oral history + interviewing (911 interviews + analysis)

textual analysis in terms of analyzing features of language and how language is used (analysis of jokes)

Inductive versus deductive analysis.
So far - we have developed theories (explanations for what is happening in our data) by first naming and classifying what is happening in the data - and then identifying what is happening in the data (looking for patterns) and then forming a "theory" about how to explain what our data show.  This is an inductive approach: start by taking an exhaustive look at the data and building your theory from what you see.

For the analysis of the literacy narratives, we will try a deductive approach : where you ask a particular question and pose a particular answer with respect to the data and then use data to prove or disprove your assumption about what the data shows (see below)

In practice, most researchers move back and forth between inductive (taking an unbiased look at what the data shows and forming a question/hypothesis) and deductive (posing a theory with respect to data and seeing how well it fits) reasoning - but it is useful to know the terms.  Scientific method is usually deductive;  messier problems - like studies of language dynamics and human patterns for language use - are often inductive.

Literacy narratives.  We spent the rest of the class talking about the sample literacy narratives = the Sample narratives 1 & 2 posted at the link to the right - and third sample handed out in class.

In class discussion you defined literacy narratives as having a focus on how the author formed his or her relationship to reading and writing.

You characterized the focus of the 3 sample literacy narratives as follows.
Sample 1.  focus on struggling to choose an identity as a writer; complicated  influences of family on relatioships to reading and writing
Sample 2. problems stepping into being a writer; collaborative writing; struggling to call herself a writer (when are you a real writer)
Sample 3. how the writer struggled to get her education (use writing in her education- decide who "owned" her writing); surprise in the ways education/her life turned out; persisting, family factor,

In our discussion of the three literacy narratives we characterized the last sample as more negative - including more "bad" experiences that were not completely resolved - than the other two.

Mainstream stories, dominant discourse (dominant patterns in the way language is used), and patterns for telling identity stories.  This last observations connects to what language researchers and psychologists  have noticed about the way individuals who are different ages tell stories about who they are.  As we will read later in this course, individuals of college age tend to tell stories where they are in control and where events lead to a positive outcome.  These researchers found that several forms similar to hero stories are a dominant form for college age narrators talking about traumatic experiences.  Other research shows that older storytellers are not so likely to tell positive stories.

This set us up for a discussion of mainstream stories - stories that are "out there" about the way the world is. These story forms are widely used by ordinary people as they put together "explanations" (stories) for who they are and why their lives have turned out the way they are.  Two important cultural stories  that we identified were the American Dream and the Literacy Myth - both of which include assumptions about how and why individuals are successful

It also set us up for a discussion of social construction theories.  In social construction theories, it is assumed that individuals put together their stories in terms of story forms (plot lines, characterizations, value judgments about what is right or wrong, and so on) that are "out there" in the culture. These theories assume that "mainstream" stories are easier to tell that non-mainstream stories (with values, perspectives and experiences that are either taboo or less talked about).

We will be talking about these ideas throughout the course - this was (another) introduction.

Analyzing the literacy narratives  At the end of class we talked about setting up an analysis of one or more of the literacy narratives.  We talked about how you might set up your analysis by asking a particular question of the data - and THEN naming (looking for) the features in the data related to your question.  I'm hoping the questions are in your notes!

For next class:
Blog 6. Set up a question you might use as the focus for a research project on one or several of these literacy narratives.  Identify the features relevant to your question. These features might characterize the people in the stories, the actions and interactions, the surrounding circumstances, the belief systems and assumptions and values of the people in the stories, and the outcomes.  Point out how these features - and the relationships among them create an answer to your question.  The more writing you post - the more feedback your classmates and I will be able to give you on your analytic process.

In class on Tuesday we will go over your posts for Blog 6.  You will also do some brainstorming to find a focus for your research project.  We will either meet in 313 - or I will have a computer lab room number posted here on the blog and by the door to 313.

9.18 Shaggy dog stories

NIH training:  I still need links from some of you.  As soon as I have access the certificates, I will forward our class list to the Kean IRB.

Comments on your blogs.  I started class with a quick overview of some of what I am seeing on your blog.  You are doing a good job of naming the different parts of the analytic process.  What is missing are the lists of the particular codes and categories  - along with examples from the data of actions, interactions, actors and settings that you used those codes/categories to name.  Writing up your analysis by identifying your codes and categories, and then explaining the relationships between the different elements within those codes and categories allows us to talk about HOW you came to your conclusions about your data.   It provides evidence of your logic and your assumptions.

For example, we noted in Brigit's data analysis that she looked at correlations between the age and the emotions of participants in the class interviews on 911.  AWESOME.  And there are great observations & hypotheses here.  What needs to be developed is the identification/classification of the different age groups + the emotions subjects of that age showed in different conversations (with respect to different subject material, etc).  The kind of analysis we are working on should function as EVIDENCE for your conclusions.  It should show what you named as a particular emotion - and what codes/categories of response were associated with that response.

When asked what was hard about this - several of you pointed out that coming up with hypotheses was hard.  Hypotheses are answers to questions about relationships in your data (what are the connections between age and emotions?  what kinds of questions got the most detailed stories?  what kind of information was contributed by off-topic talk? etc).  To develop hypotheses - ask about relationships between categories and/or codes.

Analysis of Shaggy dog stories.
We started out with a review of two of the stories on the handout.   You identified the following list of characteristics of shaggy dog stories (names for what they do/are)

• jokes
• play on words => mangling of a quote
• listeners have to know the quote to "get" it
• transliteration = switch of first letters of key nouns or names in the quote
• punchline is at the end (placement)
• switched words from the quote are introcuded at the beginning
• violence or startling interaction
• presented as a story with a beginning middle ending
• quote sums up or explains what the story means/is about/shows
• provides information so the listener buys into the new way to use the switched words

We then ranked the stories in terms of how funny we thought the stories were. 5 = funniest, 1 = not especially funny

# of votes for Funniest = 5 /4/3 /2 /1 = not funny
nate       1/4/4/4/1
friars      1/1/6/2/4
panda   7/4/-/1/2
Friday   5/3/-/2/4
chess    -/2/4/5/3/

We then talked a little about what we thought made one joke funnier than another.  You then worked in groups to identify features of the stories that made the stories "funny" (or not).  Some  categories for these features (along with some of the codes in those categories) from your notes include:

• characterization: codes = character actions (Nate's self sacrifice, Hugh beating the fiars), character identity (panda= thug; nate's integrity; nate = snake; Hugh brutal); visual image of character; 
• plot
• listener's (personal) connection to the punchline
• ridiculous punchlines: don't make sense as they are stated but make sense with letters transposed; may be tongue twisters (as in florists); connect to a widely known quote; explain the story but the story is ridiculous
• qualities of the punchline (codes/names for features of the punchline= true, ridiculous, power to explain the story)
• timing (sequence of story events); beginning middle end, funny words need to be introduced in the beginning (code = introduction of punchline word), punchline is at the end
• development  
• emotional response & features of the joke that cause the listener to be confused, surprised, shocked, satisfied (at figuring out the "twist" in the story) etc
• word choices (fpr example, words that have double meanings as in the panda joke; words that are the same with one or more letters switched

Within each category, you came up with features that contributed to the story being funny (or not).  For example, stories that happened too quickly with without development that included characterization, connection to strong visual images, and a story line (as in the chess joke) will not be as funny as jokes that present a characters and images the listener can "see" along with an extended storyline that has a double/joke meaning - as in the panda story.  Some of your categories formed larger categories.  For example, categories for listener's connection to punchline, ridiculous punchlines, and qualities of the punchline all focus on punchlines or the ENDING.  Timing, development, plot and characterization are mainly relevant to the INTRODUCTION + BODY/MIDDLE of the joke.

This exercise was to give you some experience developing the language/words + logic that you will use as evidence to support a theory about how the data works.  For this exercise, theories were supposed to be about what makes a shaggy dog story funny.

Great class!  You are doing good work on using coding, categorizing, looking for patterns and developing theories as a way to SLOW DOWN and WRITE ABOUT your analytic process in a way that you can share your ideas (and the way you developed them) with other researchers. Good job.

For next class:
Read: literacy narratives under Data Set 2  + the literacy narrative handout. As discussed in class, a literacy narrative is a story about the narrator's unfolding relationship to reading and writing over the course of a lifetime.  Writing studies researchers use literacy narratives to gather information about what kinds of experiences support literacy learning.

Update Blog 4.  DO NOT re-write it - simply add some additional writing at the end to state how you could strengthen and deepen the analysis you have posted.

Post Blog 5.  In class, we looked at 5 shaggy dog stories, ranked which were funniest, and began an analysis to identify which features make shaggy dog stories funny.  The analysis suggests which features seem funny in general, and the ranking gives an indication of what your CLASSMATES think is funny. For Blog 5, use the class ranking and our analysis of the funny features of  shaggy dog stories as a basis for predicting how our class will rank the shaggy dog stories at this link.

Your analysis should identify features of the stories at the link that are similar to features of stories our work in class suggested as "preferred" by your classmates.  In this analysis, your line of reasoning is at least as important as your conclusion.

Have fun!

9.13 Analyzing interview data

NIH Training certificates are due Sept 18.  If you haven't already, please send the link to your certificate to the course email.

Update on the room situation:  I have been informed that we have a computer lab - but it needs to be confirmed.  I will post the room number here and on the postings board beside CAS 313 as soon as I have final authorization.

What we did in class:  We began with some talk about the data you posted on your blogs.  We observed that you each had a slightly different format, and that all of you did some good observing and writing down what happened.  So good job!

Next we talked through the process for analysis when the data you are working on are the messy interactions you find in an interview - rather than a set of shapes in a logic problem.  We noted that even though the data are quite different = the steps in the process are very much the same.

1. Coding: identify/name the features of your data.  For our interview data, some of the "features" or classifications you might note include:

• questions + answers.  Identifying talk as either a question or answer can help answer questions about who is directing the interview (authority), the participants' investment or engagement with the process (hypothesis = if subjects ask more questions they are more engaged?), what kinds of information can be communicated through questions versus statements = and so on.  
• speaker's distance or emotional connection to what s/he is saying.  noting/naming connection or the speaker's relationship to what s/he is saying can help answer questions about what is important in an interview
• changes in attitude, perspective, or emotion
• statements of "fact" and statements where the speaker interprets/responsd to fact
• stories + parts of stories (introduction, presentation of problem, resolution of the problem, conclusion)
• resolution (or lack of resolution) to stories: stories might have positive or negative or unresolved endings.  
• the storyteller's language choices (are there any repeated phrases or words that signal characteristic feelings or ideas?)

I realize the notes we took will not have sufficient detail to provide solid data for most of these classifications - but that is OK.  This gives you a simplified, first opportunity to look at data and figure out how to name  what you see.

2.  Classifying:  place the different examples of questions and answers (or some other name/code) into groups.  Look for similarities and differences in your codes (as we looked for similarities and differences in the different kinds of interviews at the beginning of class).  In our analysis of Andrea's data - we kind of did this backwards.  We started by noticing the category = after the interview comments - and then we named different kinds of "after the interview comments": observations, interpretations, and evaluations.

3.  Identifying patterns.  As we talked throughAndrea's data, we identified a small pattern in terms of the order of the different kinds after the interview comments.   Corrine noted a small pattern where a subject became emotional - and that emotion seemed to influence the next question asked by the interviewer (were you confused. . . ?)  Other patterns that you noted in the data were connections between age and the the subject's perception of 911, and so on.

4. Developing hypotheses about what the patterns mean or how they fit together.  A hypotheses is a "guess" about what a pattern means or how it relates to other patterns.  In our discussion of the sequence of after the interview comments, I suggested that this was the same sequence most people use to tell stories.  They describe what happened, interpret what the events mean, and the offer some kind of meaning/moral/or evaluation.  To develop this hypothesis - i made a connection between a pattern I observed in the data - and some other pattern (story telling patterns) that is "out there" in the world.  

5. Testing the hypotheses. Continuing #4, we looked at the sequence of after the interview comments in some of the other data  - and the pattern we saw in Andrea's account was not really repeated.  So my hypothesis wasn't really a good one.  So then we tried some other hypotheses about what the patterns in our data meant.

6.  Creating a "theoretical story"is to put together an explanation of the relationships among the features of the interview you are interested in.    After you find some hypotheses that fit  the data - put them together to see if you can develop an explanation.  Several of you were looking at relationships between how old the subject was, the subject's emotions, where they were when they found out, and so on.  So we started working. on a theory - to explain why/how being a certain age shaped the experience of 911. 

I really enjoyed this class and was impressed with how much information we got out of your data!

For next class:

Blog 4: Set up an analysis of some of the oral history data posted for Blog 3.  You can analyze data from one blog or several.  The point of this exercise is for you to practice the analytic process we went through in class.  Name and classify what you see in the interview; look for and describe patterns; put forward a hypothesis and test it = and see if you can come up with a theory (explanation) that accounts for the patterns and relationships you see in the data.

On the calendar it says to read the literacy narratives, but instead, we are going to start with the shaggy dog stories.  They are posted at this link.

In class we will begin by talking about your experience working on the oral history data.  Come to class prepared to talk about what you learned (any tricks you discovered), where you got stuck, and what you'd like more practice doing.  Then we will work on a slightly different kind of analysis using the shaggy dog stories.  

See you next week! 

9.11 Interviews and Oral history

I have emailed feedback (for most of you) for Blog 1. If you have questions - be in touch or set up a time to stop by my office.

Interviews. We started talk about interviewing by thinking about the different kinds of interviews (genres) that are out there in our culture. You identified job interviews, news interviews, political and celebrity interviews, man-on-the street interviews and research interviews. Each of these different interviews have a characteristic audience, purpose and form, and they set up questions for different "subjects."

Oral history. I then introduced oral history in terms of its role in redefining the stories we use to "create" history. Oral histories generally focus on a particular life within a particular historical period or as related to a significant historical event; they may also present a life review that only incidentally connects to larger cultural happenings. Oral histories are often collected through interviews and recorded through audio or video recordings. The term "oral history" is also used to refer to the written, analytic essays that discuss the interview materials collected from oral history subjects.

Overall structure for an interview. Next we talked about how to plan the conversation for an oral history interview. I suggested that you think about the interview in parts. The first part serves as an orientation where you and the subject get to know (and hopefully feel comfortable with) eachother. This talk should provide any background information the subject will need (your objectives - if you have any) - and have some talk about any preferences/interests/agendas the subject might have. During the middle of your interview you cycle through questions (often in roughly chronological order) about the experiences that are at the center of your study. Ask open questions (questions that can't be answered with yes or no, and that don't put the subject on the spot). "Tell me about. . ." or "What was it like when . . ." or "Describe . . ." or "Tell me a story about . . ." are good lead-ins. Remember interviews are conversations - so follow up and add to your opening questions. As you come the the last part of the interview, begin some reflecting and pulling together. Make connections, ask for feelings and reflections.

911 interviews. After this introduction you worked in pairs to conduct oral history interviews about experiences on 911. One of you was the interviewer, one of you was the subject - and BOTH of you took notes. I stopped you several times to catch up with your note taking. You were instructed to note what was said by both, the timing and sequence of the unfolding information, how the speakers interacted, and descriptions of "what happened" as the interview progressed. You were instructed to write down as much as you could as you were talking, and you were given several spaces of time during and after the interview to add your "head notes" (what you remembered) to your notes. All of these notes taken together should be posted on your blog. IN ADDITION - Blog 3 should include (at the end, or added to the main post in a different color font) and other stories, observations, "quotes" conversations that you remembered as you thought back on the interview.

For next class:
Read: Methods/best practices for collecting oral histories http://www.oralhistory.org/do-oral-history/principles-and-practices/

Blog 3: Post your notes to your 911 interview (see 911 interviews above for complete directions). Title your blog "Blog 3: Interviewer (name), Subject (name) where you fill in (name) with the name of the participant in your group.

Review the process we developed for analysis and look around at your classmates' notes. Come to class prepared to analyze what we might learn from these oral histories

9.6 Analysis!

IMPORTANT NOTICE:  Class on Tuesday will meet in CAS 313.  If you have a laptop - bring it with you so you can use it to take notes.

Analysis: During the first part of today's class you worked on solving a logic problem.  You were asked to figure out what symbol would occur in a blanks space within a grid of symbols.  You worked in groups and you did an amazing job.  I was impressed by how well you worked together, by the wide range of analytic moves that you already know, and by the number of "theories" you came up with.  As I said in class - this exercise was not so much about solving the problem - as about becoming conscious of HOW you (already) do analysis - and learning to do it more intentionally and with more focused direction.

What we learned from the class exercise.

This is a list of some of the many "moves" (ways of thinking about, classifying, or explaining) you made as you worked on the problem.

• named the symbols (square, diamond, club, heart. . .)
• noticed the layout of the drawing (6x6 grid)
• noticed/named the colors
• noticed the orientation (some hearts & clubs were both upside down & right side up; you also decided on the orientation of the grid as a whole - with the directions at the bottom)
• counted how many of each symbols were on the grid
• tried out different groupings for the symbols ( columns, rows, as a "design" made by the colors or repititions . . .)
• looked for doubles by symbol
• looked for patterns by color, by shape, and by orientation

As we thought about the different kinds of moves you made - we came up with the following sequence for the different kinds of moves you made.

1. Identified and named the elements of what you are analyzing- where "elements" are the features that define or present what you are analyzing.  For this logic problem you identified named the different symbols, the layout of the grid (columns, rows, etc), color.  You identified and named elements by looking at what was there - and attaching labels or names to what you saw.  In writing studies analysis - this move is often called "coding" = where you develop names or "codes" for what you see in a particular situation.

2. Categorized or grouped together elements on the basis of similar features.  For this move you noticed what all the hearts, or all the diamonds were doing, and you described those features with a name or category.  Counting and classifying the kinds of locations and orientations for each symbol is categorizing.  It makes larger groupings and descriptions for what happens to individual named elements - or what those elements do.  This is the beginning of posing a "pattern" = your next step.

3.  Look for patterns. At the looking for patterns stage, you looked hard at the data and noticed repetitions, sequences, symmetry, etc.  Looking for patterns requires you to make a connection between a structure you know and recognize - and some structure within the problem you are looking at.  So in some sense you are looking for something you already know - but within a new situation or context.

4. Pose a hypothesis.  After you found a small or large pattern, you pose a larger, more general explanation for how that pattern can explain the whole problem or situation.  This step is about figuring out how the little pattern you saw in one part of the problem would look if it were applied to the whole problem in a general way - and making a statement to describe what that large patter would look like.

5. Testing the hypothesis.  After making a general statement of the "story" or "explanation" suggested by the small pattern that you noticed  - you then checked to see if this story or explanation "fit" or "worked" within the whole problem (all of your data, where data is the information you have about the problem). A strong hypotheses, or the "answer" to your problem, will fit and work with ALL of the data.

6. Cycling through the process.  Most of the time, our first hypothesis only explain parts of the data or small pieces of the problem. This means we need to go back to the beginning and make sure we have noticed/named the central elements of the problem, and that we have put them in useful - rather than irrelevant or misleading - categories. We also have to decide whether the patterns we connected to are "working".  If they aren't we need to come up with additional patterns - new patterns we haven't tried before - and organize them into another hypothesis (each group did this several times).

Where researchers get stuck:  Your experience with this problem was similar to researchers in that you got stuck in the same places that most thinkers/researchers get stuck.  Identifying and applying MANY possible patters (and letting go of the first couple that you found) is often the hardest part. 

During the second part of the class you worked on your blogs.  I will be looking over Blog 1 over the weekend and should have some feedback for you by Sunday night. 


For next class:
Keep working on the NIH training.  It is due 9/18

Blog 2:  In your own words=> define analysis.  What is it? How does it work (describe the process for doing it)?  Then - describe how you would use analyhsis to study one fo the areas of interest you mentioned in your first blog.  What codes might you find?  What categories for your codes might be important?  What theories might be relevant?

BRING YOUR LAPTOP to class if you have one. I will introduce oral history as a research method, and we will be thinking some more about analysis.

9.4 Introductions, questions about the syllabus, NIH training, and setting up the blog

ATTENTION: All future classes will meet in CAS 113, the computer lab on the first floor next to the Writing Center.

If you have not done so already = send an email to ENG3029@gmail.com with the url (address) for your blog so I can read what you have posted.  The address for this blog is  http://eng3029section01.blogspot.com/

Today's class got us off to a good start -I was pleased to meet each of you and am looking forward to learning more about you and your interests in writing research.

The class began with introductions and getting to know each other. As I pointed out - it is usual at Kean to be "familiar" with a few faces - but in this class we are going to get to know one another - and to work together.  We then read through the syllabus, with particular attention to course goals, how the course will be taught, and how you will receive your grades.  If you have additional question - please let me know.

After introductions we moved from CAS 313 to 113 = where we will meet for the rest of the term.  I introduced you to this blog, and we talked about the NIH training (see assignment sheet posted to the right). Because you will be doing field research for this class - you will be working with other people - or research subjects.  And because people have rights, researchers have responsibilities toward their subjects.  As described on the assignment sheet - all researchers associated with government agencies (and this is a state school, so you are) much take NIH training.  You must email the certificate you receive for completing training to me by September 18.  I suggest that you get started - it might take one or two sittings.

We had our first talk about ideas for research projects.  At this point you should be thinking about what interests you.  As I said in class, go for your passion - and as we work on refining your topic, we can find a way to make it a writing studies project - and as you move through the course, you will be able to come up with methods and a research design.  So for now - think about any aspect of language, writing, talk or interactive behaviors that you would like to study.  Some of the areas of interest that you came up with so far include:

• effects of music on writing and writing process
• cyberbullying
• video games
• sports (football)
• Anime/Manga
• acting/musical theater
• society and family

This is a good start!

You spent the rest of the class setting up your blogs.  I think everyone got a blog started, and you were working on emailing me the link (address) so I can post links to your blogs on my blog.  If anyone is stuck, I will be in CAS 113 by 10 on Thursday - and we can work on whatever technology issues we need to before class - or send me an email and we can work on it from there.

For next class:

1. Get started on the NIH training (email me the certificate of completion by Sept 18)
2. Send me the link (address) to your blog using the email you want to use to be in contact with me for this class.
3. Read:  Look through the course readings => identify topics that interest you
4. Blog 1: From class discussion and course readings, what kind of research does it look like people do in English and writing studies?  What kind of research are you interested in doing?: 

9.4 About the Course Blog

This is the course blog for ENG 3029 Section 1.  We will use this blog to keep a record of what we do in class, as a hub for communications with me and other class members, and to keep all the important course documents in one place.

Documenting what we do in class: After each class I will write up a summary of what we talked about, what you turned in, and what you are expected to do for next class.  Although I have created a class calendar - sometimes we might not do exactly what is on the list.  This blog will update the calendar and give the real story on what we accomplished and where we are going next.  You should be sure to check these updates every day.  By using the link list to the right titled Blog Archive, you will be able to check back on earlier class discussions.  I will title Blog Archive posts both by the date, and a title describing the post's content.

A hub for course communications:  You can see a link list to the right named "Course Blogs."  So far, my blog is the only link on that list.  By next week, each of you will have created your own blog.  You will send me the link in an email posted from your kean email, the account you will use for this course.  The list of course blogs will allow you to read and review writing, comments on class discussions, and questions posted by everyone in class.  If you do not want your blog to be searchable (visible to search engines), when you set up your blog set the privacy functions so that your blog is visible only to individuals who have the link.

You do not need to be tech savvy to take this course.  If you are uncertain about how to create your blog - or if you have trouble using it - stop by my office and I can talk you through it.  This is meant to be a resource for you, and if it is not working about that way let me know so we can fix it.

Course documents:  To the right you will also see several sets of link lists with links to readings, course documents, data sets, and etc.  We will be creating and accumulating these documents as we go through the course.  By posting them here - you will have access to all the assignment sheets, rubrics for assignment evaluation, and other course information - all in one place.

If you have questions - ask me in class, or email me at ENG3029@gmail.com.