1. Thinking ahead to your research
report

2. Working collaboratively online
 Google Docs (docs.google.com)
 Scholar Google (scholar.google.com)
 Academia.edu (search for research area to
find papers & books)
 Google Books (http://books.google.com)

3. Using Google Docs:
http://docs.google.com

4. Using Google Docs

5. Using Google Docs

6. Using Google Docs

7. Share your Google Docs with Us
 Use a Google doc to collaboratively
write your research report
 Add us (with editing rights) to your
doc so that we can give you timely
feedback on your writing:
 micheleknobel@gmail.com
 colin.lankshear@gmail.com

8. Using Google Scholar
http://scholar.google.com

9. Using Google Scholar

10. Using Google Scholar

11. Using Google Scholar
NB: Double quotes
around a phrase
searches for phrase

12. If you do set up a Google Doc for your
report….
 … then, share this doc (along with editing rights)
with Colin and Michele
(micheleknobel@gmail.com&colin.lankshear@gmail
.com)
 Your group may prefer to work with a Word doc that
you share via email, and that’s fine, too. You can
send it to us at key points along the way for
feedback during our final week.

13. Writing your report

14. Academic report
Purpose of this report is to examine your
experiences in producing a digital media artifact in
relation to 1-2 patterns or concepts associated with
learning to participate in a new literacy practice
You will be reflecting upon the process of learning
a new literacy in ways designed to inform our
work as teachers, learners, and cultural
producers.

15. Analysing your group’s data
There are three broad ways to approach analysing your data.
1. Theory-guided; that is, using pre-determined categories
(based on key theoretical concepts).
2. Emergent; that is, grounded analysis of data that
generates categories out of the data itself
3. A mix of both.
The main thing to begin with is to go through your group’s
data and look at what patterns start to “fall out” or emerge
(with an eye to outlier events as well, as well as to key
concepts). Play good, close attention to all your data
(written, spoken and observed).

16. Theory-guided data analysis: Using
pre-determined categories
 What pre-determined categories pertaining to learning a new
literacy can you identify from close reading of the entire data set?
(e.g., collaboration of a certain kind, participatory culture, affinity
spaces, performance before competence, distributed
expertise, just-in-time learning)
 To what extent are these patterns, categories or concepts
embodied across the different kinds of data we’ve collected?
 To what extent does the literature fully explain what you
observed? Or does your data extend/challenge the concept as
currently written about?
 See the “Krista Group” paper on the course website for an
example of theory-guided data analysis

17. Emergent data analysis: Categories
arising in a ‘grounded’ way
 What patterns,regularities, categories (or outliers) emerge
from close reading of the entire data set?
 To what extent are these patterns/categories evinced
across the different kinds of data we’ve collected?
 What—if anything—do you notice happening over time
with respect to these patterns/categories (or outliers)?
 See the
“DaraPGroup” and “LooneyTunes” papers on the
course website for examples of emergent data analysis

18. Data analysis: General comments
 It’s a recursive process—you may (1) start with a concept and
examine your data, or (2) examine your data and revisit
relevant concepts, adjust things (your understanding of the
concept, your definition of a concept, etc.). For example, your
data might challenge the concept of “affinity” in Gee’s
concept of “affinity space”—such as what constitutes an
affinity/shared interest, can it be temporary etc.
 Think about your data—what things are starting to stand out
as being pivotal moments, or key “a-ha” moments that afford
you real insights into your learning, in your “coming to be”
something, in your understanding of what it means to use
theoretical concepts to explain stuff, etc.

19. Data analysis: Coding data
• How you generate codes
• When you code data, you code either
using pre-determined categories
and/or, or you use open coding
techniques for grounded, emergent
data analysis
• Refer to your textbook for more on
this

20. Return to the theory to discuss your
findings
 To what extent and in what ways do the patterns you’ve
found resonate with concepts to do with learning, new
literacies and associated ideas (e.g., affinity
spaces, learning to be, social practice, Discourse and
literacy, participatory culture, new ethos
stuff, appreciative systems, deep
learning, collaboration, distributed
expertise, participation, just-in-time-learning, and so
on)?
 Make sure that the authors of the additional texts you
find and read “fit” with a sociocultural orientation.
Don’t be random in your write-up.

21. Writing your report
 This is more like a research report rather than an essay
 Keep in mind assessment criteria in your syllabus
 Focus on “being an academic”
 Remember that there are different types of academic
literature. These include: research literature,
commentaries, analytic papers (that analyse and discuss
concepts and ideas), and research methodology
literature (how-to-do research).

22. Possible structure for your report
 Introduction—summary of the categories at the heart of your paper; what you
hoped to learn; context and rationale for media artifact; rationale for making the
artifact
 Overview of who you are and what you did—qualitative study of X (including
who you are, the context in which you’re in this course etc.)
 An overview of the type/genre artifact you produced (e.g., what is stop motion
animation is and a little about its history,etc.)
 Review of the literature pertaining to key concepts in the literature to frame your
report
 Summary of how you collected your data (referencing academic texts, too)
 Summary of howyou analysedyour data(this will include citations to research
methodology literature, too)
 Identify briefly all the main patterns/categories you found, and identify which
ones you will focus on
 Discuss each pattern/category (including a definition of the pattern/category
based on your readings; this may be tweaked based on your data)—this includes
reference to theory stuff (this is likely to be the largest section of your paper)
 Implications for your own teaching (don’t over-generalise)
 Conclusion—summary of what you did and found and of your learning

23. Writing tips
 Don’t just slot quotes in—weave them into your discussion so
that they support your analysis and don’t stand in for your
own discussion
 Direct quotes should not start or end a paragraph
 Pay attention to dates of publication
 Make sure that direct quotes are relevant (just because two
authors use the term “collaboration” doesn’t mean they
mean it in the same way)
 Remember to use cohesive ties (e.g., moreover, in contrast,
in addition, furthermore, on the one hand + on the other
hand, however, therefore, otherwise)
 If you get stuck, just write down what you want to say in
everyday language as a starting point, then work from there
 Keep your bibliography (APA style) going as you work
 Don’t use a dictionary to define theoretical concepts
 APA referencing conventions

24. “Bad” use of quotes
“There is a real need for reflection on teachers’
conceptions of textuality and literacy as they exist “for
specific social purposes inside and outside schooling and
in the intermediary spaces and places between them”
(Nixon, 2003, p. 409). As Kelly (2000) wrote, “to move
beyond romantic notions of English is, often, to retreat
from and to reconfigure once familiar and highly invested
desires embedded in our personal and social histories” (p.
86). It is no wonder then that, as Merchant (2008)
writes, “it is hard for us [ELA educators] to know which
dispositions, values and practices will remain important
and which new ones may be required” (p. 751).”

25. Writing tips (cont.)
 Aimat sounding plausible by using a bunch of
academic discourse moves:
“The weight of spoken data suggests that over
the course of five days our ways of speaking
about photoshopping changed in a subtle but
interesting manner that signalled at least some
shift from being novices towards being more
proficient users of photoshopping tools and
techniques. These changes included a growing
use of key technical terms associated with
photoshopping: “hue”—which means ….;
“saturation”, which means …; “blur”, which
means….”

26. Writing tips (cont.)
What was perhaps most significant in this study, however, was the
degree to which being immersed in creating a series of
photoshopped images and documenting this immersion now
makes it possible to discern elements of the “new ethos”
dimension of new literacies as described by Lankshear and Knobel
(2006, p. x). To recapitulate, the “new ethos” dimension of new
literacies is concerned with …… In our data, identifiable elements
of this dimension of new literacies elements include X, Y, and Z. In
our data, X typically…. For example,
A glanced over at B’s screen and said, “Oh that looks
marvellous! Do you think he needs some shadow under his
feet to ‘ground’ him a little, though?” (C’s
fieldnotes, 13/07/10, p. 14)
In this example it is possible to see how A is demonstrating some of
the shared values of what constitutes effective photoshopping and
its goal of realism and authenticity. A talks about “grounding” the
figure in the image; this, it can be argued, demonstrates that A
understands the importance of……

27. Writing tips (cont.)
It is also possible to argue that A also understands the culture
of constructive criticism that is valued within the online DIY
photoshopping community (cf., Merchant, 2010; Potter, 2010).
A begins with a supportive evaluation, then couches her
suggestion as a question--leaving any subsequent changes to
the discretion of B. …. This pattern—supportive
evaluation, then constructive suggestion—re-appeared
throughout our records of spoken data (out of 173 documented
utterances, 102 utterances took this form). Interestingly, this
pattern resonates with reviewer feedback patterns found in
Rebecca Black’s research into fan fiction writing (Black, 2009).
Black found …. For us, this pattern in our own data suggests…
(and then link to, say, Jenkins’ concept of participatory
culture, of Gee and Black’s take on participating effectively in
an affinity space etc.).

28. Examples of final reports…
https://sites.google.com/site/ourmsvup
ages/corner-brook-2011
Different report examples are archived here.