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GCRD 6353: Seminar 2

Nov 01, 2014

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Education

This addresses material covered in our second f2f session (Truro/Halifax).

  • 1. Literacy & New Technologies GCRD 6353.81/82 Research Seminar in Curriculum Studies Colin Lankshear & Michele Knobel
  • 2. Slideshow available here: www.slideshare.net/netgrrrl
  • 3. Academic report Purpose of this report is to examine your experiences in producing a digital media artifact in relation to 1-2 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.
  • 4. Analysing your groups 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 groups 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).
  • 5. 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 concepts or categories embodied across the different kinds of data weve 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
  • 6. 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 weve collected?
    • Whatif anythingdo you notice happening over time with respect to these patterns/categories (or outliers)?
    • See the DaraPGroup paper on the course website for an example of emergent data analysis
  • 7. Data analysis: General comments
    • Its a recursive processyou 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 Gees concept of affinity spacesuch as what constitutes an affinity/shared interest, can it be temporary etc.
    • Think about your datawhat 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.
  • 8. 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
  • 9. Return to the theory to discuss your findings
    • To what extent and in what ways do the patterns youve found resonate with the concept of collaborative learning and associated ideas (e.g., affinity spaces, learning to be, social practice, D iscourse 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. Dont be random in your write-up.
  • 10. 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).
  • 11. Possible structure for your report
    • Introductionsummary 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 what you didqualitative study of X (including how you collected your data etc., time, location, resources available)
    • Review of the literature pertaining to key concepts in the literature to frame your report
    • An overview of the artifact you produced (e.g., what is stop motion animation etc.)
    • Summary of how you collected your data, and how you analysed it (this will include citations to research methodology literature)
    • Identify briefly all the main categories you found, and identify which ones you will focus on
    • Discussing each category (including a definition of the concept/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 (dont over-generalise)
    • Conclusionsummary of what you did and found and of your learning
  • 12. Writing tips
    • Dont just slot quotes inweave them into your discussion so that they support your analysis and dont 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 someone uses the term collaboration doesnt necessarily 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, considering x)
    • 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 going as you work
    • Dont use a dictionary to define concepts
    • APA referencing conventions
  • 13. 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).
  • 14. Writing tips (cont.)
    • Aim at 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 growing use of key technical terms associated with photoshopping: huewhich means .; saturation, which means ; blur, which means.
  • 15. 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 is . For example, A glanced over at Bs screen and said, Oh that looks marvellous! Do you think he needs some shadow under his feet to ground him a little, though? (Cs 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
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