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Thursday, September 9, 2010
Tuesday, February 16, 2010
(2006) in Charness, N., Feltovich, P, & Hoffman, R. (Eds.) Cambridge Handbook of Expertise and Expert Performance. Cambridge: Cambridge University Press
Chi, Michelene T.H.
This chapter differentiates two approaches to the study of expertise, which I call the "absolute approach" and the "relative approach," and what each implies for how expertise is assessed. It then summarizes the characteristics ways in which experts excel and the ways that they sometimes seem to fall short of common expectations.
Chi defines two approaches to defining expertise. In the "absolute approach" expertise is conceptualized as being a property of exceptional individuals who have some unique or perhaps innate talent. In the "relative approach" expertise is conceptualized in terms of comparing experts to novices. This conceptualization assumes that novices can become experts--that expertise can be learned. It is this latter approach that is particularly useful in educational terms, I think. As Chi states, "the goal [in the relative approach] is to understand how experts became that way so that others can learn to become more skilled and knowledgeable" (p. 23).
Chi goes on to identify ways in which experts excel, and ways in which they "fall short." Experts excel in the following ways: they generate the best solution, they can detect and see features that novices cannot, they spend a great deal of time analyzing problems qualitatively and develop problem representations by adding constraints within their area of expertise, they have more accurate self-monitoring skills, they are more successful at choosing appropriate strategies, they are more opportunistic that novices, and they can retrieve relevant knowledge with minimal cognitive effort. Of these characteristics, the one that is most important in my work is the ability of experts to choose appropriate strategies. I also think that the third feature--analyzing problems and situations qualitatively and applying constraints--is particular important to consider when educating teachers with the aim of helping them develop expertise. This characteristics get at the context dependence and importance of constraints on teaching situations, and their influence on strategic choice. Clearly, these characteristics of experts are not independent.
According to Chi, ways in which experts "fall short" include the fact that their knowledge is domain-limited, they can be overly confident, they sometimes fail to recall surface features and overlook details, their expertise is context-dependent within a domain, they sometimes have trouble adapting, they can be inaccurate in their prediction of novices' performance, and they can exhibit bias. In some ways, this list has more implications for thinking about expertise is teaching. For example, The idea of expert knowledge being domain-limited, and the idea that their expertise is context-dependent within a domain give rise to my dissertation research questions: What is the nature of the interaction between teaching knowledge and content knowledge? Specifically, should surveys of science teacher practice be couched within "science" or within specific scientific domains (e.g. physics, biology, etc)? Another of these characteristics that teacher educators should pay particular attention to is the idea that experts often predict novice performance inaccurately. This idea should be troubling to any teacher. Consider a physics teacher (who may be an expert problem solver) not being able to accurately predict the performance of their students. Given what we know about teaching and learning, and more specifically about formative assessment, this teacher would not be very effective.
Much has been written about expertise or expert/novice differences. This short piece by Chi provides a nice introduction and some good discussion points.
(2008) Journal of Teacher Education, v. 59, no. 5, 389-407
Deborah Loewenberg Ball
Mark Hoover Thames
University of Michigan
This article reports the authors’ efforts to develop a practice-based theory of content knowledge for teaching built on Shulman’s (1986) notion of pedagogical content knowledge. As the concept of pedagogical content knowledge caught on, it was in need of theoretical development, analytic clarification, and empirical testing. The purpose of the study was to investigate the nature of professionally oriented subject matter knowledge in mathematics by studying actual mathematics teaching and identifying mathematical knowledge for teaching based on analyses of the mathematical problems that arise in teaching. In conjunction, measures of mathematical knowledge for teaching were developed. These lines of research indicate at least two empirically discernible subdomains within pedagogical content knowledge (knowledge of content and students and knowledge of content and teaching) and an important subdomain of “pure” content knowledge unique to the work of teaching, specialized content knowledge, which is distinct from the common content knowledge needed by teachers and nonteachers alike. The article concludes with a discussion of the next steps needed to develop a useful theory of content knowledge for teaching.
Keywords: mathematics; teacher knowledge; pedagogical content knowledge
Deborah Ball and her colleagues have been working for some time to further explicate teachers' content knowledge for teaching, and have helped to shed some light on the often invoked but somewhat ethereal notion of pedagogical content knowledge (PCK; Shulman, 1986). In this piece, the authors state what I have come to understand through my work in this area over the past few years: "the filed has made little progress on Shulman's initial charge: to develop a coherent theoretical framework for content knowledge for teaching" (p. 394). Researchers often cite and implicitly agree (without explication) on the idea that teachers must have some "deep understanding" of their subject area that is unique to the teacher and not necessarily understood by the content area expert. But what that understanding looks like and how it relates to teachers' pedagogical knowledge is not well understood. "Instead of taking pedagogical content knowledge as given, however, we argue that there is a need to carefully map it and measure it" (p. 404). This is, in part, the aim of my work with the Flexible Application of Student-Centered Instruction (FASCI) survey.
The research program of Ball and her colleagues is focused on defining the nature of content knowledge for teaching in a methodologically precise manner (e.g. see work on the Mathematical Knowledge for Teaching (MKT) measures and associated validity arguments in the special issue of Measurement: Interdisciplinary Research and Perspectives, vol.5 issue 2-3, 2007). In defining two empirically discernible subdomains within PCK (knowledge of content and students, and knowledge of content and teaching), and the subdomain of content knowledge--common content knowledge--this work helps to map out what PCK is and how it could be more useful.
In the conclusion, a three-fold rationale is presented for this work: helping to discover which aspects of teacher knowledge are predictive of student achievement, how different approaches to teacher development have an effect of these aspects of teacher knowledge, and third, how a better definition of these knowledge constructs and sub-constructs may inform teacher education and professional development. The last of these is a particularly motivating factor for my own work in this area.
Since my blog has been inactive for quite some time now, I think it's time to define a new focus in order to spur some activity again. Before, I had been blogging about any thoughts and ideas I had about education, education research, teacher education, and technology in education. What I'd like to do now is focus on one of those things: education research.
My idea is to present brief summaries and abstracts for research articles that I'm reading related to my dissertation and other education research work. What I'm envisioning would be quite similar to what Reidar Mosvold does in the field of Mathematics Education Research in his blog. Of course, my focus will be on science education and teacher education, with a smattering of measurement pieces if necessary.
If this all goes to plan, what you'll see over the following months is a sort of annotated bibliography related to my research areas. I'm hoping this will generate some discussion and also help me to make explicit and public my research interests.
Saturday, April 4, 2009
Well, I've finished my AERA paper and my NARST paper, and now I just need to put the talks together. I thought I'd take a few minutes to write a brief blog post about preparing for these conferences and about what I'll do when I'm there.
Conference preparation is always interesting. You submit proposals eight to nine months in advance, and get around to writing the papers about 3 weeks before the conference (or at least this is how it plays out for me). By then, I find it hard to be entirely faithful to my proposal. Usually the resulting paper is much more than the proposal indicated. Crafting these written works is indeed important, because they are the vehicle by which we first share our ideas and work with colleagues outside of our immediate working group. Also, these papers are often the first formal drafts of manuscripts which will later be submitted for publication in refereed journals.
Once the paper is written, I usually put together the PowerPoint talk about a week in advance. The .ppt is perhaps a dreadful format/means by which to deliver your talk, but it is the expected norm (unless you're giving a poster). The talk itself is between eight and 15 minutes long depending on the session type and format. Usually there is time for a few questions after the talk or at the end of the session. So in all, you may have about 20 minutes "on stage" to communicate and respond directly to your audience.
To me, however, the true value of conference attendance and presentation is not necessarily in the formal delivery of the research talk. While very important and necessary for introducing people to your work, the most valuable part of this whole experience is meeting others who are interested in similar research topics and developing relationships which might lead to connection and collaboration. It is great to get to know other people in your field. to discuss ideas with each other, and to brainstorm new ideas and future work. Much like when I was a classroom teacher and used to go to NSTA every year, I felt recharged and invigorated after talking to other science teachers outside of my own school. In many ways, conference attendance can help to battle the isolation teachers and academics can feel when we're pursuing our own thing most of the year.
Of course, for myself right now at this early stage in my career as an educational researcher, these connections are also essential to make as I'll be on the job market soon. I'm not sure where this PhD will take me when I finish it within the next year, but I've got to keep all of the doors open and going to these conferences is a great way to "collect" those doors. So if you're going to be at AERA or NARST in the next couple of weeks, look me up. My AERA talk is Tuesday the 14th at 8:15 in the San Diego Marriott, San Diego Ballroom Salon B. It is entitled Can Science Teachers' Strategic Knowledge be Conceptualized as a Learning Progression? and is part of the symposium "Learning Progressions for Teacher Development. At NARST, my talk is Sunday the 19th at 4:00 and is a part of the symposium "A Longitudinal Study on Pedagogical Content Knowledge: Synthesizing our Research on Content, Pedagogy, and Practice." It is in Salon III of the Hyatt.
Thursday, March 26, 2009
This is a question that I've been interested in for years, and is central to my current dissertation work (more on that later). Since I've built up a great PLN on twitter which includes many science teachers and science enthusiasts, I decided to pose the question to my tweeps. Here is a sample of their responses:
@gregorylouie said: @Bud_T Expertise ? Subject-Matter expertise + specific understanding of learning progressions based on research using developmental psych
@martywittrock said: @Bud_T A teacher that REALLY knows the subject matter but can explain it in common sense terms that a student can apply immediately
@mwacker said: @Bud_T Expert= experience, fresh ideas, and understanding of processes...what's your answer?
@wgraziadei said: @Bud_T expertise in sci: curious, visual, tactile, analytical, interactive, collaborative, reflective, professional practitioner/learner
@elizabethonline said: @Bud_T thorough interdisciplinary knowledge, know "why we care", excitement about the exciting stuff, and skills for remembering the tedium
Interesting ideas from folks: subject matter knowledge, understanding of student thinking, curiosity, experience, interactive nature, collaborative, reflective, communication skills, etc. I certainly can't disagree with any of these things, and I'm sure the list could go on and on.
But let me refine the question a bit for the purposes of the rest of this post: what knowledge do expert science teachers hold? I purposefully parse this from dispositions in order to try and bring the conversation into teacher education and to figure out what we, as science teacher educators, can teach in order to help prepare good beginning science teachers.
Certainly, knowledge of scientific subject matter is important. I don't think anyone would disagree with this. Two other things, which are at least hinted at in the above thoughts and are central to my dissertation work, are knowledge of specific student learning difficulties in the area being taught, and knowledge of appropriate representations of subject matter. When conceptualized within contextual knowledge, these two things along with subject matter knowledge form the essential components of pedagogical content knowledge (PCK; Shulman, 1986). For a more detailed explanation of my interpretation of this model of science teacher knowledge, please see my research proposal (Talbot, 2008).
Now I'm not saying that these are unequivocally the most important knowledge domains for a science teacher to possess, though I do believe they are very important. Further, they are things we can teach prospective science teachers in our teacher education courses. Many of us already focus on these things through the teaching and inclusion of inquiry, assessment, knowing students, etc. But, can we fully articulate why these things are important? That's something I'm working on- the 30 second "elevator speech" as one of my advisers would call it. Can you (or I) convince someone of what a highly qualified science teacher must know? I think we (science teacher educators) should all be able to do this, and further I believe we should use our voices to inform and even influence policy.
Please let me know what you think. As always, comments are welcomed.
New twitter responses since this was posted:
@BeckyFisher 73 said: @Bud_T I think understanding misconceptions and being able to unteach them is huge for a science teacher.
@chrisludwig said: @Bud_T A highly qualified science teacher must know how to tell good science from bad and be able to teach students to tell the difference
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching.Educational Researcher, 15(2), 4-14.
Talbot, R. M. (2008). Measuring science teacher knowledge: Domain-general or domain-specific? (Research proposal). Boulder, CO: University of Colorado at Boulder.
Tuesday, March 10, 2009
Last night's inaugural educhat conversation on twitter prompted me to again think about how we might mine the tweetstream for information on teaching and learning. I collected all tweets tagged #educhat (thanks to the help of others, such as @aforgrave), and also did this recently for the tweets tagged #colearning from Colorado Learning 2.0. This morning while driving from place to place, I recorded some of my thoughts (via gcast) on mining and coding this data. I'd be very interested on your input and ideas- please listen and comment, email me, or contact me on twitter (@Bud_T).
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