Difference between revisions of "Social and Communicative Factors in Learning"

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During PSLC’s first four years, its [[Interactive Communication]] Cluster has studied interactions between a student and a tutor (either human or computer) or, less frequently, two students interacting with each other.  Most of the experimental manipulations and subsequent analyses have focused on the cognitive content of interaction through learning space analyses, in other words, the what and when of instruction.  Study results investigating the effect of interaction, although somewhat mixed, have largely supported the hypothesis that focused interaction promotes cognitive aspects of learning such as attention to the most important knowledge components in a domain, deeper cognitive processing, and increased engagement with the content. VanLehn and colleagues (2007) present a thorough review of this literature as well as results from recent investigations.  These results encouraged early PSLC efforts to “unpack” the nature of communicative interaction in instruction and learning. Rummel and colleagues (Diziol, Rummel, Kahrimanis, et al., 2008a, 2008b), for example have recently evaluated interactions with a rating scheme analysis that quantifies the quality of an interaction on a number of dimensions.  This work represents an important step towards the type of up close inspection of communication that many scholars believe is necessary if we are to understand, and be able to manipulate for instructional purposes, how communication works to produce robust learning.   
 
During PSLC’s first four years, its [[Interactive Communication]] Cluster has studied interactions between a student and a tutor (either human or computer) or, less frequently, two students interacting with each other.  Most of the experimental manipulations and subsequent analyses have focused on the cognitive content of interaction through learning space analyses, in other words, the what and when of instruction.  Study results investigating the effect of interaction, although somewhat mixed, have largely supported the hypothesis that focused interaction promotes cognitive aspects of learning such as attention to the most important knowledge components in a domain, deeper cognitive processing, and increased engagement with the content. VanLehn and colleagues (2007) present a thorough review of this literature as well as results from recent investigations.  These results encouraged early PSLC efforts to “unpack” the nature of communicative interaction in instruction and learning. Rummel and colleagues (Diziol, Rummel, Kahrimanis, et al., 2008a, 2008b), for example have recently evaluated interactions with a rating scheme analysis that quantifies the quality of an interaction on a number of dimensions.  This work represents an important step towards the type of up close inspection of communication that many scholars believe is necessary if we are to understand, and be able to manipulate for instructional purposes, how communication works to produce robust learning.   
  
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In our re-named Social-Communicative Factors thrust, we propose now to expand our investigations of communication as a core enabler of robust learning to include detailed study of patterns of interaction, the role of conversation and structured talk in initiating and sustaining learning, and the effects on motivation, self-attribution and commitment to a learning group that are associated with learning through social-communicative interaction.  Specifically, we propose to investigate how human linguistic interaction works in instruction and learning, and how participants in learning exchanges (both teachers and students) can best be taught productive forms of interaction.  We draw from our extensive prior work related separately to classroom discourse (Chapin & O’Connor, 2004; Bill et al., 1992; Resnick et al., 1992) and collaborative learning (Gweon et al., 2007; Joshi & Rosé, 2007; Rummel & Diziol, 2008).  We note that, although the classroom discourse and collaborative learning communities have proceeded mainly independently from one another, the conversational processes identified as valuable within these two communities are strongly overlapping.   
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In our re-named Social-Communicative Factors thrust, we propose now to expand our investigations of communication as a core enabler of robust learning to include detailed study of patterns of interaction, the role of conversation and structured talk in initiating and sustaining learning, and the effects on motivation, self-attribution and commitment to a learning group that are associated with learning through social-communicative interaction.  Specifically, we propose to investigate how human linguistic interaction works in instruction and learning, and how participants in learning exchanges (both teachers and students) can best be taught productive forms of interaction.  We draw from our extensive prior work related separately to classroom discourse (Chapin & O’Connor, 2004; Bill et al., 1992; Resnick et al., 1992) and collaborative learning (Gweon et al., 2007; Joshi & Rose, 2007; Rummel & Diziol, 2008).  We note that, although the classroom discourse and collaborative learning communities have proceeded mainly independently from one another, the conversational processes identified as valuable within these two communities are strongly overlapping.   
  
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Investigations of valuable conversational contributions have been conducted both within communities exploring the cognitive foundations of group learning and the sociocultural community.  Regardless of the theoretical framework, the same ideas have surfaced under a number of different names including [[Accountable Talk]] (Michaels, O’Connor & Resnick, 2007; Resnick, O'Connor, & Michaels, 2007), transactivity (Berkowitz & Gibbs, 1984; Teasley, 1997; Weinberger & Fishcer, 2006; King, 1999), productive agency (Schwartz, 1999), and uptake (Suthers, 2006), and have been demonstrated to predict learning both in collaborative learning contexts (Azimita & Montgomery, 1993; Joshi & Rosé, 2007) and classroom contexts  (O’Connor et al., 2007).  For example, one cognitive justification for the value of transactive conversational behavior is its connection with cognitive conflict (Piaget, 1985), where transactive conversational moves highlight differences between the mental models of collaborating students.  One can argue that a major cognitive benefit of collaborative learning is that when students bring differing perspectives to a problem-solving situation, the interaction causes the participants to consider questions that might not have occurred to them otherwise.  This stimulus could cause them to identify gaps in their understanding, which they would then be in a position to address.  This type of cognitive conflict has the potential to lead to productive shifts in student understanding.  It has the potential to elicit elaborate explanations from students that are associated with learning (Webb, Nemer, & Zuniga 2002). From the sociocultural perspective, based on Vygotsky’s seminal work (Vygotsky 1978), we can similarly argue that when students who have different strengths and weaknesses work together, they can provide support for each other that allows them to solve problems that would be just beyond their reach if they were working alone.   
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Investigations of valuable conversational contributions have been conducted both within communities exploring the cognitive foundations of group learning and the sociocultural community.  Regardless of the theoretical framework, the same ideas have surfaced under a number of different names including [[Accountable Talk]] (Michaels, O’Connor & Resnick, 2007; Resnick, O'Connor, & Michaels, 2007), transactivity (Berkowitz & Gibbs, 1984; Teasley, 1997; Weinberger & Fishcer, 2006; King, 1999), productive agency (Schwartz, 1999), and uptake (Suthers, 2006), and have been demonstrated to predict learning both in collaborative learning contexts (Azimita & Montgomery, 1993; Joshi & Rose, 2007) and classroom contexts  (O’Connor et al., 2007).  For example, one cognitive justification for the value of transactive conversational behavior is its connection with cognitive conflict (Piaget, 1985), where transactive conversational moves highlight differences between the mental models of collaborating students.  One can argue that a major cognitive benefit of collaborative learning is that when students bring differing perspectives to a problem-solving situation, the interaction causes the participants to consider questions that might not have occurred to them otherwise.  This stimulus could cause them to identify gaps in their understanding, which they would then be in a position to address.  This type of cognitive conflict has the potential to lead to productive shifts in student understanding.  It has the potential to elicit elaborate explanations from students that are associated with learning (Webb, Nemer, & Zuniga 2002). From the sociocultural perspective, based on Vygotsky’s seminal work (Vygotsky 1978), we can similarly argue that when students who have different strengths and weaknesses work together, they can provide support for each other that allows them to solve problems that would be just beyond their reach if they were working alone.   
  
 
We will proceed with two interacting research strategies: one, expanding capacities for recording, coding and analyzing interactive communication that can be at least partially automated; and two, conducting in vivo experiments on ways of teaching participants the most promising patterns of interactive communication and testing the effects of these patterns on measures of robust learning.
 
We will proceed with two interacting research strategies: one, expanding capacities for recording, coding and analyzing interactive communication that can be at least partially automated; and two, conducting in vivo experiments on ways of teaching participants the most promising patterns of interactive communication and testing the effects of these patterns on measures of robust learning.
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In the second thread of our proposed work, we will examine causal connections between these communicative processes and learning by running in vivo experiments in which specific social-communicative practices are introduced into well-defined mathematics and science units of study.  We will begin by replicating and extending a series of in vivo experiments on the effects of [[Accountable Talk]] in low-income urban classrooms with high proportions of English language learners in Chelsea, Massachusetts (O’Connor et al 2007; NHSF REC 0231893, PI: O’Connor).  In a tightly controlled series of three-day studies in 5th and 6th grade classrooms, O’Connor’s group sought to determine whether it was possible to get evidence supporting a hypothesized causal relationship between selected discourse-intensive instructional practices and student mathematics learning.  In previous non-experimental studies in Chelsea, students had shown large gains on standardized tests after a year or more of discourse-intensive instruction, but it was not possible to test the specific features of the intervention that produced these effects.  Thus it was possible that cognitive and metacognitive abilities might improve over months of practice in clarifying, justifying and describing mathematical ideas, whether or not explicit transactive communication strategies were employed.  Similarly, student motivation might have improved due to long-term participation in an intensive mathematics program, without a specific impact of particular forms of linguistic participation.   
 
In the second thread of our proposed work, we will examine causal connections between these communicative processes and learning by running in vivo experiments in which specific social-communicative practices are introduced into well-defined mathematics and science units of study.  We will begin by replicating and extending a series of in vivo experiments on the effects of [[Accountable Talk]] in low-income urban classrooms with high proportions of English language learners in Chelsea, Massachusetts (O’Connor et al 2007; NHSF REC 0231893, PI: O’Connor).  In a tightly controlled series of three-day studies in 5th and 6th grade classrooms, O’Connor’s group sought to determine whether it was possible to get evidence supporting a hypothesized causal relationship between selected discourse-intensive instructional practices and student mathematics learning.  In previous non-experimental studies in Chelsea, students had shown large gains on standardized tests after a year or more of discourse-intensive instruction, but it was not possible to test the specific features of the intervention that produced these effects.  Thus it was possible that cognitive and metacognitive abilities might improve over months of practice in clarifying, justifying and describing mathematical ideas, whether or not explicit transactive communication strategies were employed.  Similarly, student motivation might have improved due to long-term participation in an intensive mathematics program, without a specific impact of particular forms of linguistic participation.   
  
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We will design and run in vivo experiments to test more specific hypotheses concerning specific [[Accountable Talk]] moves.  Subsequent studies will test a larger intervention that includes training in the most effective conversational moves and collaborative scripts with implementation in a number of classrooms.  The studies will focus on math and science learning topics. These studies will make use of techniques from automatic collaborative learning process analysis (Rosé et al., in press; Wang et al., 2007; Donmez et al., 2005) and script-based support for productive collaboration (Dillenbourg & Jermann, 2007; Kollar, Fischer, & Hesse, 2006; Rummel & Spada, 2007; Diziol, Rummel, Kahrimanis, Spada & Avaris, 2008; Diziol et al., 2008; Walker, Rummel, McLaren & Koedinger, 2007) to carefully manipulate these properties of conversation in highly controlled and context sensitive ways.
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We will design and run in vivo experiments to test more specific hypotheses concerning specific [[Accountable Talk]] moves.  Subsequent studies will test a larger intervention that includes training in the most effective conversational moves and collaborative scripts with implementation in a number of classrooms.  The studies will focus on math and science learning topics. These studies will make use of techniques from automatic collaborative learning process analysis (Rose et al., in press; Wang et al., 2007; Donmez et al., 2005) and script-based support for productive collaboration (Dillenbourg & Jermann, 2007; Kollar, Fischer, & Hesse, 2006; Rummel & Spada, 2007; Diziol, Rummel, Kahrimanis, Spada & Avaris, 2008; Diziol et al., 2008; Walker, Rummel, McLaren & Koedinger, 2007) to carefully manipulate these properties of conversation in highly controlled and context sensitive ways.
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== Descendants ==
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To create a new project page, enclose your project name in a double set of brackets.  Details for a project format may be [[ Project_Page_Template_and_Creation_Instructions | found here.]]
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*[[Rose - Integrated framework for analysis of classroom discussions]]
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*[[Features of Adaptive Assistance that Improve Peer Tutoring in Algebra (Walker, Rummel, Koedinger)]]
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*[[Resnick Project]]
  
 
== References ==
 
== References ==
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* Chi, M.T., Roy, M., & Hausmann, R.G. (March, 2008). Observing tutorial dialogues collaboratively: Insights about human tutoring effectiveness from vicarious learning. Cognitive Science: A Multidisciplinary Journal, 32:2, 301-341.  [[Media:Chi_Observing_Tutorial_Dialogues.pdf | Click to download]]
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* Michaels, S., O’Connor, C., & Resnick, L. B. (2008). Deliberative discourse idealized and realized: Accountable talk in the classroom and in civic life. Studies in the Philosophy of Education, 27(4), 283-297.
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* Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2, 63-86. [[Media: Meier_Rating_Scheme.pdf| Click to download]]
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* Resnick, L., O'Connor, C., and Michaels, S. (2007). Classroom Discourse, Mathematical Rigor, and Student Reasoning: An Accountable Talk Literature Review.[[Media: Accountable_Talk_Lit_Review.pdf | Click to download]]
 
* Resnick, L., O'Connor, C., and Michaels, S. (2007). Classroom Discourse, Mathematical Rigor, and Student Reasoning: An Accountable Talk Literature Review.[[Media: Accountable_Talk_Lit_Review.pdf | Click to download]]
  
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* Walker, E., Rummel, N., & Koedinger, K. (2008). A Research-Oriented Architecture for Providing Adaptive Collaborative Learning Support  [[Media: Walker_Architecture_for_Learing.pdf‎ | Click to download]]
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* Rose, C., et al. (2007). Analyzing collaborative learning processes automatically: Exploiting the advance of computational linguistics in computer-supported collaborative learning. [[Media: Rose_Analyzing_Collaborative.pdf | Click to download]]
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* Walker, E., Rummel, N., & Koedinger, K. (2008). A Research-Oriented Architecture for Providing Adaptive Collaborative Learning Support  [[Media: Walker_Architecture_for_Learing.pdf? | Click to download]]
  
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* Chi, M.T., Roy, M., & Hausmann, R.G. (March, 2008). Observing tutorial dialogues collaboratively: Insights about human tutoring effectiveness from vicarious learning. Cognitive Science: A Multidisciplinary Journal, 32:2, 301-341. (Abstract-pdf)
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* Yamakawa,Y., Forman, E., and Ansell, E. (2005). The role of positioning in constructing an identity in a third grade mathematics classroom. [[Media: Yamakawa_role_of_positioning.pdf| Click to download]]
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* Walker, E., Rummel, N., & Koedinger, K. (2008). A Research-Oriented Architecture for Providing Adaptive Collaborative Learning Support (Abstract-pdf)
 
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* Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2, 63-86. (Abstract-pdf)
 
  
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* Rose, C., et al. (2007). Analyzing collaborative learning processes automatically: Exploiting the advance of computational linguistics in computer-supported collaborative learning. (Abstract-pdf)  
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[[Link title]]== Other recommended readings on the role of classroom dialogue in learning and development==
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* Adey, P.S. & Shayer, M. (1990). Accelerating the development of formal thinking in middle and high school students. Journal of Research in Science Teaching, 27(31), 267 - 285.
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* Adey, P. & Shayer, M. (1993). An Exploration of Long-Term Far-Transfer Effects Following an Extended Intervention Program in the High School Science Curriculum. Cognition & Instruction, 11, 1 - 29.
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* Adey, P., & Shayer, M. (2001). Thinking Science. London: Nelson Thormes.
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* Adey, P. (2005). Issues arising from the long-term evaluation of cognitive acceleration programs. Research in Science Education, 35, 3-22.
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* Adey, P.S. & Shayer, M. (1994). Really Raising Standards: cognitive intervention and academic achievement. London: Routledge.
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* [http://www.robinalexander.org.uk Alexander, R.] (2000) Culture and pedagogy: International comparisons in primary education Blackwell , Oxford.
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* Alexander, R. (2008) Towards teaching: Rethinking classroom talk. 4th ed., Dialogos , York, England
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* [http://www.robinalexander.org.uk Alexander, R.] Mercer, N. and Hodgkinson, S. (eds) (2005) [[Media: Robinalexander_IACEP_2005.pdf | Culture, dialogue and learning: Notes on an emerging pedagogy. Exploring talk in school]] Sage , London.
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* Anderson, R. C., Chinn, C., Waggoner, M., Nquyen, K. (1998). Intellectually stimulating story discussions. In  J. Osborn & F. Lehr (Eds), Literacy for all: Issues in teaching and learning (170-187). New York, NY: Guilford Press.
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* Anderson. R. C.,  Chinn, C., Chang, J., Waggoner, M., & Yi, H. (1997). On the Logical Integrity of Children's Arguments. Cognition and Instruction, 15 (2 ), 135 – 167.
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* Applebee, A. N., Langer, J. A., Nystrand, M., & Gamoran, A. (2003). Discussion-Based Approaches to Developing Understanding: Classroom Instruction and Student Performance in Middle and High School English. American Educational Research Journal, 40, 685-730.
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* Asterhan, C. S. C., &  Schwarz, B. B. (2009). Transformation of robust misconceptions through peer argumentation. In: B. B. Schwarz, T. Dreyfus, & R. Hershkowitz (Eds.) Guided Transformation of Knowledge in Classrooms (159-172). New York, NY: Routledge, Advances in Learning & Instruction series.
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* Asterhan, C. S. C. & Schwarz, B. B. (in press). Online human guidance of small group discussions: The case of synchronous e-argumentation in a diagram-based discussion space. International Journal of Computer-Supported Collaborative Learning.
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* Asterhan, C. S. C. &  Schwarz, B. B. (2009). Argumentation and explanation in conceptual change: Indications from protocol analyses of peer-to-peer dialogue. Cognitive Science, 33, 373-399.
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* Asterhan, C. S. C. & Schwarz, B. B. (2007). The effects of monological and dialogical argumentation on concept learning in evolutionary theory. Journal of Educational Psychology, 99, 626-639.
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* Ball, D. L., & Bass, H. (2000). Making believe: the collective construction of public mathematical knowledge in the elementary classroom. In D. Phillips (Ed.), Yearbook of the national society for the study of education, Constructivism in education. (pp. 193–224). Chicago: University of Chicago Press.
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* Beck, I. L., & McKeown, M. G., (2006). Improving comprehension with Questioning the Author: A fresh and expanded view of a powerful approach. NY: Scholastic.
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* Bernstein, B. (1971/2003). Class, Codes and Control: Theoretical studies towards a sociology of language. London, UK: Routledge.
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* Bill, V. L., Leer, M. N., Reams, L. E., & Resnick, L. B. (1992). From cupcakes to equations:  The structure of discourse in a primary mathematics classroom. Verbum, 15(1), 63-85
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* Boaler, J. (2006). How a Detracked Mathematics Approach Promoted Respect, Responsibility, and High Achievement. Theory Into Practice, 45(1), p40-46.
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* Brown, A. L., & Palincsar, A. S. (1989). Guided, cooperative learning and individual knowledge acquisition. In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 393-451). Hillsdale, NJ: Erlbaum. Cambridge, MA: Harvard University Press.
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* Cazden, C. (2001). Classroom discourse: The language of teaching and learning. Portsmouth, NH: Heinemann.
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* Chapin, S. & O’Connor, M.C.  (2004). Project Challenge: Identifying and developing talent in mathematics within low-income urban schools. Boston University School of Education Research Report No. 1, 1-6.
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* Chi, M. T. H., de Leeuw, N., Chiu, M., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.
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* Chi, M. T. H., Roy, M., & Hausmann, R. G. M. (2008). Observing tutorial dialogues collaboratively: Insights about human tutoring effectivness from vicarious learning. Cognitive Science, 33, 301–341.
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* Chi, M.T.H., Siler, S., Jeong, H., Yamauchi, T., & Hausmann, R. (2001). Learning from human tutoring. Cognitive Science, 25, 471-534.
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* Chin, C. & Osborne, J. (in press). Supporting argumentation through students’ questions: Case studies in science classrooms. To appear in the Journal of the Learning Sciences.
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* Chinn, C. A., & Anderson, R. C. (1998). The structure of discussions that promote reasoning. Teachers College Record, 100, 315–368.
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* Cobb, P., Wood, T., Yackel, E., Nicholls, J., Wheatley, G., Trigatti, B., et al. (1991). Assessment of a Problem-Centered Second-Grade Mathematics Project. Journal for Research in Mathematics Education, 22(1), 3-29.
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* Coleman, E. B. (1998). Using explanatory knowledge during problem solving in science. Journal of the Learning Sciences, 7, 387–427.
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* DeVries, E., Lund, K., & Baker, M. (2002). Computer-mediated epistemic dialogue: Explanation and argumentation as vehicles for understanding scientific notions. Journal of the Learning Sciences, 11, 63–103.
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* Driver, R., Newton, P., Osborne, J. Establishing the norms of scientific argumentation in classrooms.
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* Duschl, R. A., & Osborne, J. (2002). Supporting and promoting argumentation discourse in science education. Studies in Science Education, 38,39–72.
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* Engle, R. A. & Conant, F. C. (2002). Guiding principles for fostering productive disciplinary engagement: Explaining an emergent argument in a community of learners classroom. Cognition & Instruction, 20(4), 399-483.
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* Felton, M. & Kuhn, D. (2001) The Development of argumentive discourse skill. Discourse Processes, 32(2&3), 135–153
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* Ford, M. J., & Forman, E. A. (2006). Redefining disciplinary learning in classroom contexts. In J. Green & A. Luke (Eds.), Review of Research in Education (Vol. 30, pp. 1-32). Washington, DC: American Educational Research Association.
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* Gee, J. P. (1996).  Social linguistics and literacies: Ideology in discourses. Bristol, PA: Taylor & Francis.
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* Gillies, R. M. (2004). The effects of communication training on teachers’and students’verbal behaviours during cooperative learning. International Journal of Educational Research, 41, 257–279.
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* Goldberg, T., Schwarz, B. B., & Porat, D (2008). Living and dormant collective memories as contexts of history learning. Learning and Instruction, 18, 223-237.
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* Hart, B., & Risley, R. T. (1995). Meaningful differences in the everyday experience of young American children. Baltimore: Paul H. Brookes.
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* Howe, C., Tolmie, A., Duchak-Tanner, V., & Rattay, C. (2000). Hypothesis-testing in science: Group consensus and the acquisition of conceptual and procedural knowledge. Learning & Instruction, 10, 361-391.
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* Hugener, I., Pauli, C., Reusser, K., Lipowsky, F., Rakoczy, K., & Klieme, E. (2009). Teaching patterns and learning quality in Swiss and German mathematics lessons. Learning and Instruction, 19(1), 66-78.
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* Iordanou, K. & Kuhn, D. (2009). Arguing on the computer in scientific and non-scientific domains. In C. O'Malley, D. Suthers, P. Reimann & A. Dimitracopoulou (Eds), Computer-Supported Collaborative Learning Practices: CSCL2009 Conference Proceedings (pp. 576-585). [http://www.bestessayhelp.com custom writing services]
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* King, A., & Rosenshine, B. (1993). Effects of guided cooperative questioning on children’s knowledge construction. Journal of ExperimentalEducation, 61, 127–148.
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* Kuhn, D. & Udell, W. (2003). The Development of Argument Skills. Child Development, 74 (5), 1245-1260.
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* Kuhn, D. (1999). A developmental model of critical thinking.  Educational Researcher, 28, 16-25.[http://www.bestessayhelp.com/essay-help/buy-essay buy essays online]
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* Kuhn, D., Shaw, V., & Felton, M. (1997). Effects of dyadic interaction on argumentative reasoning. Cognition and Instruction, 15, 287–315.
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* Lefstein, A. & Snell, J. (in press). Classroom Discourse: The Promise and Complexity of Dialogic Practice. To appear in : S. Ellis, E. McCartney, J. Bourne (Eds), Insight and Impact: Applied Linguistics and the Primary School, Cambridge, UK: Cambridge University Press
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* Lipman, M. (1975). Philosophy for Children. . ERIC Document Reproduction Service No. ED103296.
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* Mason, L. (1998). Sharing cognition to construct scientific knowledge in school context: The role of oral and written discourse Instructional Science, 26: 359–389.
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* McKeown, M. G., Beck, I., & Blake, R. G. K. (2009). Rethinking reading comprehension instruction: A comparison of instruction for strategies and content approaches. Reading Research Quarterly, 44, 218-253.
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* Mercer, N., Dawes, L et al. (2004). Reasoning as a Scientist: Ways of Helping Children to Use Language to Learn Science. British Educational Research Journal, 30(3): 359-377.
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* Mercer, N., Dawes, L., Wegerif, R., & Sams, C. (2004). Reasoning as a scientist: Ways of helping children to use language to learn science. British Educational Research Journal, 30, 359–377.
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* Mercer, N. & Littleton, K. (2007) Dialogue and the Development of Children's Thinking: a sociocultural approach. London: Routledge.
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* Mercer, N., Wegerif, R. & Dawes, L. (1999). Children's Talk and the Development of Reasoning in the Classroom. British Educational Research Journal, 25, 95-111.
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* Murphy, P. K., Wilkinson, I.A.G., Soter, A. o., Henessey, M. N., & Alexander, J. F. (2009). Examining the effects of classroom discussion on students’ comprehension of text: A meta-analysis. Journal of Educational Psychology, 101, 740-764.
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* Nussbaum, E. M., & Sinatra, G. M. (2003). Argument and conceptual engagement. Contemporary Educational Psychology, 28, 384–395.
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* Nystrand, M. & Gamoran, A. (1991). Instructional Discourse, Student Engagement, Literature Achievement. Research in the Teaching of English, 25(3): 261-290.
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* Palincsar, A-M., & Brown A. L. (1984). Reciprocal Teaching of Comprehension-Fostering and Comprehension-Monitoring Activities. Cognition & Instruction, 1(2) 117-175
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* Pontecorvo, C., & Girardet, H. (1993). Arguing and reasoning in understanding historical topics. Cognition and Instruction, 11, 365-395.
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* Resnick, L. B., & Nelson-Le Gall, S.  (1997).  Socializing intelligence.  In L. Smith, J. Dockrell, & P.
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Eds.), Piaget, Vygotsky and beyond (pp. 145-158).  London/New York: Routledge.
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* Resnick, L. B., Bill, V., Lesgold, S., & Leer, M. (1991). Thinking in arithmetic class. In B. Means, C. Chelemer, & M. S. Knapp (Eds.), Teaching advanced skills to at-risk students: Views from research and practice (pp. 27-53). San Francisco: Jossey-Bass.
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* Resnick, L.B., Michaels, S., & O’Connor, C. (in press). How (well structured) talk builds the mind. In R. Sternberg & D. Preiss (Eds.), From Genes to Context: New Discoveries about Learning from Educational Research and Their Applications. New York: Springer.
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* Resnick, L. B., Salmon, M. H., Zeitz, C. M., Wathen, S. H., & Holowchak, M. (1993). Reasoning in conversation. Cognition and Instruction, 11, 347-364.
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* Reznitskaya, A., Anderson, R. C., McNurlen, B., Nguyen-Jahiel, K., Archodidou, A., & Kim, S. (2001). Influence of oral discussion on written argument. Discourse Processes, 32(2-3), 155-157.
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* Sandora, C., Beck, I. & McKeown, M. (1999). A comparison of two discussion strategies on students’ comprehension and interpretation of complex literature. Journal of Reading Psychology, 20, 177-212.
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* Schwarz, B. B., & Asterhan, C. S. C. (2010). Argumentation and Reasoning. To appear in: K. Littleton, C. Wood, & J. Kleine Staarman (Eds). International Handbook of Psychology in Education. Bingley, UK: Emerald Group Publishing. 
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* Schwarz, B. B. & Asterhan, C. S. C. (in press). E-moderation of synchronous discussions in educational settings: A nascent practice. Journal of the Learning Sciences.
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* Schwarz, B. B., Neuman, Y., & Biezuner, S. (2000). Two wrongs may make a right...if they argue together! Cognition & Instruction, 18, 461-494.
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* Seymour, J. R. & Lehrer, R. (2006). Tracing the evolution of pedagogical content knowledge as the development of interanimated discourses. Journal of the Learning Sciences, 15, 549-582.
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* Sfard, A. (2008). Thinking as communicating: Human development, the growth of discourses, and mathematizing. Cambridge, UK: Cambridge University Press.
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* Shayer, M. (1999). Cognitive acceleration through science education II: its effects and scope. International Journal of Science Education, 21(8), 883 - 902.
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* Simon, S. & Richardson, K. (2009). Argumentation in School Science: Breaking the Tradition of Authoritative Exposition Through a Pedagogy that Promotes Discussion and Reasoning. Argumentation, 23,469–493
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* Stein, M. K., Engle, R. A., Smith, M. S. & Hughes, E. K. (2008). Orchestrating Productive Mathematical Discussions: Five Practices for Helping Teachers Move Beyond Show and Tell. Mathematical Thinking & Learning, 10, 313–340.
 +
* Topping, K. J. & S. Trickey (2007a). Collaborative philosophical enquiry for school children: Cognitive effects at 10-12 years. British Journal of Educational Psychology, 77, 271-288.
 +
* Topping, K. J. & Trickey, S. (2007b). Collaborative philosophical inquiry for schoolchildren: Cognitive gains at 2-year follow-up. British Journal of Educational Psychology, 77, 787-796.
 +
* Walshaw, M., & Anthony, G. (2008). The Teacher’s Role in Classroom Discourse: A Review of Recent Research Into Mathematics Classrooms. Review of Educational Research, 78(3), 516-551.
 +
* Webb, N. M. (2009). The teacher’s role in promoting collaborative dialogue in the classroom. British Journal of Educational Psychology, 79, 1-28.
 +
* Webb, N. M., & Palincsar, A. S. (1996). Group processes in the classroom. In D. Berliner & R. Calfee (Eds.), Handbook of educational psychology (pp. 841–873). New York, NY: Macmillan.
 +
* Webb, N., Franke, M. L., Ing, M., Chan, A., De, T., Freund, D., & Battey, D. (2009). The role of teacher instructional practices in student collaboration. Contemporary Educational Psychology, 33, 360-381.
 +
* Wegerif, N., Mercer, N. & Dawes, L. (1999). From social interaction to individual reasoning: an empirical investigation of a possible socio-cultural model of cognitive development. Learning & Instruction, 9. 493-516.
  
−
* Yamakawa,Y., Forman, E., and Ansell, E. (2005). The role of positioning in constructing an identity in a third grade mathematics classroom. (Abstract-pdf)
+
== Meeting Notes ==
 +
'''Social and Communicative Factors Thrust Workshop on Coding and Analysis of Classroom Dialogue, Pittsburgh May 26-27, 2011'''
 +
*''Effects of Social Metacognition on Micro-Creativity: Statistical Discourse Analyses of Group Problem Solving'' - Ming Ming Chiu [[Media:CHIU_-Social_Metacognition.pptx | Click to download]]
 +
*''Dialogue Analysis to Inform the Development of a Natural-language Tutoring System for Physics'' - Sandra Katz, Michael Ford, Pamela Jordan, Diane Litman
 +
*''Temporal patterns of knowledge construction: Statistical discourse analysis of a role-based online discussion'' - Ming Ming Chiu & Alyssa Wise [[Media:Knowledge_construction.pptx‎ | Click to download]]
 +
*''Analyzing Teacher-Led Talks: A Talk Map Representation'' - Gaowei Chen
 +
*''Towards Academically Productive Talk Supported by Conversational Agents'' - Carolyn Penstein Rosé, Lauren Resnick, Gregory Dyke, Iris Howley, Rohit Kumar [[Media:Bio-Analysis-Carolyn.pdf | Click to download]]
 +
*''What (if anything) about framing? Is it significant? Do we need to consider it?''- Jim Greeno [[Media:WorkshopSlides.pptx | Click to download]]
 +
*''Measuring Classroom Discussions'' - Rip Correnti, Moddy McKeown, Jimmy Scherrer, Peg Smith, Mary Kay Stein, Kevin Ashley, Jim Greeno

Latest revision as of 13:39, 4 April 2013

During PSLC’s first four years, its Interactive Communication Cluster has studied interactions between a student and a tutor (either human or computer) or, less frequently, two students interacting with each other. Most of the experimental manipulations and subsequent analyses have focused on the cognitive content of interaction through learning space analyses, in other words, the what and when of instruction. Study results investigating the effect of interaction, although somewhat mixed, have largely supported the hypothesis that focused interaction promotes cognitive aspects of learning such as attention to the most important knowledge components in a domain, deeper cognitive processing, and increased engagement with the content. VanLehn and colleagues (2007) present a thorough review of this literature as well as results from recent investigations. These results encouraged early PSLC efforts to “unpack” the nature of communicative interaction in instruction and learning. Rummel and colleagues (Diziol, Rummel, Kahrimanis, et al., 2008a, 2008b), for example have recently evaluated interactions with a rating scheme analysis that quantifies the quality of an interaction on a number of dimensions. This work represents an important step towards the type of up close inspection of communication that many scholars believe is necessary if we are to understand, and be able to manipulate for instructional purposes, how communication works to produce robust learning.

In our re-named Social-Communicative Factors thrust, we propose now to expand our investigations of communication as a core enabler of robust learning to include detailed study of patterns of interaction, the role of conversation and structured talk in initiating and sustaining learning, and the effects on motivation, self-attribution and commitment to a learning group that are associated with learning through social-communicative interaction. Specifically, we propose to investigate how human linguistic interaction works in instruction and learning, and how participants in learning exchanges (both teachers and students) can best be taught productive forms of interaction. We draw from our extensive prior work related separately to classroom discourse (Chapin & O’Connor, 2004; Bill et al., 1992; Resnick et al., 1992) and collaborative learning (Gweon et al., 2007; Joshi & Rose, 2007; Rummel & Diziol, 2008). We note that, although the classroom discourse and collaborative learning communities have proceeded mainly independently from one another, the conversational processes identified as valuable within these two communities are strongly overlapping.

Investigations of valuable conversational contributions have been conducted both within communities exploring the cognitive foundations of group learning and the sociocultural community. Regardless of the theoretical framework, the same ideas have surfaced under a number of different names including Accountable Talk (Michaels, O’Connor & Resnick, 2007; Resnick, O'Connor, & Michaels, 2007), transactivity (Berkowitz & Gibbs, 1984; Teasley, 1997; Weinberger & Fishcer, 2006; King, 1999), productive agency (Schwartz, 1999), and uptake (Suthers, 2006), and have been demonstrated to predict learning both in collaborative learning contexts (Azimita & Montgomery, 1993; Joshi & Rose, 2007) and classroom contexts (O’Connor et al., 2007). For example, one cognitive justification for the value of transactive conversational behavior is its connection with cognitive conflict (Piaget, 1985), where transactive conversational moves highlight differences between the mental models of collaborating students. One can argue that a major cognitive benefit of collaborative learning is that when students bring differing perspectives to a problem-solving situation, the interaction causes the participants to consider questions that might not have occurred to them otherwise. This stimulus could cause them to identify gaps in their understanding, which they would then be in a position to address. This type of cognitive conflict has the potential to lead to productive shifts in student understanding. It has the potential to elicit elaborate explanations from students that are associated with learning (Webb, Nemer, & Zuniga 2002). From the sociocultural perspective, based on Vygotsky’s seminal work (Vygotsky 1978), we can similarly argue that when students who have different strengths and weaknesses work together, they can provide support for each other that allows them to solve problems that would be just beyond their reach if they were working alone.

We will proceed with two interacting research strategies: one, expanding capacities for recording, coding and analyzing interactive communication that can be at least partially automated; and two, conducting in vivo experiments on ways of teaching participants the most promising patterns of interactive communication and testing the effects of these patterns on measures of robust learning.

In the first thread of our proposed work, we will work toward a common conceptual framework that unifies the classroom discourse, collaborative learning and instructional tutoring communities. To this end, we plan to develop a concrete and precise formalization on a linguistic level of what counts as performing these valued conversational moves. This concrete formalization will provide a common language for documenting and investigating the specific ways in which social-communicative practices can promote (or hinder) learning of complex mathematics and science content and reasoning skills.

In the second thread of our proposed work, we will examine causal connections between these communicative processes and learning by running in vivo experiments in which specific social-communicative practices are introduced into well-defined mathematics and science units of study. We will begin by replicating and extending a series of in vivo experiments on the effects of Accountable Talk in low-income urban classrooms with high proportions of English language learners in Chelsea, Massachusetts (O’Connor et al 2007; NHSF REC 0231893, PI: O’Connor). In a tightly controlled series of three-day studies in 5th and 6th grade classrooms, O’Connor’s group sought to determine whether it was possible to get evidence supporting a hypothesized causal relationship between selected discourse-intensive instructional practices and student mathematics learning. In previous non-experimental studies in Chelsea, students had shown large gains on standardized tests after a year or more of discourse-intensive instruction, but it was not possible to test the specific features of the intervention that produced these effects. Thus it was possible that cognitive and metacognitive abilities might improve over months of practice in clarifying, justifying and describing mathematical ideas, whether or not explicit transactive communication strategies were employed. Similarly, student motivation might have improved due to long-term participation in an intensive mathematics program, without a specific impact of particular forms of linguistic participation.

We will design and run in vivo experiments to test more specific hypotheses concerning specific Accountable Talk moves. Subsequent studies will test a larger intervention that includes training in the most effective conversational moves and collaborative scripts with implementation in a number of classrooms. The studies will focus on math and science learning topics. These studies will make use of techniques from automatic collaborative learning process analysis (Rose et al., in press; Wang et al., 2007; Donmez et al., 2005) and script-based support for productive collaboration (Dillenbourg & Jermann, 2007; Kollar, Fischer, & Hesse, 2006; Rummel & Spada, 2007; Diziol, Rummel, Kahrimanis, Spada & Avaris, 2008; Diziol et al., 2008; Walker, Rummel, McLaren & Koedinger, 2007) to carefully manipulate these properties of conversation in highly controlled and context sensitive ways.

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References

  • Chi, M.T., Roy, M., & Hausmann, R.G. (March, 2008). Observing tutorial dialogues collaboratively: Insights about human tutoring effectiveness from vicarious learning. Cognitive Science: A Multidisciplinary Journal, 32:2, 301-341. Click to download
  • Michaels, S., O’Connor, C., & Resnick, L. B. (2008). Deliberative discourse idealized and realized: Accountable talk in the classroom and in civic life. Studies in the Philosophy of Education, 27(4), 283-297.
  • Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2, 63-86. Click to download
  • Resnick, L., O'Connor, C., and Michaels, S. (2007). Classroom Discourse, Mathematical Rigor, and Student Reasoning: An Accountable Talk Literature Review. Click to download
  • Rose, C., et al. (2007). Analyzing collaborative learning processes automatically: Exploiting the advance of computational linguistics in computer-supported collaborative learning. Click to download
  • Walker, E., Rummel, N., & Koedinger, K. (2008). A Research-Oriented Architecture for Providing Adaptive Collaborative Learning Support Click to download
  • Yamakawa,Y., Forman, E., and Ansell, E. (2005). The role of positioning in constructing an identity in a third grade mathematics classroom. Click to download

Link title== Other recommended readings on the role of classroom dialogue in learning and development==

  • Adey, P.S. & Shayer, M. (1990). Accelerating the development of formal thinking in middle and high school students. Journal of Research in Science Teaching, 27(31), 267 - 285.
  • Adey, P. & Shayer, M. (1993). An Exploration of Long-Term Far-Transfer Effects Following an Extended Intervention Program in the High School Science Curriculum. Cognition & Instruction, 11, 1 - 29.
  • Adey, P., & Shayer, M. (2001). Thinking Science. London: Nelson Thormes.
  • Adey, P. (2005). Issues arising from the long-term evaluation of cognitive acceleration programs. Research in Science Education, 35, 3-22.
  • Adey, P.S. & Shayer, M. (1994). Really Raising Standards: cognitive intervention and academic achievement. London: Routledge.
  • Alexander, R. (2000) Culture and pedagogy: International comparisons in primary education Blackwell , Oxford.
  • Alexander, R. (2008) Towards teaching: Rethinking classroom talk. 4th ed., Dialogos , York, England
  • Alexander, R. Mercer, N. and Hodgkinson, S. (eds) (2005) Culture, dialogue and learning: Notes on an emerging pedagogy. Exploring talk in school Sage , London.
  • Anderson, R. C., Chinn, C., Waggoner, M., Nquyen, K. (1998). Intellectually stimulating story discussions. In J. Osborn & F. Lehr (Eds), Literacy for all: Issues in teaching and learning (170-187). New York, NY: Guilford Press.
  • Anderson. R. C., Chinn, C., Chang, J., Waggoner, M., & Yi, H. (1997). On the Logical Integrity of Children's Arguments. Cognition and Instruction, 15 (2 ), 135 – 167.
  • Applebee, A. N., Langer, J. A., Nystrand, M., & Gamoran, A. (2003). Discussion-Based Approaches to Developing Understanding: Classroom Instruction and Student Performance in Middle and High School English. American Educational Research Journal, 40, 685-730.
  • Asterhan, C. S. C., & Schwarz, B. B. (2009). Transformation of robust misconceptions through peer argumentation. In: B. B. Schwarz, T. Dreyfus, & R. Hershkowitz (Eds.) Guided Transformation of Knowledge in Classrooms (159-172). New York, NY: Routledge, Advances in Learning & Instruction series.
  • Asterhan, C. S. C. & Schwarz, B. B. (in press). Online human guidance of small group discussions: The case of synchronous e-argumentation in a diagram-based discussion space. International Journal of Computer-Supported Collaborative Learning.
  • Asterhan, C. S. C. & Schwarz, B. B. (2009). Argumentation and explanation in conceptual change: Indications from protocol analyses of peer-to-peer dialogue. Cognitive Science, 33, 373-399.
  • Asterhan, C. S. C. & Schwarz, B. B. (2007). The effects of monological and dialogical argumentation on concept learning in evolutionary theory. Journal of Educational Psychology, 99, 626-639.
  • Ball, D. L., & Bass, H. (2000). Making believe: the collective construction of public mathematical knowledge in the elementary classroom. In D. Phillips (Ed.), Yearbook of the national society for the study of education, Constructivism in education. (pp. 193–224). Chicago: University of Chicago Press.
  • Beck, I. L., & McKeown, M. G., (2006). Improving comprehension with Questioning the Author: A fresh and expanded view of a powerful approach. NY: Scholastic.
  • Bernstein, B. (1971/2003). Class, Codes and Control: Theoretical studies towards a sociology of language. London, UK: Routledge.
  • Bill, V. L., Leer, M. N., Reams, L. E., & Resnick, L. B. (1992). From cupcakes to equations: The structure of discourse in a primary mathematics classroom. Verbum, 15(1), 63-85
  • Boaler, J. (2006). How a Detracked Mathematics Approach Promoted Respect, Responsibility, and High Achievement. Theory Into Practice, 45(1), p40-46.
  • Brown, A. L., & Palincsar, A. S. (1989). Guided, cooperative learning and individual knowledge acquisition. In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 393-451). Hillsdale, NJ: Erlbaum. Cambridge, MA: Harvard University Press.
  • Cazden, C. (2001). Classroom discourse: The language of teaching and learning. Portsmouth, NH: Heinemann.
  • Chapin, S. & O’Connor, M.C. (2004). Project Challenge: Identifying and developing talent in mathematics within low-income urban schools. Boston University School of Education Research Report No. 1, 1-6.
  • Chi, M. T. H., de Leeuw, N., Chiu, M., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.
  • Chi, M. T. H., Roy, M., & Hausmann, R. G. M. (2008). Observing tutorial dialogues collaboratively: Insights about human tutoring effectivness from vicarious learning. Cognitive Science, 33, 301–341.
  • Chi, M.T.H., Siler, S., Jeong, H., Yamauchi, T., & Hausmann, R. (2001). Learning from human tutoring. Cognitive Science, 25, 471-534.
  • Chin, C. & Osborne, J. (in press). Supporting argumentation through students’ questions: Case studies in science classrooms. To appear in the Journal of the Learning Sciences.
  • Chinn, C. A., & Anderson, R. C. (1998). The structure of discussions that promote reasoning. Teachers College Record, 100, 315–368.
  • Cobb, P., Wood, T., Yackel, E., Nicholls, J., Wheatley, G., Trigatti, B., et al. (1991). Assessment of a Problem-Centered Second-Grade Mathematics Project. Journal for Research in Mathematics Education, 22(1), 3-29.
  • Coleman, E. B. (1998). Using explanatory knowledge during problem solving in science. Journal of the Learning Sciences, 7, 387–427.
  • DeVries, E., Lund, K., & Baker, M. (2002). Computer-mediated epistemic dialogue: Explanation and argumentation as vehicles for understanding scientific notions. Journal of the Learning Sciences, 11, 63–103.
  • Driver, R., Newton, P., Osborne, J. Establishing the norms of scientific argumentation in classrooms.
  • Duschl, R. A., & Osborne, J. (2002). Supporting and promoting argumentation discourse in science education. Studies in Science Education, 38,39–72.
  • Engle, R. A. & Conant, F. C. (2002). Guiding principles for fostering productive disciplinary engagement: Explaining an emergent argument in a community of learners classroom. Cognition & Instruction, 20(4), 399-483.
  • Felton, M. & Kuhn, D. (2001) The Development of argumentive discourse skill. Discourse Processes, 32(2&3), 135–153
  • Ford, M. J., & Forman, E. A. (2006). Redefining disciplinary learning in classroom contexts. In J. Green & A. Luke (Eds.), Review of Research in Education (Vol. 30, pp. 1-32). Washington, DC: American Educational Research Association.
  • Gee, J. P. (1996). Social linguistics and literacies: Ideology in discourses. Bristol, PA: Taylor & Francis.
  • Gillies, R. M. (2004). The effects of communication training on teachers’and students’verbal behaviours during cooperative learning. International Journal of Educational Research, 41, 257–279.
  • Goldberg, T., Schwarz, B. B., & Porat, D (2008). Living and dormant collective memories as contexts of history learning. Learning and Instruction, 18, 223-237.
  • Hart, B., & Risley, R. T. (1995). Meaningful differences in the everyday experience of young American children. Baltimore: Paul H. Brookes.
  • Howe, C., Tolmie, A., Duchak-Tanner, V., & Rattay, C. (2000). Hypothesis-testing in science: Group consensus and the acquisition of conceptual and procedural knowledge. Learning & Instruction, 10, 361-391.
  • Hugener, I., Pauli, C., Reusser, K., Lipowsky, F., Rakoczy, K., & Klieme, E. (2009). Teaching patterns and learning quality in Swiss and German mathematics lessons. Learning and Instruction, 19(1), 66-78.
  • Iordanou, K. & Kuhn, D. (2009). Arguing on the computer in scientific and non-scientific domains. In C. O'Malley, D. Suthers, P. Reimann & A. Dimitracopoulou (Eds), Computer-Supported Collaborative Learning Practices: CSCL2009 Conference Proceedings (pp. 576-585). custom writing services
  • King, A., & Rosenshine, B. (1993). Effects of guided cooperative questioning on children’s knowledge construction. Journal of ExperimentalEducation, 61, 127–148.
  • Kuhn, D. & Udell, W. (2003). The Development of Argument Skills. Child Development, 74 (5), 1245-1260.
  • Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28, 16-25.buy essays online
  • Kuhn, D., Shaw, V., & Felton, M. (1997). Effects of dyadic interaction on argumentative reasoning. Cognition and Instruction, 15, 287–315.
  • Lefstein, A. & Snell, J. (in press). Classroom Discourse: The Promise and Complexity of Dialogic Practice. To appear in : S. Ellis, E. McCartney, J. Bourne (Eds), Insight and Impact: Applied Linguistics and the Primary School, Cambridge, UK: Cambridge University Press
  • Lipman, M. (1975). Philosophy for Children. . ERIC Document Reproduction Service No. ED103296.
  • Mason, L. (1998). Sharing cognition to construct scientific knowledge in school context: The role of oral and written discourse Instructional Science, 26: 359–389.
  • McKeown, M. G., Beck, I., & Blake, R. G. K. (2009). Rethinking reading comprehension instruction: A comparison of instruction for strategies and content approaches. Reading Research Quarterly, 44, 218-253.
  • Mercer, N., Dawes, L et al. (2004). Reasoning as a Scientist: Ways of Helping Children to Use Language to Learn Science. British Educational Research Journal, 30(3): 359-377.
  • Mercer, N., Dawes, L., Wegerif, R., & Sams, C. (2004). Reasoning as a scientist: Ways of helping children to use language to learn science. British Educational Research Journal, 30, 359–377.
  • Mercer, N. & Littleton, K. (2007) Dialogue and the Development of Children's Thinking: a sociocultural approach. London: Routledge.
  • Mercer, N., Wegerif, R. & Dawes, L. (1999). Children's Talk and the Development of Reasoning in the Classroom. British Educational Research Journal, 25, 95-111.
  • Murphy, P. K., Wilkinson, I.A.G., Soter, A. o., Henessey, M. N., & Alexander, J. F. (2009). Examining the effects of classroom discussion on students’ comprehension of text: A meta-analysis. Journal of Educational Psychology, 101, 740-764.
  • Nussbaum, E. M., & Sinatra, G. M. (2003). Argument and conceptual engagement. Contemporary Educational Psychology, 28, 384–395.
  • Nystrand, M. & Gamoran, A. (1991). Instructional Discourse, Student Engagement, Literature Achievement. Research in the Teaching of English, 25(3): 261-290.
  • Palincsar, A-M., & Brown A. L. (1984). Reciprocal Teaching of Comprehension-Fostering and Comprehension-Monitoring Activities. Cognition & Instruction, 1(2) 117-175
  • Pontecorvo, C., & Girardet, H. (1993). Arguing and reasoning in understanding historical topics. Cognition and Instruction, 11, 365-395.
  • Resnick, L. B., & Nelson-Le Gall, S. (1997). Socializing intelligence. In L. Smith, J. Dockrell, & P.

Eds.), Piaget, Vygotsky and beyond (pp. 145-158). London/New York: Routledge.

  • Resnick, L. B., Bill, V., Lesgold, S., & Leer, M. (1991). Thinking in arithmetic class. In B. Means, C. Chelemer, & M. S. Knapp (Eds.), Teaching advanced skills to at-risk students: Views from research and practice (pp. 27-53). San Francisco: Jossey-Bass.
  • Resnick, L.B., Michaels, S., & O’Connor, C. (in press). How (well structured) talk builds the mind. In R. Sternberg & D. Preiss (Eds.), From Genes to Context: New Discoveries about Learning from Educational Research and Their Applications. New York: Springer.
  • Resnick, L. B., Salmon, M. H., Zeitz, C. M., Wathen, S. H., & Holowchak, M. (1993). Reasoning in conversation. Cognition and Instruction, 11, 347-364.
  • Reznitskaya, A., Anderson, R. C., McNurlen, B., Nguyen-Jahiel, K., Archodidou, A., & Kim, S. (2001). Influence of oral discussion on written argument. Discourse Processes, 32(2-3), 155-157.
  • Sandora, C., Beck, I. & McKeown, M. (1999). A comparison of two discussion strategies on students’ comprehension and interpretation of complex literature. Journal of Reading Psychology, 20, 177-212.
  • Schwarz, B. B., & Asterhan, C. S. C. (2010). Argumentation and Reasoning. To appear in: K. Littleton, C. Wood, & J. Kleine Staarman (Eds). International Handbook of Psychology in Education. Bingley, UK: Emerald Group Publishing.
  • Schwarz, B. B. & Asterhan, C. S. C. (in press). E-moderation of synchronous discussions in educational settings: A nascent practice. Journal of the Learning Sciences.
  • Schwarz, B. B., Neuman, Y., & Biezuner, S. (2000). Two wrongs may make a right...if they argue together! Cognition & Instruction, 18, 461-494.
  • Seymour, J. R. & Lehrer, R. (2006). Tracing the evolution of pedagogical content knowledge as the development of interanimated discourses. Journal of the Learning Sciences, 15, 549-582.
  • Sfard, A. (2008). Thinking as communicating: Human development, the growth of discourses, and mathematizing. Cambridge, UK: Cambridge University Press.
  • Shayer, M. (1999). Cognitive acceleration through science education II: its effects and scope. International Journal of Science Education, 21(8), 883 - 902.
  • Simon, S. & Richardson, K. (2009). Argumentation in School Science: Breaking the Tradition of Authoritative Exposition Through a Pedagogy that Promotes Discussion and Reasoning. Argumentation, 23,469–493
  • Stein, M. K., Engle, R. A., Smith, M. S. & Hughes, E. K. (2008). Orchestrating Productive Mathematical Discussions: Five Practices for Helping Teachers Move Beyond Show and Tell. Mathematical Thinking & Learning, 10, 313–340.
  • Topping, K. J. & S. Trickey (2007a). Collaborative philosophical enquiry for school children: Cognitive effects at 10-12 years. British Journal of Educational Psychology, 77, 271-288.
  • Topping, K. J. & Trickey, S. (2007b). Collaborative philosophical inquiry for schoolchildren: Cognitive gains at 2-year follow-up. British Journal of Educational Psychology, 77, 787-796.
  • Walshaw, M., & Anthony, G. (2008). The Teacher’s Role in Classroom Discourse: A Review of Recent Research Into Mathematics Classrooms. Review of Educational Research, 78(3), 516-551.
  • Webb, N. M. (2009). The teacher’s role in promoting collaborative dialogue in the classroom. British Journal of Educational Psychology, 79, 1-28.
  • Webb, N. M., & Palincsar, A. S. (1996). Group processes in the classroom. In D. Berliner & R. Calfee (Eds.), Handbook of educational psychology (pp. 841–873). New York, NY: Macmillan.
  • Webb, N., Franke, M. L., Ing, M., Chan, A., De, T., Freund, D., & Battey, D. (2009). The role of teacher instructional practices in student collaboration. Contemporary Educational Psychology, 33, 360-381.
  • Wegerif, N., Mercer, N. & Dawes, L. (1999). From social interaction to individual reasoning: an empirical investigation of a possible socio-cultural model of cognitive development. Learning & Instruction, 9. 493-516.

Meeting Notes

Social and Communicative Factors Thrust Workshop on Coding and Analysis of Classroom Dialogue, Pittsburgh May 26-27, 2011

  • Effects of Social Metacognition on Micro-Creativity: Statistical Discourse Analyses of Group Problem Solving - Ming Ming Chiu Click to download
  • Dialogue Analysis to Inform the Development of a Natural-language Tutoring System for Physics - Sandra Katz, Michael Ford, Pamela Jordan, Diane Litman
  • Temporal patterns of knowledge construction: Statistical discourse analysis of a role-based online discussion - Ming Ming Chiu & Alyssa Wise Click to download
  • Analyzing Teacher-Led Talks: A Talk Map Representation - Gaowei Chen
  • Towards Academically Productive Talk Supported by Conversational Agents - Carolyn Penstein Rosé, Lauren Resnick, Gregory Dyke, Iris Howley, Rohit Kumar Click to download
  • What (if anything) about framing? Is it significant? Do we need to consider it?- Jim Greeno Click to download
  • Measuring Classroom Discussions - Rip Correnti, Moddy McKeown, Jimmy Scherrer, Peg Smith, Mary Kay Stein, Kevin Ashley, Jim Greeno
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