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Discourse Patterns and

Collaborative Scientific

Reasoning in Peer and Teacher-

Guided DiscussionsKathleen Hogan , Bonnie K. Nastasi & Michael

Pressley

Published online: 07 Jun 2010.

To cite this article:Kathleen Hogan , Bonnie K. Nastasi & Michael Pressley (1999)

Discourse Patterns and Collaborative Scientific Reasoning in Peer and Teacher-

Guided Discussions, Cognition and Instruction, 17:4, 379-432, DOI: 10.1207/

S1532690XCI1704_2

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Discourse Patterns and CollaborativeScientific Reasoning in Peer and

Teacher-Guided Discussions

Kathleen HoganInstitute of Ecosystem Studies

Millbrook, NY

Bonnie K. Nastasi

Institute for Community Research

Hartford, CT

Michael PressleyDepartment of Psychology

The University of Notre Dame

In this studyweexamined thediscoursecomponents, interaction patterns,andreason-

ing complexity of4 groupsof12Grade 8 students in2 science classroomsas theycon-

structed mental models of the nature of matter, both on their own and with teacher

guidance. Interactions within peer and teacher-guided small group discussions were

videotaped and audiotaped, transcribed, and analyzed in a variety of ways. The key

act of participants in both peer and teacher-guided groups was working with weak or

incomplete ideas until they improved.How this was accomplisheddifferedsomewhat

depending on the presence or absence of a teacher in the discussion. Teachersacted as

a catalyst in discussions,promptingstudents toexpandandclarify their thinkingwith-

out providing direct information. Teacher-guided discussions were a more efficient

means of attaining higher levels of reasoning and higher quality explanations, but

peer discussions tended to be more generative and exploratory. Students discourse

was more varied within peer groups, and some peer groups attained higher levels of

reasoning on their own. Ideas for using the results of these analyses to develop teach-

ers and students collaborative scientific reasoning skills are presented.

COGNITION AND INSTRUCTION,17(4), 379432Copyright 2000, Lawrence Erlbaum Associates, Inc.

Requests for reprints should be sent to Kathleen Hogan, Institute of Ecosystem Studies, Box R

(Route 44A), Millbrook, NY 125450178. E-mail: [email protected]

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In this study, we examined the nature and sophistication of peer groups collabora-

tive scientific reasoning with and without teacher guidance. Specifically, we docu-

mented the naturally occurring reasoning of eighth-grade students and teachers intwo classes engaged in an instructional unit on building mental models of the nature

of matter. By closely examining the verbal interchange in these classrooms, we

tracked the nature and development of scientific reasoning, collaborative cogni-

tion, and intellectual norms. Because the teachers in these classrooms engaged in

thoughtful dialogue with students (Bliss, Askew, & Macrae, 1996; Duschl &

Gitomer,1997;Hogan& Pressley, 1997;Polman & Pea, 1997;vanZee& Minstrel,

1997), the discussions also revealed the effects of noviceexpert interaction on the

management of ideas, use of thinking tactics, and adherence to intellectual stan-

dards such as clarity and coherence.Both task structure and social setting distinguish this study from studies of stu-

dents scientific reasoning that focus on discrete logical hypothetic co-deductive and

inductive causal reasoning skills of individuals in laboratory contexts (e.g., Dunbar,

1993; Klahr & Dunbar, 1988; Koslowski, 1996; Kuhn, Amsel, & OLoughlin, 1988;

Kuhn, Garcia-Mila, Zohar, & Andersen, 1995; Lawson, 1993; Schauble, 1996). Stu-

dents reasoning within less structured problem domains has been relatively unexam-

ined (Champagne, 1992), although there have been some studies of students

reasoning about social or controversial issues that are highly familiar and interesting to

them (Kuhn, 1991; Resnick, Salmon, Zeitz, Wathen, & Holowchak, 1993; Shachar &Sharan, 1994). However, students verbal interactions and cognitive processing are

likely to be different when talking with their peers about an issue that they have strong

opinions about and familiarity with, as well as when they work on a well-structured

problem that has a single right answer, than when they work together for a number of

days on trying to synthesize the results of several science labs into a coherent explana-

tory model.

There is an emerging recognition that discourse during such scientific inquiry

pursuits is distinctly different from everyday conversations and routine school-

work discussions and reflects a unique form of socially situated reasoning andknowledge building (Cobb & Yackel, 1996). We, thus, use students discourse as a

primary source of data to examine their scientific reasoning, namely their

coconstruction of explanations, arguments, and models from their own observa-

tions and data within classroom contexts.

THEORETICAL PERSPECTIVES

We drew from several theoretical traditions in shaping this study. Like other re-searchers who believe that theoretical pluralism is essential for a complex, applied

discipline such as education (Bereiter & Scardamalia, 1996; Cobb, 1994; Sfard,

380 HOGAN, NASTASI, PRESSLEY

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1998), our approach is pragmatic. Our ultimate goal is to generate knowledge that

can lead to improvements in classroom practice, so our use of theoretical tools re-

flects the needs encountered in that practical endeavor. Eventually, cohesive edu-cational theories can arise from such eclectic beginnings.

Cognitive and sociocultural theories together constitute the framework for

this study. There is a tremendous amount of activity among educational re-

searchers seeking to blend these perspectives into a coherent educational theory.

Some, for instance, are forging relations between situated learning and informa-

tion processing theories (Derry, DuRussel, & ODonnell, 1998), whereas others

are combining socioculturalism with cognitive constructivism (Cobb & Yackel,

1996). Understanding the growth of scientific knowledge in terms of both cogni-

tive and social processes also is gaining prominence in studies of the history,philosophy, and sociology of science (e.g., Cole, 1992; Thagard, 1994), influ-

encing science educators to view science classrooms as scientific communities

in which enculturation and personal knowledge construction are intertwined

(e.g., Driver, Asoko, Leach, Mortimer, & Scott, 1994; Kelly, Carlsen, &

Cunningham, 1993).

In this study, we examined cognition primarily as it is situated in interpersonal

interactions, rather than as situated in broader social institutional and cultural set-

tings. We recognize that examining the interpsychological plane does not consti-

tute a full sociocultural analysis (Wertsch, 1991). However, given the view thatboth scientific reasoning practices and scientific concepts are in part cultural con-

structions (Driver, Asoko, et al., 1994), we approach a broader plane of analysis

when describing the teachers role as inducting students into the norms of science.

Yet, we also rely on ideas that are central to studies of cognition, such as

metacognition and depth of processing of information through elaboration and

synthesis, to fully describe the processes and products of students and teachers

reasoning.

In contrast to many social constructivist analyses that focus on individual stu-

dents construction of identities and understandings within a social context oflearning, this analysis foregrounds group processes and knowledge products. The

primary source of data is interactive protocols (Hogan & Fisherkeller, in press).

Whereas think-aloud protocols capture verbalizations of an individuals thinking

processes that normally wouldnotbe expressed aloud, interactive protocols are the

result of purposeful communication. They are records of communicative events

rather than reports of private sense making. Although we assume that individuals

experience cognitive growth during group discourse, our analysis does not attempt

to make claims about the shift in the knowledge of individuals, or about individu-

als competencies as scientific reasoners. The interactional analyses used in thisstudy do not lead to claims about individual cognition separate from a social con-

text and collaboratively shared knowledge objects.

DISCOURSE AND SCIENTIFIC REASONING 381

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EMPIRICAL FOUNDATIONS ANDRESEARCH QUESTIONS

Much of the recent research using discourse to characterize scientific meaning

making in classrooms is framed by a view of science learning as acculturation into

thelinguistic norms that are integral to the practiceof science(Brown& Campione,

1994; Gallas, 1995; Greeno, 1992; OLoughlin, 1992; Palincsar, Anderson, & Da-

vid, 1993; Reddy, 1995; Rosebery, Warren, & Conant, 1992; Roth, 1995;

Scardamalia, Bereiter, & Lamon, 1994; Wells & Chang-Wells, 1992). Many of

these researchers report on model programs in which teachers succeed in fostering

students ability to engage productively in community discourse. Through discus-

sions, students generate and evaluate evidence to confirm or enhance their under-standing. An important unit of analysis in these studies is the classroom commu-

nity.

However, when the focus has been on the smaller unit of analysis of peer-group

discussions, the portrait of collaborative dialogue in math and science classrooms

has been less positive. Fine-grained analyses have shown that students can spend

much of their time figuring out how to complete a science task rather than gaining

higher order understandings about it. Discussions can be limited in depth and

breadth, and individualunderstandings canbe unrelated to the groups understand-

ing or to an individuals participation in the group (Bianchini, 1995). Cognitiveconflicts that emerge over mathematics problems can degenerate into social con-

flicts resolved through social dominance or teacher intervention (Nastasi,

Braunhardt, Young, & Margiano-Lyons, 1993). Also, not all children are equally

engaged in group tasks in part because their level of motivation, engagement, and

understanding is linked to the behaviors of the group leader (Basili & Sanford,

1991; Gayford, 1989; Richmond & Striley, 1996). Lower status and minority chil-

dren participate less in cognitively challenging activities such as building explana-

tions in science classrooms than do majority children of higher socioeconomic and

academic status (Anderson, 1994). Students do not always spontaneously develophypotheses, reason, explain, elaborate, and justify through their verbal interactions

during activity-based science, and they do not clarify their own or their peers un-

derstandings (Basili & Sanford, 1991; Bennett & Dunne, 1991; Roth &

Roychoudhury, 1992). Childrens talk about abstract ideas is less frequent and cer-

tain than their extensive and fluent talk associated with action and design. They

use imprecise language, often uttering short sentences or single words, which

hampers their ability to communicate ideas effectively (Bennett & Dunne, 1991).

They also often talk at cross-purposes and invoke conclusions without articulating

adequate warrants and backings to support their arguments (Eichinger, Anderson,Palincsar, & David, 1991).

Clearly much remains to understand about the sociocognitive behaviors that

support and inhibit collaborative reasoning, despite evidence that small group in-


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teractions in classrooms can promote cognitive gains (Nastasi & Clements, 1991).

Thus, in this study, we sought to understand the following:

What are the patterns of verbal interaction within peer and teacherstudent

scientific sense-making discussions?

Are there relations between discourse patterns and sophistication of scien-

tific reasoning in peer and teacherstudent discussions?

Understanding knowledge building in classroom communities requires atten-

tion both to the natural progression of reasoning among novices (the students) and

to the role of the scientific expert (the teacher) in upholding standards that may be

unfamiliar within the peer culture. Thus, by analyzing teacherstudent discourseand the associated socially distributed learning processes, we hoped to uncover

some of the limitations and potential of peer discourse as well as to explicate the

crucial role of the teacher in small group discussions. Ultimately, recommenda-

tions for melding peer and scientific cultures to optimize student motivation and

learning depend on understanding the dynamics of classroom discourse.

METHODS

Context

The context for this study was the natural setting of a complex, long-term activity

designed by a teacher for instructional purposes. The study took place in two class-

rooms of one eighth-grade teacher in a suburban school district in upstate New

Yorkduringa 12-weekunit inwhich students constructedand testedmentalmodels

of the natureof matter. A mental model is a verbal or image-based representation of

a complex phenomenon (Derry, 1996). Although the term usually refers to internal

mental constructions, in this instructional setting the term refers to students sharedknowledge objects, similar to the conceptual models that are the currency of prac-

ticing scientists interchanges.

The instructional unit had four phases. During Phase 1, students expressed prior

understandings as they did labs and demonstrations to gain experience with the

characteristics and behaviors of solids, liquids, and gases. During Phase 2, stu-

dents worked in groups to construct and then present a model as a coherent set of

ideas and pictorial images that could explain and predict the phenomena they had

observed. During Phase 3, students participated in whole class discussions and in-

vestigations to test and refine their models. Finally, in Phase 4, students used theirmodels to explain new observations.

This instructional context was unique in its focus on theory building. Often in

inquiry-oriented science classes, emphasis is placed on experiment planning and


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data-generating activities, rather than on building explanations from evidence.

Also, reward structures in classrooms typically preclude engagement in effortful,

long-term comprehension activities. However, within the instructional unit for thisstudy, complex thinking was valued, and the teacher collaborated with students to

produce it. The students goal was to produce a coherent explanatory model that

could stand up to peer critique, and they were given realistic amounts of time to

achieve this objective.

The teacher consciously adopted a style of constructivist pedagogy for this unit

that is best described as awithout the information given(WIG; Perkins, 1992) ap-

proach in which a teacher does not provide direct instruction or other exposure to

conceptual information but instead guides students direct experiences with phe-

nomena. This approach contrasts with what Perkins called the beyond the informa-tion given (BIG) constructivist practice in which teachers provide basic instruction

to students but then present challenging activities that require them to manipulate,

apply, and refine the new information.

The teacher hadadopted a WIG approach for this unit after repeatedly observing

howstudents thinking had shut downafter they weregivensomerelevant informa-

tion that they took tobe the right answer. To thwart students adeptness atplaying

the typical game of school and their reliance on her as a scientific authority, the

teacherfoundthatshehadtotakearadicalstanceofnottellingsothatstudentswould

learntorefinetheirabilitiesto formandjudgetheirownideasbasedonevidence.Shedid not expect students to induce the key tenets of kinetic molecular theory purely

fromdirectexperience. Rather, she thoughtof thisunit primarilyasprovidinganex-

periencein the processofbuilding models andtheories asscientists do, more thanas

providing a solid conceptual foundation in the nature of matter.

However, after teaching the mental model building unit early each fall, the

teacher revisited the nature of matter throughout the school year with a variety of

learning activities, includingsome direct instruction.Shefound thatthe long, some-

times frustrating phase of not being provided with direct information during the

mentalmodelbuildingunitsetstudentsuptotreattheprocessofknowledgebuildingandto attend to their own emerging models andother information that they encoun-

tered later on in ways that would not have happened through a more traditional in-

structional unit. This unit then, was embedded within a carefully considered year

long course of instruction in which the teacher made sure that students growth in

conceptual understanding was not compromised in the long run for the sake of get-

ting a taste of authentic scientific inquiry early in their eighth-grade year.

Participants

Twelve students (6 girls, 6 boys; 10 White, 1 Black, 1 Asian) from two classrooms

of one eighth-grade teacher were selected as target students to represent the diver-


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sity of students within the classrooms, relative to two characteristics presumed to

be relevant for coconstruction of ideas: science achievement level and level of ver-

balparticipation in whole-class and smallgroupdiscussions (Table 1). Selection ofstudents was based on documentation of students prior achievement in science,

teacher judgment, and researcher observations of the students for several weeks

prior to choosing them. However, we recognized that these classifications were

only broadly discriminating because students act and achieve differently in differ-

ent social and task contexts within the same classroom. These 12 students worked

in the same four heterogenous groups of three for several weeks when the majority

of the interactional data were collected.

The teacher had 25 years of teaching experience at the time of the study and was

regarded as a master science teacher within and beyond her district. She had col-laboratively designed the mental model building unit with a university professor

several years prior to our contact with her for this study. She often spoke of the pro-

cess of designing, teaching, and reflecting with the professor on the unit and on

students learning within it as having a major impact on her growth in using

constructivist pedagogy. She periodically gave workshops to other teachers about

the unit and collected her own data on students naive notions about the nature of

matter. Overall, she was a very reflective teacher who welcomed the opportunity

to participate in this study as a means of furthering her own insights into the nature

of the teaching and learning that occurred during the unit.


TABLE 1

Profile of Target Students

Achievement Level Verbal Participation Level

Group and Student No. High Medium Low High Medium Low

Group 1

Student 1 X X

Student 2 X X

Student 3 X X

Group 2

Student 1 X X

Student 2 X X

Student 3 X X

Group 3

Student 1 X X

Student 2 X X

Student 3 X X

Group 4Student 1 X X

Student 2 X X

Student 3 X X

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A male student teacher was observing and assisting in the classrooms during

the data collection period. Half of the samples of teacher-guided group discussions

used for the analyses were with the student teacher and half were with the teacher.The teacher modeled and discussed her style of interacting with student groups

with the student teacher prior to and during the unit, and he picked up on and used

her style remarkably well. The point of the analyses reported here was not to com-

pare the teachers and student teachers interactions with the students. Although

the repertoire of the student teachers discourse moves was narrower than the

teachers, the prompting behaviors that he did use in the discrete samples of inter-

actions we analyzed were very similar to the teachers use of the same types of ver-

balizations. Therefore, the two are referred to in this article as the teachers except

for in a few instances when it seemed informative to distinguish between them.

Data Collection

The student groups and their classes were videotaped and audiotaped two to three

times per week over a 12-week period. Kathleen Hogan was a complete observer

rather than a participant in the classrooms, remaining on the sidelines to take notes

and manage taping equipment, interacting minimally with the students and teach-

ers during class periods.The main data for this study are transcripts of students interactions over sev-

eral weeks during Phase 2 when they worked in their groups to: (a) build a mental

model of the nature of matter; (b) use their model to explain the characteristics of

solids, liquids, and gases and the results of 10 experiments; and (c) present and de-

fend their model to the whole class. The students tasks during this phase of the

unit were framed by four questions that the teacher presented to them:

1. What would solids, liquids, and gases look like if you could magnify them

millions of times? (The resulting pictorial images and descriptions of each state ofmatter were called the groups mental model.)

2. How can the model explain the characteristics of solids, liquids, and gases

that were explored in labs (e.g., solids have mass; liquids take the shape of their

container; the volume of gas depends on the volume of its container)?

3. How can the model explain the phase changes observed in labs (e.g., solid to

liquid, liquid to gas, gas to liquid)?

4. How can the model explain a variety of other phenomena observed during

labs (e.g., air blown intoplastic bagscan lifta heavy table;odors ofsolidscan bede-

tected even when each solid is in a cup covered with tissue paper; the mass of apiece of ice stays the same once melted; sugar cubes dissolve more quickly in hot

than in cold water)?


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Taping occurred for whole class periods during which the teachers moved in

and out of interaction with individual groups as they tackled these questions.

Therefore, data were gathered when the groups of target students were workingboth with and without a teacher. Tapes of 16 group discussions (four groups for 4

days) amounting to approximately 10 hr of conversations were transcribed for

fine-grained analysis.

Videotaping and audiotaping created somewhat intrusive conditions. Students

reported that they tried to show their best thinking during taping, commenting on

this to one another while being taped and to the researcher during class sessions

and interviews. Therefore, we interpret the results of this study as reflecting what

students regarded as their best attempts to interact productively, which may not

have been their typical level of performance in everyday classroom work.

Steps of Analysis and Coding Schemes

An overview of the analyses is presented in Table 2. The sequence of analysis steps

was not predetermined but rather emerged inductively through interaction with the

data (Miles & Huberman, 1994; Strauss & Corbin, 1990). In general, coding

schemes were gradually refined through interaction with several transcripts. Once

the codes could describe all of the data satisfactorily, the coding schemes were es-tablished and all of the transcripts were recoded using the final schemes. Each step

of analysis is described in detail within the following sections.

Macrocodes. The first step in analyzing the transcripts was to determine themajor modes of the groups discussions. The three modes that emerged were (a)

knowledge constructionpeer and teacher-guided(i.e., when the discussion topic

was scientific phenomena and ideas, without or with a teacher present); (b) logisti-

cal(i.e., when the discussion topic was concrete aspects of the task such as whatcolor markers to use for overhead transparencies); and (c)off task(i.e., when the

discussion topics had nothing to do with the science topic or task).

These categories became the macrocodes for the transcripts. The unit of analy-

sis for the macrocodes was conversational turns. A turn began when a person took

the floor in a conversation and ended when another person took the floor.

Microcodes. The next step of transcript analysis was to construct afine-grained portrayal of the types of statements students and teachers made to one

another during knowledge construction discussions.Statement units,defined as acodable unit of speech (i.e., a word, phrase, sentence, or sentences) within a turn,

were the units of analysis for microcoding.


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Through repeated readings of transcripts, three main categories of statementsemerged as pivotal discourse moves for initiating, focusing, sustaining, and deep-

ening dialogue. These wereconceptualstatements,metacognitivestatements, and

questionsqueries. The conceptual statements took many forms, such as observa-

tions, ideas, conjectures, inferences, and assertions about the nature of matter; for

example, Okay, my theory on what happens with odors of the solids is that, um,

over a period of time, little particles, little clumps of atoms will break off from the

original object and they would put out in the air, and we would smell them.

Questions and queries comprise a single statement category because their function

was similar, but they differed somewhat in form and content. Questions were simpleand direct requests for information (e.g., What did you write for the answer to that lab

question?), whereas queries articulated unknowns as large issues to ponder rather

than as questions for an immediate answer (e.g., Is a smell a gas though?).


TABLE 2

Overview of Analysis Steps, Units of Analysis, and Codes

Analysis Procedure Unit of Analysis Codes

Step 1: Code modes of

discourse

Conversational turns within

episodes: Transitions between

one speaker and the next within

a series of interactions

Knowledge construction (peer,

teacher-guided), logistical, off

task

Step 2: Code types of

statements

Statement units: The smallest

meaningful codable unit of

speech within a turn

Microcodes within conceptual,

metacognitive, questionquery

categories

Step 3: Create discourse

maps

Episode: One or more topic units

united by a common mode or

purpose

Knowledge construction (peer,

teacher-guided)

Step 4: Discern

interaction patterns

Interaction sequences: A series of

turns bounded by statements

that initiate a new level of focus

Consensual, responsive,

elaborative

Step 5: Create conceptual

proposition maps

Topic units: One or more

interaction sequences focused

on a single topic

Name of the topic (e.g.,

macroscopic properties of

solids, liquids, gases; phase

changes)

Step 6: Judge reasoningcomplexity

Conceptual proposition map: Adiagrammatic reconstruction of

the conceptual flow of

discussion about a topic

Generativity, elaboration,justifications, explanations,

logical coherence, synthesis

Step 7: Relate groups

patterns of interaction to

the reasoning complexity

they achieved

All interaction patterns and

reasoning products of each

group

Previously defined codes for

statement types, interaction

patterns, and reasoning

complexity

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Metacognitive statements were of three types:regulatorystatements that di-

rected action on the task (e.g., Now lets do the second one were supposed to

do),evaluativestatements that assessed the groups degree of progress or under-standing (e.g., We dont get this one at all), and standards-basedstatements that

communicated the nature and goals of the task according to external criteria that

the groups process or product should meet (e.g., Every explanation youmake has

to relate to the model).

A number of statement types within these three broad categories also were dis-

cerned. A complete list of microcodes is presented in Table 3. Development of

these codes proceeded recursively between inductive and deductive processes.

Some general labels of discourse statement types from the literature (e.g., Langer,

1991), as well as a search of the literature for mechanisms hypothesized to accountfor cognitive gains through peer interaction, yielded a preliminary list of

microcodes. This list framed initial examination of the transcripts, which led to re-

visions of the list to better describe the data. The coding scheme also was refined

through interactions among the researchers and others, which helped to identify

ambiguities in definitions, overlap of categories, and so forth. The microcoding


TABLE 3

List of Microcodes

Statement Category Statement Type Microcode

Conceptual Presents idea PId

Presents partial idea PPI

Presents information PIn

Presents summary PSu

Repeats self RpS

Repeats other RpO

Elaborates self ElS

Elaborates other ElO

Metacognitive Evaluates own idea EvSI

Evaluates others idea EvOI

Evaluates task difficulty EvD

Reflects on standards RfSt

Reflects on positive understanding RfU+

Reflects on lack of understanding RfU

Regulates action RgA

Questionquery Presents query PQy

Requests information RIn

Nonsubstantive Reacts agrees RA

Reacts neutral RNReacts disagrees RD

Other Digressions DI

Uncodable UC

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scheme went through eight iterations. The final scheme was applied to 5 tran-

scripts for fine-tuning and then used to code the remaining 11 transcripts.

Discourse maps. Discourse maps (cf. Frederiksen, Roy, & Chen, 1996;Green & Wallat, 1981) that depict the chronological process and content of collab-

orative cognition were constructed from the transcripts to highlight the sequencing

of the three main statement types (i.e., conceptual, metacognitive, and ques-

tionsqueries) withinepisodesof peerand teacher-guidedknowledgeconstruction.

Excerpts from discourse maps are presented in Figure 1 (from a peer dialogue) and

Figure 2 (from a teacher-guided dialogue).

The substance of the discussion is displayed in the portion of the map called thecentral interaction space.Conceptual statements appear in boxes, questions and

queries in hexagons, and metacognitive statements in ovals. The discourse moves

of each participant in the discussion are represented in columns adjacent to the in-

teraction space. In the models of teacher-guided discussions, the teachers moves

appear on one side of the interaction space and the students moves on the other.

Arrows lead to and from the participant columns and interaction space to indicate

conversational flow, or who is contributing to and building on the substance of the

discussion. Finally, topic units and digressions are indicated in the outermost col-

umns of the map. The maps, then, were a tool for portraying the dialogue datagraphically.

Interaction sequences and patterns. Although the discourse maps facil-itated comparisons of peer and teacher-guided discussions, we needed an addi-

tional analysis tool to examine the nature of the interactions in more detail. Interac-

tion sequences emerged as a productive intermediate unit of analysis between the

atomistic unit of statement types and the broad unit of discourse maps of entire epi-

sodes.Interaction sequencesare units of dialogue that begin when a speaker makes a

conceptual or metacognitive statement or poses a question or query. At least one

statement from another speaker must follow the initiating statement to comprise an

interaction sequence. The interaction sequence ends when a speaker steps back

from the flow of the interaction by posing a new question or query; by making a

metacomment that regulates, focuses, or evaluates the action; or by introducing a

conceptual statement that refocuses discussion away from a metacognitive se-

quence.

Every time a new query or question is posed, a new interaction sequence beginsbecause these statements always indicate a pulling back from the flow of the dia-

logue. However, not all conceptual and metacognitive statements initiate new in-

teraction sequences. This is because both of these statement types can occur


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391

FIGURE 1 Samplepeerdiscourse map. Boxes contain conceptual statements, ovals containmetacognitive

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392

FIGURE 2 Sample teacher-guided discourse map. Boxes contain conceptual statements, ovals cont

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multiple times in an interaction sequence without initiating a new level of focus for

the interchange. Level of focus is a key distinction. Many new ideas or several

metacognitive statements can be introduced in a segment of dialogue, yet together

comprise just a single interaction sequence. It is only when the focus of the interac-

tion switches among conceptual, metacognitive, or questionquery-based levels

that new interaction sequences are defined. The boundaries of sample interaction

sequences are defined by the dotted lines in Figures 1 and 2.

Three patternsconsensual, responsive, and elaborativeemerged as the

most parsimonious way to characterize the essence and flow of knowl-edge-building dialogue in both peer and teacher-guided groups. Brief (i.e., two to

four turns) interactions that were off task, yet not prolonged enough to constitute

an entire off-task discussion, were coded asnonconceptual.

Interaction sequences were coded as consensual when only one speaker con-

tributed substantive statements (i.e., conceptual, metacognitive, or questionsque-

ries) to the discussion (Figure 3). Another speaker responded to the initiating

speaker by (a) simply agreeing with the statement, (b) passively or neutrally ac-

knowledging the statement, (c) actively accepting what was said and thereby en-

couraging the speaker to continue, or (d) repeating the preceding statementverbatim. Thus, in consensual sequences one speaker carried the conversation,

with one or more speakers serving as a minimally verbally active audience. Al-

though consensual sequences often lasted only a few turns, sometimes a single

speaker contributed many ideas to the discussion with all of the intervening state-

ments by other speakers being nonsubstantive. The following sequence is an ex-

ample of a consensual interaction:

16 Student 1: Alright, when a liquid is heated it turns into a gas, and then

when a liquid is like frozen it gets cold and stuff, it turnsinto a solid.

17 Student 2: I know.

18 Student 1: Okay.


FIGURE 3 Consensual interaction

pattern.

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Within responsive interaction sequences, both questions and responses of at

least two speakers contributed substantive statements to the discussion (Figure 4).

Although the roles of the questioner and responder differed, both participants were

equally responsible for contributing to the substance of the discussion. Responsivepatterns often were only a few turns in length. They became longer than a few turns

when several agreements or neutral comments were embedded within the se-

quence or when a teacher posed a question and two or three students responded to

it in turn without building on one anothers responses. The following sequence

was an example of a responsive interaction:

141 Student 1: The hotter a substance gets, the lighter it is. You know that,

it has to, ya. Doesnt it go into the gas?

142 Student 2: Itdepends onwhatyou get. I justknow itsa heavy kindofliquid.

In the third and final type of interaction sequence, elaborative patterns, all

speakers contributed substantive statements to the discussion, as in the respon-

sive sequences. However, the speakers in elaborative sequences made multiple

contributions that built on or clarified anothers prior statement (Figure 5). Elab-

orations were coconstructive additions (linking a new idea to someone elses

idea or partial idea), corrections (correcting someones statement with a simple,

undisputed statement), or dialectical exchanges (disagreeing with the prior state-

ment and offering a counterargument). An elaborative interaction sequence fol-

lows.1

21 Student 1: So in other words they look the same. Is that a gas, a liquid

heated?

22 Student 2: Thats what I was talking about yesterday. If you looked at

a drop of water, if you looked at a tiny drop of water/

23 Student 3: //maybe thats what gas is, just like/

24 Student 2: //thats what it is, its a liquid, but in a (base of)/


1A single slash indicates the point where a statement is interrupted by another speaker and double

slashes indicate the start of the interrupting statement. Parentheses enclose overlapping statements.

FIGURE 4 Responsive interaction

pattern.

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25 Student 3: //(heated?)

26 Student 2: Yeah, its heated.

27 Student 3: Yeah/28 Student 2: //Yeah, ifyou lookatmoisture,on likeyourhand, ifyou put

it over anything like boiling water, you can get water out of

your hand, and it just looks like normal water/

29 Student 3: //but thats not a gas though.

30 Student 2: But it was a gas.

31 Student 3: No it wasnt, it couldnt be. You cant see gas.

32 Student 1: Yeah.

33 Student 3: So its maybe like heated to a point where it kind of sepa-

rates and goes in.

Reasoning complexity. To assess the quality of groups thinking, we cre-ated a summary portrayal of discussions about each topic, using conceptual propo-

sition maps (cf. Novak, 1990; West, Fensham, & Garrard, 1985) of each topic unit

derived from the discourse maps (Figure 6). The conceptual proposition maps re-

structured the sequential flow of the conversations into a conceptual flow. Redun-

dancies and nonsubstantive moves (e.g., simple agreements) were ignored, and

ideas that obviously were implicit in the conversation were added as explicit com-

ponents of the map (cf. Resnick et al., 1993). These modifications of the discoursemaps yielded a representation that was concise and accessible for analyzing the

content of the discussion.

The sophistication of students thinking about a given topic as represented in

the conceptual proposition maps was judged with a reasoning complexity rubric


FIGURE 5 Elaborative in-

teraction pattern.

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(Table 4). The categories of the rubric emerged inductively as the most salient

descriptors of the data but also were shaped by various existing frameworks that

describe the essential components of scientific reasoning. The first two criteria of

the rubric, generativity and elaboration, specify the amount and type of ideas andelaborations of ideas within a topic unit. The second two criteria, justifications and

explanations, specify the structure of students reasoning, meaning how their ideas

are supported and explained. Finally, the logical coherence and synthesis criteria

specify the quality of the students thinking. Together the six criteria comprise a

judgment of reasoning complexity. More detailed definitions of each criterion are

presented in Table 5.

It is important to note that judgment of reasoning complexity in this study

does not equate with judging the canonical correctness of students ideas. We

did not focus our analyses on depicting the nature of students alternative con-ceptions of the nature of matter, which have been thoroughly documented else-

where (Andersson, 1990; Driver, Squires, Rushworth, & Wood-Robinson, 1994;

Lee, Eichinger, Anderson, Berkheimer, & Blakeslee, 1993). Although we recog-


FIGURE 6 Sample conceptual proposition map.

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TABLE 4

Reasoning Complexity Rubric

Criteria 0 1 2

Generativity No observations

or ideas

One to two

observations or

confirmed

generalizations

Three or more

observations or

confirmed

generalizations

One to two

conjectu

or assert

Elaboration No elaboration One to two

elaborations of one

idea

One to two

elaborations of

more than one idea

Three or m

elaborati

idea

Justifications No justifications Single justification ofone idea

Single justificationsof more than one

idea

Multiple juof one id

Explanations No explanations Single mechanism of

one phenomenon

Single mechanism of

more than one

phenomenon

Multiple or

mechani

phenome

Logical coherence No logical

connections

invoked

Nonsensical

connections made

Vague, underspecified

connections making

superficial sense

Clear and r

connecti

lack sup

Synthesis No contrasting

views emerged

Two counter ideas

coexist separately

and unresolved

Two counter ideas

explicitly combined

without deeper

conceptual resolution

One counte

prevails

support g

397D

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nize that the content and processes of scientific thinking are thoroughly interde-pendent (Hodson, 1992; Millar & Driver, 1987; Mintzes, Wandersee, & Novak,

1998), we have found that the thinking of students who hold equally naive no-

tions about scientific phenomena can be more or less deep and generative.

Therefore, we used reasoning complexity as an alternative gauge of the quality

of students learning that highlights their ability to elaborate and justify the un-

derstandings they have, rather than judging their thinking solely by comparing

their knowledge base to that of experts (Brewer & Samarapungavan, 1991; Ho-

gan & Fisherkeller, 1996).

Reliability and Credibility

Given the first authors prolonged engagement in the study setting and intensive

immersion in the data, she was the expert judge in coding and analysis. The coau-

thors were an analytic audience whose role was to question judgments at all junc-

tures in the development and application of coding schemes. These interactions re-

sulted in more refined, rational, and warranted judgments. This process of analytic

collaboration was not reducible to tallies or percentages but rather acknowledgedthe necessity for deep contextual knowledge in making reliable and valid interpre-

tations of the data.


TABLE 5

Definitions of Reasoning Complexity Criteria

Criteria Operational Definition

Generativity Judged by the number of subtopics brought forth within the discussion. A

distinction is made between lower level reiteration of observations or

confirmed generalizations and students own ideas, conjectures, or propositions.

Elaboration A gauge of the amount of detail that is added to the subtopics that are brought up.

Justifications There are two types of justifications of ideas or assertions: evidence-based and

inference-based. Scores are based on the number of justifications per idea.

Explanations The presentation of mechanisms that account for a phenomenon. The more

mechanisms proposed, the greater the score.Logical coherence Logical coherence is judged only when a justification or explanation is evoked.

Scores increase according to the soundness of the justification or explanation

for a phenomenon. High scores do not necessarily imply that ideas are

canonically correct, but rather judgments of coherence depend on the

speakers assumptions and premises.

Synthesis A measure of how and if opposite views were accounted for, which is a

hallmark of dialectical and higher order thinking.

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Although the group did not directly control how much time the teachers spent

with them because they dedicated more of their self-guided discussion to logisti-

cal and off-task modes than to peer knowledge construction, it can be inferredthat this group was not very capable of sustaining knowledge coconstruction on

its own. Indeed, the teacher and student teacher tended to spend more time with

groups that they perceived were having the most difficulty in building knowl-

edge together.

There was great variability, then, in the amount of time teachers spent with dif-

ferent groups as they circulated around a classroom in a given class period. Focal

groups also differed in the amount of conversation they dedicated to knowledge

construction on their own. Because the overall task and the total amount of time al-

lotted for group work were identical for all groups, this difference points to differ-ences in the characteristics of the groups themselves (e.g., prior knowledge,

conceptualization of the task, goals, sociocognitive skills, interpersonal relations,

tenacity, etc.) rather than to broad contextual differences. A differentiating charac-

teristic of groups that we explore next is the nature of their coconstructive dis-

course.

Microanalysis of Statement Types Within

Peer Knowledge Construction Discussions

The frequencies and percentages of statement types that occurred during the four

groupspeerknowledge constructiondiscussions arepresented in Table 6. Because

Group 4 dedicated so few turns to peer knowledge construction (n = 21) there were

not sufficient data to determine an overall pattern in their use of statement types, so

the following comments focus on comparing several elements differentiating the

coconstructive discourse of Groups 1, 2, and 3.

Digressions. Digressionswererare for Groups1 and 2.These two groupswereextremely focusedon the business of makingsense ofdata andbuildinganexplanatory

model. In contrast, 27% of Group 3s statements were digressions, constituting the

largest proportion of their statements within the peer knowledge construction mode.

Digressions were isolated remarks embedded within knowledge construction epi-

sodes, so they did not constitute sustained off-task conversations that would have been

coded as off-task discussions at the macrocoding level. Their digressions were social

commentary aboutotherpeople,events inother classes, peoples clothing, and soonas

well as sarcastic remarks to one another about their science-related ideas. Given thatGroup 3 spent a low total amount of turns in peer knowledge construction relative to

Groups 1 and 2 (see Figure 7), it is plausible that even isolated digressions could have

undermined the sustained coconstruction of ideas.


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Queries. Missing completelyfrom Group 3sdiscoursewere queries, whereas5% of Group 1s and 3% of Group 2s statements were queries. Often queries were

students acknowledgment of what they did not know. Paraphrased summaries of

sample queries raised by Groups 1 and 2 include the following:

Whats inside the space between atoms? Does it weigh anything? If it is a

gas, then is it made of atoms?

Is an atom a solid, liquid, or gas?

Do atoms get bigger in a gas, or does the space between them get bigger?

Ifa liquiddoesnt havea definite shape,does thatmean that liquidatoms areamorphous rather than round like atoms that make up a solid?

What connectsatoms? What happens to connectors when matter changes

state?

These and other queries reflect documented areas of students difficulties with

understanding the nature of matter (Andersson, 1990; Driver, Squires, et al., 1994;

Lee et al., 1993) manifest in beliefs such as that molecules have air or solid strands

between them, that molecules expand, and that individual molecules have proper-

ties of the macroscopic substance they comprise. However, the queries that stu-dents shared revealed that many of these notions struck them as problematic.

Rather than offering the naive notions up as glib or pat explanations, they grappled

with them, seemingly because they struck them as not being quite satisfactory. The


TABLE 6

Number and Percentage of Microcodes in Four Groups

Peer Knowledge Building Discussions

Group 1 Group 2 Group 3 Group 4

Microcodes No. % No. % No. % No. %

Presents (idea, partial idea, information, summary) 255 26 86 23 23 18 5 24

Repeats (self, other) 30 3 6 2 11 9 1 5

Elaborates (self, other) 252 26 84 22 23 18 4 19

Evaluates (own, other, task) 4 0.4 2 1 1 1 0 0

Reflects (standards, understanding) 38 4 21 5 5 4 0 0

Regulates action 78 8 37 10 8 6 1 5

Presents query 47 5 12 3 0 0 0 0

Requests information 29 3 28 7 6 5 4 19

Reacts (agrees, neutral) 207 21 57 15 11 9 4 19

Reacts (disagrees) 34 3 32 8 6 5 0 0

Digressions 2 0.2 15 4 34 27 2 10

Uncodable 7 0.7 2 1 0 0 0 0

Total 983 382 128 21

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following excerpt from Group 1s discussion illustrates this point. The students are

trying to explain how it was possible to smell substances (e.g., cinnamon, garlic,

baby powder) in paper cups covered with tissue paper. Queries are articulated inturns 185, 196, 197, and 204.

178 Student 1: Okay, umm, odors of solids.

179183 [They remember and describe the lab activity.]

184 Student 1: Ooo, I know why, cause little particles like came off the/

185 Student 2: //yeah, but what does that have to do with that? [She points

to their drawings of the molecular structure of solids, liq-

uids, and gases.]

186 Student 3: Yeah, so 187 Student 1: Maybe the particles came off of it [he laughs as he points to

the drawing].

188 Student 2: Well, is that

189 Student 3: Its not going through any change, so its not

190 Student 2: No, were only dealing with solids

191 Student 1: Yeah, so

192 Student 2: Were dealing No, its not a gas.

193 Student 3: Yeah, cause this is all solid, so

194 Student 1: Well actually195 Student 3: We shouldnt

196 Student 2: Is it a gas, would you be dealing with a gas though?

197 Student 1: What is a smell?

198 Student 3: I dont know

199 Student 1: No, when you smell something, you like, intake

200 Student 2: But its in the air

201 Student 3: Oh yeah, thats true

202 Student 1: No, when you smell something you intake like little parti-

cles of a203 Student 2: But if its in the air

204 Student 1: Would that be like a gas?

205 Student 3: I dont think the

206 Student 2: I dont think the particles itself

207 Student 1: So the air

208 Student 2: would be a gas, but I think the air is a gas so the particles

go in it.

209 Student 3: Yeah.

210 Student 1: The particles go in it, in the air.211 Student 2: So in other words, the particles from the solid, we dont

know how that happened yet, goes up through and then fol-

lows the air?


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212 Student 3: I think the particles, ifwere talking about atoms, I think the

particles are gonna be too big to relate to atoms because the

particles are gonna be made up of atoms.213 Student 1: Yeah. They might be a lot more than one atom.

214 Student 2: So we cant

215 Student 3: Yeah.

216 Student 1: So maybe we should just like

217 Student 3: Let me ask her if we still have to relate it to the model. [He

leaves to find the teacher.]

The students are not sure whether an odor is a solid or a gas, and they are not

completely sure about relative sizes of grains of cinnamon for instance, and atomsand molecules. They leave these issues unresolved but come back to them several

more times in subsequent discussions.

Althoughrelativelyinfrequentoverall,queriessuchastheonesembeddedwithin

the preceding excerpt seemed to be pivotal in coconstructionepisodes because they

prompted students to thinkmoredeeplytobring forth,dwell on, elaborate on, and

connect ideas. Groups that shared more queries also spent more turns in the peer

knowledge construction mode (see Figure 7). How many queries students gener-

ated, how often students returned to discussing unresolved queries, and how they

dealt with the competing emotions of discomfort and wonderment elicited by que-rieswereindicatorsofhowthegroupsgrappledwiththecomplexityoftheirtask.

Reactions. Another interesting pattern in groups statement types was therelative amount of each groups agreements or neutral reactions (e.g., em hmm)

versus disagreements with one another. Group 1 had seven times more agreements

with and neutral reactions (21%) to one anothers ideas than disagreements (3%).

Within Groups 2 and 3, students agreed or reacted neutrally with one another only

about twice as much as they disagreed.Because Group 1 was the most successful in

sustaining peer knowledge construction discussions across 4 days of group work(see Figure 7), then overtly agreeing, affirming, andaccepting peers remarks is as-

sociated in their case with the prolonged discussion of ideas. The association be-

tweenconsonantdiscourseand sustained focus on conceptual issues does not, how-

ever, indicate anything about the quality or progress of a groups reasoning; we

examine those features of the students discussions later.

Microanalysis of Statement Types Within

Teacher-Guided Knowledge Construction Discussions

Although the teachers statements also can be described using labels from the

microcoding scheme used for student statements, the nature of the teachers state-


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ments within many of the categories was qualitatively different from the students

statements. Table 7 contains the statement types used by the teachers as they inter-

acted with student groups. The following subsections focus on the prominent ways

that teachers use of different statement types differed from how students used the

statements.

Requests information. Typically the teachers began a dialogue with a stu-dent group by checking the status of students thinking with a question such as,

Tell me what youve comeupwithso far. They then probed to the next level with

a question such as, So what distinguishes solids from liquids? At times they chal-

lenged students to apply concepts to new situations, for instance with the question,

Now how would that explain the dissolving of solids in water?

An important type of question the teachers used to request information was one

that crystallized the issue at hand, in essence by asking, So do you think (this) or

(that)? An example of this discourse move is, So you think the atoms are lighter,

or you think theyre spread out? The teachers also communicated standards forscientific discourse by requesting that students clarify their language by saying, for

example, What do you mean by connectors? or What is it that gets taken

away? Finally, they prompted reflection directly with questions such as, Would


TABLE 7

Teacher Moves in Guiding Students Knowledge Construction

General Moves Specific Moves

Requests information Checks status

Probes to next level

Probes into new territory

Calls for crystallization

Requests language clarity

Prompts reflection

Directly

Using rhetorical questions

Repeats and elaborates Restates verbatimRestates with clarity

Restates with inference

Summarizes

Elaborates own statements

Reacts Accepts or confirms students statements

Makes neutral statements

Enculturates Communicates task expectations

Communicates about science practice

Enculturates self into student world

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that support your idea? and Does (this) explain (that)? and indirectly with rhe-

torical questions such as, Do all gases rise? or How sensitive would a balance

be to microscopic pieces?The teachers requests for information established a pattern that was radically

different from teacherstudent interaction patterns in recitation-based classrooms.

They formed their questions in response to students statements, rather than ac-

cording to their own preestablished agenda. They made the most of the raw mate-

rial for thinking that students gave them to work with. They stayed with the same

topic for several turns, prompting students to think about the issue more deeply,

rather than evaluating their responses and moving on to new topics. The teachers

also held together the threads of the conversation, weaving students new state-

ments with their prior statements to help them link ideas and maintain a logicalconsistency, for example by saying, If you said (that) before, can you say (this)

now? Their statements indirectly prompted students to evaluate their own think-

ing and to discover fallacies in their reasoning.

The following excerpt illustrates some of the teachers various ways of request-

ing information. The excerpt begins just after a group of students has drawn a rep-

resentation of what they think they would see if they could magnify a solid

millions of times.

191 Teacher: Okay, now what would a liquid look like if you could mag-nify it millions of times?

192 Student 1: Probably the same thing.

193 Student 3: Yeah, just like

194 Student 1: Because we thought atoms are probably the basics, the

smallest things.

195 Teacher: So the liquid would look exactly the same?

196 Student 2: I thought it was kind of like/

197 Student 1: //Well, maybe the atoms had to be different.

198 Student 3: Maybe likespreadout more, not likeexactly a round shape.199 Student 1: Err, and they may not be stuck together, the atoms may not

be stuck together, they may be free floating.

200 Teacher: Draw me a picture of what you think youll see. [They

draw.]

201 Student 2: Sotheyd justbekinda like, theydlose their definiteshape.

202 Student 1: Yeah, theyd lose their

203 Teacher: So youre going to have the molecules having kind of dif-

ferent shapes?

204 Student 2: Yeah.205 Student 1: Yeah, and not being stuck together as much as solids.

206 Teacher: Okay, now he is sticking them together though (refers to a

student working on the drawing).


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207 Student 2: Yeah, I think theyre stuck together, well it depends, if its

like in a crowded container, theyd probably be together,

its just like/208 Student 1: //Theyd have to be together, cause what else would there

be?

209 Student 2: Yeah, theyd be

210 Student 1: so theyd always have to be together.

211 Teacher: Sowhatwould distinguish a solid froma liquid if theyhave

to be together?

212 Student 3: I think the solids would be like more tight in the circles?

213 Student 1: Well, maybe the liquid (inaudible)/

214 Student 2: //I dont know if an atom has a definite shape though, it haslike/

215 Teacher: //Wait, see what youre doing is youre making that deci-

sion, youre deciding what you want it to be, thats what

this is all about, what do you want it to be that will explain

all of those things up there (points toa poster listing the labs

and questions).

Again, students are exhibiting naive conceptions about matter by suggesting

that the shapes of atoms and molecules reflect the shapes of the substances theycomprise. The teacher simply keeps asking them questions to probe the coherence

of their ideas and mirrors their thinking back to them. Through her questioning,

and more directly in the final turn, she encourages the students to keep creating and

refining ideas.

Repeats and elaborates. One dialogue tactic the teachers used was restat-ing students words verbatim, as in the following exchange:

231 Teacher: Now is a gas the same, how is the gas, we know gases are

lighter than liquids, how would they be different from liq-

uids?

232 Student 1: Maybe theyre, theyre separated, spread apart.

233 Teacher: So youre saying the atoms are separated.

They also sometimes elaborated on students statements after repeating them

verbatim, shaping the statements into more sophisticated ideas that still reflected

the students own words. They also restated students statements with addedclarity by using more concise language than students used. Sometimes the teach-

ers added an inference to a restatement, which took the form of, So if youre

saying (this), then you must also mean (that). Teachers both repeated and re-


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shaped students statements to clarify, emphasize, or prompt reflection on what

the students were saying.

After listening to different students in a group articulate their ideas, the teacherssometimes summarized what everyone had said, often pointing out discrepancies

among different viewpoints. Finally, the teachers also elaborated on their own

statements. When students did not understand a teachers question or were at a loss

for how to answer it, the teachers added more details to their question or restated it

in a new way.

Reacts. Teachers interchanges with students were peppered with neutral re-

actions. They said okay or uh huh as students talked to communicate that theywere listening to, receiving, and following what the students were saying. They

also prefaced their own comments with a verbal acknowledgment of the students

prior statement. When they agreed, accepted, or confirmed students statements,

they did this in a low-key way, such as in line 557 of the following excerpt:

552 Student 1: [Looking at their diagram of the molecular structure of a

gas.] But whats right in the middle, like in between these

atoms?

553 Teacher: What is in between those atoms? What do you think wouldhave to be between those atoms?

554 Student 1: Ahh nothing?

555 Student 2: Theres gotta be something though.

556 Student 3: Couldnt be a gas, cause thats what it is.

557 Teacher: Thats a good thought. You think about that.

Enculturates. The teachers enculturated students into a community of scien-

tific sense making in part by communicating expectations and standards for theirwork, such as that their oral presentation of their models be coherent to the audi-

ence. They also linked students work to that of scientists, such as by explaining

what scientists expect models to do. For example, after explaining to the whole

class how scientists use models, the teacher said to one group after they showed her

their model, This is what I mean by a model. Now, the only way well know how

good this is is as you go through each of those characteristics of solids, liquids, and

gases (and see) whether or not its successful in explaining these things. In this

way the teacher set students up to judge the success of their models as scientists do,

rather than through typical school-based modes of evaluation based on a teachersauthority.

A third type of statement coded as enculturation was the teachers enculturation

into the students culture. The teachers accomplished this through adopting stu-


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dents language, such as by using the worddotsfor particles andconnectorsfor

bonds if those were the words that the students used.

Comparing the Types and Functions of Peers andTeachers Contributions to Group Discussion

The previous two sections of results summarized the microanalysis of four groups

discussions, with and without teacher participation, across 4 days of mental model

building activity. Weshift now to presenting a range of analyses comparing the sin-

gle longest peer and teacher-guided knowledge construction discussions for each

group. However, Group 1 remained in the knowledge construction mode for an en-tire class periodmuch longer than any of the other samples. So for Group 1 we

chose a knowledge construction discussion closer to the median length of the other

groups discussions. The primary data for the following analyses, then, were eight

discussions focused on knowledge construction, four among peers and four with

teachers. Each of theeightdiscussions within this subsample was mapped usingthe

discourse mapping technique described in theMethods section. Although eight dis-

cussions formed the basis for the remaining analyses, all of the transcribed and

taped discussions, as well as field notes recorded throughout the 12-week period,

were consultedas a secondary data source.The purpose was toseek confirming anddisconfirming evidence of the patterns that emerged (Miles & Huberman, 1994).

The discourse maps tracked the flow of conceptual contributions, questionsque-

ries, and metacognitive contributions within discussions, with nonconceptual moves

such as agreeing, restating, and repeating as well as digressions noted tangentially

within the maps. Table 8 presents data on the three main categories of discourse that

were tracked within the discourse maps.

The discourse maps also made it possible to determine one type of function of

each contribution to the discussions, namely how each was used to initiate interac-


TABLE 8

Number and Percentage of Three Types of Statements Contributed by Students and

Teachers in Peer and Teacher-Guided Discussions

Peer Discussions Teacher-Guided Discussions

Student Statements Student Statements Teacher Statements

Statement Type No. % No. % No. %

Conceptual 124 65 142 86 3 3Questionquery 34 18 8 5 90 81

Metacognitive 34 18 15 9 18 16

Total 192 165 111

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and confirm the intended pedagogical approach of the teachers during this unit.

They did not impart conceptual information to students but rather supported them

to construct their own mental models based on direct experience with phenomenaencountered in carefully planned and sequenced labs and demonstrations.

In teacher-guided discussions few conceptual statements initiated interaction

sequences (see Table 9) or transitions to new topics (see Table 10) relative to the

initiating function of conceptual statements in peer discussions. Within peer

groups, students initiated new topics with conceptual statements more often than

with queries or metacognitive statements about new topics (see Table 10), so the

statement of new ideas was an important means of entering into new conceptual

territory for students.

Questionsqueries. There were substantial differences in the amount ofquestions and queries that teachers and students contributed to teacher-guided

knowledge construction discussions. Of the teachers contributions, 81% were

questionsqueries, whereas only 5% of students contributions were in this cate-

gory. Students shared more than three times as many questions and queries within

peer discussions than within teacher-guided discussions (18% compared to 5%),

indicating that the structure of those two modes of discussion was quite different,

with students expressing more variety of cognitive activity when they worked to-gether without teacher input.

Qualitative differences in how teachers and students used questions and queries

also distinguish the peer and teacher-guided modes of discussion. The teachers

tended to pose questions, whereas the students more often articulated queries. This

is indicative of the relative roles of teachers and students in the knowl-

edge-building groups. The teachers were not equal participants in the dialogue be-

cause they possessed their own sophisticated models of the nature of matter,

whereas the students had relatively unformed and naive models. The teachers

questioned students from the stance of experts trying to assess and advance the sta-tus of a novices knowledge. The teachers overriding personal question was not

What is the nature of matter? but rather, What are these students thinking

about the nature of matter and how can I help them improve their reasoning and

understanding? An excerpt from a teacher-guided discussion is illustrative. The

teacher had just asked the students what they thought they would see if they could

magnify matter billions of times. One student (Student 3) said Bacteria, another

said Atoms, and another said Molecules.

12 Teacher: Now what would they look like, atoms and molecules?When you say that, I dont know what you mean by that,

you have to tell me what you mean.

13 Student 1: Lots of billions of circles.


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14 Student 2: Yeah, lots of circles.

15 Student 3: Yeah.

16 Teacher: Bunches of little circles.So you think that, so with this bac-teria idea, what was it that ?

17 Student 3: Well, I thought you could see bacteria, but I guess it would

be too big?

18 Teacher: Bacteria is too big?

19 Student 3: Yeah.

20 Teacher: So how do you think atoms and molecules are related to

your bacteria?

21 Student 3: I dont know. I think theydprobably justbe around, proba-

bly [shakes his head back and forth].22 Teacher: Im just curious when you said bacteria and then you said

atoms and molecules and you (looks at the other two stu-

dents) went with atoms and molecules, what would you en-

vision when he said bacteria, how would that be related to

this concept of atoms and molecules, because bacteria is

something.

23 Student 1: Bacteria is like everywhere so

24 Teacher: How is it related to atoms and molecules?

25 Student 1: Because atoms and molecules make up bacteria and theymake up us and they make up a lot of things.

26 Teacher: So you think bacteria itself is made up of these atoms and

molecules?

27 Student 3: Yeah.

Although the roles of teacher as questioner and student as answerer are similar to

those found in traditional recitation-based classroom interchanges, the crucial dif-

ferentiating feature of this questionanswer exchange is the lack of evaluative

statements by the teacher, a point taken up again in the next section.In contrast, the students task when talking with one another without the teacher

present was not explicitly to probe one anothers understanding, but to generate an

adequate model. The students did not take on the role of tutors responsible for

moving along a peers thinking through strategic questioning. Students shared

more queriesthe genuine statements of puzzlement described earlierthan

teacher-like questions that probed others ideas.

Questionsandqueriesinitiatedmostoftheinteractionsequencesinbothpeerand

teacher-guideddiscussionsbutdramaticallymoresoingroupswhentheteacherwas

present(seeTable4).Theinitiationofinteractionsequenceswasmorevariedinpeergroups than in teacher-guided groups, with conceptual and metacognitive state-

ments each initiating interactionsequences for abouta quarterof the totalsequences

inpeerdiscussions,andquestionsandqueriesinitiatingabouthalfofthesequences.


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Metacognitive contributions. Students made twice as many metacognitivecontributions to peer discussions (18%) as they did to teacher-guided discussions

(9%), indicating that teachers took on some of the regulatory and reflective roleswhen they joined students groups. Teachers and students both made metacognitive

statements that focused and regulated action, such as suggesting what topic to tackle

next. In addition, teachers imparted metacognitive knowledge about the nature of

the task, such as by telling students that model building is an essential activity of

professional scientists. The teachers also communicated standards and expecta-

tions with statements such as The purpose of this is not to look things up. I could

have you read a book. What were trying to do is make sense of matter, and The

model can be anything you decide it is, so long as it can explain all of the results of

your labs. The teachers standards-based metacognitive moves were means ofenculturating students into certain practices of science, as described earlier. Stu-

dents standards-based metacognitive statements echoed the more task-specific

statements of the teacher, most commonly reminding their peers that their model

had to explain their lab results.

Another type of students metacognitive statements expressed concern about

the scrutiny of knowledge claims by other student groups who would be judging

their models. In the following excerpt, the students are rehearsing how they will

explain the phenomenon of dissolving to the class in terms of their molecular

model. In the metacognitive statements in lines 268, 270, and 272, the student sug-gests that so long as they defend their model as their own construction rather than

as absolute truth, then the other students cannot give them a bad evaluation.

264 Student 1: This is the liquids [she is making a drawing],

265 Student 2: Yeah

266 Student 1: These are the little solids,

267 Student 2: Yeah

268 Student 1: One of them comes in contact with thatwe can say that to

us, we think269 Student 2: Okay.

270 Student 1: Cause theycant say, theycant markusbad ifwedont/

271 Student 2: //Yeah, thats true.

272 Student 1: Yeah, were not sayingthis isa fact, were sayingwethink.

Metacognitive awareness of others possible reactions to their models and explana-

tions propelled some groups to examine critically their own ideas and continue to

improve their knowledge claims collaboratively.

Metacognitive evaluations of students ideas were virtually absent from teach-ers statements. On the few occasions when teachers did offer an evaluation, their

statements were general and positive, and they were directed at the whole group,

such as It looks as though youve done some good thinking here, or You seem


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to be on the right track. Students also did not often step back to evaluate ideas ex-

plicitly, although they occasionally commented that either personally or as a group

they did or did not understand something. They rarely directly evaluated anotherpersons idea as good or bad but instead proposed counterevidence to challenge

each others ideas when they disagreed with what had been stated. In this way they

revised their ideas more by implicit judgment and conceptual interchange than by

explicit evaluation and subsequent revision.

Metacognitive contributions initiated a greater proportion of interaction se-

quences and transitions to new topics in peer discussions than in teacher-guided

discussions (see Tables 9 and 10). Teachers did not move students thinking along

so much through metacognitive statements as through directly questioning their

ideas.

R

hogan, nastasi, pressley. 2010. discourse patterns and collaborative scientific reasoning in peer...

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