Scaffolding Preservice Science Teachers' Evidence-Based Arguments During an Investigation of Natural Selection

Research in Science Education 32: 437–463, 2002.© 2003 Kluwer Academic Publishers. Printed in the Netherlands.

Scaffolding Preservice Science Teachers’ Evidence-Based Arguments Duringan Investigation of Natural Selection

Carla Zembal-Saul1, Danusa Munford1, Barbara Crawford1,Patricia Friedrichsen2 and Susan Land1

1The Pennsylvania State University2University of Missouri at Columbia

Abstract

In this qualitative case study, preservice science teachers (PSTs) enrolled in their advanced methodscourse participated in a complex, data-rich investigation based on an adapted version of the Strugglefor Survival curriculum. Fundamental to the investigation was the use of the Galapagos Finchessoftware and an emphasis on giving priority to evidence and constructing evidence-based arguments.The questions that guided the research were: (1) What is the nature of the scientific argumentsdeveloped by PSTs? (2) How do PSTs go about constructing scientific arguments (emphasis onprocesses and strategies)? (3) In what ways do the scaffolds embedded in the Galapagos Finchessoftware influence the development of PSTs arguments? Two pairs of PSTs were selected for in-depthexamination. The primary sources of data were the electronic artifacts generated in the GalapagosFinches software environment and the videotaped interactions of both pairs as they investigated thedata set, constructed and revised their arguments, engaged in peer review sessions, and presentedtheir arguments to the class at the end of the unit. Four major patterns emerged through analysis ofthe data. First, using the software, PSTs consistently constructed claims that were linked to evidencefrom the investigation. Second, although PSTs consistently grounded their arguments in evidence,they still exhibited a number of limitations reported in the literature. Third, the software served as apowerful vehicle for revealing PSTs knowledge of evolution and natural selection. Finally, the PSTsapproach to the task had a strong influence on the way they used the software.

Key Words: argumentation, evolution, preservice science teachers, software scaffolding

Contemporary reform efforts in science education call for science teaching thatsupports all students’ meaningful learning (e.g., Mintzes, Wandersee, & Novak1998) and scientific inquiry (American Association for the Advancement of Science(AAAS), 1990; National Research Council (NRC), 1996, 2000). In particular, theNational Science Education Standards (NRC, 1996) call for the centrality of inquiryin science learning, emphasising that students should “actively develop their under-standing of science by combining scientific knowledge with reasoning and thinkingskills” (p. 2). The importance of inquiry in school science has an established history(Bybee & DeBoer, 1994; DeBoer, 1991; Trowbridge & Bybee, 1990) dating backto Dewey (1910) and Schwab (1962, 1978). However, the renewed emphasis on sci-entific inquiry reflects a distinct shift from science as exploration and experiment toscience as argument and explanation (NRC, 2000, p. 113). From the reform perspec-tive, priority is given to evidence and the development and evaluation of scientific

438 CARLA ZEMBAL-SAUL ET AL.

explanations. During all phases of the inquiry process, “Students and teachers oughtto ask what counts? What data do we keep? What data do we discard? What patternsexist in the data? Are these patterns appropriate for this inquiry? What explanationsaccount for the patterns? Is one explanation better than another?” (p. 18).

This approach to science learning presents new challenges for students engagedin authentic investigations of science phenomena. Loh, Radinsky, Reiser, Gomez,Edelson, and Russell (1997) explained, “The complexity of open-ended investiga-tions poses difficulties for groups of students who must continually negotiate plansand share understandings throughout an investigation” (p. 1). Not only do studentsstruggle with organising evidence and interpreting results, they often leave importantquestions unanswered when they are unable to make critical connections across var-ious aspects of their investigations. The question for science educators becomes oneof how to support learners as they participate in complex, data-rich investigations ofscientific phenomena that require giving priority to evidence and constructing andevaluating scientific arguments. Furthermore, can preservice and practicing teachersbe supported in orchestrating these types of learning opportunities for their studentswhen most have not experienced learning science in this way themselves?

In this study, we engaged preservice secondary science teachers enrolled in theiradvanced methods course in an extended, complex, data-rich investigation. Giventhe perceived need to engage preservice science teachers in authentic investigationsof natural phenomena that require them to give priority to evidence and constructevidence-based arguments, experiences which they report not having had previously(Munford, 2002), we used the Galapagos Finches software and an adapted versionof the Struggle for Survival curriculum, both of which were designed with thesepurposes in mind (see the Instructional Context section for an in-depth descriptionof the software). The questions that guided our research were: (1) What is the na-ture of the scientific arguments developed by preservice teachers? That is, how dopreservice teachers structure their arguments? In particular, what evidence do theyuse and how do they use it? In addition, to what extent are their arguments consistentwith scientifically accepted constructs in the domain? (2) How do preservice teachersgo about constructing scientific arguments (emphasis on processes and strategies)?(3) In what ways do the scaffolds embedded in the Galapagos Finches softwareinfluence the development of preservice teachers’ arguments?

Literature Review

As mentioned previously, the renewed emphasis on scientific inquiry in contem-porary reform efforts shifts the focus to science as argument and explanation (NRC,2000, p. 113). Practices, such as assessing alternatives, weighing evidence, inter-preting texts, and evaluating the potential viability of scientific claims are all seenas essential components in constructing scientific arguments (Driver, Newton, &Osborne, 2000; Latour & Woolgar, 1986). Recently, various authors have calledattention to the significance of argumentation to science education. For example,

SCAFFOLDING PRESERVICE SCIENCE TEACHERS’ ARGUMENTS 439

Jimenez, Rodriguez, and Duschl (2000) explained, “Argumentation is particularlyrelevant in science education since a goal of scientific inquiry is the generation andjustification of knowledge claims, beliefs and actions taken to understand nature”(p. 758). Other authors highlight the importance of argumentation for a variety ofreasons. First, learners can experience scientists’ practices that situate knowledge inits original context (Brown, Collins, & Duguid, 1989), as well as provide opportuni-ties to learn about science, not merely science concepts (Driver, Newton, & Osborne,2000; Osborne, Erduran, Simon, & Monk, 2001). Second, learners’ understandingsand thinking can become more visible (Bell & Linn, 2000), representing a tool forreflection and assessment (Abell, Anderson, & Chezem, 2000; Sandoval & Reiser,1997; Zembal-Saul & Land, 2002). Finally, argumentation can support learners in de-veloping different ways of thinking (Kuhn, 1991, 1992, 1993) and facilitate sciencelearning, taking into consideration the role of language, culture and social interactionin the process of knowledge construction (Pontecorvo, 1987).

As suggested above, constructing scientific arguments as one aspect of engag-ing in school-based scientific inquiry and supporting meaningful science learning isbecoming more prominent in the literature (e.g., Driver et al., 2000; Kuhn, 1993;Linn, 2000; Newton, Driver, & Osborne, 1999). However, scholarship in this areais somewhat “messy,” often making reference to argument and explanation inter-changeably. In this study, we rely on the construct of argumentation in school scienceas described by Zembal-Saul (2002). That is, in the context of this study, preserviceteachers were instructed to explain particular phenomena by constructing argumentsthat consisted of claims, evidence, and justification. Claims are assertions groundedin data/evidence that are intended to account for the phenomena under investigation.Evidence is drawn directly from the investigation, can assume multiple forms (e.g.,graphs, numerical data, field notes), and should be directly connected to the claim itis intended to support. Finally, justification provides an explicit rationale indicatinghow/why a particular piece of evidence is appropriate for supporting the claim towhich it is linked.

It also has been asserted that the purpose of argumentation in school science isdifferent than in everyday life (Zembal-Saul, 2002). More specifically, argumentationin school science is not merely intended to persuade others to join one’s position, butto explain the phenomena under investigation. In addition, the process of construct-ing the argument is one of reasoning (Kuhn, 1991, 1993) in context. The processrequires students to negotiate their developing understandings by constructing andre-constructing their arguments in light of new evidence and learning. Given that thefundamental outcome of engaging in argumentation is for students to learn scienceconcepts and learn about scientific inquiry, the process itself is equally, if not more,important than the final product or argument.

To be clear, approaching science learning with an emphasis on argumentation iscomplex and fraught with difficulties. Over the past decade, researchers have been in-vestigating the role of instructional scaffolds to facilitate learner comprehension andreflection on complex tasks (Brown, 1992; Palincsar & Brown, 1984). The constructof scaffolding is based on Vygotsky’s notion of the zone of proximal development


(Vygotsky, 1978). That is, learners are assisted by a “more knowledgeable other”in solving problems and/or accomplishing tasks that they otherwise would not havebeen able to do. Although much of the research on scaffolding has focused on therole of social interaction (Palincsar & Brown, 1984), others have promoted the use ofcomputer-based tools to scaffold learning and reflection (Lin & Lehman, 1999; Sa-lomon, Globerson, & Guterman, 1989). For the purposes of this research, scaffoldingis defined as software features that support students in performing tasks that theywould otherwise have been unable to accomplish and in learning from that experi-ence (i.e., improve performance on future, related tasks) (see Quintana, Reiser, &Davis (2002) and Reiser (2002)).

Recently, the Project ASSESS (Analyzing Software Scaffolds in Educational Set-tings for Science) research group (see http://www.letus.org/kdi/index.htm) has beenworking to characterise the software scaffolding strategies used to support learnersas they engage in school-based scientific inquiry. This effort has resulted in a seriesof guidelines, or general scaffolding strategies (Quintana et al., 2002) that attend tothe aspects of the work that learners are engaged in and that the scaffolding strategyis intended to address (e.g., generating, analysing and understanding artifacts, suchas graphs), the obstacles that learners are likely to encounter when dealing withparticular aspects of scientific investigations (e.g., learners can become overwhelmedin a complex investigation and lose focus/direction), and the various dimensions ofgeneral scaffolding strategies. These guidelines include the general software scaf-folding strategies for supporting scientific inquiry, such as using representations thatcan be inspected by learners to reveal important properties of the underlying data,facilitating articulation, and providing easy access to instructional support and/orexpert knowledge. Examples from a wide variety of software tools for supportingscientific inquiry are used to illustrate each of the guidelines and scaffolding strate-gies. Moreover, a number of these tools include scaffolds specific to assisting learnersin constructing scientific arguments.

Despite the strong support for argumentation and the growing number of softwaretools designed specifically to scaffold the process, argumentation practices have beenrare in science classrooms (Newton et al., 1999). Teachers’ lack of pedagogicalstrategies to support students in engaging in argumentation, as well as the limitedresources to assist teachers in doing so, have been identified as the major barriers tothe inclusion of argumentation in school science (Driver et al., 2000; Zeidler, 1997).It is unrealistic to expect teachers to adopt argumentation as a pedagogical practiceto teach science if they do not themselves develop more elaborated understandingsof argumentation in the context of science learning. Such development is possibleonly if teachers engage in “the practice of constructive argumentation” (Zeidler,1997, p. 485). However, virtually nothing is known about how science teachers,and in particular future science teachers, engage in scientific argumentation (Newtonet al., 1999). Therefore, the purpose of this study was to investigate the nature anddevelopment of preservice teachers’ arguments (i.e., structure and use of evidence;consistency with scientifically accepted knowledge) during an investigation of nat-ural selection, the processes in which they engaged to construct those arguments, andthe software scaffolds that influenced the development of their arguments.


Instructional Context and Software Description

As mentioned previously, the participants in this study were undergraduate sec-ondary science majors enrolled in their advanced methods course, which takes placeduring the last semester prior to student teaching. The course was modified by theinstructor (i.e., third author) in consultation with the rest of the research team toinclude as much time as feasible for the preservice teachers to participate in theinvestigation-based, technology-enhanced curriculum. More specifically, five two-hour class sessions were directly related to the implementation of the investigation(i.e., approximately ten hours of class instruction and computer lab work across athree week period). It should be noted that this time frame was substantially less thanthat provided for high school students to engage in a similar task (Sandoval & Reiser,1997). However, the entire course only spanned ten weeks followed by a five-weekpracticum experience. Moreover, our goals for providing this experience were dif-ferent than in school science settings. That is, our intention was to provide first-handexperiences for preservice teachers in which they could participate in an extended,data-rich, technology-enhanced science investigation that emphasised giving priorityto evidence and the construction of evidence-based arguments.

During implementation, preservice teachers worked in pairs to investigate an au-thentic problem, one that the biologists Rosalyn and Peter Grant were confrontedwith during the 1970s when working on one of the Galapagos Islands (Grant, 1986;Weiner, 1994). The pairs were required to explain the drastic decrease in the popu-lation of ground finches in 1977, as well as determine why some birds were able tosurvive. To do this, they used the Galapagos Finches software to study a rich datasetfrom the island habitat, Daphne Major. We intentionally selected the GalapagosFinches software and the supporting curriculum, Struggle for Survival, because oftheir attention to creating a context for scientific inquiry and supporting the con-struction of evidence-based arguments. The software and curriculum are part of theBiology Guided Inquiry Learning Environment (BGuILE) project directed by BrianReiser at Northwestern University (see http://www.letus.org/bguile/index.html) andsupported by LeTUS (Learning Technologies in Urban Schools) (see http://www.letus.org).

Reiser and colleagues characterised the Galapagos Finches software as a “strate-gic tool” (Tabak, Smith, Sandoval, & Reiser, 1996) and described the software asfollows:

The Galapagos Finches enables learners to investigate changes in populations of plants and animals inan ecosystem, and serves as a platform for learning principles of ecology and natural selection. Thetool makes explicit key strategies for examining ecosystem data – scientists can study a populationthrough time (a longitudinal comparison) or split a population according to some dimension of interest(a cross-sectional comparison). These two families of comparisons are options students must select whenconstructing a query (shown as the choices “seasons” and “subgroups”). Similarly, students must articulatewhat type of comparison they wish to perform (looking at individual differences, relationship betweentwo variables, and so on). . . In the Explanation Constructor, disciplinary frameworks are representedin the explanation guides that students use to ensure that their explanations address key features of theframework. (Reiser, 2002, pp. 4–5)


Figure 1: Population Tool in Data Query component of Galapagos Finches soft-ware.

All datasets in the Galapagos Finches software were pre-selected for the purposeof targeting particular scientific principles (e.g., natural selection). This scaffoldingstrategy is referred to as restricting a complex task by setting “proper boundaries”(Quintana, Reiser, & Davis, 2002). Figure 1 illustrates how population data compar-isons are structured in the Data Query component of the software. Other relevantdata also are accessible for examination and comparison through Data Query, suchas environmental factors (e.g., properties of various plants and animals, numbersof various species of plants and animals in a given season), field notes that de-scribe bird behavior, and profiles of characteristics of individual birds. Data Query isconceptually organized and requires learners to communicate the query they wouldlike to conduct in terms of disciplinary strategies (see above quote). This scaffold-ing strategy is known as structuring functionality according to explicit disciplinarystrategies.

As students use the Galapagos Finches software to explore the data, it automat-ically generates graphs so that learners can focus on analysing the data rather thanconstructing graphs. This scaffolding strategy is called automating portions of thetask to reduce extraneous cognitive demands (Quintana, Reiser, & Davis, 2002).Graphs and other data that learners examine are automatically stored in the DataLog. Here, students can annotate the results of each “slice” of the data that they haveattempted, and they can categorize results based on a discipline-specific frameworkin order to look for patterns in the data. These features of the Data Log exemplifythe scaffolding strategy, facilitating the organisation of work products.


Figure 2: Explanation Constructor.

Figure 2 shows the Explanation Constructor component of the software in whichstudents articulate questions and their corresponding arguments. Learners structurekey components of their arguments in the Organiser panel (upper left), and articulateclaims (Selected Explanation panel; middle left) that are linked to specific piecesof supporting evidence (Evidence panel; lower right) imported from the Data Log.In addition, students can “rate” their arguments and provide a rationale for theirrating (lower left). The Explanation Guides (upper right) are intended to providediscipline-specific support. The actual templates (i.e., Organiser and Selected Expla-nation panels) used to construct arguments serve as scaffolding for highlighting epis-temic features of explanations to support the development of scientific explanations(Quintana, Reiser, & Davis, 2002).

Note that although the software uses the language of explanations (e.g., Explana-tion Constructor, Explanation Guides), in this study we refer to preservice teachers’explanations as arguments because they were structured around claims, evidenceand justification. Claims intended to explain the driving questions (i.e., Why are thefinches dying? Why are some finches surviving?) were constructed in the SelectedExplanation panel. Each claim was supported by evidence that was explicitly linkedto it. Preservice teachers also were instructed to provide justification (i.e., a rationalefor how/why a particular piece of evidence was appropriate for supporting the claimto which it was linked) by annotating each piece of evidence in the Data Log as theyused it to construct their arguments.

Prior to introducing the Galapagos Finches software, several low-tech activitieswere conducted to focus the preservice teachers on central concepts associated with


the investigation. These lessons emphasised initial variation in a population andnatural selection. Lessons during the next three weeks included activities from allphases of the Struggle for Survival curriculum. First, preservice teachers generatedand examined drawings that represented their preconceived images of the GalapagosIslands. Next, they were introduced to the investigation through a video clip describ-ing the finch study and the island habitat of Daphne Major. This was followed by abrainstorming activity in which preservice teachers proposed possible hypothesesabout why so many finches died and why some of them survived. These initialhypotheses were pursued through a low-tech activity in which information aboutindividual finches and the finch population (provided on data cards) was graphed andinterpreted. The computer-based aspect of the investigation followed. During this pe-riod, preservice teachers explored the driving questions by analyzing data available inthe Galapagos Finches software, constructing scientific arguments grounded in data,and engaging in peer reviews of arguments. The instructional unit culminated withpresentations to the class in which preservice teachers were encouraged to participatein dialogue and debate around the scientific arguments of their peers.

Method

This study adheres to a qualitative case study design (Creswell, 1998; Stake, 1995,2000; Yin, 1989) that was naturalistic and interpretive, and sought to examine mean-ing in context. The overarching case is one of preservice science teachers’ argumentconstruction during a technology-enhanced investigation of natural selection. Instru-mental cases were purposefully selected to constitute the collective case study. Stake(2000) defined this type of case as that which is “examined mainly to provide insightinto an issue or to redraw a generalization” (p. 437). The instrumental cases includedin this study consisted of two pairs of preservice science teachers who were se-lected on the basis of providing insight into the nature and development of argumentconstruction in the context of an investigation-based, technology-rich instructionalsetting embedded within an advanced science methods course. Additional selectioncriteria included extensive coursework in biology at the college level and a minimumof one course in evolution. Each pair of preservice teachers also included at least onemember who had experience working in a research laboratory. It should be notedthat Helen and Eleanor both had earned advanced degrees in biology-related fields(i.e., biochemistry and plant physiology, respectively) before seeking certification.All four participants were receptive to taking part in the study. Finally, rich and com-plete data sets were available for these preservice teachers across the entire period ofimplementation.

A number of studies have documented the prevalence of alternative conceptionsassociated with evolution among college students and the general public (Bishop& Anderson, 1990; Good et al., 1992). Thus, our purpose for employing the afore-mentioned selection criteria, particularly those related to subject matter knowledge,was to minimise some of the potential domain-specific issues associated with the


Table 1Participants’ Science Experiences and Backgrounds.

Participant Science Experience

Shirley Secondary Science Education, Chemistry

Experience working in a plant evolution lab on campus

High school and college level coursework included evolution

Mark Secondary Science Education, Biology

Coursework included evolution

Helen Secondary Science Education, Biology

M.S. in Biochemistry

Experience working in a research laboratory

Eleanor Secondary Science Education, Biology

M.S. in Plant Physiology

Experience participating in scientific research

investigation, allowing us to focus on the nature and development of preservice sci-ence teachers’ arguments and their use of software scaffolds. The relevant sciencebackground and experiences for each participant is provided in Table 1.

Triangulation was achieved using a data source protocol (Stake, 1995). Multiplesources of data associated with the preservice science teachers’ argument construc-tion were collected across all phases of implementation. The primary sources ofinformation for the study were the electronic artifacts generated in the GalapagosFinches software environment and the videotaped interactions of both pairs as theyinvestigated the data set, constructed and revised their arguments, engaged in peerreview sessions, and presented their arguments to the class at the end of the unit.Electronic artifacts were collected after each class session so that the contributionof various iterations could be monitored. Videotaped interactions were collected insuch a way as to capture pairs’ conversations, as well as their work in the softwareenvironment. That is, the video cameras were placed so that software interactionswere clearly visible on the screen, while an external microphone simultaneouslyrecorded participants’ conversations.

Data analysis involved categorical aggregation and a search for correspondenceand patterns (Stake, 1995) that was guided by the constructs identified in the re-search questions. Analysis was conducted in several phases, beginning with thedevelopment of independent cases and culminating with a cross-case comparison.


First, the electronic artifacts for each pair were examined. The rubric used to analysepreservice teachers’ arguments is included in Appendix A. Emphasis was placed onthe structure of the arguments, particularly the kinds of claims that were made, theextent to which claims reflected scientifically accepted ideas about evolution andnatural selection, the appropriateness of the evidence used to support claims, theways in which evidence was justified in light of the claims being supported, andwhether and how alternative explanations were pursued. Case reports characterisingthe nature of preservice teachers’ arguments were then generated.

Next, the videotaped interactions for each pair were transcribed. Transcripts in-cluded direct quotes, as well as narrative descriptions of on-screen actions. Theywere then divided into episodes, which were defined by a series of interactions as-sociated with a particular idea and/or activity. Episodes of interaction were codedusing strategies consistent with constant comparative analysis (Strauss & Cobin,1998). Codes were developed and refined using the research questions as a guide.Selected examples from the analysis scheme used to address research questions twoand three are included in Appendix B. During this phase of analysis emphasis wasplaced on various aspects of the process of argument-building, including preserviceteachers’ approach to the problem, their strategies for investigating the data set, theirevaluation and use of evidence in the construction of claims, and their attention torelevant subject matter. Multiple researchers coded the data independently, and thencollectively the codes were examined and renegotiated until all discrepancies wereresolved. Emerging patterns regarding the ways in which preservice teachers’ wentabout constructing their arguments were identified. The case reports were updated toreflect this.

Finally, transcripts of the episodes of interactions were revisited with a differentlens – that of the influence of software scaffolds. In this phase of analysis, we at-tended to when and how preservice teachers used the scaffolds embedded in thesoftware as they investigated the dataset and constructed their arguments. In addition,scaffolds that were not employed in the process were noted. Case reports were againupdated, and cross-case analyses were conducted. Themes across the two pairs weregenerated and interpreted in light of information about participants’ backgroundsand experiences in science, the intended contributions of the software scaffolds, andwhat is known from the literature regarding argumentation in school science and theinfluence of scaffolding. In an attempt to minimise the potential for bias, a researchteam that included all five authors, consistently met to review the emerging findingsand check for disconfirming evidence.

Findings and Discussion

Analysis of the data associated with this case of preservice science teachers’ argu-ment construction in the context of a technology-enhanced investigation of naturalselection yielded four central themes: (1) software supported the development ofevidence-based arguments; (2) issues associated with preservice teachers’ arguments


a) Why did so many finches die in 1977?Decrease in rainfall (1) ⇒ decrease in seeds (2) ⇒ finches eat seeds ⇒ reducedfood supply for finches (3) ⇒ only Tribulus was available (4) ⇒ finches havedifficulty eating Tribulus (5) ⇒ many finches died (6)

b) Why were some birds able to survive?Bigger beak sizes (7) ⇒ enables finches to eat Tribulus seeds (8) ⇒ Tribulus seedshave harder shells (9)

Figure 3: Causal sequence for Shirley and Mark’s argument.

persisted; (3) software served to reveal domain-specific knowledge; and (4) the ap-proach to the task influenced the use of the software. This section is structuredaround these themes. Evidence from both pairs is used to illustrate major points,and findings are discussed in light of current research on argumentation in schoolscience, software scaffolding, and science learning.

Theme 1: There were no instances in which preservice teachers failed to link theclaims they constructed to supporting evidence.

Although they went about constructing their arguments in different ways (seeTheme 4), both pairs linked evidence directly to every claim they generated usingthe tools in Explanation Constructor. Preservice teachers were frequently observeddiscussing whether they had enough evidence to support a particular claim. Discus-sions regarding the quality of the evidence, however, were rare. Nevertheless, thereis a great deal of evidence from the literature suggesting that students rarely providegenuine evidence to support their explanations in science (Kelly, Druker, & Chen,1998; Kuhn, 1991, 1993; Yerrick, 2000). In addition, they have difficulty distinguish-ing explanations from evidence (Kuhn, 1993). Unlike the students described in theliterature, the participants in this study consistently supported their arguments withevidence, which was directly linked to claims.

Analysis of Shirley and Mark’s electronic journal revealed that their argument forwhy so many finches died and why some were able to survive was based on beak size(see causal sequence, Figure 3). They provided at least one piece of evidence for eachclaim that constituted their argument, relying heavily on field notes and artifacts fromthe Environment Window. When using field notes as evidence, the pair consistentlyincluded additional sources of evidence. Shirley and Mark also generated scatterplots for use as evidence; however, the graphs were constructed without sorting forthe finches’ age, sex, or mortality.

Like Shirley and Mark, Helen and Eleanor’s argument for why so many finchesdied was also based on beak size. However, they pursued an alternative explanationto beak size for why some birds were able to survive – weight (see causal sequence,Figure 4). This pair also supported the claims of their arguments with evidence. Theyrelied heavily on the use of frequency graphs and artifacts from the EnvironmentWindow, using field notes in only one instance. When using graphs to support theirclaims, Helen and Eleanor consistently relied on multiple pieces of evidence.


a) Explanation 1: Beak sizeLack of rain (1) ⇒ decrease in plant population (2) ⇒ fewer seeds ⇒ reduction infood supply for finches ⇒ those with bigger beaks survived (3)

b) Explanation 2: WeightHeavier finches survived (1) ⇒ more fat and energy storage (2) ⇒ went longerwithout food (3)

Figure 4: Causal sequence for Helen and Eleanor’s argument.

In related research on the high school students’ use of the Galapagos Finchessoftware, Sandoval and Reiser (1997) reported that the participants in their study alsoused evidence to support their claims. Thus, one of the most significant contributionsof the software and associated curriculum is its potential to scaffold learners’ argu-ment construction by highlighting epistemic features of explanations to support thedevelopment of scientific explanations (Quintana, Reiser, & Davis, 2002), particu-larly in terms of constructing evidence-based arguments. More specifically, evidencewas easily imported from the Data Log to the Explanation Constructor and linked tospecific claims using the linking tool, explicitly supporting the connection betweenargument and evidence. In addition, the software provided distinct spaces for learnersto generate evidence (i.e., Data Query), to collect and interpret evidence (i.e., DataLog), and to articulate their developing arguments (i.e., Explanation Constructor).This structure assisted learners in distinguishing between generating evidence andbuilding arguments during the investigation.

Theme 2: Although preservice teachers consistently grounded their arguments inevidence from the investigation, their arguments still displayed a number of limita-tions reported in the literature.

The preservice teachers’ arguments in this study differed from those reported inthe literature in terms of supporting claims with evidence; however, a number ofissues associated with their arguments were evident and persisted throughout thestudy. These issues were not ameliorated by interactions with instructors and/or thesoftware, or by participating as learners in the investigation. Rather, they were uncov-ered during careful analysis of the electronic artifacts and videotaped interactions.For instance, the arguments described here lacked complexity and, in the case ofShirley and Mark, did not include alternative causes (e.g., natural selection and/orchange in behavior) or explore the possibility that different factors could be involvedin the same cause (e.g., selection of different traits). Kuhn (1991, 1993) suggestedthat being able to conceive of alternative explanations is a fundamental aspect ofargumentation. More specifically, fully evaluating an argument depends on beingable to judge it against alternatives, recognizing the features that make one argumentmore convincing than another.

While Shirley and Mark did not explore counter arguments during the investiga-tion, there is evidence in the literature suggesting that their approach was typical.For example, in an extensive study on informal argumentation, Kuhn (1991, 1993)


reported that participants only offered alternative arguments when requested to doso by the researcher. Bell and Linn (2000) described similar findings in their studyof science students learning about light. Although students were presented with twoopposing hypotheses, the authors reported that they rarely included backing (i.e.,evidence) for the warrants (i.e., justification) in their arguments. The researcherspurported that backing was included in arguments only as warrants were called intoquestion, and the lack of backing was probably related to the fact that students wereunable to conceive of counter arguments. More specifically, despite being providedwith two alternatives, students aligned with one of them and did not consider theother to be a viable option.

Another issue associated with preservice teachers’ arguments was their problem-atic use of evidence. For example, although Shirley and Mark consistently supportedtheir claims with evidence, they only used multiple pieces of evidence to supporta given claim when using field notes. When used as evidence, graphs tended tostand alone. Moreover, the pair did not combine different types of evidence for anyone claim (e.g., field notes and graphs), and rarely used the same piece of evidencemore than once in their argument. In contrast, Helen and Eleanor consistently usedmultiple pieces of evidence to support their claims; however, they only constructedfrequency graphs. Their argument for finch survival relied solely on those graphs, andno evidence of bird behavior was presented. Like Shirley and Mark, this pair nevercombined different types of evidence, nor did they use the same piece of evidencemore than once in their argument.

Both pairs also exhibited what Zeidler (1997) called “inadequate sampling of evi-dence,” particularly “hasty conclusions or generalizations.” An example of this is to“seek too little information to warrant a firm conclusion or to achieve credibility inthe transfer of particular instances to other settings” (p. 491). Zeidler argued that thisissue has “less to do with protecting a core belief than knowing what counts as rea-sonable evidence”(p. 491), which is further complicated by the need to apply context-dependent criteria (Driver et al., 2000; Newton, Driver, & Osborne, 1999; Zeidler,1997).

The preservice teachers in this study, particularly Helen and Eleanor, generateda number of graphs using Data Query, a scaffold intended to automate portions ofthe task to reduce extraneous cognitive demands (Quintana, Reiser, & Davis, 2002).However, although Data Query is organised conceptually to structure functionalityaccording to disciplinary structures, both pairs were consistently unable to applya domain-specific framework for identifying and evaluating appropriate and com-pelling evidence in the specific context (Newton, Driver, & Osborne, 1999), whichresulted in inadequate sampling. Shirley and Mark, for example, accepted the firsttwo graphs that they generated to support a key claim in their argument. These graphsdid not represent the most appropriate or powerful evidence to support the claim.Helen and Eleanor also made hasty generalisations, rejecting their initial argumentfor the survival of the finches (i.e., beak size) when confronted with a graph thatdid not confirm their hypothesis. They did not question the evidence, nor did theyattempt to interpret it. Again, in both of these cases, neither the instructors nor the


software adequately supported preservice teachers in considering “what counts asevidence” within the context of the investigation.

A final issue associated with preservice teachers’ arguments was that they did notprovide justification. This pattern has been extensively documented in the literature(Bell & Linn, 2000; Sandoval & Reiser, 1997; Zembal-Saul & Land, 2002). Forexample, Sandoval and Reiser (1997, March) reported that middle school studentsusing the Galapagos Finches software tended not to provide justification for therelevance of evidence. They proposed two possible explanations for the lack of jus-tification in students’ responses. First, students may have seen justification as beingredundant because they considered the relationship between evidence and claims tobe obvious. Second, students may have viewed the plausibility of the claim to besufficient justification.

Theme 3: The software served as a powerful vehicle for revealing preserviceteachers’ knowledge of evolution and natural selection.

Recall that the participants in this study were selected based on their extensiveprior coursework and research experiences in science, particularly biology-relatedfields. Again, the intent was to minimise issues associated with domain-specificknowledge so that we could focus on the structure of preservice teachers’ argu-ments, the process in which they engaged to construct their arguments, and theways in which the software influenced the structure and development of their argu-ments. Although a number of studies have documented the prevalence of alternativeconceptions associated with evolution among college students and the general pub-lic (Bishop & Anderson, 1990; Good et al., 1992), the limitations in participants’domain-specific knowledge were largely unexpected and disconcerting. The Galapa-gos Finches software, particularly the population tool in Data Query, and the problemcontext were pivotal in revealing these limitations in preservice teachers’ knowledgeof natural selection.

A holistic examination (i.e., natures of claims and supporting evidence used inelectronic journal and final presentations) of Shirley and Mark’s argument suggestedthat they struggled with the concept of differential survival. As mentioned previ-ously, Shirley and Mark did not consider variables that were available to sort theindividual birds when constructing population graphs (e.g., age, sex, mortality). Thisis particularly problematic given that their argument was structured on the premiseof differential survival. At the most basic level, biologists are aware that there aredifferences, particularly in size, that are related to sex and age. In the finch scenario,considerations about differences in sex are critical because from 1973 to 1977 therewas an increase in the proportion of males in the finch population. In light of this,one might attribute the increase in mean beak length to changes in the sex ratio.Furthermore, a biologist would notice that there are two distinct groups in the graphfrom the wet season of 1973 (see Figure 5), and attempt to determine what thesegroups represented (i.e., adults versus fledglings). In contrast, Shirley and Mark didnot interpret the variation that was depicted in the representations they constructed.

Another limitation in domain-specific knowledge that the pair exhibited was theiremphasis on changes in individuals versus changes in populations. Shirley and Mark


Figure 5: Scatter Plot showing two distinct groups (i.e., adults v. fledglings) in thewet season of 1973.

experienced difficulty not only in terms of showing change in the population, but alsoin presenting evidence to illustrate how those changes might have occurred. Recallthat they did not sort for mortality or construct frequency graphs. Given the absenceof frequency graphs, the evidence that the pair used did not appropriately supportan argument involving a shift in the frequency of a trait in the population. The pairmerely relied on evidence that illustrated a shift in the mean of individuals throughtime. Therefore, it is likely that Shirley and Mark did not hold robust understandingsof a Darwinian explanation for change in population traits.

Related to this are Shirley and Mark’s teleological understandings (i.e., individ-uals change in response to need) (Bishop & Anderson, 1990; Demastes, Good, &Peebles, 1995; Jensen & Finley, 1996), revealed through an analysis of the field noteevidence used in both parts of their argument. Limitations and contradictions in theirunderstandings are evident in the overall argument, particularly when one examinesthe evidence used to support claims in the first and the second question. Initially,the pair stated that all finches (without distinction among individuals) had difficultyeating Tribulus seeds. To support their claim, Shirley and Mark used evidence of thesame individual eating seeds of different species of plants at different periods, expe-riencing more difficulty eating Tribulus, and eating it as the last resource. Implicit inthese pieces of evidence is the notion that a change in behavior took place, and birdsdeveloped the ability to eat seeds with thicker shells only when there was nothingelse left. In other words, the pair’s supporting evidence suggested that they believedthat the finches would need to eat seeds with thinner shells, not that some individualswould be unable to eat thicker-shelled seeds and eventually die. Later, to addressthe question of why some finches survived, Shirley and Mark implicitly argued thatbirds with bigger beaks would be able to eat seeds with thicker shells. At that point,they stated that surviving birds were able to eat the thicker-shelled Tribulus seedsand related that capability to having bigger beaks. However, they never presenteddirect evidence that the particular individuals that survived had bigger beaks. Taken


together, their explanation and supporting evidence indicated that initial variationand differential survival were not concepts that informed the development of theirargument.

It should be noted that Shirley and Mark appeared to experience tension betweenthese conceptions and more scientifically accepted ones. Although persistent issueswere still evident, they were able to appropriately use concepts of the Darwiniantheory to articulate their arguments during the final presentation to the class. Thismay suggest that the pair was beginning to use their knowledge as tools, reveal-ing more robust understandings of natural selection (Brown, Collins, & Duguid,1989; Jimenez, 1992). Moreover, because Shirley and Mark experienced a conflictbetween their conceptions and scientifically accepted understandings and made aneffort to integrate natural selection into their argument, it is possible that they werein fact rethinking their notions about evolutionary phenomena. Demastes and col-leagues (1996) described these instances as patterns of conceptual change (i.e., dualconstruction and incremental change, respectively).

A similar analysis of Helen and Eleanor’s argument revealed their familiarity withsome basic concepts in the domain. First, they sorted individuals by sex and age,indicating an awareness of variability across these groups. They also sorted by mor-tality, indicating intention to identify traits in the population that might be relatedto their survival. This approach demonstrated the pair’s knowledge of differentialsurvival. Finally, they used frequency graphs, which suggests that they were awareof the importance of the concept of population and the ways in which frequencyconnects to individual data, representing variation within a population.

Although Helen and Eleanor’s approach to constructing their argument revealed anumber of strengths in their domain-specific knowledge, problematic aspects of theirunderstandings of natural selection were uncovered. The most striking trend was thatthe pair’s argument lacked many fundamental aspects of the theory of natural selec-tion (e.g., extended time frame, identification of selective pressure) and illustratedLamarckian conceptions (e.g., ignoring inheritance of traits as relevant) (Bishop &Anderson, 1990; Jensen & Finley, 1996; Demastes, Good, & Peebles, 1995). Thiscan be illustrated using several examples. First, Helen and Eleanor did not take intoaccount the fact that the weight of the birds typically changed from the dry seasonto the wet season. Moreover, they did not consider the potential complexities asso-ciated with the inherited component of weight as an explanation for finch survival.Second, the pair failed to identify a selective pressure that resulted in the changein the population. More specifically, they did not attend to environmental factors,such as variations in the thickness of seed coats of different species of plants, evenafter one of the instructors called their attention to it. In addition, the pair did notrecognize that after the drought the finches ate seeds from only one plant species.Third, Helen and Eleanor did not present evidence to support a connection betweenform and function (e.g., birds with bigger beaks could eat seeds with thicker shells).In sum, they did not try to establish explicit causal relationships between certainfactors of the environment and a change in frequency of certain traits over time.

Unlike Shirley and Mark, Helen and Eleanor did not appear to recognise any con-flict between their explanation and Darwinian ideas. During their final presentation


to the class, the pair began by providing an accurate formal definition of the prin-ciples of natural selection and contrasted it with the Lamarckian perspective. Theyproceeded to present their argument without making connections to the first half oftheir presentation or using natural selection as an explanatory framework. One canspeculate that Helen and Eleanor’s strong orientation for experimental science mayhave played a role in their inability to apply knowledge to an authentic, problem-solving context in a non-experimental field (Rudolph & Stewart, 1998). However,there is no data from this study to explore such a hypothesis.

Theme 4: Preservice teachers’ approach to the task had a strong influence on theway they used the software.

During the first day of the investigation, Shirley and Mark engaged in a thought-ful, iterative process of exploring, discussing and reflecting on evidence that theycollected. They gained entry into the problem through the Environmental Window,and began developing an initial argument for the decline in the finch population.Using the Environment Window, the pair analysed the pattern of rainfall from thewet season of 1973 through the dry season of 1978, noting a decrease in rainfall inthe first season examined. Continuing to use the Environmental Window, the paircompared plant types and the number of seeds produced each year.

This exploratory, analytical approach to the task did not continue in the followingdays of the unit. On the second day of investigation, Mark explicitly stated, “See Ithink the difference is, cause we know it has something to do with their beaks, justfrom knowing something about genetics.” The pair went on to collect most of theirevidence very purposefully, and were attentive to details provided in the database.However, they now had a hypothesis in mind, so they only selected evidence thatthey thought would support it, repeatedly ignoring evidence that contradicted theirhypothesis. Shirley and Mark’s approach is illustrated by the following discussionthat took place on the second day they were constructing their argument for why somany birds died. The pair was using Data Query to examine field notes.

[Shirley clicks to the field notes about individual ground finches. Throughout this next section, the pairscans field notes on different individuals’ foraging behavior during wet 1976. This is the last wet yearbefore no rainfall, although there is a small drop in rainfall beginning in wet 1976.]

Shirley: This is a new trick that we learned, like we can pick a finch here [reads field note] and #71 iseating spiders [says with surprise], so that’s no good. But we can go to the next one, [clicks on anotherindividual] no foraging, waiting for its parents.

Mark: [reads a foraging field note] Soft fruit.

Shirley: Where was that? Some spiders or soft fruit? Are any of those things soft fruit?

Mark: Let’s see if we can find something else about seeds.

Shirley: [Shirley scans more individuals and reads foraging field notes.] For food, spiders. [clicks to thenext individual and reads the foraging notes] Leaves. Flowers.

Mark: No.

[Shirley clicks to another individual’s field note.]

Mark: [reads the field note] No, spiders.


[Shirley clicks to another individual’s foraging field notes. They scan the field note.]

Mark: No, spiders.

[Shirley clicks to the next foraging note.]

Mark: Spiders.

[Shirley clicks through more individuals but they have blank field notes on foraging. She clicks to adifferent individual, and silently reads a foraging field note from the wet season of 1976.]

Shirley: Ok, so there’s one of the plants we had. So that’s good. [pause] Oh, my goodness!

Mark: [finishes reading the field note] Didn’t eat it.

Shirley: [laughs] We might be in trouble here. I bet this is a trap that kids fall into, too.

They systematically continued to look through the field notes for confirming evi-dence that the ground finches ate seeds while ignoring the contradictory evidenceabout eating spiders.

Using Chinn and Brewer’s taxonomy (1993), this response can be classified as “re-jection of anomalous data.” In these instances, individuals do not accept the evidenceas valid, and consequently they do not alter their current argument. Nevertheless,they still do offer an explanation for the data. Different kinds of explanations fallinto the category of rejection of anomalous data, such as “explain[ing] that the datashould not be believed because the scientists may have made a mistake or evencommitted fraud” (p. 64). Interestingly, Shirley and Mark attributed the occurrenceof anomalous evidence to “a trap that kids fall into, too.” In other words, the pairwas so convinced that they knew the right answer that they were willing to attributeanomalous data to teacher fraud rather than reconsidering their argument and/orevidence.

Helen and Eleanor responded differently to anomalous data at different points intheir investigation. Before examining the data set, Helen and Eleanor had an expla-nation for the events that took place on Daphne Major (i.e., beak size). The pair’sapproach to investigating the beak argument began with collecting information onthe plants in the Environment Window. On the second day of instruction, the pairexplored the database further. In the Population section of Data Query they obtainedan unexpected result from a comparison and decided to explore an alternative argu-ment associated with weight. As they pursued their second hypothesis, the pair againfound inconclusive evidence and struggled.

In contrast to Shirley and Mark, this pair’s identification of disconfirming evi-dence prompted them to pursue an alternate hypothesis. Chinn and Brewer (1993)categorised this action as “theory change.” Once the pair began investigating analternative argument, about which they were less certain in terms of correctness, theyadopted a much more exploratory approach and used domain-specific scaffolds moreappropriately. Instead of seeking only confirming evidence, the preservice teachersbegan examining their own methods for generating graphs and attempted to deter-mine other ways in which to explore the data. Claims were constructed as a resultof generating, collecting, and inspecting multiple pieces of evidence. This process


was much more iterative and illustrated the intended use of the software to supportinvestigating the problem and articulating an argument.

Conclusions

The findings of this study suggest that, when used appropriately, scaffolding strate-gies embedded in software can support learners in engaging in complex, long-terminvestigations. In particular, software scaffolds can play a role in supporting thearticulation and development of evidence-based scientific arguments. Not only didthe participants consistently support their arguments with evidence, but one pairalso pursued alternative arguments during the investigation. While these findingscan be considered hopeful, it is important to take into account that regardless of howthoughtfully software features and curricula are designed, the instructional supportand learning environment are fundamental to successful participation in these kindsof investigations. Preservice teachers in this study did not receive the level of supportthey needed from instructors for a number of reasons, the most influential beingthat it was our first attempt to integrate and enact this technology-enhanced curricu-lum. In subsequent versions of implementation, emphasis was placed on learningthe targeted science concepts through argumentation while engaging in an investi-gation of natural phenomena (see Munford, 2002; Munford & Zembal-Saul, 2002;Zembal-Saul, Munford, & Friedrichsen, 2002).

Although the preservice teachers constructed arguments supported by evidencefrom their investigations, their arguments were still considered problematic in a num-ber of ways. For instance, the arguments described in this study lacked complexityand exhibited limitations regarding the nature and use of evidence. Given the appar-ent success of the linking tool with regard to making connections between evidenceand explanation, it may be useful to explore software features based on scaffoldingstrategies designed to address known limitations in students’ arguments. For exam-ple, integrating features that require learners to evaluate evidence, explicitly providejustification when creating a link between evidence and claims, and/or pursue atleast one alternative explanation may serve to ameliorate some of the problematicaspects of argument construction observed here. As alluded to previously, however,regardless of the scaffolding strategies embedded in the software, the instructor playsa crucial role in supporting students in engaging in argumentation. Conversationsthat explicitly attend to ways to explore data, the nature and quality of evidence, andalternative explanations for phenomena must become part of the social discourse ofclassrooms.

Another important finding of this study was the powerful influence of students’approaches to the task and to their own learning. It was unclear that the preserviceteachers here understood why they were engaged in constructing arguments as partof the investigation, or that they viewed the process as contributing to their learn-ing, especially their understanding of how natural selection plays-out in a simulatedpopulation. Our research group is currently conducting a long-term study aimed at


better understanding these issues. Related to participants’ perceptions of the task andof their own learning is the nature of the task itself and its role in determining howstudents go about interacting with the software. In particular, tasks for which the“right answer” is not obvious or easily assumed may minimise a confirmation biasand promote an exploratory approach to the investigation (Munford, 2002).

Finally, this study uncovered problematic aspects of preservice science teachers’knowledge of natural selection (see Crawford, Zembal-Saul, Friedrichsen, & Mun-ford, 2002). Of particular concern were Helen and Eleanor, who both held advanceddegrees in biology and have extensive experiences in scientific research. As dis-cussed previously, the investigation and process of explanation articulation revealedthat much of their knowledge of evolution was inert. That is, the pair was unableto use their knowledge in an authentic, problem-based context. How then will thesepreservice science teachers be able to support their students’ science learning in waysthat are consistent with the vision of reform? Unfortunately, there is no “quick fix”for this issue. Preservice teachers need multiple opportunities, like that provided bythe Galapagos Finches software and Struggle for Survival curriculum, to learn thescience in authentic, problem-based contexts in order to develop more robust anduseful understandings. Within a socio-political climate that rewards subject matterpreparation alone and dismisses subject-specific pedagogy by promoting paths foralternative certification, science teacher educators have a responsibility to raise thisissue. Quality teacher education experiences must include opportunities to learn sci-ence in ways that reflect effective, reform-based pedagogies, as well as transformthose experiences for the purposes of supporting students’ science learning.

Acknowledgement

This material is based upon work supported by the National Science Foundation(NSF REC 9980055). Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the authors and do not necessarily reflect theviews of the National Science Foundation.

Correspondence: Carla Zembal-Saul, College of Education, 274 Chambers Build-ing, The Pennsylvania State University, University Park, PA 16802, USAE-mail: [email protected]

Appendix Note

1. Based on Kuhn (1991); Sandoval and Reiser (1997).


References

American Association for the Advancement of Science (AAAS). (1990). Science forall Americans. New York, Oxford: Oxford University Press.

Abell, S., Anderson, G., & Chezem, J. (2000). Science as argument and explanation:Inquiring into concepts of sound in third grade. In J. Minstrell & E. v. Zee (Eds.),Inquiring into inquiry learning and teaching in science (pp. 65–79). Washington,DC: American Association for the Advancement of Science.

Bell, P., & Linn, M. C. (2000). Scientific arguments as learning artifacts: Designingfor learning from the web with KIE. International Journal of Science Education,22, 797–817.

Bishop, B. A., & Anderson, C. W. (1990). Student conceptions of natural selectionand its role in evolution. Journal of Research in Science Teaching, 27, 415–427.

Brown, A. (1992). Design experiments: Theoretical and methodological challengesin creating complex interventions in classroom settings. The Journal of LearningSciences, 2(2), 141–178.

Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture oflearning. Educational Researcher, 18(1), 32–42.

Bybee, R. W., & Deboer, G. (1994). Goals for the science curriculum. In Handbookof research on science teaching and learning. Washington, DC: National ScienceTeachers Association.

Chinn, C. A., & Brewer, W. F. (1993). The role of anomalous data in knowledgeacquisition: A theoretical framework and implications for science instruction.Review of Educational Research, 63, 1–49.

Crawford, B., Zembal-Saul, C., Friedrichsen, P., & Munford, D. (2002). Usinginquiry-based software as the context for learning to teach the nature of scienceand evolution. A round table discussion presented at the annual meeting of theAmerican Educational Research Association (AERA), Seattle, WA.

Creswell, J. W. (1998). Qualitative inquiry and research design: Choosing amongfive traditions. Thousand Oaks, CA: Sage Publications.

Deboer, G. (1991). A history of ideas in science education: Implications for practice.New York: Teachers College Press.

Demastes, S. S., Good, R. G., & Peebles, P. (1996). Patterns of conceptual change inevolution. Journal of Research in Science Teaching, 33, 407–431.

Demastes, S. S., Good, R. G., & Peebles, P. (1995). Students’ conceptual ecologiesand the process of conceptual change in evolution. Science Education, 79, 637–666.

Dewey, J. (1910). How we think. Lexington, MA: D. C. Heath.Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific

argumentation in classrooms. Science Education, 84, 287–312.Good, R., Trowbridge, J., Demastes, S., Wandersee, J., Hafner, M., & Cum-

mins, C. (Eds.). (1992). Proceedings of the 1992 Evolution Education ResearchConference, Louisiana State University at Baton Rouge, 4–5 December.

Grant, P. R. (1986). Ecology and evolution of Darwin’s finches. Princeton, NJ:Princeton University Press.


Jensen, M. S., & Finley, F. N. (1996). Changes in students’ understandings of evo-lution resulting from different curricular and instructional strategies. Journal ofResearch in Science Teaching, 33, 879–900.

Jimenez, M. P. (1992). Thinking about theories or thinking with theories?: A class-room study with natural selection. International Journal of Science Education,14, 51–61.

Jimenez, M. P., Rodriguez, A. B., & Duschl, R. A. (2000). “Doing the lesson” or“doing science”: Arguments in high school genetics. Science Education, 84, 757–792.

Kelly, G. J., Druker, S., & Chen, C. (1998). Students’ reasoning about electricity:Combining performance assessments with argumentation analysis. InternationalJournal of Science Education, 20, 849–871.

Kuhn, D. (1991). The skills of argument. Cambridge, MA: Cambridge UniversityPress.

Kuhn, D. (1992). Thinking as argument. Harvard Educational Review, 62, 155–178.Kuhn, D. (1993). Science as argument: Implications for teaching and learning

scientific thinking. Science Education, 77, 319–337.Latour, B., & Woolgar, S. (1986). Laboratory life: The construction of scientific facts.

Princeton, NJ: Princeton University Press.Lin, X., & Lehman, J. (1999). Supporting learning of variable control in a computer-

based biology environment: Effects of prompting college students to reflect ontheir own thinking. Journal of Research in Science Teaching, 36(7), 837–858.

Linn, M. (2000). Designing the knowledge integration environment. InternationalJournal of Science Education, 22(8), 781–796.

Loh, B., Radinsky, J., Reiser, B., Gomez, L., Edelson, D., & Russell, E. (1997). TheProgress Portfolio: Promoting Reflective Inquiry in Complex Investigation En-vironments. Paper presented at the Computer Supported Collaborative Learning,Toronto, Ontario.

Mintzes, J., Wandersee, J., & Novak, J. (Eds.). (1998). Teaching science forunderstanding: A human constructivist view. San Diego: Academic Press.

Munford, D. (2002). Situated argumentation, learning and science education: Acase study of preservice teachers’ experiences in an innovative science course.Unpublished doctoral dissertation, The Pennsylvania State University.

Munford, D., & Zembal-Saul, C. (2002, April). Learning science through argu-mentation: Preservice teachers’ experiences in an innovative context. A paperpresented at the annual meeting of the National Association for Research inScience Teaching (NARST), New Orleans, LA.

National Research Council (NRC). (1996). The National Science Education Stan-dards. Washington, DC: National Academy Press.

National Research Council (NRC). (2000). Inquiry and the National Science Educa-tion Standards. Washington, DC: National Academy Press.

Newton, P., Driver, R., & Osborne, J. (1999). The place of argumentation in thepedagogy of school science. International Journal of Science Education, 21,553–576.


Osborne, J., Erduran, S., Simon, S., & Monk, M. (2001). Enhancing the quality ofargument in school science. School Science Review, 82(301), 63–70.

Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehensionfostering and comprehension-monitoring activities. Cognition and Instruction,2, 117–175.

Pontecorvo, C. (1987). Discussing for reasoning: The role of argument in knowledgeconstruction. In H. D. Corte, R. Parmentier, & P. Span (Eds.), Learning andinstruction: A publication of the European Association for Research on Learningand Instruction. Oxford: European Association for Research on Learning andInstruction.

Quintana, C., Reiser, B., & Davis, B. (2002, April). Design guidelines for soft-ware scaffolds: “The Big Table.” Paper presented at the annual meeting of theAmerican Educational Research Association, New Orleans, LA.

Reiser, B. (2002). Why scaffolding should sometimes make tasks more difficult forlearners. In G. Stahl (Ed.), Computer support for collaborative learning: Founda-tions for a computer supported collaborative learning community (pp. 255–264).Hillsdale, NJ: Erlbaum.

Rudolph, J. L., & Stewart, J. (1998). Evolution and the nature of science: On the his-torical discord and its implications for education. Journal of Research in ScienceTeaching, 35, 1069–1089.

Salomon, G., Globerson, T., & Guterman, E. (1989). The computer as a zone of prox-imal development: Internalizing reading-related metacognition from a readingpartner. Journal of Educational Psychology, 81(4), 620–627.

Sandoval, W., & Reiser, B. (1997, March). Evolving explanations in high schoolbiology. Paper presented at the annual meeting of the American EducationalResearch Association, Chicago, IL.

Schwab, J. (1962). The teaching of science as enquiry. London: Oxford UniversityPress.

Schwab, J. (1978). Science, curriculum and liberal education (selected essays).Chicago: University of Chicago Press.

Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: SagePublications.

Stake, R. E. (2000). Case studies. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbookof qualitative research (pp. 435–454). Thousand Oaks, CA: Sage Publications.

Strauss, A. L., & Cobin, J. (1998). Basics of qualitative research: Techniquesand procedures for developing grounded theory. Thousand Oaks, CA: SAGEPublications.

Tabak, I., Smith, B. K., Sandoval, W. A., & Reiser, B. J. (1996). Combining gen-eral and domain-specific strategic support for biological inquiry. In C. Frasson(Ed.), Proceedings of the Third International Conference on Intelligent TutoringSystems (pp. 288–296). London: Springer Verlag.

Trowbridge, L., & Bybee, R. (1990). Teaching science by inquiry in the secondaryschool. Columbus, OH: Merrill Publishing Company.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychologicalprocesses. Cambridge, MA: Harvard University Press.


Weiner, J. (1994). The beak of the finch. New York: Knopf.Yerrick, R. K. (2000). Lower track science students’ argumentation and open inquiry

instruction. Journal of Research in Science Teaching, 37, 807–838.Yin, R. K. (1989). Case study research: Design and methods. Newbury Park, CA:

Sage Publications.Zeidler, D. (1997). The central role of fallacious thinking in science education.

Science Education, 81, 483–496.Zembal-Saul, C. (2002, April). Toward science as argument and explanation. In

V. N. Lunetta & A. Hofstein, The Laboratory in Science Education: Foundationsfor the 21st Century, A symposium at the National Association for Research inScience Teaching, New Orleans, LA.

Zembal-Saul, C., & Land, S. (2002, April). Scaffolding the construction of scientificarguments by preservice teachers in a problem-based environment. A paper pre-sented at the annual meeting of the American Educational Research Association,New Orleans, LA.

Zembal-Saul, C., Munford, D., & Friedrichsen, P. (2002, January). Technology toolsfor supporting scientific inquiry: A preservice science education course. A paperpresented at the annual meeting of the Association for the Education of Teachersof Science, Charlotte, NC.

Appendix A: Rubric Used to Analyse Arguments1 (Research Question #1)

1. Causal Coherence/Causal Structurea) A network representation of causal relations was constructed based on stu-

dents’ explanations.b) Description of the causal sequence

i. Do explanations articulate specific cause-and-effect relationships?ii. Are causal relationships logically connected?iii. Are causal relationships and their connections explicitly stated?iv. Do they consider the possibility of more than one cause (multiple causal

lines)?c) Do they consider the possibility of multiple factors interacting to produce a

phenomenon?d) Does the causal structure reflect domain-specific principles (e.g, selective

pressure, change in frequency traits in population, initial variation, differentialsurvival)?

2. Evidencea) Is there evidence to support each claim?b) Is the evidence relevant to the claim?c) Do they make valid inferences from data?d) Do they use principles of knowledge within the domain?


e) Do they sort data in appropriate ways (e.g., based on population characteris-tics such as sex and age)?

f) In which cases do they have more or less pieces of data linked as supportingevidence? What distinguishes parts that are supported with several pieces ofevidence and those that are not?

g) Do they tend to use individual data or representations of population pat-terns such as graphics? In what circumstances do they use different kinds ofevidence?

h) Do they tend to use qualitative data or quantitative data to support their claims?In what circumstances do they use different kinds of evidence?

i) How do they describe their pieces of evidence (e.g., annotation box in soft-ware)? Do such descriptions vary depending on the type of evidence (e.g.,graphs, field notes)?

j) Is it possible to identify any changes in these aspects across the unit (e.g.,when do they start to use a type of evidence?)?

3. Data justificationsa) Do students provide justification for why data is relevant to support a claim?b) What kind of justification do they use?c) Are there particular instances in which justification is absent/present?

4. Thinking about their explanations (evaluating their explanations)a) How do they categorize their explanations (e.g., accepted completely; ac-

cepted with changes)?b) How do they justify this categorization?


Appendix B: Selected Examples from Coding Scheme (Research Questions 2 and 3)

Research Question 2: How Do Preservice Teachers Go about Constructing Scientific

Arguments (Emphasis on Processes and Strategies)?

Sub-questions Examples of Examples

categories of codes

How do participants usegeneral strategies in theprocess of argument con-struction?

use of evidence – using “plausibility” topersuade– presenting evidence tosupport ideas

alternative hypothesis – exploring alternativehypothesis in face ofinconclusive evidence– discarding alternativehypothesis to supportargument

How are scientificallyaccepted constructsreflected in the processesand strategies ofargument construction?(domain-specificstrategies)

use of natural selectionconcepts

– using general domainknowledge to discardalternative hypothesis– ignoring variation oforganisms

How do participantsinteract with each otherthroughout the process ofconstructing argumentstogether?

engaging in dialogue – pairs not discussingcourse of action– interactions with peersand discussion of how toexplore evidence

What are participants’perceptions, purposes,goals and motivationsthroughout the process?

goals and purposes – searching for “the rightanswer”– searching for the bettersupported explanation


Research Question 3: In what Ways do the Scaffolds Embedded in the Galapagos

Finches Software Influence the Development of Preservice Teachers’ Arguments?

Sub-questions Examples of Examples

categories of codes

What kinds of dialoguedoes the software pro-mote and under whichcircumstances?

features promoting dia-logue

– graphs generating discus-sion on how to analyze data– lack of discussion whenfield notes are used as evi-dence

How does the softwaresupport/limit the develop-ment of general domainknowledge?

strategies for providingsupporting evidence

– linking evidence to claimas automatic

strategies for generatingalternative hypothesis

– using software scaffoldsto generate alternativehypothesis

How does the softwaresupport/limit the develop-ment of domain-specificknowledge?

strategies for assessingvariation and change inthe population

– ignoring scaffolds whensorting population– using sorting scaffoldsfor refining explanation

Documents

Scaffolding Preservice Science Teachers' Evidence-Based Arguments During an Investigation of Natural Selection