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This article was downloaded by: [University of California, San Francisco] On: 07 October 2014, At: 02:01 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK International Journal of Science Education Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tsed20 Lakatos’ Scientific Research Programmes as a Framework for Analysing Informal Argumentation about Socioscientific Issues ShuNu Chang a & MeiHung Chiu b a Aletheia University , Taiwan—Republic of China b National Taiwan Normal University , Taiwan—Republic of China Published online: 26 Sep 2008. To cite this article: ShuNu Chang & MeiHung Chiu (2008) Lakatos’ Scientific Research Programmes as a Framework for Analysing Informal Argumentation about Socioscientific Issues, International Journal of Science Education, 30:13, 1753-1773, DOI: 10.1080/09500690701534582 To link to this article: http://dx.doi.org/10.1080/09500690701534582 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &

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Page 1: Lakatos’ Scientific Research Programmes as a Framework for Analysing Informal Argumentation about Socio‐scientific Issues

This article was downloaded by: [University of California, San Francisco]On: 07 October 2014, At: 02:01Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

International Journal of ScienceEducationPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/tsed20

Lakatos’ Scientific ResearchProgrammes as a Framework forAnalysing Informal Argumentationabout Socio‐scientific IssuesShu‐Nu Chang a & Mei‐Hung Chiu b

a Aletheia University , Taiwan—Republic of Chinab National Taiwan Normal University , Taiwan—Republic of ChinaPublished online: 26 Sep 2008.

To cite this article: Shu‐Nu Chang & Mei‐Hung Chiu (2008) Lakatos’ Scientific Research Programmesas a Framework for Analysing Informal Argumentation about Socio‐scientific Issues, InternationalJournal of Science Education, 30:13, 1753-1773, DOI: 10.1080/09500690701534582

To link to this article: http://dx.doi.org/10.1080/09500690701534582

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to orarising out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &

Page 2: Lakatos’ Scientific Research Programmes as a Framework for Analysing Informal Argumentation about Socio‐scientific Issues

Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

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International Journal of Science EducationVol. 30, No. 13, 17 October 2008, pp. 1753–1773

ISSN 0950-0693 (print)/ISSN 1464-5289 (online)/08/131753–21© 2008 Taylor & Francis DOI: 10.1080/09500690701534582

RESEARCH REPORT

Lakatos’ Scientific Research Programmes as a Framework for Analysing Informal Argumentation about Socio-scientific Issues

Shu-Nu Changa* and Mei-Hung ChiubaAletheia University, Taiwan—Republic of China; bNational Taiwan Normal University, Taiwan—Republic of ChinaTaylor and FrancisTSED_A_253321.sgm10.1080/09500690701534582International Journal of Science Education0950-0693 (print)/1464-5289 (online)Research Report2007Taylor & Francis0000000002007Prof. [email protected]

The purpose of this study is to explore how Lakatos’ scientific research programmes might serve asa theoretical framework for representing and evaluating informal argumentation about socio-scien-tific issues. Seventy undergraduate science and non-science majors were asked to make writtenarguments about four socio-scientific issues. Our analysis showed that the science majors’ informalarguments were significantly better than the non-science majors’ arguments. In terms of theresources for supporting reasons, we find that personal experience and scientific belief are the twocategories that are generated most often in both groups of the participants. Besides, science majorsmade significantly greater use of analogies, while non-science majors made significantly greater useof authority. In addition, both science majors and non-science majors had a harder time changingtheir arguments after participating in a group discussion. In the study of argumentation in science,scholars have often used Toulmin’s framework of data, warrant, backing, qualifiers, claims, andrebuttal. Our work demonstrates that Lakatos’ work is also a viable perspective, especially whenwarrant and backing are difficult to discern, and when students’ arguments are resistant to change.Our use of Lakatos’ framework highlights how the ‘hard core’ of students’ arguments about socio-scientific issues does, indeed, seem to be protected by a ‘protective belt’ and, thus, is difficult toalter. From these insights, we make specific implications for further research and teaching.

Introduction

Over the past few decades, thinking, argumentation, and their relationship havebecome the important issues in science education for understanding how peoplemake decisions and behave, and for promoting individuals’ thinking skills. It has

*Corresponding author. College of Liberal and General Education, Aletheia University, 32 Chen-Li Street, Tamsui, Taipei, 25103, Taiwan, R.O.C. Email: [email protected]

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been mentioned that the goal of science education ought to be not only learningspecific scientific knowledge, but also developing skills of scientific thinking (Driver,Newton, & Osborne, 2000; Kuhn, 1993; Zohar & Nemet, 2002); and the skills ofargumentation play important roles in high-level brain-storming, such as criticalreasoning, creative thinking, and problem-solving (Coles & Robinson, 1989). Peoplenormally judge and draw conclusions based on their beliefs or evidence they haveexperienced in life (Kuhn, 1993), so the skills of argumentation have become essen-tial knowledge for modern citizens and professionals, and ought to be taught inschool (Driver et al., 2000; Nussbaum, 2002). Since 1998, Taiwan has madeintensive efforts to promote scientific thinking in schools, such as by reforming thecurriculum and adding habits of mind as one of the indicators for the students ofGrades 1–9 in the curriculum. These efforts assume the students have the ability tointegrate information, make judgements and infer from socio-scientific issues (SSI),solve problems, and so forth (Ministry of Education, 1998). Although the impor-tance of the skills of argumentation is known, how students become proficient insuch skills has not been clear. Thus it becomes essential to investigate such problemsin order to assess how well students understand the skills of argumentation, and thisstudy tries to make such an effort.

Science and society share a complex interdependent relationship nowadays, andthe issues involved in these relationships have been termed socio-scientific issues—it isknown that society creates needs, and scientists investigate and develop the solutionsfor those needs (Sadler & Zeidler, 2004b). Many researchers have made great effortsto promote the public’s awareness of the significance of SSI and popularized issues-based curricula for school science (Driver et al., 2000; Pedretti, 1999; Sadler &Zeidler, 2004a). Together with the SSI trend, the relationship between informalreasoning and informal argumentation has been pointed out by some researchers aswell (Means & Voss, 1996; Voss, Perkins, & Segal, 1991; Zohar & Nemet, 2002).These researches seem to result in a common consensus that informal reasoningusually happens when individuals need to make a decision or judgement regardingSSI or daily life issues in an ill-structured and open-ended context; that is, informalreasoning is also taken as everyday reasoning (Perkins, Allen, & Hafner, 1983;Perkins, Faraday, & Bushey, 1991). SSI, in particular, provide the kind of context inwhich informal reasoning would be involved in problem-solving or decision-making(Patronis, Potari, & Spiliotopoulou, 1999; Sadler, 2004). Therefore, it is natural forus to adopt SSI as the scenario to explore people’s informal argumentation in thisstudy.

Moreover, in science education, the perspectives on the cognitive psychology andphilosophy of science have become the justification of research in argumentation(Erduran, Simon, & Osborne, 2004). Based upon psychological and epistemologicalprinciples, the processes responsible for theory development and structure oftheoretical knowledge have implications for design and development of scienceinstruction (Duschl & Hamilton, 1992; Erduran et al., 2004; Nersessian, 1989;Perkins, 1985; Perkins & Salomon, 1989; Resnick, 1987). Therefore, in this paperwe adopt a theoretical model from the philosophy of science: Lakatos’ scientific

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research programmes to investigate undergraduates’ informal argumentation regard-ing SSI. Besides, we would like to know what kind of reasons undergraduates wouldpropose when making their arguments. Based on the results of this study, we hope tobenefit future instructional design for science education.

In the next section, we review the theoretical aspects of formal and informalargumentation, the indicators embedded into informal argumentation, and thetheory of Lakatos’ scientific research programmes.

Theoretical Context

In this section, we think it is important to point out the differences between formaland informal argumentation; next, we delineate the indicators of informal argumen-tation and the theoretical model of Lakatos’ programmes. Meanwhile, we explainwhy we choose to use Lakatos’ programmes for analysing informal argumentation inthis study.

Differences between Formal and Informal Argumentation

The notions of ‘argumentation is the core of thinking’ and ‘thinking as an argu-ment’ have been around for a long time. Since the early periods, philosophers suchas Plato, Socrates, and Aristotle thought that reasoned arguments construct thecore of thinking (Kuhn, 1991). Since then, formal logic had been considered thebest model of thinking until the middle of the twentieth century. In 1958, Toul-min published The Uses of Argument—in which he points out the limitations ofusing formal logic to think, provides his own model of a reasoned argument, andemphasizes the advantages of using argumentation as a kind of thinking. Basedupon the idea that ‘reasoning is the core of argumentation’ (Means & Voss, 1996),we could say argumentation is a form of discourse embracing a process of reason-ing (Halpern, 1996; Voss & Means, 1991). Nowadays reasoning is categorized aseither formal or informal (Means & Voss, 1996; Sadler, 2004; Voss et al., 1991;Zohar & Nemet, 2002). Means and Voss point out that, unlike the categoricalsyllogism structures of formal reasoning, the features of informal reasoning arecentral to its evaluation, and the evaluation may vary with a person’s attitude,beliefs, knowledge, and/or values in terms of the different topics (Means & Voss,1996; Voss & Means, 1991). According to the notion of informal reasoning, in thispaper we think argumentation needs to be discriminated from formal and informalargumentation as well, for specifying the connection between informal reasoningand informal argumentation.

To make a clear presentation of the study, it is necessary to clarify the differencesbetween formal and informal argumentation. First, in terms of formal argumenta-tion, all premises are fixed, and adding and deleting any content of the premises arenot allowed. However, due to informal reasoning containing cognitive and affectivefeatures (Perkins et al., 1991; Sadler, 2004; Voss, 1991), in informal argumentation,individuals could change the premise based on their personal knowledge and belief,

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and on information from newspapers, textbooks or life experiences, and so forth(Perkins et al., 1991). Second, from the perspective of reasoning structure, formalreasoning normally proceeds as a linear structure; however, this kind of reasoningmodel is not considered practical in daily life (Nickerson, 1991). In people’s every-day lives, individuals often draw on information from multiple sources in informalreasoning and come to a possible conclusion that is more tentative by nature. As aresult, such reasoning structure could be better represented by a tree-like featurewith many branches (Perkins et al., 1991; Means & Voss, 1996). Considering thepractical relevance, the research regarding argumentation we discuss in this paperrefers to informal argumentation.

Indicators of Informal Argumentation

The skills of argumentation have been deemed important skills people shouldpossess in modern society. Before evaluating students’ practice of informal argumen-tation in this study, we need to know what criteria are embraced as indicators oftheir performance. We review some research regarding argumentation and informalreasoning during the past decade to conclude the indicators. As mentioned above,Toulmin was the first researcher to present the model of argumentation, whichincludes data, warrant, backing, qualifiers, claim, and rebuttal (Toulmin, 1958). Afew decades later, Voss and Means (1991) and Kuhn (1991) characterized goodinformal reasoning to incorporate the counter-argument to re-evaluate one’s ownclaim. Some other researchers emphasize the importance of the weighing process toevaluate personal and other arguments, and this implicit process is embedded inreasoning as well (Driver et al., 2000; Kuhn, 1993; Means & Voss, 1996; Voss &Means, 1991). Meanwhile, Perkins and colleagues point out that an experiencedreasoner could evaluate pros and cons of certain elements of an argument—so-called‘critical epistemology’ (Perkins et al., 1983). Concerning the feature of qualifiermentioned less by Toulmin (1958), Means and Voss (1996) provide an alternativedefinition that states a qualifier could offer the opportunity to consider alternativelines of inquiry. Based upon the studies above, we identify the indicators of informalargumentation as follows:

1. Making claims: individuals could make the claims for the issues.2. Providing supporting reasons: individuals could provide reasons or information

to support their claims.3. Presenting counter-arguments: individuals could sense the opposite argument

or the limitation/weakness of the argument they make.4. Showing qualifiers: individuals could provide alternative solutions for expanding

their claims.5. Evaluating arguments: individuals could evaluate their own or other people’s

arguments.

In this study, we analyse undergraduates’ performance of informal argumentationaccording to these five indicators.

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Theoretical Model of Lakatos’ Scientific Research Programmes

The visual model and the theoretically constructed model could both be used toimprove students’ learning (Glynn, Yeany, & Britton, 1991; Keys, 1997). Regardingthe model of argumentation, presently Toulmin’s model is applied by many scienceeducators primarily to analyse arguments that occur in group or classroom discourse(Erduran et al., 2004; Jimenez-Aleixandre, 2002; Kelly & Chen, 1999; Kelly,Druker, & Chen, 1998; Osborne, Erduran, & Simon, 2004; Russell, 1983; Simon-neaux, 2001; Tirri & Pehkonen, 2002); however, we have adopted an alternativeframework to overcome the particular problems encountered with Toulmin’s modelin this study. At first, we tried to use Toulmin’s model to analyse the written reportswe collected from 10 students’ self-generated informal argumentation regarding SSIin the pilot study, and we faced difficulties in finding the elements of warrant, quali-fier, and backing as defined by Toulmin. The same difficulty has been revealed andpresented by some researchers as well. Erduran et al. (2004) remind us that, whenusing Toulmin’s model, we need to pay careful attention to the contextualized use oflanguage, and also the problem has been revealed that Toulmin’s scheme isrestricted to relatively short arguments (Kelly et al., 1998). Further in the studyconducted by Kelly and Chen (1999), they modify Toulmin’s model by drawing onthe work of Latour to analyse students’ writing as well. We present an examplebelow to shown one of the students’ written responses about genetically modifiedfood from the pilot study, in which we faced difficulty in clarifying some componentsof student’s arguments:

I would buy the genetically modified food, because I have not heard about any humandying because of eating it. Besides, genetically modified food perhaps is good researchto prevent the crisis of food deficiency in the future.

For this example, it is easy to code the claim, ‘I would buy the genetically modifiedfood’, and the data, ‘I have not heard about any human died because of eating it’.Yet, this student mentions another issue unrelated to ‘data’, which is ‘modified foodperhaps is good research to prevent the crisis of food deficiency in the future’, and itis hard to define this statement to be the warrant or backing. However, the unrelatedissue the student presents could be easily coded as the indicator of ‘qualifier’ asdefined by Means and Voss (1996). Considering that the above single instance mayrepresent a general phenomenon where people collect more indirect (or unrelated)arguments to strengthen their reasoning, we turned to the philosophy of science tosearch for an alternative theoretical model in order to accommodate the indicator of‘qualifier’ to analyse informal argumentation regarding SSI. We found Lakatos’research programmes are the most appropriate framework for investigating ourproblems in this study.

Lakatos’ programmes emphasize the concept of a series of theories instead of atheory, which is the basic concept from the logic of discovery (Lakatos, 1978). Inaddition, the coherence of Lakatos’ programmes is rightfully stressed, and this aspectis stressed as a particular feature of informal reasoning (Sadler, 2004; Sadler &Zeidler, 2004b). In terms of the components of Lakatos’ programmes, there are four

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connected components embedded in Lakatos’ programmes: the hard-core (HC)located in the core of the programmes, the protective belt (PB) surrounding theHC, and the negative heuristic (NH) and positive heuristic (PH), which are bothheld in the PB (Lakatos, 1970). The HC is the core and foundation of the theory,and it possesses firm and unchangeable features that are very difficult to attack anddegenerate in the programmes; the PB is composed of auxiliary hypotheses forpreventing the HC from being attacked; the NH and PH are both strategies embed-ded in the PB with separate functions to forbid rebuttals and to expand theory. ThePB deserves particular attention as it has an important function of judging theanomaly and absorbing it by using NH and PH. It is not hard to see that Lakatos’programmes could embrace the five indicators of informal argumentationmentioned earlier. The relationship between Lakatos’ programmes and the five indi-cators of informal argumentation is presented in Table 1. The representation ofLakatos’ programmes and the five indicators of informal argumentation are shownin Figure 1. The two arrows show the PH (clockwise) and NH (counter-clockwise)in the PB. The indicators of claim and supporting reasons are located in the HC,the NH represents the counter-argument or limitation that should be sensed whenarguing, the PH is the qualifier showing the alternative line to inquiry, and the PBpresents the indicator of evaluation.Figure 1. Representation of Lakatos’ scientific research programmesIn summary, to better serve our research purpose of analysing undergraduates’self-generated informal argumentation regarding SSI, we adopt Lakatos’programmes. Following the research purpose, we wish to investigate whetherstudents of science majors and of non-science majors perform differently in informalargumentation. Besides, their uses of resources for supporting reasons for theirclaims are also explored. Moreover, as mentioned before, one of the features ofLakatos’ programmes is that HC is firm and unchangeable; we would like to have a

Table 1. Relationship between Lakatos’ programmes and the five indicators of informal argumentation

Components of Lakatos’ programmes Skills of informal argumentation Definition

Hard-core (HC) (1) Making claims Individuals could provide their own claim supporting by one or more reasons.

(2) Providing supporting reasonsNegative heuristic (NH) (3) Presenting counter-

argumentsBased on the claim, individuals could know the limitation of the claim they made.

Positive heuristic (PH) (4) Showing qualifiers Based on the claim, individuals could know the progress or the extension of the claim.

Protective belt (PB) (5) Evaluating arguments Individuals could evaluate arguments.

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Informal Argumentation 1759

preliminary investigation on understanding whether it is also hard for students tochange their arguments. Meanwhile, the presentation of anomalous data could stim-ulate students’ science learning, and it is crucial for science education to know howstudents respond to contradictory information (Chinn & Brewer, 1993). Therefore,in this study we arranged group discussions to allow students to provide contradic-tory information while discussing, and we examine the differences of students’ infor-mal argumentation before and after the group discussion.

Methods

In this section, we describe our experiment set-ups and procedures. These includethe participants, the development of the instruments, the data collection process,and the analytical procedure.

Participants

Seventy undergraduates participated in this study. The 40 science majors are fromthe medical school of a private university, and the other 30 non-science majors arefrom a national art university. Both of these two universities are located withinTaipei County, and all the participants were from the first author’s psychologyclasses. Since some early studies (Kuhn, 1991; Means & Voss, 1996) show thatneither gender nor age (after adolescence) is a major factor that influences theperformance of argumentation, we did not make particular efforts to ensure equalrepresentation of gender and age for the two groups. There are 32 males and eightfemales in the science major group, and 10 males and 20 females in the non-science

Negative Heuristic (NH)Counterargument

Positive Heuristic (PH)

Qualifier

Hard Core (HC)Claim and reasons

Protective Belt(PB)

Evaluationprocess

Figure 1. Representation of Lakatos’ scientific research programmes

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major group. The average age was19.45 (SD = 0.68) years for the science majorsand 23.1 (SD = 2.14) years for the non-science majors.

Development of the Instruments

The source of data to analyse students’ informal argumentation was mainlystudents’ written reports. During the past decades, the writing form has been used asa way to investigate reasoning and problem-solving, and it also has been considereda good instrument allowing students to present their informal reasoning (Applebee,1991). Although writing may present some limitations, such as probing the dynamicprocess while students conduct reasoning, which we address further in thediscussion section of this paper, we thought take-home written reports would be agood way to provide students with sufficient time to think and seek the backgroundinformation for each SSI topic. Therefore, to allow students enough time, we let allthe participants take the instrument booklet home to write down their ideas concern-ing each SSI topic.

We designed four scenarios regarding SSI shown in the instrument text tostudents. Each scenario is divided into two main parts: the first part probesstudents’ arguments about each SSI, students needed to present their claims/conclusions and supporting reasons, and perhaps the PH and NH; the secondpart assesses students’ skills of evaluation. Because evaluation is an implicitprocess in argumentation, for the second part we adopted a method from aformer research (Means & Voss, 1996) to develop some arguments related toeach scenario and to let students conduct the evaluation and weigh the priorityaccording to their acceptance. The Appendix shows an example of the arrange-ment of text regarding the scenario about genetically modified food in our instru-ment. The arrangement of the text is similar to that of the other three scenarios:‘organic food’, ‘DDT and malaria’, and ‘the dispute about dioxins’. Except for‘the dispute about dioxins’, the other three topics were generated and modifiedfrom the WISE web site (Linn, Clark, & Slotta, 2003). Concerning the context ofeach SSI topic, for genetically modified food and organic food, we provided somebasic background information first to avoid the bias generated from students’background knowledge. Then we asked students whether they would want to buygenetically modified food and organic food in each scenario. In the scenario aboutthe dispute of dioxin, we provided a background story first and asked students toplay the role of a judge who must make a decision whether to sentence the chem-istry company, which produced dioxin. The background story is that some veter-ans used dioxin against weeds during the Vietnam War (1962–1971) andafterwards found out that some soldiers developed cancer. From the data thechemistry company provided, the concentration of dioxin in the blood of 886selected veterans who had been exposed to dioxin was not at a significant levelcompared with the other 804 selected veterans who were not exposed to dioxin.Therefore, students were asked to make an argument as a judge. Regarding thetopic of DDT and malaria, we asked students to play the role of the president of

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a developing country that suffers from malaria. From the introduction section inthe instrument text, students knew that DDT has a serious effect on humans andthe environment but that the use of DDT was the only efficient method to get ridof malaria at that time. Students had to decide whether they should let their citi-zens continue using DDT or not. In selecting these four topics, we deemed genet-ically modified food and organic food to be two hot topics in Taiwan recently, astheir long-term serious harmful effects on humans are unknown; in contrast, wechose the other two topics regarding DDT and dioxins because their harmfuleffects are well known. These selections were made to avoid bias. Since our maininstrument is presented as text, we also adopted a well-developed language-reasoning test, which has been regularly implemented in schools, to ensure thatstudents’ reading ability does not differ significantly and to prevent the bias in thisstudy.

Concerning the validity of the instrument, we first developed the validity sheetpresenting the questions for each scenario, and also described what we want to findout about the indicators of informal argumentation from each scenario. We invitedtwo professors from the biology and science education fields to check the validity ofthe construction, and we discussed any concern or need for improvement with thempersonally.

Analytic Procedure

To analyse students’ written reports, we developed two coding schemes based onLakatos’ programmes and the resources of supporting reasons to code students’written reports regarding the four SSI topics. In terms of the performance ofinformal argumentation, we adopted Lakatos’ programmes to analyse; we codedthe HC (claim and supporting reasons), the PH (the alternative idea for expand-ing the HC or the future progress of the HC student made), and the NH (thestatement mentioning the rebuttal or limitation of the HC). Concerning the PB,because we assessed it via participants’ evaluation of other arguments provided inthe second part of the text described in the paragraph about the instruments, wedid not need to code it but counted the quantitative scores instead. The calcula-tion method is presented later in this section. To analyse the resources forsupporting reasons, we adopted two resources from the classification of reasonsgenerated by Means and Voss’s results, which include ‘personal experience’ and‘authority’ (Means & Voss, 1996). In addition, from the results of our pilot study,we generated three more categories of resources for the supporting reasons:general belief, scientific belief, and analogy. A total of five resources were codedfrom students’ HC in advance, and the quotations are presented in the resultssection. Concerning the validity and inter-rater reliability of coding, we invitedtwo graduate students—who were from the science education field and had morethan one year of qualitative research experience—to check and discuss the defini-tion of the coding scheme. After validation, 10 students’ written reports wererandomly selected and were independently analysed by the first author of this

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paper and the other two invited graduate students. Then the first author checkedthe coding results with each of the graduate students and discussed the differencesseparately. According to the inter-rater reliability counting formula (Merriam,1988), our results produced an inter-rater reliability of 0.97. Moreover, concern-ing the grain size of the coding, we took ‘sentence’ as a unit to give a code (Chi,1993; Merriam, 1988).

Based upon the coding results from the written reports, we adopted the Indepen-dent t-test (SPSS 10.0) as the quantitative approach to analyse students’ perfor-mances of informal argumentation. According to the calculation method providedby Means and Voss (1996), the total scores on the performance of informal argu-mentation were assessed according to whether students could make an HC thatincludes claim and supporting reasons (one point for each resource of reason). Wealso assessed whether students could generate a NH (one point for each NH) and aPH (one point for each PH). Regarding the PB, which represents students’ weighingability, as mentioned before, we provided three arranged arguments (coded A, B,and C) for each scenario and let students present their own sequence of acceptance.If the sequence of acceptance were totally correct (ABC), we assigned 3 points; forpartially correct (ACB or BAC), we assigned 2 points; for BCA or CAB, we assigned1 point; for CBA, we gave no points. In brief, the scores on students’ performance ofinformal argumentation were evaluated from whether they could present HC, PH,NH, and scores on PB. The total scores from four scenarios represent each student’sperformance of informal argumentation. According to our counting method, wemeasured relative scores instead of maximum scores to present each student’sperformance of informal argumentation.

After gathering the quantitative data from students’ performance of informal argu-mentation, we arranged group discussions with eight students in two groups to seewhether they would change their arguments after debating. One group of fourstudents consisted of science majors, and the other group was comprised of non-science majors. In each group, we especially invited students who had opposite viewson each scenario to join the discussions. The group discussions were video-recordedto investigate why students changed their claims after discussion.

Results

In this section, we present the students’ performance results regarding the four SSIscenarios with qualitative data and show that Lakatos’ programmes could be analternative framework for analysing informal argumentation regarding SSI. Weprovide the quantitative data to present the difference of the performance betweenscience majors and non-science majors. The resources for the supporting reasons arealso revealed. Moreover, we discuss the results to see whether or not students wouldchange their arguments after group discussion. To enable a concise presentation, wehere would like to introduce abbreviations for representing the topics of each SSIscenario, which include GMF for genetically modified food, OF for organic food,DDT for the topic of DDT and malaria, and DAD for the topic regarding the

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dispute about dioxins. Finally, we will use S to represent a science major, and A fora non-science major from an art university.

Undergraduates’ Performance of Informal Argumentation

The results suggest that the framework of the Lakatos’ programmes is workable inanalysing informal argumentation regarding SSI. According to Lakatos’programmes, a good informal argumentation model ought to embrace the HC withclaims and reasons, use the PB to evaluate, and generate the NH and PH to preventthe HC from being attacked and to expand the HC. People who show all these fiveelements in their argumentation are deemed to have good informal argumentationskills. According to the four SSI scenarios, quotations from students are presented inthe following.

Genetically modified food. The text construction we provided to students is shown inthe Appendix. After providing some background information about GMF, we askedstudents whether they would buy GMF or not. Concerning GMF, more than one-half of both science majors (63.5%) and non-science majors (73.3%) would buy it.We quote a complete argument with the HC, PH, and NH generated by a non-science major below:

[HC] I would buy the genetically modified food [claim], because I learned about genesfrom a biology course, which makes me know our genes will not change after we eat thegenetically modified food [reason]. Besides, genetically modified food has its exploitablevalue, if our government did not make an effort, then our country will fall behind othercountries [PH]. Generally, we have not heard anything harmful to humans, but it isnecessary to conduct clinical trials like the process before marketing the medicine [NH].(Student A015)

Organic food. The same text construction as for GMF was provided with some back-ground information on OF to students who were asked whether they would like tobuy OF. Regarding the topic of OF, more non-science majors (86.7%) would buy OFthan science majors (42.5%) would. Most non-science majors would buy it for healthreasons, and the most frequent reason for not buying it from science majors is the highprice of OF sold in Taiwan. We present a quotation from one science major below:

[HC] I would love to eat organic food [claim], because it is much more natural andhealthy to humans [reason]. However, the price is too high in Taiwan and not so manypeople can afford it [NH]. I think our government should subsidize the farmers andmake the price of organic food lower [PH]. (Student S009)

Dispute about dioxins. In the scenario about DAD, students needed to argue as ajudge about sentencing the chemistry company or not. Fewer than 50% of both thescience majors (42.5%) and non-science majors (40%) considered the chemistry

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company guilty. We quote one science major’s argument below, which presents acomplete model of Lakatos’ programmes in this scenario.

[HC] I would not sentence the chemistry company [claim], because there might nothave been any method to detect the harmfulness of dioxin to humans when theyproduced dioxins [reason]. But from another perspective, although there might nothave been any method to examine the harmfulness to humans, the chemistry companystill needed to consider the possibility that dioxin might be harmful to humans andpresent this information to the US army [NH]. The most important thing is, from thescientific evidence that the concentrations of dioxin from 886 veterans’ blood were notat a significant level compared with the other 804 veterans’ data and the average valueof dioxin worldwide [PH]. Therefore, we still cannot sentence the chemistry company[claim repeated]. (Student S006)

DDT and malaria. Regarding the DDT scenario, we asked students to play the roleof the president of a developing country that suffers from malaria. Students had todecide whether a country should let its citizens use DDT or not. We found that52.5% of the science majors said no to using DDT in the country, but 73.3% of thenon-science majors agreed to keep using DDT. The following is one science major’scomplete argument:

[HC] I will keep using DDT [claim] to prevent the serious deaths caused by malaria inmy country [reason]. However, I will ask my citizens to use DDT restrictedly with atime schedule according to different regions to decrease the total amount of usage in thecountry and to help prevent the accumulation of DDT in our body and the environ-ment [NH]. The most important thing is to get rid of mosquitoes, so I will ask mycitizens and also the national army to clean our environment at the same time to preventthe spreading of mosquitoes [PH]. (Student S018)

After presenting the quotations above, we evaluated students’ performances byaveraging the scores earned from indicators including the HC (claims and thenumber of reasons), the PH and NH (students presented to expand the HC and toshow the limitation of the HC), and the PB (the scores students obtained fromevaluating other arguments). According to our results, the science majors (totalscores = 15.41) performed better than the non-science majors (total scores = 13.74)by a statistically significant difference (p <.05). Furthermore, looking at how thestudents performed in detail (see Table 2), we found the science majors performedbetter in providing the supporting reasons and PH, at a significant difference(p <.01) from the non-science majors. Moreover, we wanted to know the sciencemajors’ and the non-science majors’ distribution at the different performance levels.We categorized all 70 students into three performance levels according to thestudents’ total scores: 25 students at the top level (top 27%), 16 students at thebottom level (bottom 27%), and the other 29 students at the middle level (46%between). In addition, we discovered that 76% of top-level students (19 students)are from science majors, and only 24% are non-science majors (Table 3). Hence,these results of performance distribution provide some evidence that science majorsperformed better in informal argumentation than non-science majors in this study.

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Table 2. Performance of informal argumentation

Resources for Supporting Reasons

From our results, we found the reasons students adopted to support their claimsvaried. In general, students proposed five resources to support their claims: (1) generalbelief, the individual used a Chinese or Taiwanese proverb to support the conclusion;(2) scientific belief, this resource could be categorized into scientific attitude (the indi-vidual emphasized the value of research, evidence, and scientific methods), nature ofscience (the individual pointed out the temporary and uncertain nature of science),and ethics (the individual thought that the progress of science will/might hurt humansin the future); (3) authority, the reason comes from a textbook, experts’ opinions,teachers’ instruction, parents’ thoughts, and so on; (4) personal experience, the indi-vidual focused on personal belief or preference; and (5) analogy, the individual coulduse examples or knowledge coming from other fields as the reason for supporting theclaim. The quotations and the resources are presented in Table 4.

After having found these five resources for supporting reasons in students’ infor-mal argumentation regarding SSI, we compared the differences of the resources

Science majors Non-science majors

Element M SD M SD p value

HC (claim and reasons) 8.25 2.36 7.30 1.60 0.035*PB (evaluation) 5.85 1.48 5.80 1.40 0.436PH (expending the HC) 0.63 0.90 0.17 0.38 0.000**NH (limitation of HC) 0.68 1.02 0.47 0.78 0.160Total scores 15.41 3.65 13.74 2.10 0.000**

Notes: *Correlation is significant at the .05 level (two-tailed). **Correlation is significant at the .01 level (two-tailed).

Table 3. Distribution of students’ performance

PerformanceScience majors

(total 40 students)Non-science majors (total 30 students)

High (top 27%, total 25 students)Number 19 6% 76 24

Middle (46% between, total 29 students)Number 12 17% 41.4 58.6

Low (bottom 27%, total 16 students)Number 9 7% 56.3 43.7

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between the science majors and non-science majors. Table 5 shows that both groupsof students proposed most of their reasons based on personal experience. Only theresources of authority and analogy had significant differences. Science majors usedanalogy more than non-science majors did (p <.05), and non-science majorsappealed more to authority (p <.01).

Table 4. Quotations for the resources for supporting reasons

Resource for supporting reasons Quotation

General belief [GMF] It is not a good idea if we always follow other countries’ steps. Just as the proverb says, “repeating what others say is not good. (Student S013)

Scientific beliefScientific attitude [DAD] I will not accuse the Chemistry Company, because the

evidence tells us there was no significant difference in the dioxin value in the blood between the veterans who had used dioxin before and the other veterans who did not use at all. (Student A002)

Nature of science [GMF] No harm to humans now does not mean it will not harm in the future. (Student S007)

Ethics [DAD] I consider the chemistry company as guilty, no matter whether there are veterans with cancer or not, since dioxin has caused permanent harm to our environment and we should be concerned about all lives in our environment. (Student S011)

Personal experience [OF] I would buy organic food, since I have not heard that organic food is harmful to humans during the past time. (Student S031)

Analogy [GMF] I will not choose genetically modified food, since I think research in this kind of food should follow the same rules as developing a medical product for which clinical trials have to be conducted. (Student S021)

Authority [OF] I will buy any kind of vegetable, which has passed the examination by our government. (Student S017)

Table 5. Comparison of resources for supporting reasons

Science majors Non-science majors

Resource for reasons M SD M SD p value

Personal experiences 3.30 1.03 2.87 0.94 0.114Authority 0.50 0.64 1.30 0.75 0.000*General belief 0.29 0.48 0.30 0.47 0.515Scientific belief 2.50 1.24 2.73 1.51 0.069Analogy 1.66 0.71 0.10 0.31 0.000*

Note: *Correlation is significant at the .01 level (two-tailed).

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Change of Argument after Group Discussion

Because the HC of Lakatos’ programmes is the most important part that could notbe attacked, we were interested in investigating whether participants would changetheir arguments after discussing all four SSI topics with participants who had oppo-site claims. We selected four target students from each group of science majors andnon-science majors. Only one participant from each group changed his or her argu-ments regarding the topics of GMF and DDT. Regarding GMF, all changesstemmed from the idea that GMF is without serious harm to humans at present.The participant from the science major group originally decided to choose GMFbecause of the quality of food (more rich with nutrients in GMF). However, hechanged his reason for wanting to buy GMF to be due to the harmlessness of GMFhe heard about from other participants during the discussion, and he thoughtharmlessness to humans is a more important reason in making the decision.

Researcher: Why do you want to change your idea?Student S004: Well … after hearing what other classmates said, I think GMF is

harmless to humans and it is important to humans’ health. There-fore, I want to change my original idea.

For the participant from the non-science major group, the high price was the originalreason she did not want to choose GMF. However, she changed her mind to want-ing to buy GMF because this kind of food is harmless to humans so far, and she alsothought if more people bought GMF, then more GMF would be produced, therebydecreasing the price of GMF.

Researcher: Why do you want to change your argument?Student A002: Mmm … Originally, I did not want to buy genetically modified food,

because it is expensive and I thought it is not necessary to eat it. Butnow, through my classmates’ discussion, I think it is harmless tohumans so far, and I think the price will decrease after we produceand sell more in the market.

Likewise, regarding the topic of DDT, both of the participants changed theiroriginal arguments from the concern that using DDT will cause serious adverseeffects on our environment and humans to the idea that solving the problem citizensface at present is the most important thing.

Researcher: Why do you want to change your argument?Student S001: After discussion, I think decreasing the number of dead citizens is

much more important than thinking about the future, so I will changeto letting my citizens use DDT and getting rid of malaria first. At thesame time, I will ask citizens to use DDT with a restricted time andvolume to decrease the harm to the environment.

Researcher: Why do you want to change your argument?Student A004: Yes … if I insisted that I do not let my citizens use DDT to get rid of

malaria, then there might be no people surviving in my country. Sowhy should I be concerned about the future? I think it is better toallow people to use DDT, and I will ask scientists to find anothersolution instead of DDT in the meantime.

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Discussions and Conclusions

Based upon psychological and epistemological principles, more and more research-ers think how the processes responsible for theory development and structure oftheoretical knowledge have implications for design and development of scienceinstruction (Duschl & Hamilton, 1992; Erduran et al., 2004; Nersessian, 1989;Perkins, 1985; Perkins & Salomon, 1989; Resnick, 1987). For the same purpose ofdeveloping instruction, some researchers point out that models can provide thevisual perception of physical structure and relationship, and theory can delineate andinterpret the meaning of the structure (Glynn et al., 1991; Keys, 1997). In thisstudy, we offer an alternative theoretical model for evaluating informal argumenta-tion. We adopt Lakatos’ model and provide evidence to show that Lakatos’programmes can be a workable model for analysing informal argumentationconcerning SSI as Lakatos’ programmes embrace both physical and interpretativefeatures of model and theory.

Regarding the students’ performance of informal argumentation, two kinds ofresearch results have been found in the past. Some researchers posit that perfor-mance is related to background knowledge, but others disagree and claim there is nosignificant relationship between background knowledge and performance of argu-mentation (Kuhn, 1991; Perkins, 1985). Our study shows that science majorsperform better than non-science majors, and that background knowledge is relatedto the ability of informal reasoning and argumentation (Means & Voss, 1996;Perkins & Salomon, 1989; Sadler & Zeidler, 2004a; Tytler, Duggan, & Gott, 2001).The different results found from the past research may be because of the topics ofpast studies were far from students’ daily lives. For example, the students were asked‘Why does a criminal go back to jail again?’ and ‘What are reasons for getting fired?’Specifically, part of the reasons why science majors performed better than non-science majors found in this study is because that the former generated moreresources for supporting reasons and the PH; and these results are consistent with anearly study conducted by Means and Voss (1996). Another observation found in ourstudy is that both groups of students fell short of proposing the NH and evaluatingothers’ arguments (PB), consistent with that found in some previous studies (Driveret al., 2000; Sadler, 2004). It is slightly surprising for us to find out that only nineparticipants could generate the complete indicators of informal argumentationfor some SSI topics. This implies that there is a great need for undergraduates’performance of informal argumentation to be further developed.

Regarding the resources for supporting reasons, the categories of personal experi-ence and scientific belief were found to be the top two resources for both sciencemajor and non-science major groups. This finding is similar to Voss’ study, whichmentions the cognitive and affective as two factors to construct informal reasoning(Voss, 1991). Personal experience was previously found the main reason forsupporting claims in other studies (Sadler & Zeidler, 2004a; Tytler et al., 2001). Inour study, we also observed that only two of the five resources showed significantdifferences between the two groups of students: analogy and authority—science

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majors used more analogies, but non-science majors cited authorities more often.Considering the observation that science majors performed better than non-sciencemajors, these results imply that the high-performance group provided more reasonsfrom analogy than that of the low-performance students, which is in line with Meansand Voss’s (1996) study.

Concerning the change of argument, we found it is difficult for students to changetheir argument, as was reported earlier by Kortland (1996) and Driver et al. (2000),who reported that participants usually persist in keeping the arguments they madeoriginally. The difficulty in changing arguments revealed in this study seems toprovide additional evidence to support Lakatos’ programmes as an alternative modelto represent informal argumentation because Lakatos claims that the HC is verydifficult to attack and degenerate in the programmes. Because of the limitation ofthe written reports, some findings obtained in our study may serve as preliminaryyardsticks, and further investigation or extension is necessary.

Implications for Teaching and Research

In this study we found there were seldom any participants who could present acomplete model of informal argumentation, and this suggests a great need topromote the skills of argumentation in Taiwan. Accordingly, school education inTaiwan ought to emphasize cultivating students’ skills of argumentation and helpstudents become familiar with SSI from now on. Our study shows that Lakatos’model could be used to analyse informal argumentation, and therefore it should beadopted to teach informal argumentation in schools as well. Our results also implythat the PH and NH are the two parts that need to be emphasized while designingthe instruction to make students know the pros and cons of their arguments. Basedon the findings obtained in this study, we suggest that group discussion and theevaluation process could both be useful to induce students’ thinking about the PHand NH. In addition, an issue-based context would be a more effective way toteach and learn informal argumentation, as students are more able to generateinterests and resources from the issues that are their daily lives’ scenario. In ourstudy, we let students think about the choices of food and play a role in discussingthe cases of DDT and dioxins, and we found students could generate their ownclaims easily and could argue more enthusiastically. Moreover, it is also importantto provide students with various topics and multi-information to discuss and tolearn in class.

Concerning the implications for research, it is necessary to explore what factorscould influence informal argumentation; for example, the features of topics studentsargue about, and the different backgrounds and the age levels of the participants.For the sake of future policy-making and school-teaching, we need to know whetherindividuals use different resources for supporting different aspects of topics andwhether individuals from different backgrounds possess some specific models whilearguing. In addition, from the perspective of developmental psychology, the age levelcould be a factor that influences informal argumentation that should be investigated

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further. In the meantime, although we found it is hard to make students change theirown arguments, we also must make efforts to explore which conditions could makestudents change their arguments. This will benefit instruction, no matter whether itis from the aspect of cultivating students’ skills of informal argumentation, equip-ping the students with the open-minded thinking for alternative reasoning, orcorrecting students’ wrongly obtained misconceptions. Moreover, concerning thewritten reports we conducted in this study, we found them to be limited in investi-gating the process students use when evaluating arguments; the resources forreasons students chose for supporting their arguments and ultimately discarded; andwhy some students could think about the PH and NH and others could not. Theseare all important perspectives we need to reveal in the future in order to design suit-able instructional methods such as a think-aloud stratagem while writing.

The ability to argue well plays a critical role in modern society, so researchers andeducators should make long-term efforts to promote investigating and teachinginformal argumentation.

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Informal Argumentation 1773

Appendix. Example for the arrangement of instrument text

Scenario I. Genetically modified food Text mining

What is genetically modified food?It is a kind of biotechnology. Based on this biotechnology, people could get the specific gene from the cell of one species, and then insert the specific gene to another cell of anther species. The purpose is to transfer the good characteristic to another species. For example, there were scientists taking the gene with the feature of antifreeze from some kind of fishes live in the North Pole, and then inserting the gene to tomato for enhancing the production of tomato.

Introduction of the basic background knowledge concerning the topic.

Question I:If our government is promoting a biotechnology project and focus on the research of genetically modified food with a good achievement. Will you buy the genetically modified food to eat? Why?

Main question to probe students’ performance of informal argumentation to see if students could present HC (claim and supporting reason), PH and NH.

Question II:The research on genetically modified food is a well-known research and has good results in enhancing the quality of food and preventing the harmful insects. If government wants to market genetically modified food and would like to ask for citizens’ opinion first. Now there are three citizens’ arguments concerning genetically modified food as below, according to your own acceptance to judge which one is the best argument and please rank these three arguments by the priority of your acceptance.(A) If government wants to market genetically modified food, they should use the same clinical trial as medicine for confirming it is harmless to human first.(B) The research of genetically modified food is a global research, so we should follow the trend for promoting the competition of our country.(C) I don’t think our government needs to waste money on this research; our government should spend money on the problem of unemployment.

To probe student’s skill of evaluating arguments (PB).

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