Annie Champagne Queloz, PhD. ETH Zürich



Je souhaite clore mon blogue pour me consacrer à de nouvelles activités. Mes articles restent disponibles et vous pouvez toujours communiquer avec moi via mon courriel.

Tout du bon!!


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Conférence: Les changements climatiques: une croyance ou une science?

Les changements climatiques sont un thème de plus en plus enseigné dans les cours de sciences. Toutefois, les informations rapportées par les médias, par l’entourage de l’étudiant ou même par la méconnaissance de certains enseignants peuvent grandement influencer la qualité de son apprentissage. Pour mieux comprendre cette problématique, la Haute école pédagogique Vaud vous invite donc à cette conférence intitulée: Changements climatiques: entre sciences, croyances et fake news. Elle se tiendra le mardi 28 novembre, à 18:30. Elle sera présentée par M. Martin Beniston, professeur honoraire à l’Université de Genève et prix Nobel de la Paix en 2007.

Informations pratiques

Mardi 28 novembre 2017 à 18h30
HEP Vaud, salle C33-229
Avenue de Cour 33, Lausanne
Entrée libre

Lien vers la conférence

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Séminaire: “Comment savez-vous que c’est vrai?”


Voici une conférence, dont le titre complet est: “Comment savez-vous que c’est vrai? Ou pourquoi voulez-vous que j’apprenne ça alors que les scientifiques sont même pas d’accord?” qui pourrait aider bien des enseignants en science! Elle sera présentée par M. François Lombard, M. Andreas Müller et M. Bruno J. Strasser, tous de l’IUFE de l’Université de Genève, le lundi 27 novembre 2017 de 12:15 à 13:15. Elle se tiendra à IUFE, dans la salle 234.




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Mining “Origin of Species” with Iramuteq

IramuteqRecently, I have discovered Iramuteq (R Interface for multidimensional analysis of texts and questionnaires) developed by the Laboratoire d’Études et de Recherches Appliquées en Sciences Sociales at Toulouse University, France. This free text mining software can provide basic text analyzes such word frequencies (word clouds), or more complex ones such descending hierarchical classification, post-hoc correspondence analysis and similarity analysis. Iramuteq is relatively simple to use. It is an interface based on in R and Python languages. The software offers complete English and French dictionary. Other languages are also available, but in beta version only. For example, in German, plural words and adjectives are not considered, thus the lemmatization (to find word roots; infinitive verbs, singular nouns, adjectives in singular masculine) is not done.


Origin of Species by Darwin: Analysis of the First Chapter

“À la bonne franquette”, I’m describing a simple example of how Iramuteq can be used. The first chapter of the Origin of Species by Darwin will be my text corpus for the analysis (available here). Before to start an analysis, you should review the text to avoid spelling mistakes or errors to be taken into account as different words (mainly true for open-question surveys). In addition, all acronyms and abbreviations must be consistent. Then, you can download the text corpus in Iramuteq. I avoid describing all technical information about the segmentation of a corpus or how algorithms work. I could not better explain than information available on the website or from the help available on the Iramuteq forum. Moreover, the helpdesk available per forum usually answers your questions quite quickly.


Let’s start easy!

First, you have to download your text corpus and select the language of it. After, I usually start with a similarity analysis that allows to identify co-occurrences of words. Indeed, it reveals the clustering of words based on how often they were associated and it gives you a pretty co-occurrence tree (Figure 1). In our example, we can observe that “breed” is the most frequent word in the first chapter of Origin of Species and it is often associated with “domestic”, “animal”, or “pigeons” (Figure 1). In Figure 2, you can see the parameters that I have selected. Here, I have restricted the analysis on words having a frequency in the text higher than 10 times. Of course, more the text to analyze is elaborated, more the interpretation of this type of graph is complex. The vertices’ size is proportional to the words frequency. It is also possible to simply create a cloud word, illustrated the word frequency (Figure 3).

Figure 1: Word similarity tree


Figure 2: Parameters to generate the similarity tree

Figure 2: Word cloud

Figure 3: Word cloud

A little bit more complex…

Another cool analysis done by Iramuteq is the words clustering (a friendly name for Descending hierarchical classification or the Reinert method) (Figure 4). This classification is based on a correlation chi-squared test. A dendrogram is generated showing repartition of classes and their association. For each class, we obtain the most associated words. For our analyzed chapter, we observe 5 classes of words. Two subclasses (Classes 2 and 3; Classes 1, 4 and 5) are revealed. Note that a word can be found in different classes.



Figure 4: Word clustering

With Iramuteq, a correspondence analysis can be easily done (Figure 5). Briefly, the CA is often used to represent and model categorical/categorized data as “clouds” of points in a multidimensional Euclidean space. It is really useful to illustrate associations between variables. The variables are expressed as vectors and correlations as angles between vectors from the origin of the graph. An indication of a strong correlation between variables is represented by a small angle between vectors. In Figure 5, we can see the 5 classes of words in distinguishing colours. For example, “seeds”, “plants”, “cultivate”, “flowers” and “variety” (in pink) are closely associated. To the upper side of the graph, “pigeon”, “wild”, “birds”, “domestic” and “descend” (in red) are associated. The word clustering and the CA are often used to analyze discourses of different people or group of people (here is an example).

Figure 4: Correspondance analysis graph

Figure 5: Correspondance analysis graph

Have fun!

Iramuteq is really a cool software for text mining. On the website, you can find tutorial in English describing steps to learn how using it and how to analyze results. It is quite simple. However, the analysis of the results can sometimes be complex, especially with long texts. Have fun to try it! À découvrir!











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C’est la rentrée!




L’automne s’amène avec sa panoplie d’activités, de conférences et de formations en science et en didactique. Comme première activité, le 27 septembre, je vous suggère le workshop Science on Stage Switzerland 2017. Vous pourrez aller à la rencontre des participants suisses du festival européen Science on Stage qui avait eu lieu à Debrecen (Hongrie) cet été. Vous aurez la possibilité de partager leur expérience pendant ce festival et de visiter les laboratoires publics de l’Université de Genève.

Pour connaître le programme détaillé de l’événement, cliquez ici.

Le lieu: Université de Genève

Heure: 10:00 à 16:30

Science on Stage Switzerland est une association faisant la promotion de l’enseignement des sciences. Des enseignants suisses sont sélectionnés pour participer au festival européen organisé par Science on Stage Europe. Ceux-ci doivent présenter des idées innovantes d’enseignement pour divers sujets scientifiques.

Bonne rentrée!!


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Exploring how students represent the concepts taught through the use of concept inventories


Your students are able to complete the activities you give them and they perform quite well on formal assessments. Thus, we can presume that your students have an authentic understanding. But are you really sure about this? Almost twenty years ago, Eric Mazur, physicist and educator at Harvard University, and his colleagues tested the students’ understanding of the Newton’s Law by asking them some questions of the Force Concept Inventory (Hestenes et al. 1992).

“One of the questions, for example, requires students to compare the forces that a heavy truck and a light car exert on one another when they collide. I expected that the students would have no trouble tackling such questions, but much to my surprise, hardly a minute after the test began, one student asked, “How should I answer these questions? According to what you taught me or according to the way I usually think about these things?” To my dismay, students had great difficulty with the conceptual questions. That was when it began to dawn on me that something was amiss.”(Mazur 2009)

This investigation demonstrated how students really (poorly…) represent such basic concepts taught. Consequently, Mazur and his colleague were highly motivated to induce important changes in teaching physics at Harvard University by promoting the peer instruction and the questioning teaching approach (Mazur 2009; Crouch & Mazur 2001).

The tool revealing students’ misconceptions

Concept inventories, or concept tests, are really interesting pedagogic tools to reveal students’ thinking on diverse common subjects taught at school. In general, there are multiple-choice or two-tier questions (mix of true-false and multiple-choice questions). The main distinction of such questionnaires is in the distractors, the wrong answers. Indeed, the distractors are corresponding to the most popular wrong thinking, or misconceptions, of students. The development of concept inventories takes time, but at the end, you get a questionnaire revealing the authentic understanding of students. In other words, you can find out how they represent themselves or conceptualize the knowledge you tend to teach them. In parallel, concept inventories can be useful for evaluating educational needs of students before initiating any reform of a curriculum. For example, at ETH Zürich, the weak results of students on the Biological Concepts Instrument (BCI) have initiated some changes in teaching methods and on concepts taught in introductory biology courses (see our papers here and here for more details).

The construction

Thus, the common development of a concept inventory is usually done like that. The first step is to interview students or to distribute open-ended questionnaires and asked them to explain their understanding of varied phenomena. Then, after compiling the most popular misconceptions, you can create new questions and used the misconceptions as distractors. Consequently, when students are selecting such distractors, it gives you a quick idea that the students do not really understand the concept taught. However, we have to keep in mind that, by selecting the correct answer, you should not assume that students really understand. Indeed, it might be possible that the distractors are just not corresponding to their thinking. They have selected the best answer only by a process of elimination.

Some “plug and play” questionnaires

As I have explained before, developing concept inventories takes time, so here is a list of some interesting questionnaires available in biology and biochemistry. For some of them, you need to contact directly with authors to have access to the questionnaire

  1. Biological Concepts Instrument. (Klymkowsky, Underwood & Garvin-Doxas, 2010)
  2. Biological Experimental Design Concept Inventory. (Deane, Nomme, Jeffery, Pollock & Birol, 2014)
  3. Central Dogma Concept Inventory. (Newman, Snyder, Fisk & Wright, 2016)
  4. Chemical Concepts Inventory. (Barbera, 2013)
  5. Conceptual Inventory of Natural Selection. (Anderson, Fisher & Norman, 2002)
  6. Diffusion and Osmosis Diagnostic Test. (Odom & Barrow, 1995)
  7. Dominance Concept Inventory. (Abraham et al., 2014)
  8. Dynamics Concept Inventory. (Gray et al., 2005)
  9. Enzyme-Substrate Interactions Concept Inventory. (Bretz & Linenberger, 2012)
  10. Evolutionary Developmental Biology Concept Inventory. (Perez et al., 2013)
  11. Genetic Drift Inventory. (Price, et al., 2014)
  12. Genetics Literacy Assessment Instrument. (Bowling et al., 2008)
  13. Heat and Energy Concept Inventory. (Prince et al., 2012)
  14. Homeostasis Concept Inventory. (McFarland et al., 2017)
  15. Host-Pathogen Interactions Concept Inventory. (Marbach-Ad et al., 2009)
  16. Introductory Molecular and Cell Assessment. (Shi et al., 2010)
  17. Lac Operon Concept Inventory. (Stefanski & Gardner, 2016)
  18. Meiosis Concept Inventory. (Kalas, O’Neill, Pollock & Birol, 2013)
  19. Molecular Biology Capstone Assessment. (Couch et al., 2015)
  20. Natural Selection Open Response Instrument. (Nehm & Schonfeld, 2008)
  21. Photosynthesis: Diagnostic Question Clusters. (Parker et al., 2012)
  22. Osmosis and Diffusion Conceptual Assessment. (Fisher, Williams & Lineback, 2011)
  23. RaProEvo. (Fiedler, Tröbst & Harms, 2017)
  24. Thermal and Transport Science Concept Inventory. (Streveler et al., 2011)
  25. Thermochemistry Concept Inventory. (Wren & Barbera, 2013)

If you know some questionnaires in biology or related topics which are not in this list, don’t hesitate to communicate with me. I will be happy to update my list!



Crouch, C.H. & Mazur, E., 2001. Peer Instruction: Ten years of experience and results. American Journal of Physics, 69(9), pp.970–977.

Hestenes, D., Wells, M. & Swackhamer, G., 1992. Force Concept Inventory. The Physics Teacher, 30(March), pp.144–158.

Mazur, E., 2009. Education. Farewell, lecture? Science, 323(5910), pp.50–51.


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Idées reçues sur la théorie de l’évolution de Lamarck


L’utilisation ou non des organes = évolution?

Certaines idées reçues observées chez les étudiants sont parfois en lien avec certains concepts de la théorie de l’évolution suggérée par Jean-Batiste de Lamarck (1744-1829) (Ha & Nehm 2013; Shtulman 2006; Kampourakis & Zogza 2007b). Brièvement, sa principale théorie consistait à reconnaître que l’utilisation ou la non-utilisation d’un organe en réponse directe à des conditions environnementales déterminait sa persistance chez un individu et sa transmission, ou non, d’une génération à une autre. Autrement dit, la théorie de la transmission des caractères acquis.  Lamarck ne reconnaissait pas le rôle du hasard dans les processus biologiques, ni l’extinction des espèces. Plutôt, il croyait à la complexification des organismes par des mécanismes mécaniques (de Lamarck 1809). Encore aujourd’hui, ce type de raisonnement de l’utilisation/non-utilisation d’un organe est observé parmi des étudiants de niveau pré-universitaire et dans les premières années d’études universitaires (Klymkowsky et al. 2010; Champagne Queloz et al. 2016; Champagne Queloz et al. 2017; Nehm & Ha 2010). En contrepartie, cette représentation ne devrait pas être étiquetée « modèle Lamarck », comme on peut encore trouver dans certains manuels de biologie. En effet, bien des scientifiques de cette époque, dont Charles Darwin, partageaient cette idée (Ha & Nehm 2013). On nomme cette théorie « le transformisme ». Cette théorie suggère qu’en réponse à certains facteurs environnementaux, les organismes vont transformer un organe en fonction de son utilisation. Ainsi, les nouvelles propriétés de cet organe seront transférées à la génération suivante (Shtulman 2006; Kampourakis & Zogza 2007b).

Kampourakis et Zogza (Kampourakis & Zogza 2007a) ont montré que d’autres conceptions alternatives étaient aussi faussement associées à la théorie de Lamarck. Premièrement, Lamarck ne croyait pas en cette explication téléologique qui suggère que les organismes évoluent en suivant un plan défini prédéterminé par une force quelconque et qui conduit vers un certain idéal. Deuxièmement, on associe à tort à sa théorie le « bon vouloir » ou la « volonté » d’évoluer, alors que Lamarck lui-même rejetait ces idées.  En fait, ces conceptions alternatives seraient nées d’une erreur de traduction des textes Lamarck (du français à l’anglais). Le mot « besoin » utilisé dans les textes de Lamarck, a été traduit par want (vouloir) au lieu de need to (avoir des besoins) (Mayr 1982; Kampourakis & Zogza 2007b). Les textes de Lamarck ont été lus par de notables évolutionnismes anglo-saxons de l’époque et ultérieurs. Ils ont, sans le vouloir, perpétué cette idée fausse de volonté.  Troisièmement, pour Lamarck, ce n’est pas l’environnement qui induit directement les changements génétiques. C’est plutôt l’utilisation des organes en fonction de conditions environnementales données, c’est-à-dire une action mécanique. Cette conception de l’évolution par Lamarck est maintenant reconnue comme étant erronée. Toutefois, elle reste encore une idée reçue fréquente qui freine l’apprentissage des processus évolutifs.

On dit donc parfois à tort que les étudiants ont une idée « lamarckienne » des processus évolutifs (Bishop & Anderson 1990; Demastes et al. 1995). Kampourakis et Zogza (Kampourakis & Zogza 2007b) ont demandé à des étudiants âgés de 15 ans d’expliquer comment les girafes allongeaient leur cou ou d’expliquer comment certains organismes dans un environnement donné peuvent changer de couleur. La majorité de ceux-ci ont expliqué que des besoins environnementaux poussaient les girafes à s’étirer le cou ou les animaux à changer de couleurs. Ces animaux induisant donc des changements génétiques permettant l’adaptation à des situations de stress. Sinon, il y a extinction de l’espèce. Au contraire, Lamarck ne croyait pas à l’extinction des espèces, mais suggérait plutôt qu’ils se transformaient pour survivre en adaptant des organes pour des besoins particuliers.

Lamarck et les girafes

En passant, cette représentation des girafes qui doivent allonger leur cou pour atteindre les feuilles les plus hautes dans les arbres est souvent associée à Lamarck. Toutefois, il est très intéressant d’apprendre par Kampourakis et Zogza (Kampourakis & Zogza 2007b), que Lamarck n’a pas vraiment étudié les girafes. D’ailleurs, lui-même n’a jamais eu l’occasion de les observer dans leur milieu naturel dans la savane. Dans son livre Philosophie Zoologique (de Lamarck 1809), il fait une seule courte remarque à propos de cet animal (citée ici). Il ne propose donc pas de connaissances factuelles pour expliquer le mécanisme de l’allongement du cou, sauf à part que c’est par l’utilisation de celui-ci par son étirement. Parallèlement, il ne suggère pas que la volonté de l’animal est responsable de l’élongation du cou. Des observations plus détaillées des girafes auraient plutôt été faites par Etienne Geoffroy Saint-Hilaire (1772-1844), un naturaliste français. En 1827, celui-ci avait été engagé par le roi Charles X pour s’occuper d’une girafe offerte par le gouverneur de l’Égypte, Méhémet-Ali (lire ici l’histoire de la girafe Zarafa!). Saint-Hilaire partageait des idées qui s’apparentaient au transformisme de Lamarck. Enfin, l’idée que les girafes allongent leur cou pour atteindre les feuilles les plus hautes avait déjà été suggérée en 1805 par Giuseppe Gautieri (1769-1833) (pour plus de détail à ce sujet, lire ici).

Controverse : et si Lamarck avait eu raison?

On ne peut passer sous silence le fait que certains chercheurs, suite à de récentes découvertes en biologie moléculaire et en génétique (par exemple, la technologie CRISPR), ravivent le modèle évolutif suggéré par Lamarck, souvent qualifiée de modèle quasi-Lamarckien (Koonin & Wolf 2009; Wang & Wood 2011; Burr et al. 2001). Sans vouloir entrer dans les détails de cette controverse (lire plutôt l’article en français de Casane et Laurenti (Casane & Laurenti 2016), les phénomènes génétiques suivant une tendance lamarckienne restent encore très marginaux et ont très peu d’influence dans les processus évolutifs. L’action du hasard tant au niveau de l’apparition des mutations, de la fixation ou de la perte des gènes, de l’embryogénèse et de la formation de nouveaux gènes, ainsi que la sélection naturelle sont grandement plus importantes dans l’évolution des organismes vivants.

Sobriquet ou non?

La classification et la nomination des concepts sur des bases historiques et épistémologique doit être faite avec parcimonie. Il faut éviter les dichotomies faciles entre les différents courants de pensée (le mauvais/le bon modèle). Certaines conceptions alternatives d’étudiants sont souvent classifiées sous un nom générique (dans le cas ci-présent, dites lamarckiennes, « la mauvaise »). En fait, elles partagent très peu de points communs avec le modèle originel. Ceci peut faire ombrage à certains scientifiques qui ont tout de même contribué de manière significative au développement de la pensée scientifique d’un concept. Comme suggéré par Kampourakis et Zogza (Kampourakis & Zogza 2007b), il faudrait aborder les conceptions alternatives des étudiants sans faire de classification fondée sur des références historiques. Le sens de certains concepts évolue avec le temps. Il peut alors être interprétés différemment et s’éloigner ainsi de l’idée originale proposée. Les implications pour l’enseignement peuvent être importantes, car on utilise souvent des références historiques pour renforcer l’importance d’un concept enseigné. De manière générale, bien des étudiants pensent que l’évolution des organismes se fait pour combler des besoins, vers l’atteinte d’un idéal. Ce raisonnement nuit à la compréhension authentique de l’évolution. Ce qui compte avant tout dans l’enseignement, c’est de savoir repérer, fissurer et franchir (Astolfi & Peterfalvi 1993) les conceptions alternatives pour mieux faire place aux savoirs scientifiques approuvés, et ce, peu importe le sobriquet attribué.



Astolfi, J.P. & Peterfalvi, B., 1993. Obstacles et construction de situations didactiques en sciences expérimentales. ASTER, 16, pp.103–141.

Bishop, B.A. & Anderson, C.W., 1990. Student conceptions of natural selection and its role in evolution. 27(5), pp.415–427.

Burr, T., Hyman, J.M. & Myers, G., 2001. The origin of acquired immune deficiency syndrome: Darwinian or Lamarckian? Philosophical Transactions of the Royal Society B: Biological Sciences, 356(1410), pp.877–887.

Casane, D. & Laurenti, P., 2016. Le cas CRISPR, mutations « ready-made» et évolution lamarckienne d’un système immunitaire adaptatif. médecine/sciences, 32(6), pp.640–645.

Champagne Queloz, A. et al., 2016. Debunking Key and Lock Biology: Exploring the prevalence and persistence of students’ misconceptions on the nature and flexibility of molecular interactions. Matters Select, pp.1–7.

Champagne Queloz, A. et al., 2017. Diagnostic of students’ misconceptions using the Biological Concepts Instrument (BCI): A method for conducting an educational needs assessment M. Hermes-Lima, ed. PLoS ONE, 12(5), pp.e0176906–18.

de Lamarck, J.B., 1809. Philosophie zoologique,

Demastes, S.S., Good, R.G. & Peebles, P., 1995. Students’ conceptual ecologies and the process of conceptual change in evolution. Science Education.

Ha, M. & Nehm, R.H., 2013. Darwin’s Difficulties and Students’ Struggles with Trait Loss: Cognitive-Historical Parallelisms in Evolutionary Explanation. Science & Education, 23(5), pp.1051–1074.

Kampourakis, K. & Zogza, V., 2007a. Students’ intuitive explanations of the causes of homologies and adaptations. Science & Education, 17(1), pp.27–47.

Kampourakis, K. & Zogza, V., 2007b. Students’ Preconceptions About Evolution: How Accurate is the Characterization as “Lamarckian” when Considering the History of Evolutionary Thought? Science & Education, 16, pp.393–422.

Klymkowsky, M.W., Underwood, S.M. & Garvin-Doxas, K., 2010. Biological Concepts Instrument (BCI): A diagnostic tool for revealing student thinking. arXiv.org.

Koonin, E.V. & Wolf, Y.I., 2009. Is evolution Darwinian or/and Lamarckian? Biology Direct, 4(1), pp.42–14.

Mayr, E., 1982. The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Havard  University Press. 974 p.

Nehm, R.H. & Ha, M., 2010. Item feature effects in evolution assessment. 48(3), pp.237–256.

Shtulman, A., 2006. Qualitative differences between naïve and scientific theories of evolution. Cognitive Psychology, 52(2), pp.170–194.

Wang, X. & Wood, T.K., 2011. IS5 inserts upstream of the master motility operon flhDC in a quasi-Lamarckian way. The ISME Journal, 5(9), pp.1517–1525.

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Ma thèse en 180 secondes: Le déterminisme génétique

Capture d’écran 2017-05-17 à 10.11.21

Félicitations à Florian Stern qui a gagné le second prix à la finale genevoise du concours « Ma thèse en 180 secondes ». Il a brillamment présenté ses travaux de recherche sur les conceptions alternatives (les idées reçues) en génétique chez des étudiants au niveau pré-universitaire. Sa présentation vidéo est disponible ici: https://mediaserver.unige.ch/play/101508/Florian%20Stern

De plus, Florian participera à la finale Suisse, ce jeudi 18 mai à 18h30, à l’Université Dufour de Genève. Venez nombreux pour le soutenir : l’entrée est gratuite, avec inscription obligatoire :https://www.mt180.ch/finale-suisse-2017/


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Diagnostic of students’ misconceptions using the Biological Concepts Instrument (BCI)


Youpi! Our paper “Diagnostic of students’ misconceptions using the Biological Concepts Instrument (BCI)” is now available online here in PlosOne: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176906.

Article in pdf is available here: Champagne_misconceptions

Congratulations to all collaborators! And many thanks!


Capture d’écran 2017-05-17 à 09.24.38

Results on questions 15, 16 and 20. Many participants were attracted by the oversimplifying analogy of puzzle pieces to explain molecular interactions and underestimated random diffusion and collisions as the main influence to spread and separate associated molecules.




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Debunking Nature of Science (Part 2)

The Duplo Vitruvian Man. Background figure presented by Prof Galili (not that one, but the original!). The anatomy of Science education = subject matter, pedagogy and didactics, cognitive sciences, philosophy and history. Who knows? Whom to ask?

Last Monday, I have been to an interesting presentation (see previous post here) titled: “The need of refinement of the features of the Nature of Science sometimes stated to be the “consensus view” in science education discourse” by Igal Galili, professor at the Hebrew University of Jerusalem. Prof Galili has background in physics and has a very strong interest in physics education (see here his remarkable contribution in divers scientific journals). The structure of knowledge into a discipline and perceptions of students on knowledge that educators tend to teach them are central themes of his research. In addition, he suggests an alternative model of the nature of science (NOS) features often taught to future science teachers. The presentation was interesting because it reflected quite well the development of knowledge: (re)-elaboration, refutation and re-elaboration of a model. You will see why by reading the following post…

Who knows? Whom to ask?

In general, NOS refers to the study of knowledge, i.e. the epistemology of science. Philosophers and historians of science, scientists and scientist educators are contributing to analyzing scientific conceptualization models or paradigms (Kuhn 1962) and attempt to determine the origin, the value and scope of knowledge (Lederman et al. 2013). The underlying questions of NOS are who knows and whom to ask (here is an interesting chapter about Prof Joseph Schwab (1939-1986) and his contribution in the emergence of contemporary NOS debates). The nature of science (NOS) is always more promoted in teaching biology. Indeed, it is well reported that many students do not realize how scientific knowledge (or data) are elaborated and are they can be “fixed” over time (Sadler et al. 2007; Burgin & Sadler 2015; Lederman et al. 2013). The teaching of NOS can improve scientific literacy, i.e. “an individual’s ability to make informed decisions about scientifically-based personal and societal issues” (Campanile et al. 2013, p. 206). In addition, the consideration of the NOS helps to understand the fallibility of science and consequently, driving the scientific research process continuously through new discoveries or innovations. We can easily understand how important learning NOS can be for students who expect working in scientific or technology research (and also for all students).

NOS characteristics

The NOS underlying 7 characteristic guidelines (Lederman et al. 2013) (read here for a complete description of each characteristic):

  • There is a distinction between observation and inference.
  • There is a distinction between scientific laws and theories
  • “Even though scientific knowledge is, at least partially, based on and/or derived from observations of the natural world (i.e., empirical), it nevertheless involves human imagination and creativity”.
  • “Scientific knowledge is subjective or theory-laden”.
  • “Science as a human enterprise is practiced in the context of a larger culture and its practitioners (scientists) are the product of that culture”.
  • “It follows from the previous discussions that scientific knowledge is never absolute or certain”.
  • “Individuals often conflate NOS with science processes (which is more consistent with scientific inquiry)”. There is not a single scientific method.

Features of Science

At first sight, the Ledermann 7-NOS features make sense for many people in education, including me, who often observed students’ weak scientific literacy. Such features are accessible (philosophical or historical backgrounds are not required to understand them) and can catalyze very interesting discussions between educators and students in science courses. However, as everything, there is a “but” to address the 7-NOS features with students. Here comes the main theme of Prof Galili’ presentation, who explained some limits of this model. The main concern is the overgeneralization of the features. For example, the distinction between laws and theories is quite debatable. A theory can be everything! It includes laws, models, principles, rules, definitions, experiments and epistemology aspects. This dichotomised thinking is not relevant in teaching science. Another example is about the subjectivity of science. Being subjective means for the majority of people that knowledge are influenced by someone’s personal feeling rather the facts. Or that knowledge exists only in someone’s mind. Biology or physics teachers can be unsafe to introduce the subjectivity of science to students. Being potentially destabilized in their learning, students may question the knowledge they have learned and asking why they have to learn it (which I’m considering this questionning totally relevant). As Prof Galili suggested, being objective does not presume being universally correct. “Knowledge is objective in certain conditions (the facts) over which arbitrary will have no control”. Here are its suggestions to specify the 7-NOS features in an educational context (see also Matthews 2012, available here):

  • Theory-empirical symbiosis.
  • Theories and laws in a based cultural structure
  • Enculturation
  • Objective product (theory) subjective inquiry (form)
  • Socially independent essence
  • Hypothesis, tentativeness, certainty
  • Scientific method, rules and procedure not anything goes

I will not detail all Prof Galili 7-NOS revisited features. Rather, I simply recommend to read this chapter: “Changing the Focus: From Nature of Science to Features of Science” by Michael R. Matthews in Advances in Nature of Science Research (M.S. Khine, ed.), available here. As Prof. Galili, Matthews considers the 7-NOS list incomplete and superficial. He suggests additional features covering realities of science studies and to change of focus from NOS to FOS, for Features of Science. Prof Galili argues “for addressing the features of science in the span of variation objective-subjective, tentative-certain, and so on depending on the context” (as cited in the presentation abstract, below).

Conclusions (tentative of…)

The idea of this post is not to decide who suggest the best model for teaching the construction of scientific knowledge. Both demonstrate the necessity to explore NOS with students to induce the development of scientific literacy. Interestingly, this debate reflects quite well the development of knowledge: (re)-elaboration, refutation and re-elaboration of a scientific model. All knowledge are subject to negotiations and consensus (Kuhn 1962).  To conclude, I quote Prof Galili’s argument: “that comparing and contrasting the contributions of scientists addressing similar or the same subject could not only enrich the picture of scientific enterprise, but also possess a special appealing power promoting genuine understanding of the concept considered” […] Considering this difference is educationally valuable, illustrating the meaning of what students presently learn in the content knowledge […], as well as the nature of science and scientific knowledge” (Galili 2015, in the abstract). I could not conclude better!



Burgin, S.R. & Sadler, T.D., 2015. Learning nature of science concepts through a research apprenticeship program: A comparative study of three approaches. Journal of Research in Science Teaching, pp.n/a–n/a.

Campanile, M.F., Lederman, N.G. & Kampourakis, K., 2013. Mendelian Genetics as a Platform for Teaching About Nature of Science and Scientific Inquiry: The Value of Textbooks. Science & Education, 24(1-2), pp.205–225.

Galili, I., 2015. From Comparison Between Scientists to Gaining Cultural Scientific Knowledge. Science & Education, 25(1), pp.115–145.

Kuhn, T.S., 1962. The Structure of Scientific Revolutions, 4th Edition, 2012, University of Chicago Press.

Lederman, N.G., S, L.J. & Antink, A., 2013. Nature of Science and Scientific Inquiry as Contexts for the Learning of Science and Achievement of Scientific Literacy. International Journal of Education in Mathematics, Science and Technology, 1(3), pp.138–147.

Sadler, T.D., Chambers, F.W. & Zeidler, D.L., 2007. Student conceptualizations of the nature of science in response to a socioscientific issue. International Journal of Science Education, 26(4), pp.387–409.


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