Posts Tagged ‘Education’
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
- Biological Concepts Instrument. (Klymkowsky, Underwood & Garvin-Doxas, 2010)
- Biological Experimental Design Concept Inventory. (Deane, Nomme, Jeffery, Pollock & Birol, 2014)
- Central Dogma Concept Inventory. (Newman, Snyder, Fisk & Wright, 2016)
- Chemical Concepts Inventory. (Barbera, 2013)
- Conceptual Inventory of Natural Selection. (Anderson, Fisher & Norman, 2002)
- Diffusion and Osmosis Diagnostic Test. (Odom & Barrow, 1995)
- Dominance Concept Inventory. (Abraham et al., 2014)
- Dynamics Concept Inventory. (Gray et al., 2005)
- Enzyme-Substrate Interactions Concept Inventory. (Bretz & Linenberger, 2012)
- Evolutionary Developmental Biology Concept Inventory. (Perez et al., 2013)
- Genetic Drift Inventory. (Price, et al., 2014)
- Genetics Literacy Assessment Instrument. (Bowling et al., 2008)
- Heat and Energy Concept Inventory. (Prince et al., 2012)
- Homeostasis Concept Inventory. (McFarland et al., 2017)
- Host-Pathogen Interactions Concept Inventory. (Marbach-Ad et al., 2009)
- Introductory Molecular and Cell Assessment. (Shi et al., 2010)
- Lac Operon Concept Inventory. (Stefanski & Gardner, 2016)
- Meiosis Concept Inventory. (Kalas, O’Neill, Pollock & Birol, 2013)
- Molecular Biology Capstone Assessment. (Couch et al., 2015)
- Natural Selection Open Response Instrument. (Nehm & Schonfeld, 2008)
- Photosynthesis: Diagnostic Question Clusters. (Parker et al., 2012)
- Osmosis and Diffusion Conceptual Assessment. (Fisher, Williams & Lineback, 2011)
- RaProEvo. (Fiedler, Tröbst & Harms, 2017)
- Thermal and Transport Science Concept Inventory. (Streveler et al., 2011)
- 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!
References
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.
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!
References
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.
Le bien-fondé des cours préalables : une question de symbiose !
Nombre de fois où j’ai voulu sauter des étapes lors de ma carrière estudiantine, mais les cours préalables m’ont bien vite coupé mon élan ! Pour le mieux ou pas ? Ils sont souvent une source de frustration pour bien des étudiants. Les raisons sont diverses : l’obligation ne plait pas, trop généraux, pas de lien direct avec une profession, trop basiques, manque de cohésion entre les cours, etc.
La « découverte » scientifique…
Tout récemment, Brian K. Sato et son équipe (Sato et al. 2017) se sont intéressés à cette question des cours préalables dans un cursus scientifique (l’article original en anglais est disponible ici). Ils ont évalué les bénéfices des prérequis pour un cours théorique de microbiologie et de son pendant pratique, la période de laboratoire. Un questionnaire de « familiarité » des concepts a été développé pour mesurer l’état de connaissances des étudiants. Plus précisément, cette échelle de familiarité consiste à mesurer l’habilité de l’étudiant à répondre à une question théorique à partir de ses connaissances acquises lors d’un cours prérequis. De manière générale, ils ont constaté que les étudiants qui participaient au cours théorique de microbiologie ne performaient pas mieux que ceux qui ne le suivaient pas. De là, on peut donc remettre en question le bien-fondé des cours prérequis !
Préalable en fonction de quoi ?
La réussite d’un cours préalable obligatoire est une façon de s’assurer que l’étudiant/e a acquis/e un certain niveau de connaissances de base. On peut comparer cela à la construction d’une fondation de savoirs (idéalement solide !) permettant d’accueillir des connaissances de plus en plus complexes. J’ai exploré le « comment » on définit les préalables, mais j’ai trouvé bien peu de littérature sur le sujet. De manière générale, les instructeurs semblent souvent déterminer les prérequis en fonction de leur expérience personnelle en enseignement, mais aussi en fonction leur propre expérience en tant qu’étudiants (Rovick et al. 1999).
Qui vient en premier ? La théorie ou la pratique ?
Revenons à Sato et ses collègues et à leur grille de « familiarité ». Simplement, des questions peuvent être « très familières », « familières » ou « non-familières » en fonction des connaissances acquises préalablement. Ainsi, en mesurant l’habilité des étudiants à répondre à certaines questions de connaissances, ils ont pu évaluer si le cours théorique de microbiologie était nécessaire pour réussir le cours de laboratoire. De manière générale, les étudiants qui avaient fait le cours théorique de microbiologie avaient significativement les mêmes résultats sur les examens théoriques et de laboratoire que les étudiants n’avaient pas complété ce cours théorique normalement prérequis pour le laboratoire. Ils ont aussi rencontré les étudiants pour connaître leurs perceptions de ces prérequis. Pour 89.3% des étudiants, les prérequis sont nécessaires pour acquérir des connaissances de base. Pour, respectivement, 35.7%, 25.0% et 21.4%, les connaissances préalables agissent comme un « filet de sécurité », déterminent leurs succès futurs et contribuent à l’intérêt de la discipline enseignée. Toutefois, pour 51.7% des étudiants rencontrés, le cours théorique représente aussi un casse-tête administratif, surtout au niveau de l’établissement de l’horaire des cours. Beaucoup considèrent ce cours comme une perte de temps et d’argent (37.9%) ou mal intégré dans le cursus (31.0%). Il est intéressant de constater que seulement 17% pensent que le cours théorique de microbiologie est inutile. Pour Sato et ses collègues, les résultats obtenus ont permis de créer une ligne directrice pour amorcer certains changements dans les cours de microbiologie. Toutefois, ils ne suggèrent aucune avenue pour résoudre l’énigme de ce qui doit venir en premier ; la théorie ou le laboratoire ?!
Ce que l’on doit retenir
L’idée de ce type d’investigation n’est pas de démontrer que les prérequis ne sont pas nécessaires. En effet, multiples études montrent l’importance de ceux-ci et présentent des résultats qui contrastent avec l’étude menée par Sato et ses collègues (Soria & Mumpower 2012; Choudhury & Robinson 2007; McCoy 2004; Donovan & Wheland 2009). Il faut plutôt retenir l’importance de remettre en question certaines façons de faire, qui sont souvent solidement ancrées depuis de nombreuses années. L’acquisition de connaissances fondamentales est essentielle pour la construction d’un réseau de plus en plus complexe. Les cours prérequis sont une forme de standardisation du système éducatif assurant un niveau d’instruction minimum nécessaire à la réussite de l’étudiant (en théorie !). Toutefois, il serait important de réévaluer son efficacité car un tel système évolue aussi en fonction de contextes socio-économiques et technologiques donnés. Selon moi, des résultats présentés comme ceux de Sato et ses collèges démontrent uniquement la nécessité de remodeler un curriculum de façon à ce que les cours offerts deviennent totalement réciproques, c’est-à-dire en symbiose. Les prérequis sont donc un bien-fondé, si ceux-ci sont raisonnés !
Références
Choudhury, A. & Robinson, D., 2007. Effect of prerequisite on introductory statistics performance. Journal of Economics and Economics Education Research, 8(3), pp.19–32.
Donovan, W.J. & Wheland, E.R., 2009. Comparisons of Success and Retention in a General Chemistry Course Before and After the Adoption of a Mathematics Prerequisite. School Science and Mathematics, 109(7), pp.371–382.
McCoy, E.D.P.S.K., 2004. The Function of Course Prerequisites in Biology. American Institute of Biological Sciences.
Rovick, A.A. et al., 1999. How accurate are our assumptions about our students’ background knowledge? Advances in Physiology Education, 21(1), pp.S93–S101.
Sato, B.K. et al., 2017. What’s in a Prerequisite? A Mixed-Methods Approach to Identifying the Impact of a Prerequisite Course. D. Barnard, ed. CBE-Life Sciences Education, 16(1), pp.ar16–20.
Soria, K.M. & Mumpower, L., 2012. Critical building blocks: Mandatory prerequisite registration systems and student success. NACADA Journal, 32(1), pp.30–42.
“Energy is required to perform a work” is meaningless in biology education
“Energy is required to perform a work.”
In an university introductory biology course, I have investigated undergraduates’ thinking about the concept of energy. The question was simply: “Define energy”. This question was simple in construction in order to avoid influencing students’ answers (Schurmeier et al. 2010). In addition, I was curious to find out the discipline influence in the student’s reasoning. The most popular explanation was “energy is required to perform a work”, mainly inspired by knowledge learned in physical courses. In biological contexts, such reasoning doesn’t really help to understand the energy requirement in biological processes. For example, understanding molecular binding of medicaments or antibodies requires the recognition of energetic properties of molecules and understanding some thermodynamics principles (more details here). “Perform work” is quite meaningless in such microscopic scale. Cooper and Klymkowsky (Cooper & Klymkowsky 2013) consider that the focus on macroscopic events in physics courses (the most classic example is an object rolling down a hill) harms to develop an interdisciplinary understanding of this concept, mainly in biology introductory courses. This problem is referred as multimodalities in representing the concept of energy (Tang et al. 2011). Indeed, differences in discourse between disciplines make the concept energy confused for many students (Hartley et al. 2012).
Energy?
How can we define clearly energy that may help students to improve their biological understanding? Let’s check on Wikipedia.
“In physics, energy is the property that must be transferred to an object in order to perform work on – or to heat – the object, and can be converted in different forms, but not created or destroyed. […]. Common energy forms include the kinetic energy of a moving object, the potential energy stored by an object’s position in a force field (gravitational, electric or magnetic), the elastic energy stored by stretching solid objects, the chemical energy released when a fuel burns, the radiant energy carried by light, and the thermal energy due to an object’s temperature”. (Wikipedia)
“In biology, energy is an attribute of all biological systems from the biosphere to the smallest living organism”. (Wikipedia)
Hartley and al. (2012) have investigated energy definitions in popular chemistry, physics and biology textbooks (Figure 1).
Figure 1: Textbook definitions and index-term usage of energy and matter (from Hartley et al. 2012)
We can notice that the idea of capacity to do work, the form of energy (potential, kinetic, heat, thermal energy), conservation of energy are common terms among chemistry, physics and biology textbooks. However, we mainly retain that energy is an abstract concept, not observable and impossible to measure directly. To cite Richard Feynman (1963), “It is important to realize that in physics today, we have no knowledge of what energy is“. In 2017, the definition is not really more elaborated. Energy is still a hard concept to teach and to learn. If we cannot easily define it, maybe we can analyze the potential origin of the confusion.
Interdisciplinary Confusion
As we can see, energy is a core concept in education of sciences. Energy underlies all processes in physics, chemistry and biology. The main problem in biology courses is that many students do not consider energy as the main driver of molecular interactions. It includes movements, binding and detachments of molecules in cells. Such interactions directly influence, for example, expression of genes and consequently, the determination of morphological traits. Students often restrict their reasoning by having a macroscopic view of physical principles. For examples, a ball rolling down a hill (kinetic vs potential energy) or the energy requires to maintain muscles in action. In addition, many research demonstrated that students have many misconceptions on the concept of energy (entropy, potential/kinetic energy) (Neumann et al. 2012; Haglund et al. 2015; Geller et al. 2014). It might be possible that such misconceptions are transferred into biological contexts. Megan Nagel and Beth Lindsey (Nagel & Lindsey 2015) have shown that students who leaving an introductory general chemistry course do not recognize how distance between molecules are determinate by the energy of a system. We know that many students struggle to understand how molecules “find each other” or get apart again (Klymkowsky et al. 2010; Champagne Queloz et al. 2016).
In parallel, the misconceptions “energy is stored in chemical bonds” and “energy is released when bonds break” is well popular among the learners. It indicates that students often consider chemical bonds as a physical entity.
“This notion of a chemical bond as matter thus appeared to be linked to the everyday notion that building any structure requires energy input, and its converse, destruction, releases energy, to form the basis for the prevalent alternative conception that bond making requires input of energy and bond breaking releases energy”. (Boo 1998) p. 574
In biology contexts, there is this false idea that breaking chemical bonds of food by digestion (in other words, a catabolism reaction) releases energy. The focus should be on the chemical reactions. Precisely, the reaction between oxygen and the food through the cellular respiration transforms the potential energy into chemical (ATP) and thermal (heat) energy. This thermal energy is essential to govern all biological processes.
The thermodynamics factor, the thermal energy, is the “force” pushing the molecules in diverse directions, engendering collisions and then, causing random movements of its. Hartley et al. (2012) reported that in the majority of biology textbooks, the focus is on movement, i.e. the transfer through ecosystems and transformations of energy. In their investigation, they found that only few textbooks were referring to the conservation of energy or law of thermodynamics to describe biological processes.
There is another problem. In chemistry and physics courses, energetic models are most of the time presented in equilibrium closed-systems, or in controlled-environmental systems. In contrast, biological systems are open, i.e. there are exchanges between organisms and the exterior environment. The exchanges consist of continuous building up and breaking down of molecules (Bertalanffy 1950). Here you can find fancy explanations about this principle. Again, such energetic exchanges take origin in thermodynamics processes.
Some solutions?
The concept of energy is difficult to teach because there is not explicite consensus among scientific disciplines. Hartley and al. (2012) paper gives some insights helping to be aware of the interdisciplinary confuse meaning of energy. According them, simply to increase the awareness of the differences in how biologist, chemists and physicists define energy might help to better teach it. It also improve understanding of students.
Moreover, students need help to make spontaneous connections between knowledge taught in physics, chemistry and biology classes (Nagel & Lindsey 2015; Tang et al. 2011). Megan Nagel and Beth Lindsey (Nagel & Lindsey 2015) showed that only few of them have the abilities to transfer their knowledge through different disciplines.

Figure 2: Some students can think that energy is a physical entity, such a liquid or a solid.
The last point is about the terminology used to describe energy. Everyday language can conduct through a wrong understanding of this concept. For example, we often read, “chemical reactions produce/create energy”. The energy is transferred or transformed, but it is never produce or create. This wrong idea is again the first law of thermodynamics, the conservation of energy. Another example is the use of the word “substance” to define energy. Some students can think that energy is a physical entity, such a liquid or a solid. Moreover, some consumable products, such energetic drinks or energetic bars increase the prevalence of this “substance” thinking. Such everyday expression should be used carefully when the concept of energy is taught.
Conclusions
As you can see, teaching and learning energy takes a lot of energy! Only awareness of such difficulties can make it easier, I think. The general idea of that post was that, to inform about some issues and unfortunately, not to give a precise definition of this interdisciplinary concept. I have the humility to recognize that it’s definitely over my scientific competencies!
References
Bertalanffy, von, L., 1950. The theory of open systems in physics and biology. Science, 111(2872), pp.23–29.
Boo, H.K., 1998. Students’ understandings of chemical bonds and the energetics of chemical reactions. Journal of Research in Science Teaching, 35(5), pp.569–581.
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.
Cooper, M.M. & Klymkowsky, M.W., 2013. The Trouble with Chemical Energy: Why Understanding Bond Energies Requires an Interdisciplinary Systems Approach. CBE-Life Science Education, 12(2), pp.306–312.
Geller, B.D. et al., 2014. Entropy and spontaneity in an introductory physics course for life science students. American Journal of Physics, 82(5).
Haglund, J., Andersson, S. & Elmgren, M., 2015. Chemical engineering students’ ideas of entropy. Chemistry Education Research and Practice, 16(3), pp.537–551.
Hartley, L.M. et al., 2012. Energy and Matter: Differences in Discourse in Physical and Biological Sciences Can Be Confusing for Introductory Biology Students. BioScience, 62(5), pp.488–496.
Klymkowsky, M.W., Underwood, S.M. & Garvin-Doxas, K., 2010. Biological Concepts Instrument (BCI): A diagnostic tool for revealing student thinking. arXiv.org.
Nagel, M.L. & Lindsey, B.A., 2015. Student use of energy concepts from physics in chemistry courses. Chemistry Education Research and Practice, 16(1), pp.67–81.
Neumann, K. et al., 2012. Towards a learning progression of energy. Journal of Research in Science Teaching, 50(2), pp.162–188.
Schurmeier, K.D. et al., 2010. Using Item Response Theory To Assess Changes in Student Performance Based on Changes in Question Wording. Journal of Chemical Education, 87(11), pp.1268–1272.
Tang, K.S., Tan, S.C. & Yeo, J., 2011. Students’ Multimodal Construction of the Work–Energy Concept. International Journal of Science Education, 33(13), pp.1775–1804.
Être ou ne pas être un illettré des sciences!
Juste avant d’entrer dans le vif du sujet, je vais faire une courte présentation de Mike Klymkowsky, professeur de biologie moléculaire, cellulaire et développement à l’Université du Colorado Boulder (voir ici pour plus d’info sur ses travaux de recherche et d’enseignement). Il était membre de mon comité de thèse (la présentation de mon projet est ici) et est souvent invité par l’ETH Zürich (Suisse), à présenter ses idées concernant l’enseignement et le design de curricula en biologie. Sa conception de la biologie est très holistique, c’est-à-dire que la compréhension des processus biologiques ne peut se faire sans l’appui de connaissances issues de la physique, de la chimie et des mathématiques. Son équipe participe au développement d’activités éducatives qui intègrent cette perspective interdisciplinaire (Klymkowsky, Rentsch, et al. 2016; Klymkowsky, Koehler, et al. 2016). Ils s’intéressent notamment aux idées reçues (Klymkowsky et al. 2010) et aux obstacles didactiques (Clément 2015).
Tout récemment, Mike (ouais, comme je le connais bien, pour moi il est amicalement Mike!) a publié un billet intéressant sur la «littéracie» et l’«illittéracie» scientifique, des expressions encore très peu utilisées dans la francophonie (pour lire la version originale, cliquer ici). La définition classique de la littéracie est la capacité à lire et à écrire. Cette définition s’est quelque peu élargie du côté anglo-saxon, et fait aussi référence à la culture scientifique. En effet, selon le programme PISA (Program for International Student Assesment) de l’Organisation de coopération et de développement économiques (OCDE), la littéracie scientifique (ou biolittéracie, spécifiquement pour la biologie) englobe les connaissances et les compétences acquises par l’étudiant nécessaires à l’analyse de problèmes sociaux, environnementaux ou de santé publique. Ces savoirs devraient donc l’amener à prendre position sur un sujet donné et sur les meilleurs comportements à adopter, «en tant que citoyen réfléchi» (lire ici l’enquête PISA sur la culture scientifique). Toutefois, cette définition est plutôt large et est difficilement mesurable dans un contexte d’enseignement (Roberts 2007). De plus, certaines études montrent qu’il y a très peu ou pas de liens significatifs entre une «bonne» connaissance scientifique et les attitudes «d’un citoyen réfléchi» (Gaskell et al. 2004; Allum et al. 2008; Priest et al. 2003). Mike, suggère plutôt de tourner le problème et de s’intéresser aux conséquences l’illittéracie scientifique.
Par exemple, en Suisse par son système de démocratie directe, un citoyen a la chance de participer à l’établissement des lois et des règlements qui sont obligatoirement soumis au vote populaire.

Un vote à main levée (“Landsgemeinde”) dans la ville de Glaris, en Suisse.
Une question soulevée pourrait être: comment des citoyens «illettrés» en sciences peuvent prendre des décisions éclairées sur des questions environnementales ou de santé publique? Selon Mike, la littéracie scientifique intègre deux compétences essentielles: 1- la personne doit être capable de comprendre la question, et 2- la personne doit posséder les connaissances pour répondre à la question. Si elle ne possède pas les connaissances nécessaires, elle doit tout d’abord reconnaître qu’il y a un manque et ensuite trouver des sources d’information fiables pour combler ses lacunes. Ces compétences se développent par la pratique et par un système de rétroactions («feedbacks» en bon français!). L’illettré scientifique va présenter des erreurs théoriques importantes, va exposer un manque de logique ou des contradictions. Il peut aussi ne pas reconnaître les limites des connaissances scientifiques, un principe phare de la nature de la science (le développement des savoirs scientifiques). Mike cite en exemple les effets secondaires des médicaments qui varient d’une personne à une autre, principalement attribuables à des variabilités génétiques, environnementales ou physiologiques. Les savoirs relatifs aux effets secondaires des médicaments sont, on pourrait dire dans une zone grise, car ceux-ci sont quasiment imprévisibles. Une personne qui comprend cette limite de la science a développé une certaine habileté de raisonnement et lui permet alors de prendre position de manière la plus réfléchie possible. L’enseignement des sciences devrait donc se faire, non pas dans l’apprentissage par coeur de connaissances en vrac dénudées de tous contextes, mais plutôt dans la perspective de promouvoir le développement de la culture scientifique, qui intègre l’analyse de problème et la prise de décision.
Je vais donc dans la même direction que Mike en suggérant de tenir compte des idées reçues ou des lacunes de compréhension des étudiants en (ré)- établissant la discussion en classe comme le faisait Socrate à une autre époque. On ne pourra peut-être pas mesurer directement le lien entre leur littéracie scientifique et leurs actions citoyennes, mais on pourra au moins diagnostiquer des lacunes de compréhension qui nuisent à leur culture scientifique.
En passant, je viens tout juste de publier le même billet (ici) sur Medium dans le but d’élargir mon lectorat.
Références
Allum, N. et al., 2008. Science knowledge and attitudes across cultures: a meta-analysis. Public Understanding of Science, 17(1), pp.35–54.
Clément, P., 2015. Le Délai de Transposition Didactique (DTD) dans les Livres du Maître. Exemples en Biologie., pp.1–27.
Gaskell, G. et al., 2004. GM foods and the misperception of risk perception. Risk Analysis, 24(1), pp.185–194.
Klymkowsky, M.W., Koehler, K. & Cooper, M., 2016. Diagnostic assessments of student thinking about stochastic processes, Cold Spring Harbor Labs Journals.
Klymkowsky, M.W., Rentsch, J.D., et al., 2016. The design and transformation of Biofundamentals: a non-survey introductory evolutionary and molecular biology course. CBE-Life Science Education.
Klymkowsky, M.W., Underwood, S.M. & Garvin-Doxas, K., 2010. Biological Concepts Instrument (BCI): A diagnostic tool for revealing student thinking. arXiv.org.
Priest, S.H., Bonfadelli, H. & Rusanen, M., 2003. The “trust gap” hypothesis: Predicting support for biotechnology across national cultures as a function of trust in actors. Risk Analysis, 23(4), pp.751–766.
Roberts, D.A., Scientific literacy/science literacy. I SK Abell & NG Lederman (Eds.). Handbook of research on science education (pp. 729–780). 2007, Mahwah, NJ: Lawrence Erlbaum.