DidacBiol

Recently, 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 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 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!

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!

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.

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.

Aura lieu le mardi 2 mai, à 12:15, un séminaire qui a pour titre : “The need of refinement of the features of the Nature of Science sometimes stated to be the “consensus view” in science education discourse”. Ce séminaire sera présenté par le Professeur Igal Galili, de la Hebrew University of Jerusalem. Le rendez-vous a lieu à IUEF du Pavillon Mail, à Genève, dans la en salle PM10.

On Tuesday, May 2 at 12:15, the seminar titled: “The need of refinement of the features of the Nature of Science sometimes stated to be the “consensus view” in science education discourse”  is presented by Professor Igal Galili, of the Hebrew University of Jerusalem. The seminar takes place at IUEF of the Pavillon Mail, in Geneva, in the room PM10.

Voici le résumé de la présentation/here is the abstract of the presentation:

Abstract. Until recently, features of nature of science (NOS) were often not addressed in science curriculum at all or addressed superficially, drawing on an oversimplified perception of philosophy of science.  Within the attempt to improve the situation, a specific discourse has been developed by researchers in science education.  Since describing the nature of science involves the knowledge of history and philosophy of science, the discourse on NOS in education is not immune to confusion and speculative statements that require clarification to the wide population of students and practitioners. Such are, for instance, the popular claim of science to be “subjective” or rejecting the need of history of science for containing obsolete knowledge. We have performed several studies, and participated in HIPST European international project to provide a more comprehensive account for the subject.  Within this approach, we have developed so called discipline-culture framework to represent scientific knowledge seeking cultural content knowledge (CCK)* as well as addressing epistemological aspects of science.  The two require different accounts for presenting different types of culture – the culture of rules (the content knowledge) and the culture of texts (the scientific method) (**).  In my talk, I will describe our understanding of the NOS features as mentioned in literature (***) and their correspondent refinement.  We argue for addressing the features of science in the span of variation objective-subjective, tentative-certain, and so on depending on the context.

(*) Galili, I. (2012). Cultural Content Knowledge – The Case of Physics Education. International Journal of Innovation in Science and Mathematics Education, 20(2), 1-13.  Galili, I. (2014). Teaching Optics: A Historico-Philosophical Perspective. In M. R. Matthews (ed.).  International Handbook of Research in History and Philosophy for Science and Mathematics Education, pp. 97-128, Springer.

(**) Lotman, Yu. (2010). The problem of learning culture as a typological characteristic. In What people learn. Collection of papers and notes (pp. 18-32). Moscow: Rudomino.

(***) Lederman, N., Abd-el-Khalick, F., Bell, R.L. & Schwartz, R.S. (2002). Views of Nature of Science Questionnaire: Toward Valid and Meaningful Assessment of Learners’ Conceptions of Nature of Science.  Journal of Research in Science Teaching, 39(6), 497–521.

Pour plus d’information sur les projets du Professeur Galili, cliquer ici.

“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.

Ce printemps, l’Institut universitaire de formation des enseignants (IUFE) de l’Université de Genève propose des séminaires sur la recherche et la pratique en science de l’éducation (Research and Practice in Education Spring 2017). Le premier séminaire, qui aura lieu le lundi 6 mars, à 12:15, a pour titre : “Démarche d’investigation en classe de biologie: analyse de 25 séquences mises en oeuvre par les enseignants stagiaires”. Ce séminaire sera présenté par Mme Marie Merminod et M. Rémi Kopp. Le rendez-vous a lieu à IUEF, à Genève, dans la salle 225.

D’autres séminaires auront lieu durant tout le printemps. Voici l’horaire des présentations: Programme Printemps 2017

This spring, the Institute of Teacher Education (IUFE) at the University of Geneva offers the seminar “Research and Practice in Education”. The first seminar, on Monday, March 6 at 12:15, is titled: “Investigation approach in biology class: analysis of 25 sequences implemented by trainees- teacher”, by Mme Marie Merminod and M. Rémi Kopp. The seminar takes place at IUEF, in Geneva, in the room 225.

Here you can find the spring schedule 2017 of all presentations: Programme Printemps 2017

On March 25, 2017, Swiss Science Education organizes a workshop (SwISE “Innovationstag”) titled: “Naturwissenschaftlich-technischer Unterricht”, at PH FHNW, Campus Brugg-Windisch (09:15 Uhr – 16:40 Uhr).

Recently, the Department of Biology at ETH Zürich, in Switzerland, has introduced new forms of teaching such flipped classroom. It aims to encourage students to become more involved in their learning (see the article here).

“Deblocking” teaching in well-established universities!

Traditional educational practices 

It is often difficult to initiate educational reforms in prestigious or top-ranked universities (this idea of top-ranked universities is quite debatable… Article 1. Article 2. Article 3). It requires commitment and some humility to recognize the limits of a system and the need to change it. Usually, traditional educational practices are strongly anchored into well-establish universities. Traditional teaching refers to a lecturer who is the main actor involved into the transfer of knowledge. In this context, students have a passive role by absorbing knowledge. Common assessments are usually constructed to measure abilities of students to memorize large amount of knowledge and to distinguish/describe “the right” and the “false” statements. The principal exchange between the lecturer and the students is normally during informal oral questions sessions during or at the end of the lecture. Most of the time, only few students are willing to share their questioning or comments. In addition, the room to discuss in class is often restricted, dominated by the time requires to teach the content.

At ETH Zürich, some professors were unsatisfied with such traditional approach. They have realized that, even if students are learning something, they don’t demonstrate any ability to discuss or to develop critical thinking. Such competencies are fundamental to develop a better scientific literacy. In addition, many students interpret wrongly what we tend to teach them by demonstrating important misconceptions (read here our article about this subject). Those misconceptions are often immutable when not addressed and not revealed by common assessments.

Flipped Classroom

A flipped classroom consists for students to get acquainted with the subject of the lecture before to come in class through self-study using interactive learning exercises with texts and videos available via a learning platform. Then, students are coming in class and the lecturer introduces briefly the subject. After this short introduction, students are working in small teams to do some learning activities and discuss between them, with the lecturer and the teaching assistants. Developing such educational approach takes considerably a lot of time to prepare and update the material and a workforce to assist students in large-enrolled groups during discussion sessions.

A survey done at the end of every semester reveals that ETHZ students are highly happy with this approach. In addition, according to the lecturers, the teaching assistant and the students, the discussions immediately reveal some weak understanding, offering the possibility of the lecturer to readjust his teaching quickly. Consequently, students develop a better conceptual understanding.

Center for Active Learning (CAL)

The Department of Biology has founded the Center for Active Learning (CAL). The team is offering counselling and development services for the department’s lecturers. They collaborate with the department of Educational Development and Technology at ETH Zürich to improve the learning platform.

Educational Tasks of Universities

Prestigious or top-ranked universities should remain at the forefront of the key improvements in education, not only in research activities. The main role of universities is the formation of future professionals or researchers having knowledge, of course, but also demonstrating conceptual understanding and critical thinking. Traditional education doesn’t accord to measure such competencies. Obviously, this suggests that authorities must therefore show a certain open mind for changes. Challenging a well-establish system demands engagements, the conviction that changes are needed, but, principally, some humbleness to recognize that we can do better.

In February 2017, I’m giving a talk about my ideas on reforming biology education in Switzerland. This theme has taken origin in my doctorate thesis (available here). I have written, in an unpretentious way, that my work could be considered as a first step to reform biology curriculum. Honestly, I have probably underestimated the value of this quote, and thus, now, I have to assume it! Consequently, I’m invited to explain such ideas during the “Praktikumslehrerfortbildung”, a workshop organized every two years for Swiss teachers from different disciplines.

Reforming the content

In the first part of my talk, I will show some of the most important results of my doctorate project. For me, while the results I have collected give important insights about misconceptions in biology held by Swiss students, my contribution is only the first step in the initiation of a reform. Indeed, I consider my research project as an educational needs assessment, i.e. the identification of a problematic situation. Kaufman et al. (2002), specialists in educational curricula design, define “need” as a gap between observable and desired results. During my studies, I have diagnosed some problematic understanding of particular biology concepts by using the Biological Concepts Instrument (BCI), a multiple-choice questionnaire built on students’ thinking (click here for more information). We were interested in how students can interpret the content (the scientific knowledge) that we tend to teach them. We know that students have persistent “Carebears” thinking on how biological processes work that need to be explicitly addressed during the course of instruction.

Many students have a “Carebears” thinking on how biological processes work.

Otherwise some of those ideas can harm to construct a solid network of knowledge and to develop an authentic conceptual understanding (see this previous post). In parallel, many of undergraduates met have not demonstrated an interdisciplinary perspective of thinking, i.e. they had some difficulties to connect different disciplinary knowledge together. The project revealed some problematic understanding that should be addressed in the course of instruction, requiring some changes or adaptation to the current science curriculum at the secondary and university level. However, are the results sufficient to catalyze a national educational reform in Switzerland?

Reforming the context

Then, here come what I consider the second step. Educational reforms initiated to address some socio-scientific issues can make science education more relevant for the students (see that reference for the meaning of “relevance”, Stuckey et al. 2013). In sociology of education, briefly, some are saying that education can reform the society (for example, by promoting better health and civic engagement) (Sadler 2011). In contrast, others are saying that the society is responsible for reforming education by defining professional and economic needs (see Meyer (1977) for an interesting review about the effects of education as an institution). Despite this contradiction, I was curious to investigate some socio-scientific issues, i.e. the context, that could be improved by reforming biology curriculum in Switzerland.

Despite important progress since the last 30 years by deploying important campaign again tobacco addiction, approximately 37% of the people between 20 and 34 years old are smoking in Switzerland (here is the reference, Addiction Suisse), positioning the country on the 25th rank, out of possible 182 (the source is here). Another example is the constant increase of the numbers of cases of chlamydia, gonorrhea and syphilis in many occidental countries (WHO, 2016), including Switzerland (Statistiques, Office fédéral de la santé publique). Those public health issues could be used to develop a phenomenon-based learning approach, as Finland have initiated recently (here in an interesting article about Finnish educational reform). Many science topics such immunology, microbiology, cancer development, genetics (mutations), evolution (mutations), molecular biology (movements and structures of molecules), etc. could be taught though those socio-scientific issues as contexts in which student’s knowledge can be applied. To quote Sadler (2011, p.4): “If our goal is to help students become better able to contribute to debates and decisions about important societal issues with links to science and technology, then we need to create learning contexts such that learners actually confront some of these issues and gain experiences negotiating their inherent complexities”. By the existence of such socio-scientific issues and the low interests of its, I think that we failed in our way to teach biology (or science in general) in promoting a better science culture in earlier stages of education (indeed, usually such investigations are showing that higher level of education reduces the incidence of tobacco addiction or infectious sexual diseases).

Of course, it is hard to measure how the socio-scientific issues integrated in science curricula and reforms in education will necessarily lead to more informed citizens and better decision makers. The society will evaluate this citizenship competency (a question that could be raised: who is the society…?!). Reforming the content should be constantly done with respect to the development of scientific innovations and progress in science education. Reforming the context by catalyzing some changes in education system is also pertinent when some socio-scientific issues are observed in society. Such contexts make learning science relevant to students.

References

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.

Kaufman, R., Watkins, R. & Guerra, I., 2002. Getting Valid and Useful Educational Results and Payoffs: We Are What We Say, Do, and Deliver. International Journal of Educational Reform, 11(1), pp.77–92.

Meyer, J.W., 1977. The Effects of Education as an Institution. American Journal of Sociology, 83(1), pp.55–77.

Sadler, T.D., 2011. Socio-scientific Issues in the Classroom T. D. Sadler, ed., Dordrecht: Springer Science & Business Media.

Stuckey, M. et al., 2013. The meaning of “relevance” in science education and its implications for the science curriculum. Studies in Science Education, 49(1), pp.1–34.

In spring semester 2017, the “Forschungskolloquium der Naturwissenschafts-, Technik- und Sachunterrichtsdidaktik” takes place at Pädagogischen Hochschule der FHNW, Basel. The detailed program can be found here as the direction to find the place. The talks give insight into current subject-matter themes and research.

• Place: FHNW, Pädagogische Hochschule, 1st Floor, Room 106, Steinentorstr. 30, 4051 Basel (about 5 ‘walk from Basel SBB station. Here is the plan)
• Time: on Mondays, from 16.15 to 17.45 hours

Language: German

For more information:
Manuel Haselhofer: manuel.haselhofer@fhnw.ch