Keywords
Science Education, Higher Education, Interdisciplinarity, Formative Assessment, Assessment and Evaluation, Naïve Conceptions, Conceptual Change, Transfer
Introduction
Applying the Biological Concept Inventory (BCI, Klymkowsky et al. 2010) to biology bachelor students in their first and third semester at University showed that the understanding of certain biological concepts did not increase substantially despite 1.5 years of instruction (Queloz et al. 2016, Figure 1). Interestingly, students struggle most with biological questions requiring knowledge transfer from other STEM (science, technology, engineering and mathematics) disciplines, which are also taught during the first year of studies (Queloz et al. 2017). One of the reasons for the persistently poor performance in the BCI might be that students hold many naïve conceptions in chemical and physical concepts themselves. This makes it even harder, if not impossible, to acquire new knowledge from biology based on those interdisciplinary concepts. In addition, the likelihood of knowledge transfer between different contexts is increased the closer the two context resemble each other (Perkins & Salomon 1992). However, in most biology curricula students study physics, chemistry and biology in a disjointed manner with different lecturers in different courses. This leads to very different contexts in which fundamental knowledge is taught in chemistry and physics and then used in biology (Figure 2).
Figure 1. Example question from the study performed by Queloz et al. (2016).
Figure 2. Functional Context of Reduction-Oxidation Reactions in chemistry (left) and biology (right). The contexts and the involved molecules with which students are confronted with Redox-Reactions differ greatly.
Goals
Therefore, in this project we will develop an assessment tool to measure students’ understanding of physical & chemical concepts that are crucial for a holistic understanding of biology. To achieve this we will mostly follow Adams and Wieman’s (2011) suggestion to develop instruments to measure learning. Using this instrument (later called the FPCI) and the BCI, we will assess students’ conceptual understanding of these physical & chemical as well as biological concepts over the course of their studies at university. This will allow us to estimate how the understanding of physical and chemical concepts relates to the understanding of core biological topics.
We are also interested in investigating how a more integrated, interdisciplinary approach of teaching affects the conceptual understanding of the physical & chemical principles underlying biology. Since in 2020 the department of biology implemented a new, more integrated life science curriculum, we will be able to compare students’ improvements in the classical approach of teaching STEM subjects in a biology curriculum to those obtained in the new biology curriculum at ETH.
The goal of our work is to address the following questions: How does students’ understanding of physical & chemical concepts relate to their understanding of biological concepts over the course of their studies? How does a more interdisciplinary way of teaching STEM subjects in a life science curriculum change students’ understanding of physical & chemical and biological concepts? Results for these questions will then hopefully pave the way to designing effective interventions to address interdisciplinary concepts, and allow instructors to improve the interdisciplinarity of lectures in life science curricula in general.
Figure 3. Research timeline.
State of the project
To design the concept inventory tackling chemical and physical concepts we first conducted interviews with experts (professors) and novices (first semester students) to define the chemical and physical concepts in which most alternative conceptions exist. For these we then created preliminary open-ended questions which novices solved in think-aloud interviews. Results from the interview guided the further development of the questions as well as correct and incorrect answers for a multiple-choice format of the test. An example for such a question as shown to students is shown in Figure 4.
Figure 4. Example question about hydrogen bonds. “Which of the following statements are correct AND contribute to the differences in boiling temperatures between water, hydrogen fluoride and ammonia?”
Finally we administered the test to two cohorts (238 and 140 students) in the first and third semester of the biology curriculum. For the purpose of validity and reliability arguments for the FPCI we created item response curves and calculated the difficulty and discrimination index as well the binomial distribution for every single answer (Ding & Beichner 2009. An example for this analysis for the question in Figure 4 is shown in Figure 5. We are currently working on improvements of the items where needed and preparing for the next cohorts of first, third and fifth semester students in order to compare their results to previous cohorts and measure the change in performances. Also we are working on the publication of the First Principle Concept Inventory.
Figure 5. Example of an item validation. Item response curves for every possible answer are shown in the graph on the left, difficulty, discrimination and binomial distribution are shown in the table on the right.
Publications
Känzig, C.D. (2020). An Interdisciplinary Approach to Addressing Naïve Conceptions in Life Science Education. Annual Conference of the Junior Researchers of the European Association for Research on Learning and Instruction (EARLI), Porto, Portugal (Conference cancelled) https://dl.acm.org/doi/abs/10.1145/3410404.3414260
To go further
If you are interested in Biology Education, you can also take a look at this project:
Improving conceptual understanding in biology through storytelling (link)
References
[Adams & Wieman 2011] Adams, W. K., & Wieman, C. E. (2011). Development and validation of instruments to measure learning of expert‐like thinking. International Journal of Science Education, 33(9), 1289-1312.
[Ding & Beichner 2009] Ding, L., & Beichner, R. (2009). Approaches to data analysis of multiple-choice questions. Physical Review Special Topics-Physics Education Research, 5(2), 020103.
[Klymkowsky et al. 2010] Klymkowsky, M. W., Underwood, S. M., & Garvin-Doxas, R. K. (2010). Biological Concepts Instrument (BCI): A diagnostic tool for revealing student thinking. arXiv preprint arXiv:1012.4501.
[Perkins & Salomon 1992] Perkins, D. N., & Salomon, G. (1992). Transfer of learning. International encyclopedia of education, 2, 6452-6457.
[Queloz et al. 2016] Queloz, A. C., Klymkowsky, M. W., Stern, E., Hafen, E., & Köhler, K. (2016). Debunking Key and Lock Biology: Exploring the prevalence and persistence of students’ misconceptions on the nature and flexibility of molecular interactions. Matters Select, 2(8), e201606000010.
[Queloz et al. 2017] Queloz, A. C., Klymkowsky, M. W., Stern, E., Hafen, E., & Köhler, K. (2017). Diagnostic of students’ misconceptions using the Biological Concepts Instrument (BCI): A method for conducting an educational needs assessment. PloS one, 12(5), e0176906.
Carina Känzig
Dr. Katja Köhler
Prof. Dr. Ernst Hafen
