10 SSR September 2015, 97(358)

Teaching Mendelian genetics with a virtual Drosophila laboratory

Mustafa Çakır and Özgür Kıvılcan Dogan

Mendelian genetics is one of the most complex and difficult topics to understand in secondary science classrooms. Researchers have been examining misconceptions in genetics for decades (Baxter and Amory, 2004; Karagoz and Cakir, 2011; Stewart and Dale, 1989). The use of traditional lecturing styles has been shown to spread some of these misconceptions about high school genetics, which is already complicated (Barras, 1984; Cakır and Aldemir, 2011). In contrast to traditional teaching, well-designed inquiry-based classrooms provide learning environments where students collect data, analyse and interpret them and also discuss their arguments with their peers.

Science educators have reported that translating inquiry-based teaching into classroom practice is a very challenging task for science teachers (Cakir, 2011). There is much in the literature discussing the value of inquiry instruction coupled with interactive visualisations, virtual laboratories and hypothesis testing (Baxter and Amory, 2004; Windschitl and Andre, 1998). Inquiry-based teaching, as the term is used in this article, implies that students participate in investigations that require them to develop questions and hypotheses, collect data, analyse data, and draw and test conclusions. In addition to the basic abilities of conducting a scientific investigation, inquiry learning should include an understanding of how scientists do their work (NRC, 2000).

Recently, web-based resources that are integrated with inquiry-driven strategies have become operational science teaching tools. The aim of this study was to implement virtual courseware into inquiry-based genetics teaching

in order to achieve meaningful understanding and conceptual learning. Therefore, the research questions of this study were the following:l Are there any conceptual Mendelian genetics

learning differences between high school students who receive inquiry-based virtual laboratory instruction and those who receive traditional lecturing;

l Does inquiry-based virtual laboratory instruction have any positive effects on students’ attitudes towards biology?

Theoretical framework and the softwareA constructivist approach to computer-mediated learning environments has the potential to provide learners with the opportunity to create, test and evaluate their own hypotheses freely in a richly contextualised environment (Windschitl and Andre, 1998). A virtual laboratory enables teachers and students to collaboratively experience inquiry-based problem solving, construct knowledge and engage in modelling as a part of science learning (Penner, 2001). In today’s classrooms, information and communication technology has become an indispensable part of education. Zandvliet (2002) indicated that successful use of technology such as computer simulations means involving students and teachers in the learning process together. It is clear that implementing information and communication technologies in science classrooms does not guarantee effective learning; however, together with carefully planned structured or semi-structured inquiry investigations, such tools can enable teachers to prepare suitable environments to foster engaging collaborative learning.

Science notes10 Teaching Mendelian genetics with a virtual Drosophila laboratory Mustafa Çakır and Özgür

Kıvılcan Dogan15 Are chemicals good for you? Randal Henly16 What kind of oil are we running out of? What do young people think of when we talk

about oil in the classroom? Phil Murphy17 Do you have a smoke alarm? Randal Henly17 The strange behaviour of carbon dioxide in latex balloons Alan Goodwin22 Using corrugated boards to introduce the concept of ‘turning effect of forces’ to less

academically inclined students Nazir Amir

SSR September 2015, 97(358) 11

Integration of inquiry-based teaching strategies with computer simulations, such as the Drosophila virtual lab described in this article, creates opportunities for students to learn not only required content knowledge but also to gain science process skills.

Drosophila (sciencecourseware.org/vcise/drosophila) is an interactive, web-based simulation that was developed by the Virtual Courseware for Inquiry-based Science Education (VCISE) project (www.sciencecourseware.com/vcise) at the California State University (Desharnais and Limson, 2007) and is designed to improve traditional high school biology curricula by providing supplements to experimental laboratory work.

So, what is inquiry-based teaching and what is the relationship between inquiry-based teaching and the Drosophila virtual lab? According to Furtak (2006), an inquiry-based teaching strategy has four dimensions:l methodological;l conceptual;l epistemological;l social.

The methodological dimension of the classroom has to do with imitating the scientific inquiry process by involving students in a process where they design experiments (Figure 1), generate questions and hypotheses (Figure 2), analyse data

and then interpret the findings. It is unquestionable that providing a proper environment for students to develop such methodological skills is an essential part of inquiry-based classrooms (Furtak, 2006). The Drosophila software allows all students to participate and to research processes as scientists. For example, students can generate various traits in flies and explore those traits by mating specific flies. Drosophila generates genetically valid offspring. Then, students can hypothesise about gene or allele interactions or inheritance models of a trait. Drosophila also provides a scaffold to allow students to run chi-squared analyses, empowering them to test their initial hypotheses by comparing observed results with expected results. The result of the analysis is interpreted, so students do not need special statistical knowledge to use the test.

The conceptual dimension of inquiry is related to the methodological dimension, and they interact with each other (Furtak, 2006). The conceptual dimension is about the students’ content knowledge. Basically, when students try to produce an explanation for a natural event, they need to have not only sufficient content or theoretical knowledge about the event (Posner et al., 1982) but also knowledge about methods and procedures of inquiry in that specific context.

After analysing their results, students can record all their actions, including calculations,

in the software’s electronic notebook (Figure 3). Students and their teachers are able to share all processes and feedback.

The Social dimension of the software provides students with an effective learning environment. Constructing knowledge in a social environment is one of the main ideas in contemporary inquiry-based classrooms.

The epistemological dimension of inquiry is especially significant as it relates to the general purpose of science education (Hogan and Maglienti, 2001). The epistemic beliefs of Figure 1 The web-based Drosophila software main page

Science notes

12 SSR September 2015, 97(358)

scientists and students play a central role in the whole inquiry process. Beliefs with regard to ‘What is science?’, ‘How does science work?’, ‘What is the nature of scientific knowledge?’, ‘Who are these people we call scientists?’ and ‘What is the role of empirical evidence in science?’ are some of the aspects that have been investigated by science educators. Engaging students in an

inquiry process enables them to construct and/or to reflect on their beliefs about science (Puvirajah, 2007). When students actively engage with this software, they implicitly rely on these questions and act as scientists.

Design and methodThe participants in this study were 120 students

from four 10th grade (age 15–16) classes in an urban high school in Istanbul. Each class consisted of 30 students. Two classes were randomly chosen as an experimental group. All four classes completed 8 hours of the Mendelian Genetics unit. The experimental group received inquiry-based Mendelian Genetics instruction with the Drosophila lab (VCISE) simulation, whereas the control group did not receive any special treatment and continued with traditional teaching practices using the textbook and the activities it contained. The unit was completed in a semester of instruction.

All tests and questionnaires were conducted with all participants. Students were assessed using pre- and post-tests. The students’ understanding before and after instruction was measured with a Mendelian Genetics Conceptual Test that had been developed by the researchers. Additionally, the participants were given another paper-and-pencil test on their understanding

Figure 2 Students can examine their own hypotheses

Figure 3 Students can record all their actions in the electronic notebook

Science notes

SSR September 2015, 97(358) 13

of genetics concepts (the achievement test) for grading purposes.

An attitude questionnaire was also used to measure the students’ attitudes towards biology at the end of the unit. The questionnaire consisted of 12 statements, each with a Likert scale from 1 to 5, where a higher number would correspond to a higher level of agreement with that particular statement. Negative statements were recoded before scoring the questionnaires. Each student’s attitude score was the average of their 12 answers. An average of attitude scores for each group was calculated and used in statistical analyses.

A statistical software package was used to conduct independent sample t-tests to determine whether there was a significant difference between the experimental and control groups’ mean scores. A Pearson correlation test was also conducted to assess the consistency between the post-test and the achievement test scores.

ResultsTable 1 shows the statistical analysis of the pre-test scores. There was no statistically significant difference between the pre-test scores of the experimental and the control groups (P = 0.087; P > 0.05). In other words, the students in the experimental and control groups had similar knowledge before the intervention. The mean scores of the groups were 46.3 for the experimental group and 41.2 for the control group.

The argument that guided this study was that virtual labs are important tools for conceptual learning. A statistically significant difference was found between the post-test scores (Table 2) of the

experimental and the control groups (P = 0.000; P < 0.05). The mean score of students who received traditional lecturing increased by about 8 points from 41.2 before the intervention to 49.4 after the intervention. However, the mean score of the experimental group increased by about 31 points from 46.3 to 77.2.

The additional academic achievement test was administered to all groups for testing the post-test results. As shown in Table 3, there was a statistically significant difference between the means of the achievement test scores of the experimental and the control groups (P = 0.000; P < 0.05).

As can be seen in Table 4, the post-test and achievement test scores were highly correlated (r = 0.80; P < 0.05). The positive and strong correlation between the simultaneously administered post-test and achievement test scores supports the reliability of our findings.

An attitude questionnaire was used after the intervention to determine how the students had reacted to the two different biology teaching styles. As can be seen in Table 5, there was a statistically significant difference between the mean attitude scores of the experimental and the control group students (P = 0.000; P < 0.05), with the experimental group having a more positive attitude (3.18) than the control group (2.75).

ConclusionStructuring scientific inquiry as an investigation to develop explanations provides meaningful context for promoting understanding of science content. This research has shown that hypothesis

Table 1 Results of the independent sample t-test for the pre-test scores

Group N Mean Standard deviation Degrees of freedom t PExperimental 60 46.3 17.8 118 1.73 0.087Control 60 41.2 13.9

Table 2 Results of the independent sample t-test for the post-test scores

Group N Mean Standard deviation Degrees of freedom t PExperimental 60 77.2 13.3 118 11.27 0.000Control 60 49.4 13.7

Table 3 Results of the independent sample t-test for the achievement test scores

Group N Mean Standard deviation Degrees of freedom t PExperimental 60 79.1 12.2 118 9.17 0.000Control 60 56.1 15.1

Science notes

14 SSR September 2015, 97(358)

testing can support the integrated acquisition of conceptual knowledge in science. The students’ conceptual elaborations of Mendelian inheritance were enhanced. Inquiry-based learning experiences with the virtual Drosophila courseware not only facilitated conceptual genetics learning but also provided an excellent opportunity for students to develop inquiry abilities such as hypothesis testing and experimental design. Our findings support the research of White et al. (2007). It was concluded that an inquiry-based teaching method with the Drosophila simulation is feasible and beneficial, and has the potential to support conceptual learning of the principles of inheritance. Similar to the findings of Tüysüz (2010), the current research showed that students’ motivation and interest in the biology class increased after they engaged with the virtual biology laboratory. The Drosophila

software also has ‘notebooks’ where students can make notes about their hypothesis and inquiry. However, analysis revealed that the students barely used these notes to reflect on their own learning process. They rather haphazardly followed the instructions and did not really engage cognitively in the process. Since interpreting results of their own experiments would serve as an instructional scaffold in students’ conceptual development, the importance of systematic note taking and data recording during an inquiry process should repeatedly be emphasised. Such an approach would encourage students to use the notebook feature of Drosophila.

Acknowledgement

This study was supported by a grant (EGT-D-050614–0255) from Scientific Research Projects Center of Marmara University.

ReferencesBarras, R. (1984) Some misconceptions and

misunderstandings perpetuated by teachers and textbooks of biology. Journal of Biological Education, 18, 201–206.

Baxter, D. and Amory, A. (2004) Development of a 3D virtual learning environment to address misconceptions in genetics. In World Conference on Educational Multimedia, Hypermedia and Telecommunications, Vol. 2004, No. 1, pp. 1256–1263.

Cakir, M. (2011) Enhancing Mendelian genetics concepts using a guided computer-mediated inquiry. Journal of Baltic Science Education, 10(3), 156–167.

Cakır, M. and Aldemir. B. (2011) İki Aşamalı Genetik Kavramlar Tanı Testi Geliştirme ve Geçerlik Çalışması. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 16(8), 335–353.

Desharnais, R. A. and Limson, M. (2007) Designing and implementing virtual courseware to promote inquiry-based learning. Journal of Online Learning and Teaching, 3(1), 30–39.

Furtak, E. M. (2006) The Dilemma of Guidance in Scientific Inquiry Teaching. Unpublished doctoral dissertation. Stanford, CA: Stanford University.

Hogan, K. and Maglienti, M. (2001) Comparing the epistemological underpinnings of students’ and scientists’ reasoning about conclusions. Journal of Research in Science Teaching, 38(6), 663–687.

Karagoz, M. and Cakir, M. (2011) Problem solving in genetics: conceptual and procedural difficulties. Educational Sciences: Theory and Practice, 11(3), 1668–1674.

National Research Council (NRC) (2000) Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. Washington, DC: National Academy Press.

Penner, D. (2001) Cognition, computers, and synthetic science: building knowledge and meaning through modeling. In Review of Research in Education, ed. Secada, W. pp. 1–35. Washington, DC: American Educational Research Association.

Table 5 Results of the independent sample t-test for attitude towards biology

Group N Mean Standard deviation Degrees of freedom t PExperimental 60 3.18 0.31 118 6.61 0.000Control 60 2.75 0.39

Table 4 Results of the Pearson correlation between post-test and achievement test scores

Post-test Achievement testPost-test Pearson correlation 1.000 0.796*

P (2-tailed) 0.000N 120 120

Achievement test Pearson correlation 0.796* 1.000P (2-tailed) 0.000N 120 120

* Correlation is significant at the 0.01 level (2-tailed).

Science notes

SSR September 2015, 97(358) 15

Posner, G. J., Strike, K. A., Hewson, P. W. and Gertzog, W. A. (1982) Accommodation of a scientific conception: toward a theory of conceptual change. Science Education, 66(2), 211–227.

Puvirajah, A. (2007) Exploring the Quality and Credibility of Students’ Argumentation: Teacher Facilitated Technology Embedded Scientific Inquiry. Unpublished doctoral dissertation. Detroit, MI: Wayne State University.

Stewart, J. and Dale, M. (1989) High school students’ understanding of chromosome/gene behavior during meiosis. Science Education, 73(4), 501–521.

Tüysüz, C. (2010) The effect of the virtual laboratory on students’ achievement and attitude in chemistry. International Online Journal of Educational Sciences, 2(1), 37–53.

Available at: www.iojes.net/userfiles/article/iojes_167.pdf.White, B., Bolker, E., Koolar, N., Ma, W., Maw, N. N. and

Yu, C. Y. (2007) The Virtual Genetics Lab: a freely-available open-source genetics simulation. The American Biology Teacher, 69(1), 29–32.

Windschitl, M. and Andre, T. (1998) Using computer simulations to enhance conceptual change: the roles of constructivist instruction and student epistemological beliefs. Journal of Research in Science Teaching, 35(2), 145–160.

Zandvliet, D. B. (2002) Learning environments in technology-rich classrooms. In Studies in Educational Learning Environments, ed. Goh, S. C. and Kahle, J. B. pp. 49–72. Singapore: World Scientific Publishing.

Mustafa Çakır is an associate professor of biology education at the Department of Secondary Science and Mathematics Education, Atatürk Faculty of Education, Marmara University, Istanbul, Turkey. Email: mustafacakir@marmara.edu.tr Özgür Kıvılcan Dogan is a research assistant at the Department of Secondary Science and Mathematics Education, Atatürk Faculty of Education, Marmara University, Istanbul, Turkey. Email: odogan@marmara.edu.tr

Are chemicals good for you?

Randal Henly

One of the tasks that came my way when I retired from full-time teaching was to become a supervisor of student teachers for the University of Limerick. This involves sitting at the back of classrooms when the students are let loose on teaching practice in schools. At the end of one class during the last year, the student teacher said to her pupils ‘Next day you’ll be in the lab and you’ll be using chemicals so you’ll have to be extra careful.’ Obviously, like so many journalists, she hadn’t a clue what the word ‘chemicals’ means. When we had a talk after the class was over, I said to her: ‘Didn’t the children in the class all use chemicals today? What about the soap they (hopefully) had washed with? What about the salt put on an egg or in a sandwich, or the sugar in the tea, or the medical tablet taken for some reason or other? Look at the ingredients on a tube of toothpaste – you’ll find a dozen chemicals there.’ I think she got the message.

There are, of course, ‘bad’ chemicals as well as ‘good’ ones, and the media is largely to blame for the public misconception of ‘chemicals’ by giving the name ‘chemicals’ only to the bad ones; the good chemicals are usually termed something else!

There was a very good article about this issue a while ago in Chemistry World by Professor Hal Sosabowski (2011) of the University of Brighton. He started by quoting from an article in a recent

issue of the Daily Telegraph newspaper: ‘Ozone can now be used to preserve food without the use of chemicals.’ He wondered whether the newpaper reporting on the harmful effects of ozone would then call it a ‘chemical’. He mentioned the reported benefits of organic food, the benefit of which appears to be that it is produced without the use of ‘chemicals’. What is the manure or compost used if it isn’t chemical?

The public’s fear is not one of science; it is one of language. To a scientist, a ‘chemical’ is any substance or material (of course, most everyday substances are mixtures of chemicals) but to many (most?) of the public, it is a substance that has the potential to harm, pollute or destroy, and too often they associate the word with all that is unwholesome and unhealthy. This perception is, of course, completely false, and the public (particularly journalists) need to be educated as to what chemicals are. Science teachers (not just chemistry teachers) can make the start at school (in fact, it might be regarded as their duty) by ensuring that all their pupils understand this word ‘chemicals’.

When I present my demonstration show Fun with Science, I make a point of using the word ‘chemical’ for everyday substances such as salt (sodium chloride), bread soda (sodium bicarbonate), aspirin (acetylsalicylic acid) and washing up liquid

Science notes