30 SES 08 B, Environmental Citizenship
General description on research questions, objectives, and theoretical framework
Citizen science (CS) projects are scientific endeavors that engage the public in collecting and/or processing data (Philips et al., 2018). CS has been recognized as a valid European science knowledge producer (European Commission, 2019). While contribution to the scientific project, CS participants often enhance their knowledge, cognitive and affective skills (Philips et al., 2018). Because of its dual emphasis on research and education, CS is sometimes categorized as a form of informal science learning (Bonney et al., 2009). Recently CS is also integrated into school educational systems. CS has the potential to make scientific content more tangible involving students in hands-on, active learning. Student engagement in CS can make STEM learning more meaningful. (Jenkins, 2011; Sagy et al., 2019). Such integration can enhance students’ interest in science and learning relevant (Kelemen-Finan et al., 2018). As many CS projects focus on ecological and environmental research, participating in such projects can achieve environmental education outcomes as well (Dickinson et al., 2012). In schools, it may provide opportunities to convergence environmental with science education through meaningful learning experience while being engaged in local environmental projects. (Wals, et al., 2014). Furthermore, active engagement in local ecological issues can foster community-based decision making and environmental stewardship capabilities, which are some of the main goals of education for sustainable development. TCSS (taking citizen science to school) center in Israel, acknowledges these potential benefits and promotes the integration of CS in schools. For this purpose, TCSS fosters a network of research-practice partnerships with diverse stakeholders such as educational practitioners, policy makers and representatives of ecological and environmental NGOs (Hod, Sagy, Kali & TCSS, 2019). TCSS envisions a “Mutualistic Ecology of Citizen Science” (MECS) in which all parties benefit from their involvement (Sagy et al. (2019). Thus, in addition to network-wide gatherings that invite interactions between diverse stakeholders, and knowledge sharing through the innovative insights platform, TCSS members develop learning materials and support teachers who integrate CS in their teaching (Sagy et. al., 2020). One of the challenges for integration CS in teaching, especially for teachers with standards-driven curriculum, is that it’s not part of the formal curriculum (Jenkis, 2011). Another challenge relates to students’ limited experience in data collection and analysis, and other scientific activities required throughout the process (Shaha & Martinez, 2016). Understanding teachers' views, their motivation to integrate CS, and the challenges they confront is therefore essential for developing productive ways for integrating CS in schools.
We present here initial findings of a study that explores the perceptions of teachers who chose to integrate ecological CS projects in their classes. More specifically, we aim to investigate how teachers understand the concept of CS and its contribution to students’ learning. A second objective is to understand their motivations for integrating CS and how it fits their own professional goals. Finally, we aim to study how teachers perceive the organizational and professional context in which they work, and how it promoted or inhibited their educational initiatives.
The theoretical frameworks used to understand and analyze teachers' perceptions and motivation are (1) teacher achievement goals theory, which focuses on inter-personal sources for teaching motivation, and how it is affected by external contexts such as time constrains and professional pressures. (Butler, 2014), and (2) MECS which focuses on mutual relationships between various stakeholders as means for effective integration of CS to schools (Atias et. al., 2020; Sagy et al., 2019).
Method To understand teachers' perceptions on integrating CS in their classes, we employ a phenomenography approach for data collection and analysis as it enables describing the different ways a group of people understand and experience a phenomenon (Marton, 1981). The data collection method we use is semi-structured interviews. Data Collection. Twenty semi-structured interviews with teachers who integrated ecological CS into their teaching were conducted. Teachers were recruited by either a direct request from members of the TCSS community, or by a request delivered through the Israeli biology teachers' network. All interviewees integrated ecological CS projects in their teaching. Projects varied from bee's distribution to birds monitoring or identifying mammals' tracks. Teachers were interviewed through zoom meetings that were recorded and transcribed and lasted 45-60 minutes. The interview questions focused on teachers' perceptions of CS and its contribution to students, their motivation to integrate CS in teaching, and the ways contextual factors affected this integration. Examples of semi-structured interview questions include: (1) how do you define CS? (2) In what ways do you think that participating in CS contributes to your students learning (3) In what ways teaching science through CS is in line with your own professional goals? Data Analysis. Data was analyzed, so far, in three phases of coding following grounded theory (Charmaz, 2006) and phenomenography (Larson & Holmström, 2007) analyses protocols. In the first phase transcripts of three interviews were analyzed by two of the researchers to develop initial conceptualization of the main themes. After further discussion and debate an initial set of categories was agreed upon. Two levels of categories were identified: "pure" general categories which were not directed at identifying variations between individuals (e.g. description of advantages to students), and a set of specific sub-categories related to each general category (e.g. understanding of how scientific research is developed or the development of social and cognitive capabilities). The third phase was an analysis of the whole dataset based on to the initial set of categories. During this phase we identified several new sub-categories. In the last phase of the analysis, we searched for internal relations between the categories, and defined the structural relations between them (Larson & Holmstrom, 2007).
Teachers characteristics. Seventeen of the interviewees were science teachers. Eleven taught in elementary schools, and the rest in secondary schools. Teachers integrated ecological CS projects either as part of science lessons, or as environmental project (not related to science lessons). In many cases they participated in more than one project. These variations implie on the various ways CS can be integrated in schools. Teachers' goals: A major sub-category regarding student-development-goals was affective: teachers wanted their students to be motivated, interested and curios in their learning. They were less concerned about students' grades. In a similar way teachers' goals regarding their own professional development also focused on interest in their work and on professional development as a continuous process. Perception of CS contribution to students. The interviewees perceived various ways by which CS contributed to their students’ learning and development. Sub-categories of contribution to students included: personal development, development of citizenship understanding and capabilities, awareness to environmental issues, and various competencies. In addition, the interviewees perceived CS as an excellent way of teaching science, in an authentic, hand-on, and active way, that familiarize students with real scientific projects. Challenges. We were surprised that the main challenge described by interviewees was not related to external pressures, and overload, but rather, to students' low levels of previous knowledge and experience in monitoring and analyzing data (aligned with Shaha & Martinez, 2016), and with affective aspects of students' participation. The findings highlight the potential of ecological CS projects to convergence environmental with science education through meaningful learning experience while being engaged in local environmental projects, as suggested by Wals, et al., 2014, and to promote environmental learning objectives such as environmental awareness and civic involvement, along with science literacy.
Atias, O., et.al., (2020). “Sometimes you’re not wrong, you’re just not right”. Chais Conference for the Study of Innovation and Learning Technologies. Ra’anana, Israel. Bonney, R., et.al., (2009). Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. A CAISE Inquiry Group Report.Online Submission. Butler, R. (2014). What teachers want to achieve and why it matters: an achievement goal approach to teacher motivation. In Richardson, P. W., et al., (Eds.), Teacher Motivation: Theory and Practice. New York: Rutledge. Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. sage. London, Great Britain Dickinson, J. L., et.al., (2012). The current state of citizen science as a tool for ecological research and public engagement. Frontiers in Ecology and the Environment, 10(6),291-297. European Commission (2019). Open Science. Retrieved on January 2021 from: https://ec.europa.eu/info/sites/info/files/research_and_innovation/knowledge_publications_tools_and_data/documents/ec_rtd_factsheet-open-science_2019.pdf Hod, Y., et.al., (2019). The opportunities of networks of research-practice partnerships and why CSCL should not give up on large-scale educational change. International Journal of Computer-Supported Collaborative Learning, 13(4), 457–466 Jenkins, L.L. (2011). Using citizen science beyond teaching science content: A strategy for making science relevant to students’ lives. Cultural Studies of Science Education, 6(2),501-508. Larsson, J.,&Holmström, I. (2007). Phenomenographic or phenomenological analysis: Does it matter? Examples from a study on anaesthesiologists’ work. International Journal of Qualitative Studies on Health and Well-being, 2(1),55-64. Marton, F. (1981). Phenomenography—describing conceptions of the world around us. Instructional science, 10(2), 177-200. Kelemen-Finan, J., et.al., (2018). Contributions from citizen science to science education: an examination of a biodiversity citizen science project with schools in Central Europe. International Journal of Science Education,40(17), 2078-2098. Phillips, T., et.al., (2018). A framework for articulating and measuring individual learning outcomes from participation in citizen science. Citizen Science: Theory and Practice,3(2). Sagy, O., et.al., (2019). Citizen science: An opportunity for learning in a networked society. In Y. Kali, et.al., (Eds.), Learning in a networked society: Spontaneous and designed technology enhanced learning communities (pp. 97-115). Springer, Cham. Sagy, O., et.al., (2020). Taking Citizen Science to School: A mutualistic ecology of science learning, presented at the European conference for citizen and participatory science 2020 in Trieste, Italy. Shah, H. R.,&Martinez, L. R. (2016). Current approaches in implementing citizen science in the classroom. Journal of microbiology & biology education, 17(1),17. Wals, A. E., et.al., (2014). Convergence between science and environmental education. Science,344(6184),583-584.
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