One of the aims of contemporary education is to enable individuals to understand that society and science are mutually influenced by each other. The concept of Socio-Scientific Issues (SSI) is scientifically based controversial dilemmas such as biology, sociology, ethics, politics, economy and environment that concern the society. The process of dealing with SBK requires students to make sound decisions and schools to train knowledgeable individuals. In SSI education, students' ability to think critically, associating subjects with daily life and raising individuals as individuals who can cope with these issues come to the fore.

The purpose of the argument is to convince oneself and other participants of the peculiarity of one's own reasoning (Krummheuer, 1995). Reasoning occurs interactively during mathematical modeling processes (Lesh, Doerr & Carmona, 2003). Thus, argumentation, defined as interactions in the observed class, relates to deliberate disclosure of a solution's reasoning, during or after the development of a solution. It can be a trigger for the modeling processes of the participants. In this context, this study examines the arguments created by the participants in the mathematical modeling cycle and interprets these arguments by taking into account the participants' modeling processes. In the broadest sense, cognitive argumentation is defined as an argumentation, justification process in which more than one person (student or teacher) has a mathematical claim and presents evidence to support this claim (Conner, et. al., 2014).

The cognitive argumentation considered in this study considers the arguments of small groups or individuals working on different learning and teaching activities (Conner et. al., 2014; Yackel) rather than examining participants' arguments during proving activities (Inglis, Mejia-Ramos & Simpson, 2007). & Cobb, 1996). The focus is on the interactional aspect of argumentation. To investigate cognitive arguments, Krummheuer (1995) proposes the Toulmin argumentation scheme.

When students engage with modeling tasks, transitions between school mathematics and the real world, their cognitive reasoning in a real-world context can be supported during model development. By doing this, they try to reach consensus through their reasoning by discussing the claims put forward by the group members. In this process, they actively formulate and justify arguments. Therefore, since it is believed that the arguments created in the modeling cycle are based on the modeling processes, it is possible that the examination of the modeling processes will give an idea about the arguments of the students. The mathematical modeling cycle (Blum & Niss, 1991) was chosen as the research framework because it clearly explains the modeling processes that occur during the modeling cycle based on the modeling definition. This study will reveal the arguments in the mathematical modeling cycle by taking into account the modeling processes based on SSI issues.

Considering the focus of mathematical modeling, it is seen that this study has a different context from other cognitive modeling studies due to its argumentative nature. On the other hand, if the focus is on Cognitive Argument, the study is again different from previous literature examining student arguments during proving and learning/teaching activities due to its emphasis on modelling. Working to uncover the arguments in the modeling cycle will ultimately enable to identify the particular aspects that make in-group arguments meaningful, such as how they formulate the claims, how they refute each other's claims to reach the best common solution, what they warrant, what claims they make use of, and how they arrive at a solution.

The aim of the study was to explore how teacher candidates engage use their models whilst arguing about contextual of the COVID-19 a socioscientific issue and to explore whether and how the process of arguing is linked with the modelling process.

This is an exploratory study of how teacher candidates engage in the practices of argumentation and modelling and how one practice can support or constrain the other. More specifically, the research questions guiding this study are as follows: (a) The pre-service teachers were given a task belonging to the context at the center of their lives. This context is a mathematical modeling activity related to the COVID-19 pandemic. After reading the task, pre-service teachers were expected to first produce two questions about the COVID-19 epidemic and the virus that caused it. (b) In the second stage, they were asked to explain why they produced these questions and asked them with a purpose. The aim here is to enable them to determine their arguments on COVID-19 through the questions they produce. (c) In the third stage, the routine procedure of how to diagnose a person with coronavirus is explained. Then, the data of a patient who came to the hospital was shared with them and they were asked to explain statistically whether that person had COVID-19, based on a mathematical model. Since we seek to explore whether and how the process of arguing about the phenomenon is intertwined with the modelling process, a learning environment was designed to enable the teacher candidates to participate in the scientific practices of argumentation and modelling. The learning environment was designed based on project based learning (Krajcik et al., 1998), sociocultural theories of learning (Rogoff, 2003) and what we already know regarding how teacher candidates construct and use models (Louca & Zacharia, 2011) in contextual enviroment of SSI. Based on our theoretical framework, modelling refers to constructing and using statical models to understand a phenomenon and explain or predict possible changes (Windschitl et al., 2008). The study was carried out with 112 third grade teacher candidates who took the Critical and Analytical Thinking course. Modeling processes are integrated into the course contents. Local SSIs were presented to the pre-service teachers as a problem situation in the lessons, and they were asked to perform problem solving processes by using argumentation and modeling. The case scenario with SBK content developed by the researchers was discussed with the students during a 2-week (40x4 min) lesson. Students were asked to express their arguments in writing. Mathematical modeling and Toulmin's argumentation model were used in the analysis of the obtained data.

Participants tried to determine whether the person who came to the hospital had COVID-19 by using PCR test results and other information about the person. They tried to make a claim based on the available data. To arrive at this claim, they used the information and statistical data contained in the task paper to develop the argument. They also ignored the claim that a person was 100% COVID, even if the PCR test was positive, as refuting. They did not feel the need to justify this sub-argument as they made a claim based on direct data. When the above-mentioned solution is considered in terms of the mathematical modeling process, the statistical information given in the task has become the real models used by the participants. Based on the real-life experiences of the participants and the concrete data they used, they assumed that the probability of a person with a positive PCR test to be COVID should be supported with other data, and they focused on building the mathematical model of the task based on these real models and made some calculations. They were able to construct sub-argument schemes in which the drawing of a mathematical model based on their assumptions became the assertion. According to the results of the preliminary analysis, the focus of this study is the arguments of the participants, as the study examines the arguments generated within the modeling cycle. In this context, different sub-arguments of the participants emerged throughout the modeling cycle. The first important result of the study is that most sub-arguments are combined with data assertions. This is in line with studies that have found that the sub-arguments are linked to the data claim (Krummheuer, 1995; Conner et. al., 2014).

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