Scientific literacy extends far beyond the mere memorization of facts and formulas. It encompasses an understanding of the scientific process and its practical application in daily life. This capability empowers individuals to make informed decisions, critically evaluate information, and actively participate in discussions on environmental, economic, and societal issues. Furthermore, scientific literacy involves a comprehension of systems—a crucial skill for addressing the intricate environmental, social, and economic challenges of contemporary life.

Science education plays a pivotal role in fostering the higher-order thinking skills necessary for solving complex problems. Among these skills, systems thinking provides a valuable framework for understanding and addressing multifaceted systems by examining underlying structures, feedback loops, and dynamics (Richmond, 1994). This approach is particularly significant for tackling global challenges such as water scarcity and biodiversity loss (Arnold et al., 2021). By promoting systems thinking, science education enables learners to grasp the interconnectedness of various systems, ultimately fostering a sustainable perspective (Karaarslan Semiz & Teksöz, 2023). In light of the growing emphasis on understanding complex systems, contemporary science education increasingly highlights topics like systems thinking and students’ comprehension of intricate phenomena (Budak & Ceyhan, 2024; Elmas et al., 2021; Feriver, 2021; Uskola & Puig, 2022).

The present study investigates students’ understanding and their systems thinking skills (STSs) within the context of the water cycle. STSs include the ability to identify system components, comprehend relationships between them, and discern the causal patterns governing the system’s behavior (Khajeloo & Siegele, 2022; Meadows, 2008). Conceptual understanding, on the other hand, refers to a deep grasp of scientific concepts (Duit & Treagust, 2003), while misconceptions are ideas that deviate from scientifically accepted knowledge (Schaffer, 2013). Previous research has examined students’ STSs across various contexts, including sustainability (Karaarslan, 2016; Öztaş, 2018), energy (Can, 2020), and the carbon cycle (Turan, 2019). While commonly studied STSs focus on identifying components and their relationships, fewer studies have delved into causal patterns (Khajeloo & Siegele, 2020; Grotzer, 2012).

This study uniquely contributes to the literature by exploring diverse causal patterns within the water cycle using a single tool. Moreover, there is a scarcity of research examining pre-service teachers’ conceptual understanding and STSs together. Given the increasing prevalence of water-related challenges such as scarcity and environmental degradation, fostering a holistic perspective on the water cycle is essential. Understanding the cycle’s components and relationships while addressing misconceptions can significantly aid in addressing these pressing issues.

Given the critical role of pre-service science teachers in shaping future generations, their STSs and conceptual understanding of the water cycle hold importance. ,

The study is guided by the following research questions:

1. What are PSTs’ causal patterns regarding the water cycle as an indication of their STSs?

2. What is PSTs’ conceptual understanding of the water cycle?
   2.1. What are PSTs’ misconceptions about the water cycle?

3. Is there a relationship between PSTs’ STSs and their conceptual understanding of the water cycle?

By addressing these questions, the study aims to provide valuable insights for educators, stakeholders, policymakers, and researchers regarding the current state of pre-service teachers’ knowledge and skills. The findings can inform revisions to educational materials across various levels, ensuring a deeper understanding of the water cycle and better equipping pre-service teachers to fulfill their influential roles in education.

The design of the study was a correlational study. A convenience sampling method was used. The accessible population consisted of approximately 420 pre-service science teachers enrolled in science education programs, of which data was collected from 254 PSTs, representing about 60% of the accessible population. Two instruments were used for data collection: The Water Cycle Concept Map (WCCM) and The Water Cycle Diagnostic Test (WCDT). WCCM was designed to evaluate PSTs’’ STSs within the context of the water cycle. Concept maps were utilized to reveal participants’ mental models. Considering the cognitive challenges of constructing a concept map from scratch (Tripto et al., 2018), PSTs were provided with predetermined concepts to facilitate the process. To determine the predetermined concept and their number, the researcher reviewed literature on concept map development and the water cycle, ultimately identifying 20 concepts. These concepts were validated through the opinions of three science education experts. Providing concepts reduces participants’ cognitive load (Grotzer et al., 2017), allowing them to focus on causal patterns which are domino, cyclic, mutual and relational causality. Participants demonstrating a greater ability to create diverse causal patterns on their maps were considered to have higher levels of STSs (Khajeloo & Siegel, 2022). To ensure validity, the WCCM was reviewed for content, construction, and face validity by three experts. Reliability was addressed using intrarater and interrater reliability measures. MAXQDA and Excel were used for the analysis. The second instrument was the WCDT, a three-tier diagnostic test developed by Schaffer (2013), was used to assess participants’ conceptual understanding of the water cycle. It comprised 15 questions, with each question featuring three tiers: content, reason, and confidence. The test was also analyzed to identify misconceptions, considering all responses across its three tiers. SPSS and Excel were used for the analysis. The reliability value of WCDT in the current study was .754. To answer first research question WCCM results considered, second research question WCDT results considered, and third research question WCCM score and WCDT scores correlated. Participants completed the instruments in their classroom environment in around 40-50 minutes. Data collection took around one month. Before data collection, participants were informed about the purpose of the research and the instruments being used. Additionally, to enhance their understanding and familiarity with the concept map as a data collection tool, students were informed about concept maps.

The analysis WCCM scores revealed that PSTs mostly included only one or two causal patterns in their concept maps. Majority of the PSTs performed domino and cyclic patterns. Relational patterns were the least frequently observed. PSTs that form domino causality, mostly perform precipitation infiltration into surface and groundwater (n=56) or precipitation and cloud formation (n=51) while forming domino causality. PSTs that form cyclic causality, mostly performed simplified water cycle diagrams (n=53) and phase changes of water (n=48). In examining mutual causality, participants frequently incorporated human components into their concept maps (n=47). PST that forms relational causality, uses human relationships with the water cycle (n=25) while forming relational causality. Regarding the WCDT results, the mean score was 8.03 (SD = 2.07) when only the choice tier responses were evaluated. When all three tiers were considered, the mean score decreased to 2.95 (SD = 2.054). Thus participants lacked a sophisticated understanding about the water cycle. Despite their understanding that oceans are the primary source of moisture in the water cycle and recognizing that oceans contain significantly more water compared to other sources they displayed misconceptions about various topics. One common misconception was that carbon dioxide is the most prevalent greenhouse gas in the atmosphere. Other observed misconceptions pertained to the conditions necessary for deposition to occur and the melting of floating sea ice as a cause of sea level rise. The relationship between participants STSs and conceptual understanding showed that there was a medium, positive correlation between them, r = .418, n = 254, p < .001. There are similar findings that showed a positive relationship between system thinking and conceptual understanding (Batzri et al., 2015; Turan, 2019; Sweeney & Sterman, 2007). If participants' conceptual understanding is low, they seem to focus superficially on the domino causality.

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