Developing Systems Thinking Skills with a Global Climate Change Module: A Mixed Methods Design

Abstract

Global climate change is an important, complex problem worldwide. Systems thinking skills enable us to solve complex problems from a holistic perspective. Based on this relationship, in this study, we aimed to investigate the effect of a systems thinking based global climate change module on students’ systems thinking skills. A mixed method explanatory design was used with 104 eighth grade students in Turkey. The systems thinking based global climate change module was implemented face to face with first group and with a blended learning method with second group. Activities for a control group were designed according to the curriculum objectives. Students’ systems thinking skills were analyzed quantitatively with the Systems Thinking Skills Test and qualitatively with document analysis. The results showed that the students who used the module, regardless of the implementation method, increased their systems thinking skills significantly, providing more complex answers, ideas, and solutions regarding issues associated with global climate change. The new generation will have to cope with the complex problems of today’s world and produce solutions to them. Therefore, it is recommended that their systems thinking skills be supported by different disciplines, thus developing a holistic approach.

1. Introduction

Education systems should analyze and reflect the changes occurring across all sectors of society and in individuals’ living conditions (Garrison & Kanuka, 2004). Since the beginning of the 21st century, rapid advancements in science and technology have significantly influenced people’s lives and expectations. As a result, the direction of education has also been shaped by these technological developments and evolving societal needs. Around the world, the desired profile of future citizens is defined as individuals who can generate knowledge, use it efficiently and appropriately, solve problems, think critically, show empathy, and stay up to date with technological advancements (National Research Council, 2012; MoNE, 2013).

In Turkey, analytical thinking skills are prominently featured in the national curriculum (MoNE, 2018). Analytical thinking involves breaking down a concept, event, or whole into smaller parts in order to understand each component (Mella, 2012). However, analytical thinking alone is insufficient to fully comprehend, evaluate, and develop effective solutions to the complex global issues affecting all individuals (Meadows & Wright, 2008). Challenges such as those related to health, education, the environment, governance, the economy, and climate change require a systems thinking perspective (Mella, 2012).

In his research, Beach (2023a) explored the intersection of global climate change and systems thinking. He emphasized that climate change should be taught through a systems-based framework, integrating systems thinking with critical inquiry. According to Beach, systems thinking should be central as students analyze and critique each component of this complex issue.

As countries strive to keep pace with a rapidly changing world and aim to develop adaptable individuals, it is essential that the systems thinking approach be incorporated into educational practices (Higgins, 2015). Moreover, students should be encouraged to apply systems thinking not only in academic settings but also in their daily lives—as active citizens confronting complex and evolving global challenges (Lyons, 2014).

Global climate change, one of the most pressing issues of our time, is characterized by its complex nature and was chosen to be addressed through systems thinking skills in this study. This topic was selected because it is included in the science curriculum and represents a responsibility that students, as citizens, should bear (Hestness et al., 2015). To effectively address the challenges of climate change mitigation and adaptation, both national and international principles need to be established, green technologies must be developed, and financial incentives should be provided. However, it is important to recognize that while these measures are essential, they alone do not offer a comprehensive solution to the complex issues associated with sustainable development and global climate change, as emphasized by Buckler and Creech (2014).

There is a direct link between human actions and greenhouse gas emissions, and thus, long-term behavioral changes are necessary to mitigate and adapt to global climate change (Nolet, 2009). The 13th sustainable development goal of the United Nations is focused on climate action, with one of its targets being the improvement of education and the raising of awareness. Education is considered a key factor in changing environmental behaviors, and as a result, it has become a central strategy in the global plan to address climate change (Chew Hung, 2014).

In response to the rapid development of technology and its growing importance in all aspects of life, countries have increasingly incorporated educational technologies into their systems, giving them a permanent place in education (Driscoll, 2002). The COVID-19 pandemic that emerged globally in 2019 has accelerated the integration of educational technologies, the internet, and distance learning into everyday education far more quickly than anticipated, and this trend will likely continue (Anderson, 2020). Given these developments, it is no longer feasible to confine education within traditional classroom walls. If education is to be a lifelong process, independent of time and space, it must be shaped by the new realities of the world (Anderson, 2020).

According to Horton (2000), the highest efficiency in learning can be achieved through blended learning environments that combine the advantages of online learning with the practical opportunities of traditional education. In this thesis study, the blended learning model was also included in order to stay up to date when addressing a current issue such as global climate change, and to clearly observe the effects of blended learning within a module that incorporates systems thinking skills.

According to Waha and Davis (2014), traditional teaching and learning practices from the past can no longer meet the knowledge needs of today’s society. Since a life without computers or smartphones is unimaginable for all age groups, it is no longer possible to rely solely on traditional methods to design educational activities. With the transition to the information age, traditional approaches are insufficient to address students’ needs (Nistor, 2014). In line with the demands of the 21st century, all educational institutions have taken action and started to integrate educational technologies into their systems (Hwang et al., 2009). Furthermore, it has been observed that fully online courses fall short in implementing certain components of learning, which has created a need for blended learning environments (Nielson & González-Lloret, 2010). Blended learning combines various instructional methods such as online and face-to-face learning, offering students diverse learning styles. In this way, the most effective materials and techniques are used to achieve the desired outcomes (Horton, 2000). According to the study by Akkoyunlu and Soylu (2008), while online learning offers students flexibility and freedom, face-to-face learning enhances social communication and interaction. These two modalities compensate for each other’s shortcomings and together provide a rich and goal-oriented learning environment.

Blended learning not only offers numerous benefits such as flexible timing, personalized materials, and face-to-face interaction with instructors, but also creates a student-centered environment that fosters individuals who can take responsibility for their own learning and develop independent learning skills. Students have access to an unlimited virtual space where they can reach information, as well as a classroom environment where they can share and receive feedback (Kazu & Demirkol, 2014). In order to catch the times in addressing a current issue such as global climate change and also to clearly observe the effects of blended education in a module where systems thinking skills are used, it was felt necessary to address the blended learning in this study.

Considering all the above, this study aimed to investigate the effects of systems thinking based global climate change module on students’ systems thinking skills with face-to-face and blended learning methods. Research was guided by the following research question,

What is the influence of implementing the systems thinking based global climate change module through face-to-face and with blended learning on students’ systems thinking skills?

In addition to the quantitative method, the qualitative method was also employed to obtain more in-depth answers while addressing the research questions. The hypotheses developed for the quantitative part of the study are as follows.

• There is a significant difference between the systems thinking skills post-test scores of the groups in which the systems thinking based global climate change module was implemented and the control group.
• There is no significant difference between the systems thinking skills post-test scores of the groups in which the systems thinking based global climate change module was implemented face to face and with blended learning.
• The systems thinking skills post-test scores of the groups in which the module was implemented are higher than those of the group in which it was not implemented.

1.1. Systems Thinking

To understand systems thinking, it is first necessary to define what a system is. A system is a collection of independent or regularly interacting components. It consists of three main elements: components (or elements), interconnections, and a purpose. Examples of systems include ecosystems, the human body, a country’s economy, or a sporting event. Some systems are entirely natural, while others are man-made. In some cases, components of a system may themselves be systems, referred to as subsystems. Each subsystem has its own purpose and is interconnected with others. The world, as an ecosystem, is a prime example of a complex system composed of many subsystems such as forests, biogeochemical cycles, and living organisms (Meadows & Wright, 2008).

Systems thinking is a holistic approach that focuses on the relationships among system components, feedback mechanisms, and the dynamic behavior of systems over time (Arnold & Wade, 2017). It emphasizes change, interdependence, and adaptability. Researchers have associated systems thinking with scientific reasoning, problem-solving, and critical thinking, and have classified it as a high-level cognitive skill (Assaraf & Orion, 2005).

Several frameworks have been developed in the literature to assess systems thinking skills. While Assaraf and Orion (2010) and Karaarslan (2016) designed subject-specific measurement tools, Richmond (2000), Sweeney and Sterman (2000), Stave and Hopper (2007), and Arnold and Wade (2015) created more general instruments that can be applied across different domains. While some researchers have found no hierarchical structure in systems thinking skills (Richmond, 2000), others have proposed hierarchical models (Assaraf & Orion, 2010).

1.2. Blended Learning

Blended learning, in its simplest definition, is a contemporary educational model that emerges from the integration of traditional face-to-face instruction with online learning materials. Also known as hybrid learning, blended learning enriches conventional teaching by incorporating various instructional technologies and methods. It is a flexible model, free from rigid or strict rules, and the learning environment and methods are shaped according to the learners’ needs (Pesen, 2014). In blended learning, the concepts of teaching and learning are considered as two sides of the same coin. The model emphasizes the importance of both (Hrastinski, 2019). While the teaching component reflects the presence of an instructor as in traditional education, the learning component highlights the role of learners who actively participate in the educational process through online learning (Üstün, 2011).

The goals of blended learning vary depending on students’ individual differences, course content, and specific contexts. Osguthorpe and Graham (2003) identified six fundamental objectives that underpin the adoption of blended learning,

• To enhance the richness of learning by increasing flexibility in the teaching-learning process through the use of various instructional methods,
• To enable students to access information through a range of online tools,
• To improve both student-student and student-teacher interaction, allowing for timely feedback and correction, while also supporting peer learning and increasing social engagement,
• To minimize teacher guidance by encouraging students to take individual responsibility for their learning activities,
• To reduce costs by making time spent in educational environments more efficient and productive,
• To allow for easy revision of online resources or the blended learning design when necessary (as cited in Üstün, 2011).

Blended learning aims to help individuals realize their potential by offering the most suitable instructional methods at the right time and place, aligned with specific learning objectives (Sarıtepeci & Yıldız, 2014). It seeks to provide learners with enriched content throughout the learning process, thereby engaging disadvantaged students and promoting equal opportunities (Wang et al., 2015). Additionally, it aims to optimize both learning outcomes and the cost-effectiveness of program implementation (Dikmen & Ocak, 2020).

Blended learning also provides educators and administrators with opportunities to connect and communicate through both face-to-face and online platforms. It allows for the use of instructional materials in both formats, offers learners the chance to apply what they learn in practical settings across both environments, and supports the formation of communities through peer interaction—whether in-person or online (Mossavar & Larson, 2007).

2. Materials and Methods

2.1. Design of the Study

A mixed method explanatory design was employed in this study. Since both qualitative and quantitative data were collected and analyzed through pre- and post-tests, the use of a mixed method was deemed appropriate (Creswell & Clark, 2007). In the quantitative phase, a multiple-choice Systems Thinking Skills Test was used to compare the groups and evaluate their levels of systems thinking. To conduct a more in-depth analysis of these skills and to identify which specific aspects of systems thinking changed as a result of the implemented module, document analysis was utilized as the qualitative method.

Systems thinking based global climate change module was developed by the researcher in alignment with the learning outcomes specified in the science curriculum. While designing the module, activities were included to enhance students’ systems thinking skills, encourage their application in daily life, and foster their use in problem-solving contexts. The module activities were implemented face to face with the first group (n = 35). For the second group (n = 35), selected activities from the module were adapted and implemented through a blended learning approach. Students in this group completed certain tasks online, sometimes in coordination with the teacher and classmates, and at other times independently. The third group (n = 34), in contrast, did not receive the systems thinking based module. Instead, alternative activities covering the same climate change topics were designed based on curriculum objectives and textbook content. Further details regarding the module are provided in the Section 2.4 named as “Module Development”.

In the quantitative part, Systems Thinking Skills Test developed by Doğanca (2013) was administered as a pre- and post-test to assess students’ systems thinking skills. The test results were analyzed using SPSS, and comparisons were made between the groups. In addition, qualitative data collection was employed to gain deeper insight into the students’ reasoning processes and the inferences they drew from their experiences (Merriam & Tisdell, 2015). Before and after the intervention, students were given a real, published news article related to global climate change. They were then asked open-ended questions designed to assess each dimension of systems thinking. Using a predefined rubric, the students’ responses were evaluated to determine which systems thinking skills they demonstrated and at what level. These qualitative data were analyzed descriptively through document analysis. Further details regarding the Systems Thinking Skills Test and the document analysis process are presented in Section 2.3.

2.2. Participants

The participants of this study (n = 104) were 8th grade students from Istanbul, Turkey. In the Turkish education system, 8th grade students are typically 12 to 13 years old, depending on the age at which they began formal schooling. The face-to-face group consisted of 35 students, including 18 females; the blended learning group also comprised 35 students, with 17 females; and the control group included 34 students, again with 17 females. The gender distribution across all three groups was balanced.

The implementation took place in a public school located in Bakırköy, a district of Istanbul known for its high socio-economic status. The families of the students generally belonged to middle to upper socio-economic backgrounds, and most parents were well-educated, with many holding university degrees.

The study included two experimental groups and one control group. To ensure fairness and consistency, three classes with similar academic performance in the previous semester were selected, and the groups were assigned in an unbiased manner. The experimental groups were exposed to a systems thinking-based global climate change module.

For the qualitative part of the research, purposive sampling was employed as recommended by Merriam and Tisdell (2015). In mixed method studies, the qualitative sample is typically a smaller subset drawn from the larger quantitative sample (Creswell & Clark, 2007). In this study, eight students were selected from each of the three groups based on the purpose of the research.

2.3. Instruments

2.3.1. Systems Thinking Skills Test

Systems Thinking Skills Test (STST) is a quantitative assessment tool developed by Doğanca (2013) as part of her doctoral dissertation. The test items were designed in such a way that students could respond without requiring prior knowledge of specific systems concepts.

In the feedback question, students are presented with two independent scenarios and are expected to interpret them through a feedback loop. They are asked to fill in blanks using the terms “increases” and “decreases”. In the second part of the question, they are prompted to identify similarities or differences in the patterns of change, again in terms of increase or decrease. Through this structure, students are expected to develop a sense of feedback “loop”, beginning and ending with the same variable.

In the delay question, a course completion graph is provided. Under normal circumstances, students are expected to graduate two months later than planned. Participants are asked to plot the changes in graduation numbers over time and compare two different groups. This item assesses their awareness of the concept of a delay period—specifically, a two-month delay.

Two items in the test assess stock-flow thinking skills. These were adapted by the researcher to be appropriate for the students’ cognitive level. One question asks students to calculate a student’s remaining money after paying off a debt, while the other involves calculating the number of passengers on a bus.

The highest possible score on the test is 11.5. The reliability of the test was confirmed with a Cronbach’s alpha coefficient of 0.73, and a Spearman-Brown split-half reliability coefficient of 0.69 was calculated using the parallel-test method.

2.3.2. Document Review

As Tilbury (2011) emphasized, incorporating real-life content into educational practices not only enhances students’ learning experiences regarding the environment and sustainable development but also strengthens their sense of personal responsibility for their actions. In this study, an online news article titled “Ecological Destruction in the Marmara Sea: What is Mucilage (Sea Slobber)? What is Planned for the Solution?” (Euronews, 2021) was presented to students both before and after the intervention. The selected news item was carefully chosen to ensure that it not only addressed environmental issues but also reflected systemic components influencing ecosystem changes.

Each of the eleven open-ended questions developed in relation to the article was designed to assess a specific systems thinking skill. To determine the most appropriate systems thinking skills for both the students’ cognitive level and the subject of global climate change, frameworks from Assaraf and Orion (2010), Arnold and Wade (2017), and Karaarslan (2016) were utilized. Based on these sources, a total of eleven systems thinking skills were selected and evaluated using a rubric specifically developed for this study.

Researcher created a rubric tailored to assess the eleven systems thinking skills at the 8th grade level. Each skill was categorized into three proficiency levels within the rubric. In developing the rubric, insights were drawn from existing literature (Arnold & Wade, 2017; Karaarslan, 2016; Assaraf & Orion, 2010; Turan, 2019). To ensure content validity, the initial version of the rubric was reviewed by two academics specializing in science education, two practicing science teachers, and one academic expert in environmental education, whose feedback was used for revisions. For inter-coder reliability, 30% of the data were independently coded by another researcher. The inter-coder reliability coefficients for the eleven skills ranged between 0.90 and 0.95, indicating a high level of agreement. The final version of the systems thinking skills rubric is presented in

Table 1. Systems thinking skills rubric.

Systems Thinking Skills	Levels
	Low Maturity	Developing	High Maturity
Maintaining boundaries	Can not define the boundaries of the system	Defines the boundaries of the system using most of the necessary elements	Accurately defines the boundaries of the system despite changes in the system.
Differentiating and quantifying elements	Can not define the elements in the system	Able to identify the elements in the system and differentiate the events from static components	Able to identify the most of the elements and differentiate the static components from processes with high accuracy
Identifying and characterizing relationships	Unable to identify the relationships with accuracy	Able to recognize the relationships and tell these relationships with explanations that does not consist of answer to how questions	Recognizes most of the relationships including non- obvious ones and explains the relationships in details giving answer to how it works questions
Identifying and understanding feedback	Unable to recognize feedback loops	Makes an effort to identify cycles	Identifies cycles and describes them as positive and negative
Exploring multiple perspectives	Addresses only one aspect of the issue, e.g., emphasizes only global warming	Recognizes the existence of different perspectives. Tries to look at the issue from more than one side, including different ideas	Actively emphasizes and compares many aspects of the topic, without ignoring conflicting ideas
Recognizing hidden dimensions	Cannot recognize hidden dimensions	Recognizes hidden dimensions in the system but cannot make clear connections between them	Makes sense of hidden dimensions in the system and makes clear connections between them
Describing and predicting future behavior	Cannot establish a relationship between the past, present and future	Makes an effort to relate past, present and future. Usually relates two time dimensions (e.g., past and future)	Can clearly establish relationships between past, present and future
Developing empathy with other people	Cannot develop empathy with other people	Tries to empathize with people but cannot give adequate explanations without blaming them	Empathizes with people by explaining their needs and reasons behind their behavior without blaming them
Developing a sense of place	Cannot develop a sense of place	Tries to develope a multidimensional sense of place. Can describe the place in one or two dimensions	Can construct a multidimensional, holistic sense of place. Can attribute meanings to places (psychological, social, cultural)
Identifying intervention points	Cannot identify intervention points	Can identify intervention points with low leverage	Can identify intervention points with high leverage
Seeing nature as a system	Do not have a perspective that sees nature as a system	Can look at nature as a system considering two or three aspects of holistic ecology	Can look at nature as a system considering many aspects of holistic ecology and describe the human-nature relationship in a holistic way

.

2.4. Module Development

Climate change is one of the most pressing global issues of our time, and its resolution is increasingly being entrusted to future generations. It is essential to implement the most effective instructional approaches to help students change their habits and transfer their learning into everyday life. Based on a comprehensive literature review, systems thinking—recognized for its broad applicability across various domains and its capacity to foster essential competencies—was selected as the core pedagogical approach for this study (Richmond, 2000). In line with the objectives outlined in the Science Curriculum (MoNE, 2018), a four-week global climate change module was developed to integrate systems thinking principles into classroom instruction.

2.5. Intervention

Intervention phase of the study was conducted during the spring semester of the academic year, within the scope of the 8th grade science unit titled Cycles and Environmental Problems. All activities were implemented by the researcher and spanned a total of 26 class hours. The Systems Thinking Skills Test was administered to all three groups both before and after the intervention. Additionally, eight students from each group were randomly selected to participate in document analysis, which was conducted pre- and post-intervention.

Ethical approvals for the study were obtained from both the Ministry of National Education and the affiliated university prior to the implementation phase (Ref: E-59090411-44-48298531). Informed consent was also obtained from all participating students and their guardians. Moreover, permission was secured from the original authors for the use of the measurement tools employed in this research.

In designing the activities for both the experimental and control groups, alignment with the 8th grade science curriculum was ensured. The specific topics included in the systems thinking-based global climate change module are presented in

Table 2. The topics included in the systems thinking based global climate change module.

Topic	Duration of Teaching
Systems and Systems Thinking	2 Lesson hours
Water cycle	2 Lesson hours
Nitrogen cycle	2 Lesson hours
Oxygen and carbon cycle	2 Lesson hours
Greenhouse effect and global climate change	2 Lesson hours
Human impacts on global climate change	2 Lesson hours
Scientific studies about global climate change	2 Lesson hours
Consequences of climate change	2 Lesson hours
Global action taken against global climate change	2 Lesson hours
Personal responsibilities regarding global climate change	2 Lesson hours

.

Although the topics listed in the table were covered in all three groups, different instructional methods were employed for each. In the first experimental group, all activities from the systems thinking based module were implemented entirely through face-to-face instruction in the classroom. In the second experimental group, the module was delivered in a blended learning format. Students in this group participated in some activities face to face, while others were conducted through a virtual classroom via the educational portal to which they were registered. Through this platform, students engaged with animations and videos, utilized simulations, and took part in online activities designed to enhance systems thinking skills. In contrast, students in the control group participated in activities solely through face-to-face instruction, without an explicit focus on systems thinking. Although they spent the same amount of instructional time on the same global climate change topics as the experimental groups, their lessons were planned strictly in alignment with the 8th grade science curriculum established by the Ministry of National Education and followed the prescribed activities in the official textbook.

2.6. Data Analysis

The quantitative data obtained in the study were analyzed using the SPSS 17.0 statistical software. Since the distribution of the data met parametric assumptions, ANOVA was employed to analyze the results of the Systems Thinking Skills Test.

In the qualitative part of the study, students’ responses to the document analysis were evaluated using qualitative content analysis. A rubric developed by the researcher was utilized to assess students’ systems thinking skills. For each skill, the rubric included three proficiency levels. Students’ responses were coded based on these levels, and the qualitative data were then transformed into quantitative data for further interpretation.

3. Results

Both quantitative and qualitative measurement tools were employed to assess students’ levels of systems thinking skills. For the quantitative assessment, the Systems Thinking Skills Test developed by Doğanca (2013) was administered to all students before and after the intervention. For the qualitative assessment, students were asked to respond to open-ended questions based on a news article that presented a real-life scenario related to global climate change and included systemic elements. Students’ levels and progress in each systems thinking skill were evaluated using the rubric developed for the study.

3.1. Results of Systems Thinking Skills Test (STST)

This is an experimental study with three different groups that need to be examined and compared. The experimental and control groups took the same tests. In order to compare the systems thinking skills of the experimental and control groups, a one-factor analysis of variance (ANOVA) was used for a mixed design with three separate treatments and pre- and post-treatment values.

To understand the difference between the systems thinking skills of the groups before the application, ANOVA was applied for the STST pre-tests since the results of all three groups were normally distributed (p > 0.05) according to the Shapiro-Wilk test.

The data obtained from the application of the systems thinking skills test as a pre-test are given in

Table 3. ANOVA Results of Groups’ STST Pre-test.

Group	N	Mean	Std. Deviation	F	Df	p
Face to face	35	3.91	1.74	0.734	2	0.483
Blended	35	3.60	1.54
Control	34	3.48	1.23
Total	104	3.66	1.52

. According to the table, STST pre-test averages were close to each other for all three groups, and no significant difference was found between them.

To find out whether there was a significant difference between the STST results of the three groups after the different interventions they received, ANOVA was conducted since their distributions were normal according to the Shapiro-Wilk test.

As a result of the analysis that can be seen in

Table 4. ANOVA Results of Groups’ STST Post-test.

Group	N	Mean	Std. Deviation	F	df	p
Face to face	35	6.25	1.88	19.85	2	0.000
Blended	35	5.77	1.82
Control	34	3.66	1.72
Total	104	5.24	2.12

, while the STST average of the face-to-face group (6.25) and blended learning group (5.77) were close to each other, a difference was observed between the STST average of these two groups and the control group (3.66). ANOVA applied to the results of the three groups revealed that there was a significant difference between groups.

To identify which specific groups contributed to the observed significant difference, a post-hoc analysis was conducted, as presented in

Table 5. Post Hoc analysis of STST post-tests.

Group (I)	Group (J)	Mean Difference	p
Face to face	Blended	0.4857	0.797
	Control	2.595 *	0.000
Blended	Face to face	−0.4857	0.797
	Control	2.109 *	0.000
Control	Face to face	−2.595 *	0.000
	Blended	2.109 *	0.000

The significance value for the difference of factor levels is less than 0.05, an asterisk (*) is printed by the difference.

.

In a manner supporting the hypotheses section, a significant difference was observed between the classes where the module was applied and the control group (p < 0.05). The systems thinking skills of the classes that used the module were higher in the post-test results compared to the control group. However, no significant difference was observed among the classes that used the module, despite differing learning methods (p > 0.05). According to the results of this table, we can say that the students who used the systems thinking based climate change module were more successful in STST than the control group.

3.2. Results of Document Review

Students’ systems thinking skill levels are discussed in more depth in this section through document review. The students took the document including a news article with title ‘Ecological destruction in the Marmara Sea: What is mucilage (sea slobber)? What is planned for the solution?’ (Euronews, 2021) before and after the intervention. Students were asked to examine it in line with the questions posed. A systems thinking skills rubric (Table 1) was developed to determine students’ levels for each of the eleven systems thinking skills. For each skill, the levels were categorized as ‘low maturity’, ‘developing’ and ‘high maturity’. To observe the impact of each intervention on the groups, the levels of the students for each skill before and after the intervention were given in

Table 6. Systems thinking skill levels of the groups before implementation.

Systems Thinking Skills	Face to Face			Blended			Control
	Low Maturity	Developing	High Maturity	Low Maturity	Developing	High Maturity	Low Maturity	Developing	High Maturity
STS 1	8	-	-	8	-	-	8	-	-
STS 2	8	-	-	7	1	-	7	1	-
STS 3	8	-	-	7	1	-	7	1	-
STS 4	2	6	-	2	5	-	2	6	-
STS 5	4	4	-	5	3	-	3	5	-
STS 6	6	2	-	6	2	-	5	3	-
STS 7	3	5	-	2	6	-	3	5	-
STS 8	-	7	1	-	8	-	-	8	-
STS 9	2	6	-	3	5	-	3	5	-
STS 10	5	3	-	6	2	-	6	2	-
STS 11	6	2	-	5	3	-	5	3	-

and

Table 7. Systems thinking skill levels of the groups after implementation.

Systems Thinking Skills	Face to Face			Blended			Control
	Low Maturity	Developing	High Maturity	Low Maturity	Developing	High Maturity	Low Maturity	Developing	High Maturity
STS 1	5	2	1	5	2	1	8	-	-
STS 2	1	6	1	-	6	2	5	3	-
STS 3	1	7	-	1	7	-	4	3	-
STS 4	-	5	3	-	5	3	-	8	-
STS 5	-	6	2	-	5	3	3	4	1
STS 6	-	6	2	2	4	2	5	3	-
STS 7	-	4	4	-	3	5	2	4	2
STS 8	-	6	2	-	6	2		6	2
STS 9	-	6	2	-	5	3	1	7	-
STS 10	-	5	3	-	4	4	4	4	-
STS 11	-	3	5	-	3	5	3	5	-

. The systems thinking skills’ (STS) numbers in these tables were given according to order of the rubric in Table 1.

The level of each student for each system thinking skill was coded. A numerical value of ‘0’ was entered for ‘Low maturity’, ‘1’ for ‘Developing’ and ‘2’ for ‘High maturity’. According to the data entered, the averages for each group before and after the intervention were calculated as shown in

Table 8. Mean Scores of Groups’ Systems Thinking Skills Before and After the Intervention.

Groups	Averages Before Intervention	Averages After Intervention
Face to face	5.25	13.37
Blended	4.62	14
Control	4.87	7

. Before the intervention, all three groups’ average systems thinking skills were nearly the same, but after the intervention there was a gap between the experimental and control groups’ scores. The groups which used modules doubled the scores of control group.

The Section 4 includes an analysis of the changes observed in each systems thinking skill before and after the implementation, along with overall interpretations.

4. Discussion

In the quantitative phase of the study, students’ systems thinking skills were assessed using a test designed to evaluate their abilities in analyzing stock-flow relationships, understanding delays, and interpreting feedback mechanisms. The test also required students to adopt a holistic perspective, interpret graphs, and analyze cause-and-effect relationships. The maximum score achievable on the test was 11.5. Prior to the intervention, the mean scores were relatively low and closely aligned across the groups: 3.91 for the face-to-face group, 3.60 for the blended learning group, and 3.48 for the control group.

Following the implementation of the instructional module, the mean scores increased significantly in both experimental groups (Face-to-face group: 6.25 and the blended learning group: 5.77). In contrast, the control group’s average slightly increased to 3.66, a change that was not statistically significant. These results support the first hypothesis of the study ‘There is a significant difference between the systems thinking skills post-test scores of the groups in which the systems thinking based global climate change module was implemented and the control group.’ These findings suggest that the systems thinking based module effectively enhanced students’ skills in the experimental groups, while traditional instruction in the control group did not yield comparable gains.

The observed improvement in the experimental groups may be attributed to the module’s inclusion of targeted activities such as graph interpretation, table analysis, feedback loop construction, basic calculations, and examination of causal relationships (Doğanca, 2013). These activities likely contributed to students’ improved performance in the post-test. Although both experimental groups showed statistically significant improvement compared to the control group, no significant difference was found between the two experimental groups themselves. Post-hoc analyses were conducted to identify the specific group differences.

These results are consistent with previous research. For instance, Nuhoğlu and Nuhoğlu (2007) demonstrated that seventh-grade students who were exposed to system dynamics instruction within the “spring-mass systems” topic improved their ability to recognize causal relationships, construct graphs, and discuss system structures. Similarly, Grotzer and Basca (2003) argued that conventional curricula often fall short in addressing students’ misconceptions about environmental issues. They emphasized that merely delivering factual information is inadequate for fostering an understanding of dynamic systems. Instead, they proposed classroom discussions and systems thinking-based activities as more effective instructional strategies, which proved successful in correcting misconceptions related to ecological dynamics.

In the qualitative component of the study, students were asked to analyze a news article and respond to questions designed to assess each of the eleven systems thinking skills. The rubric assigned a score of 0, 1, or 2 for each skill, and the total scores are presented in Table 8. The qualitative findings were largely consistent with the quantitative results, indicating that both experimental groups exhibited significantly greater improvements in systems thinking skills compared to the control group. Notably, students in the experimental groups produced responses that were more detailed, complex, and demonstrated clearer causal reasoning.

While the control group generally maintained their pre-test levels, students in the experimental groups advanced by one, and in some cases, two rubric levels in specific skills. These improvements varied across the eleven systems thinking skills. Prior to the intervention, most students demonstrated low proficiency in skills such as maintaining boundaries, differentiating and quantifying elements, and identifying and characterizing relationships. Following the intervention, students in the experimental groups showed significant gains in these areas, while no notable progress was observed in the control group. The experimental group students also used a greater number of relevant keywords when describing boundaries and elements. However, although the experimental groups improved in identifying and characterizing relationships, their causal explanations remained somewhat superficial.

The skill of identifying feedback loops did not initially present as weak as the other skills. Yet, only after the intervention did students in the experimental groups demonstrate an ability to distinguish between positive and negative feedback loops and achieve high maturity levels. This suggests that while students may recognize feedback structures, the intervention enabled them to better understand the roles and effects of these loops within a system. Real-life examples and analysis tasks embedded in the module may have supported this improvement (Tilbury, 2011).

Prior to the intervention, students generally scored at a low level in the skills of exploring multiple perspectives and recognizing hidden dimensions. Post-intervention, students in the experimental groups—particularly those in the face-to-face group—showed notable development in these skills. This can be attributed to the module’s emphasis on discussion-based activities and collaborative learning environments, which encouraged students to consider different viewpoints (Arnold & Wade, 2017).

Regarding the skill of describing and predicting system behavior, considerable progress was made in the experimental groups, with students demonstrating the ability to analyze systems across time—considering past conditions, present dynamics, and future outcomes. In contrast, no student in the control group referenced all three temporal dimensions in their responses. The module’s structured activities, which required students to reflect on temporal changes, were instrumental in promoting this skill (Assaraf & Orion, 2005).

Interestingly, students initially demonstrated relatively higher proficiency in developing empathy and sense of place skills compared to others. This may be due to the inherently emotional and personal nature of these competencies, which may not rely as heavily on scientific or mathematical reasoning. Given the cultural and societal context in Turkey, students may already possess a natural tendency toward empathy and place-based attachment. The intervention did not produce significant differences between the groups for these two skills, possibly due to the module’s limited focus on local or outdoor contexts. Future studies could enhance these outcomes by integrating localized content or extending the duration of the intervention (Karaarslan, 2016; Can, 2020).

Substantial improvements were also observed in the skills of identifying intervention points and seeing nature as a system among students in the experimental groups, while control group students showed minimal progress. The module’s problem-solving activities likely contributed to these outcomes by encouraging students to investigate complex systems, uncover hidden components, and adopt a holistic perspective (Arnold & Wade, 2017). Additionally, the face-to-face group performed better in these skills than the blended learning group. This difference may stem from the fact that, in the blended learning environment, students were responsible for completing some activities independently, whereas the face-to-face group benefited from richer in-class discussions and collaborative problem-solving. These shared experiences may have enhanced their ability to identify intervention points and grasp systemic structures (Garrison & Kanuka, 2004).

To express the qualitative findings more clearly using quantitative data, the number of students in each of the three groups assessed at the levels of low maturity, developing, and high maturity as shown in Table 7, was quite similar before the implementation. After the module was implemented, the results of the groups, whose systems thinking skills were assessed using a rubric across three levels, can be summarized as follows: in the face-to-face group, students were evaluated at the low maturity level only 7 times across 3 different systems thinking skills. In the blended learning group, low maturity assessments also occurred 8 times, again across 3 skills. In all other skills, students were evaluated at either the developing or high maturity level. Unfortunately, in contrast to these groups, students in the control group were assessed at the low maturity level 35 times across all 9 systems thinking skills. This indicates that the module clearly contributed to the development of systems thinking skills in the intervention groups. Almost no student remained at the initial (low maturity) level after the intervention.

When we evaluate the highest level reached by the students, the findings are similarly telling. Students in the control group achieved the high maturity level only 5 times across 3 systems thinking skills. In contrast, students in the face to face and blended learning groups reached the high maturity level in 10 skills, with only one skill in which no student reached this level. A total of 25 high maturity evaluations were recorded in the face to face group, and 30 in the blended group. These results show that the systems thinking based global climate change module not only helped almost all students progress beyond the initial level but also enabled many of them to reach the highest level of performance. This provides strong evidence of the effectiveness of the developed module and the implemented activities.

The average scores presented in Table 8 are compared, it can be seen that all three groups had similar pre-implementation averages, close to 5 (face-to-face: 5.25; blended: 4.62; control: 4.87). In fact, the control group initially had a higher average than the blended group. However, following the intervention, the difference between the scores increased substantially. The face-to-face group raised its average to 13.37, and the blended group to 14, while the control group’s average score only to 7. While qualitative analyses had already revealed differences in individual skills, the quantitative data also strongly support the conclusion that the systems thinking-focused global climate change module had a powerful positive effect on students’ systems thinking skills, aligning with the purpose of the study.

5. Conclusions

Given the importance of systems thinking in analyzing complex and multifaceted phenomena, this study addressed the issue of global climate change—a topic that encompasses numerous interconnected elements and dimensions. The developed instructional module was grounded in systems thinking principles, which are especially effective in understanding intricate structures such as climate systems. Accordingly, the module aimed to cultivate students’ systems thinking skills that are transferable across various domains including economics, healthcare, education, and engineering (Aronson, 1996; Daellenbach et al., 2012; Higgins, 2015).

To enhance student engagement, especially for those with high interest in technology, a blended learning approach was employed. This model combined digital instructional materials and self-directed tasks with face-to-face learning. As a result, students developed greater awareness of their learning responsibilities, set personal goals, and improved their self-regulation skills (Garrison & Kanuka, 2004).

One of the strengths of this study lies in its experimental design, which included three groups, i.e., two experimental and one control, allowing use to undertake a comparative analysis using both pre- and post-test measures. Moreover, the integration of both quantitative and qualitative data enriched the analysis and provided deeper insights. The researcher personally conducted all interventions across the groups, thereby minimizing variability stemming from different implementers.

The module was designed with an interdisciplinary and holistic approach that emphasized higher-order thinking within the context of climate change, while also incorporating basic mathematical competencies through select activities. Quantitative data were collected using a Systems Thinking Skills Test (STST) administered before and after the intervention. The test was not limited to environmental topics and included mathematical reasoning tasks relevant to systems thinking, making it adaptable to various disciplines (Doğanca, 2013).

The findings revealed that students in both experimental groups significantly improved their systems thinking skills, while no such improvement was observed in the control group. These results support the hypothesis that integrating systems thinking activities into curricula has a positive impact on student learning. Furthermore, these outcomes align with Beach (2023b), who highlighted the need for systems thinking as one of the seven key challenges in addressing climate change in teacher education programs. In this regard, embedding systems thinking as a cross-curricular competency is essential for preparing students to address the complex, interdisciplinary problems of the future (Budak & Ceyhan, 2023; Glissen et al., 2020).

Another critical issue identified in this study was students’ general lack of proficiency in fundamental skills such as interpreting tables, reading graphs, and performing basic mathematical operations. These deficiencies, which are also reflected in Turkey’s PISA results, negatively influence students’ performance and self-confidence across various subjects (Karaduman, 2023). Just as literacy is essential for storytelling and numeracy for solving arithmetic problems, systems thinking requires familiarity with system dynamics and foundational mathematical understanding. Therefore, integrating systems dynamics into diverse disciplines using a variety of instructional methods could enrich both the literature and educational practices.

The qualitative findings further supported the quantitative results. Students who received the module produced responses that were more complex and holistic compared to those in the control group. These students demonstrated an improved ability to understand systems—from cellular structures to global climate—through a more integrated lens, recognizing interrelationships and dynamic processes. This suggests that a multidimensional issue like global climate change requires a multidimensional thinking approach, such as systems thinking, which should be supported across all areas of the educational system (Demssie et al., 2023).

In this study, one experimental group received the module via traditional face to face instruction, while the other experienced it through a blended format. Despite the differences in implementation, no significant discrepancies in outcomes were observed. Students in the blended learning group benefited from engaging multimedia content such as simulations, animations, and videos, and demonstrated increased responsibility and independence. When accompanied by consistent teacher guidance and feedback, blended learning can be a highly effective model for improving students’ self-regulation, motivation, and time management (Akkoyunlu & Soylu, 2008; Kazu & Demirkol, 2014; Anderson, 2020).

The overarching goal of this study was to enhance students’ systems thinking skills and equip them to approach complex global challenges—such as climate change—from a more holistic and solution-oriented perspective. Both the quantitative and qualitative results clearly indicate that the developed module successfully met these objectives. Only students who participated in the intervention showed significant improvement in their systems thinking abilities and were able to offer more advanced, nuanced responses. This finding reinforces the significance and applicability of the study’s approach.

Lastly, it is evident that complex global issues—such as food security, climate change, and educational inequality—cannot be resolved through simplistic, short-term solutions. These challenges require long-term, systemic thinking and cross-disciplinary collaboration. Educating future generations with a strong foundation in systems thinking is essential to nurturing the necessary awareness and skills to address such issues effectively (Beasy et al., 2023). All students, both in Turkey and globally, deserve access to educational opportunities that foster systems thinking and climate change awareness, as demonstrated in this study.

6. Limitations

The participants of this study were limited to 104 students from a single school. The students’ diverse backgrounds, lifestyles, and the regions they live in may have influenced the research outcomes. Including participants from different socio-economic backgrounds and various schools could have strengthened the study. The systems thinking skills test used in the study also involved mathematical skills, and students who were more successful in this area may have achieved higher test scores. The research was limited to a specific time frame; however, since systems thinking is a high-level skill, it would be more beneficial to integrate it throughout the entire academic year and across various subjects, and ideally to introduce it starting from early ages.