systems thinking education

What Is Systems Thinking in Education? Understanding Functions and Interactions in School Systems

Schools, districts, and classrooms are dynamic environments, full of energy and talent. Managing them calls for creative leadership and teaching approaches. Leaders in education need to anticipate how interconnected aspects of schools interact and affect each other.

Systems thinking in education offers a valuable approach for teachers working to build student engagement. The approach also helps leaders organize schools by harnessing their assets. American University’s EdD in Education Policy and Leadership trains educators to apply systems thinking and other effective leadership approaches to transforming schools for the better.

The Systems Thinking Model

An education system is composed of many interdependent components working together. How well these components operate and interact determines the system’s health.

Education systems at the national, state, and local levels consist of interacting parts, including:

• Laws and regulations
• Funding and funding policies
• Schools and administrative offices
• Teachers and staff
• Books, computers, and instructional materials
• Students, parents, and communities

Those seeking to improve an education system might choose to analyze the system’s parts. In this way, they can identify individual characteristics of each part and evaluate how it functions. While this approach can offer some benefits, it has limitations. It stops short of examining the relationships between the parts.

For example, limited school funding might result in high student-teacher ratios and inadequate supplies for students. These factors then lead to lower levels of student achievement which, in turn, puts further strain on teachers to help their students meet achievement benchmarks, and so on.

Responding to the growing demands placed on US education, solving problems such as achievement gaps, and dealing with shrinking school budgets are significant challenges. To face them effectively, educators need to value their system’s high level of interconnectivity and interdependency.

Applying Systems Thinking in Education

Systems thinking is a mindset that helps educators understand the complex education system in a more holistic way. Teachers and administrators using systems thinking might ask questions such as:

• How might cuts to arts education impact student performance in math?
• How can policies linking teacher salaries to standardized test scores affect a low-achieving school’s ability to attract accomplished teachers?

The goal is to consider several possible scenarios to find solutions to interconnected challenges.

Helping teachers solve classroom management issues, for instance, may involve addressing missing support structures in classrooms, such as a need for special education teachers, or adjusting student schedules to give time and space for children to unwind and release their energy.

As a mindset, systems thinking guides educators to deliver thought-provoking, engaging lessons. It encourages school leaders to coordinate districts and manage schools with improved efficiency. It can also replace piecemeal approaches to implementing policies with organized and systematic approaches that bring success across the board.

Specifically, educators can use systems thinking as a framework to structure classrooms and deliver instruction, while school and district leaders can apply it to their management and organizational styles. Additionally, administrators can use systems thinking as an approach to restructuring educational systems or schools.

Systems Thinking in the Classroom

Systems thinking can be a powerful classroom tool, giving students a participatory role in the learning process. By viewing teaching through a systems thinking lens, educators can help students recognize how seemingly disparate systems interact, identifying meaningful connections in the world around them. This not only deepens students’ understanding of specific subjects, but also strengthens their critical thinking abilities.

For example, teachers at Orange Grove Middle School in Tucson, Arizona, used a systems thinking approach to develop a project that strengthened their students’ abilities to analyze and problem solve. They tasked students with developing plans for a new national park that met specific design requirements: parks needed to be attractive to users, inflict limited environmental harm, and respect an Indian burial ground on the chartered land.

During the process of developing their designs, students discovered connections between the social, ecological, and economic components of the project.

Leadership and Systems Thinking

Systems thinking in education empowers education leaders to align school initiatives, improve instruction, increase efficiency, eliminate waste, and strengthen student outcomes.

For example, by closely monitoring student data, administrators can adjust budgets to allow for the purchase of the instructional materials they need most.

A systems thinking approach lets administrators build systems that do the following:

• Recognize and adapt to changes (technological advances, policy reforms), coordinating with other parts of the system fluidly
• Include mechanisms that allow for self-reflection and self-correction
• Process information quickly and make it available to all parts of the system
• Distinguish between situations that need adjustments and those that need overhauls

Discover How an EdD in Education Policy and Leadership Prepares Education Leaders to Excel

Building collaborative cultures in districts and schools calls for a holistic, innovative approach. Systems thinking in education allows education leaders to not only recognize the relationships between the different components of a school system but also use them to solve problems.

Explore how American University’s EdD in Education Policy and Leadership cultivates the knowledge and expertise leaders in education need to confront obstacles and transform schools.

The Role of Educational Leadership in Forming a School and Community Partnership

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5 Effective Principal Leadership Styles

Getting Smart, “Why School System Leaders Need to Be Systems Thinkers”

Journal of School Leadership , “Sources of Systems Thinking in School Leadership”

The Learning Counsel, “What Is Systems Thinking in Education?”

Medium, “How to Practice Systems Thinking in the Classroom”

Systems Thinker, “Revitalizing the Schools: A Systems Thinking Approach”

Systems Thinker, “Systems Thinking: What, Why, When, Where, and How?”

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Teaching Students About Systems Thinking

These strategies guide students to explore the interconnected parts of complex systems like the human body, governments, and ecosystems.

Our world is interconnected and complex. As a result, our students need to move beyond fragmented ways of thinking, which look at problems in isolation or focus on short-term solutions. By developing our students to be systems thinkers, we can enable them to see patterns and organize their learning both inside and outside of school.

Let’s break this idea down by first describing what we mean by a system. Generally speaking, a system is a group of interconnected elements that are organized for a function or a purpose. System elements, or parts, may be physical or intangible things.

Importantly, system parts are interdependent. A change in one element can produce change within the entire system. This means systems are nonlinear. When consequences occur, they’re not isolated. They ripple through a system. Systems we encounter daily include the human body, cities, governments, social networks, and the Earth’s climate.

To give a narrative example, in Dr. Seuss’s well-known book The Lorax , the parts of the system are things like the water, air, Truffula Fruits, Brown Bar-ba-loots, and Humming-Fish, as well as the Once-ler’s greed and desire for economic growth above all else. Imagine if the Once-ler had truly understood how his behaviors impacted the Truffula Tree ecosystem, including the sustainability of his own Thneed production. His inability to think holistically led not only to a range of negative environmental consequences, but also to the collapse of his own business. 

In a global issue such as plastic pollution, system parts may include crude oil production, plastic manufacturing, companies, consumers, wastewater, and greenhouse gas emissions.

Systems thinking helps students manage complexity

Systems thinking is a mindset as well as a set of tools that enables students to recognize and understand relationships and interconnectedness. It’s an ability to toggle between the parts and the whole of a system to understand how interactions produce negative or positive behaviors. 

Systems thinking supports our students to understand the complexity of the world and manage its uncertainty, especially in a time of increased globalization; it is an essential component of critical thinking that teachers can apply across the curriculum. For example, using systems thinking, students can do the following:

• Chart character development in a piece of literature with behavior-over-time graphs
• Map nonlinear causes and consequences of historical or political conflicts
• Understand the relationships between parts of a cell, as well as between cells, organs, and body systems
• Analyze and take action on real-world issues, such as global warming, poverty, or overfishing

Teachers, curriculum coordinators, and school leaders can also use systems thinking tools, such as Agency by Design’s Mapping Systems protocol , to better understand the way parts of our educational system connect to produce positive or negative outcomes for students, such as lower attendance, higher referrals to learning interventions, or increased mental health issues.   

Fostering systems thinking as critical thinking

There are a number of ways teachers can facilitate systems thinking in the classroom. By slightly shifting how we interact with students—our questions or thinking prompts—we can promote “thinking in systems.”

Question with intention: Knowing we want to move away from “A leads to B” linear thinking, we can intentionally ask questions that encourage students to reflect on multiple parts of a system and how they connect. Instead of asking, “What caused this?” which communicates that there is a single cause, we can instead ask, “What factors contributed to this?” allowing students to search for multiple causes and nonlinear relationships.

Take a helicopter view: Toggling between the details and the big picture is an important systems thinking skill and one of the habits of a systems thinker . When looking at a situation, event, or particular issue, encourage students to discuss systems as a whole. For example, in the classroom we may create a circle, where each student represents a system part and makes connections with a ball of string. Students name how they connect to another system part as they toss the ball of string to one another, with each student retaining some of the string as they pass the ball around. At the end, students can see the interconnectedness of parts by gently tugging on the yarn and seeing who is affected.

Encourage pattern recognition: We want students to see the web of interconnections within systems and recognize how systems connect to other systems. During the Covid-19 pandemic, for instance, we saw how health systems impacted transportation and the economy, leading to certain goods being unavailable. By asking, “What’s this got to do with that?” we nudge students to go both deep and wide in an investigation.

Strategies for Teaching systems thinking

Many strategies for systems thinking encourage students to visualize and create “system pictures.” Because of the high degree of interaction within systems, many strategies invite students to map connections in nonlinear ways. Here are some concrete strategies we can use in the classroom.

Connected circles: In this strategy, a circle represents a particular system, and the parts of the system are written around the outside. Using a case study such as an article, video, or real-life experience, students chart connections across the parts of the circle, writing the relationship between parts on the connector line. A connected circles template can be modified for any system that students will explore.

Systems models: After researching a system such as a tropical rainforest or coral reef, students create a systems model using divergent physical materials, e.g. Lego, magnetic tiles, wooden blocks, paper, cotton balls, shells, stones, etc. After making representations of the system and its parts, students annotate the model with sticky notes, arrows, etc. to show relationships between them. This may also include inputs and outputs of the system. For example, sunlight and carbon dioxide go into the rainforest (inputs), and oxygen and water vapor come out (outputs).

Games and simulations: Matthew Farber has written extensively about the use of constructionist gaming to promote thinking about complex systems. He shows how making and thinking come together to allow students to play with systems. The Joan Ganz Cooney Center at Sesame Workshop also writes about the role of digital learning to promote understanding of systemic causes in young children. 

By inviting students to play with and explore systems thinking tools, we enable them to see structures and patterns within and across the content areas. Such engagements can empower students to find solutions to local, global, and intercultural issues that may have previously seemed unsolvable.

Systems thinking to transform schools: Identifying levers that lift educational quality

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Bruce fuller and bruce fuller sociologist - university of california, berkeley, author - "when schools work" (2021) hoyun kim hoyun kim ph.d. student - berkeley school of education.

September 12, 2022

The United Nations has set forth an ambitious vision for education systems around the globe: cultivating lifelong learning from early childhood through an individual’s civic and work life. Schools must support children and youth in basic learning—including crucial socio-emotional, literacy, and numeracy competencies—to contribute to sustainable societies. State-run education systems and their communities must now engage these global goals by 2030.

But in the wake of the global pandemic, virtually every country in the world is far behind. Prior to the pandemic, a severe learning crisis held back hundreds of millions of children. Analysts project that 9 out of 10 children in low-income countries and 5 out of 10 in middle-income countries will not develop core secondary education skills in literacy and numeracy by 2030. The pandemic has only deepened the learning crisis and widened achievement gaps.

By crisply defining what systems entail in the education sector and which levers yield organizational change, education leaders and their partners can do better in rethinking the aims of schooling and raising student achievement.

Specific country cases remain distressing: More than half of fifth grade students in India are not proficient in second-grade literacy. In Nigeria, just 1 in 10 girls completing grade six can read a single sentence in their native language. In the United States, children of African-American or Latino heritage attending fourth grade read at two grade levels below white peers on average.

Beyond deepening inequality in foundational learning, calls to rethink the underlying aims of education grow louder and more urgent. The next generation’s future—marked by global warming, fragile economic sustainability, and worsening inequality—requires new skills and wider awareness, too often poorly addressed in classrooms around the globe. The digital revolution has already shifted what and how children learn and explore and the knowledge pathways they maneuver—a radical change that many education systems fail to harness to advance learning.

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Against this evolving backdrop, the global education community—catalyzed by the U.N. Secretary General’s Transforming Education Summit (September 2022)—is looking past recovering from the pandemic to consider full-scale system transformation. This blossoming policy discourse is replete with hopes for radically improving and transforming education systems. But how to define educational systems and then reshape them remains poorly defined. We cannot merely utter this ambitious goal without precisely defining how to surround the system, identify potent levers for change, and rethink the aims and means of human learning on a fragile planet.

INFORMING POLICY DEBATES

This brief informs these discussions of system transformation by reviewing the historical roots of systems thinking and what they contribute to education reform. It draws primarily on the intellectual traditions and literature in the Global North but also illustrates how these ideas have traveled to the Global South, in part through the work of organizations such as the World Bank. We recognize how elements of education systems may unfold quite differently across diverse societies—for example, rethinking how teachers are prepared and motivated to recast what students are expected to learn—and can draw from a range of cultural traditions. Our goals are simply to lift up how we think about systems and harness their strengths to rethink what children should learn and how classrooms and communities can better motivate achievement and civic engagement.

The brief is arranged in the following four sections:

• A short history of systems thinking, emphasizing the pressure points or organizational levers inside the education institution that touch classrooms.
• How systems thinking moved into the education sector (from biology and mechanics), along with how differing versions of systems reform take root and are conceptualized.
• Clarifying the various concepts and pathways associated with systems thinking in the education sector.
• Concluding reflections, informing how education leaders might interrogate system improvement and transformation efforts.

We summarize cases around the globe where systems thinking has yielded discernible gains for students and teachers. By crisply defining what systems entail in the education sector and which levers yield organizational change, education leaders and their partners can do better in rethinking the aims of schooling and raising student achievement.

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LOOKING BENEATH THE SURFACE

The Education Changemaker’s Guidebook to Systems Thinking

• Topics: Systems Change

Systems thinking can be a powerful element of systems change, no matter whether we decided to pursue transition or it was thrust upon us.

Systems thinking can help us grapple with the complex and interconnected world around us and make visible our own perceptions of how it works. Ultimately, it can help us deepen our understanding of what stands between us and our aspirational visions and articulate what it might take to bring those visions to reality.

This guidebook introduces education stakeholders and changemakers to the theories, language, mindsets and tools of systems thinking for the purpose of informing approaches to systems change. The content is organized into four lessons that introduce core concepts of systems thinking and include practice questions and exercises.

• Lesson 1: Framing the Focus of a Systems Problem Setting the scope of a systems exploration and identifying systems behavior that stakeholders wish to change
• Lesson 2: Visualizing the Structure of a Systems Problem Drawing the components and interactions related to a problem that stakeholders agree is important
• Lesson 3: Looking for Leverage to Create Change Identifying possible actions and their potential depth of impact on the systems problem being explored
• Lesson 4: Anticipating Futures of a Systems Problem Evaluating the effects of various interventions or events on a systems problem and the larger system in which it sits

Systems thinking tools and processes help groups identify novel, non-obvious solutions and reframe problems. They serve as gateways to new ways of thinking and collaborating and can help groups begin the journey toward transformation. Begin your transformation with our guidebook.

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What Is Systems Thinking?

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• Laura Cabrera 4  

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This chapter provides a brief overview and understanding of the historical evolution of the field of systems thinking, which has been characterized as occurring in three waves, the last of which recognized a plurality of methods and approaches. In the last decade, a fourth wave has emerged that is based on four simple cognitive tasks or “rules” – making distinctions and recognizing systems, relationships, and perspectives (DSRP). These four rules combine in infinitely complex ways to produce the emergent property of systems thinking. They underlie and serve to integrate the diverse methods and approaches of systems thinking. Applying DSRP is a new skill that extends and enhances popular systems thinking tools and approaches. DSRP provides a common language and analytical method to span the multiple subfields that have often worked in isolation, allowing the tremendous pluralism in systems thinking to exist alongside universality. Importantly, the simplicity of the DSRP rules makes it far easier to teach and learn systems thinking. The fourth wave makes systems thinking more accessible than ever before, as DSRP cognitive skills can be taught to individuals at all levels in all disciplines. The corollary development of systems modeling techniques are accessible ways to capture and measure one’s progress in developing the skills required for systems thinking. The historical overview and description of where the field is headed will provide context for an introduction to the role of systems thinking in human and organizational development and in particular the relevance for educational systems.

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Cabrera, D., Cabrera, L. (2023). What Is Systems Thinking?. In: Spector, M.J., Lockee, B.B., Childress, M.D. (eds) Learning, Design, and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-17727-4_100-2

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DOI: https://doi.org/10.1007/978-3-319-17727-4_100-3

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By: MIT xPRO on September 14th, 2022 5 Minute Read

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Ask an MIT Professor: What Is System Thinking and Why Is It Important?

Professional Development | Leadership | Systems Thinking

System Thinking Is the Cognitive Skill of the 21st Century

Look around you, and you’ll see: life as we know it is becoming more and more complex. 

From the iPhone in your pocket to the organizations driving public health, national defense, finance, criminal justice, and [insert just about anything else you can imagine], the world is powered by increasingly intricate systems working behind the scenes to integrate countless moving pieces into a meaningful whole. 

“One of the characteristics of the 21st century is that we’re investing more in complexity, and things are just getting damn complicated,” says Professor Edward Crawley , Ford Department of Engineering, Department of Aeronautics and Astronautics, MIT. 

Professor Crawley is one of the MIT lead faculty instructors for MIT xPRO’s online course on system thinking , a skill that helps organizations examine and simplify complexity, recognize patterns, and create effective solutions to challenges. He considers system thinking “ the cognitive skill of the 21st century.” We recently sat down with Professor Crawley to discuss system thinking and what learners can expect from his course. 

What is system thinking? 

Professor Crawley explains that “system thinking is simply thinking about something as a system: the existence of entities—the parts, the chunks, the pieces—and the relationships between them.” 

There are measures of both performance and complexity in system thinking. “Complexity is what we invest in: more parts, more sophisticated parts, more parts talking to more parts,” Professor Crawley states. “Performance is the benefit that emerges.” 

Who uses system thinking, and how might they use it?

“System thinking is for everyone on this side of the life-death line,” Professor Crawley jokes. Anyone who has taken a course he teaches will tell you that he has an excellent sense of humor.

More specifically, system thinking is broadly used by:

• Leaders who have a high-level view of how different parts of a system fit together and need to be able to step back and see how all the pieces connect.
• Individual contributors who want to understand how the part they’re responsible for fits into the bigger picture so that they can perform at their highest potential.

In a professional setting, leaders and individual contributors use system thinking all the time to understand: 

• How organizations work (e.g., team dynamics) 
• Complex technologies (e.g., smartphones and other devices) 
• The optimal ways to track, organize, and utilize information (e.g., medical records) 
• Intricate processes (e.g., the tax system: who pays taxes, how much they pay, and how the revenue is distributed)

Professor Crawley specializes in using system thinking to understand the space system, exploring the answers to questions like: Who builds the satellites? What orbits are they in? How do they communicate with each other? How can humans produce brilliant images like those from the James Webb Space Telescope ? “Those images are an example of an emergent value proposition that resulted from NASA’s multi-year effort on the James Webb Space Telescope,” remarks Professor Crawley. 

What pedagogical methods and tools do you use to get learners comfortable with system thinking?

The big challenge in being one of the faculty instructors for MIT xPRO’s system thinking course, explains Professor Crawley, is using examples that exhibit just the right amount of complexity. The systems need to be complicated enough that the answers aren’t too obvious but not so complicated that no one can understand how they work, even after learning the tools for system thinking. 

Professor Crawley prefers using examples that he categorizes as “middle-complexity systems that people commonly encounter in their lives.” One example is a bicycle. If a rollerblade is too simple and an automobile is overly complex, a bicycle is just right. “You want to train your mind and train your methodology to think about automobiles, but it’s a hard place to start,” says Professor Crawley. “So you start with the middle-complexity system.” 

Professor Crawley uses these types of examples to teach students:

• The principles underlying the system
• The methods used to think about the system
• The concrete tools that system thinkers activate each day 

What are some challenges learners face during a system thinking course? 

Nevertheless, getting comfortable with system thinking can be extraordinarily challenging for learners! Why? Because system thinking is, in essence, an entirely new way of thinking. 

“You’re literally neurologically tuning up your brain. You’re creating connections between neurons that didn’t exist before because you’re developing new neural pathways that allow you to think about things differently,” states Professor Crawley. 

“I tell my class at MIT at the beginning of the term, ‘I predict that within a week or two, you’ll have headaches,’” he says with a grin. “They look at me and laugh. But sure enough, I check in with them two weeks later, and I’m right.” 

What would you say to someone considering enrolling in a system thinking course? 

“You’ll get over the headaches once the brain is rewired,” Professor Crawley jokes. 

On a serious note, Professor Crawley encourages students to take a system thinking course because learning a new way of thinking about the world is of vital importance in the 21st century. 

“Life is only getting more complex,” he says. If you see him in person, ask him to tell the story about how he and a colleague—two actual rocket scientists—couldn’t figure out how to make a photocopy. “That was two decades ago, and already technology was so complex that you had to be trained to operate it!” he exclaims. 

With devices and organizations becoming ever more complicated, system thinking can give learners the skills to succeed.

Those skills include being able to engage in the unknown and think differently about the relationships between the parts that make up a system; ultimately, learners evolve from reductionist thinkers to integrative thinkers ready to face a limitless future. 

If you’d like the opportunity to learn from Professor Crawley, as well as Professors John Sterman, Daniela Rus, and Hasma Balakrishnan, enroll in MIT xPRO’s 5-week online system thinking course . 

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Systems Thinking: What, Why, When, Where, and How?

I f you’re reading The Systems Thinker®, you probably have at least a general sense of the benefits of applying systems thinking in the work-place. But even if you’re intrigued by the possibility of looking at business problems in new ways, you may not know how to go about actually using these principles and tools. The following tips are designed to get you started, whether you’re trying to introduce systems thinking in your company or attempting to implement the tools in an organization that already supports this approach.

What Does Systems Thinking Involve?

Tips for beginners.

• Study the archetypes.
• Practice frequently, using newspaper articles and the day’s headlines.
• Use systems thinking both at work and at home.
• Use systems thinking to gain insight into how others may see a system differently.
• Accept the limitations of being in-experienced; it may take you a while to become skilled at using the tools. The more practice, the quicker the process!
• Recognize that systems thinking is a lifelong practice

It’s important to remember that the term “systems thinking” can mean different things to different people. The discipline of systems thinking is more than just a collection of tools and methods – it’s also an underlying philosophy. Many beginners are attracted to the tools, such as causal loop diagrams and management flight simulators, in hopes that these tools will help them deal with persistent business problems. But systems thinking is also a sensitivity to the circular nature of the world we live in; an awareness of the role of structure in creating the conditions we face; a recognition that there are powerful laws of systems operating that we are unaware of; a realization that there are consequences to our actions that we are oblivious to. Systems thinking is also a diagnostic tool. As in the medical field, effective treatment follows thorough diagnosis. In this sense, systems thinking is a disciplined approach for examining problems more completely and accurately before acting. It allows us to ask better questions before jumping to conclusions. Systems thinking often involves moving from observing events or data, to identifying patterns of behavior overtime, to surfacing the underlying structures that drive those events and patterns. By understanding and changing structures that are not serving us well (including our mental models and perceptions), we can expand the choices available to us and create more satisfying, long-term solutions to chronic problems. In general, a systems thinking perspective requires curiosity, clarity, compassion, choice, and courage. This approach includes the willingness to see a situation more fully, to recognize that we are interrelated, to acknowledge that there are often multiple interventions to a problem, and to champion interventions that may not be popular (see “The Systems Orientation: From Curiosity to Courage,”V5N9).

Why Use Systems Thinking?

Systems thinking expands the range of choices available for solving a problem by broadening our thinking and helping us articulate problems in new and different ways. At the same time, the principles of systems thinking make us aware that there are no perfect solutions; the choices we make will have an impact on other parts of the system. By anticipating the impact of each trade-off, we can minimize its severity or even use it to our own advantage. Systems thinking therefore allows us to make informed choices. Systems thinking is also valuable for telling compelling stories that describe how a system works. For example, the practice of drawing causal loop diagrams forces a team to develop shared pictures, or stories, of a situation. The tools are effective vehicles for identifying, describing, and communicating your understanding of systems, particularly in groups.

When Should We Use Systems Thinking?

Problems that are ideal for a systems thinking intervention have the following characteristics:

• The issue is important.
• The problem is chronic, not a one-time event.
• The problem is familiar and has a known history.
• People have unsuccessfully tried to solve the problem before.

Where Should We Start?

When you begin to address an issue, avoid assigning blame (which is a common place for teams to start a discussion!). Instead, focus on items that people seem to be glossing over and try to arouse the group’s curiosity about the problem under discussion. To focus the conversation, ask, “What is it about this problem that we don’t understand?”

In addition, to get the full story out, emphasize the iceberg framework. Have the group describe the problem from all three angles: events, patterns, and structure (see “The Iceberg”). Finally, we often assume that everyone has the same picture of the past or knows the same information. It’s therefore important to get different perspectives in order to make sure that all viewpoints are represented and that solutions are accepted by the people who need to implement them. When investigating a problem, involve people from various departments or functional areas; you may be surprised to learn how different their mental models are from yours.

How Do We Use Systems Thinking Tools?

Causal Loop Diagrams. First, remember that less is better. Start small and simple; add more elements to the story as necessary. Show the story in parts. The number of elements in a loop should be determined by the needs of the story and of the people using the diagram. A simple description might be enough to stimulate dialogue and provide a new way to see a problem. In other situations, you may need more loops to clarify the causal relationships you are surfacing.

THE ICEBERG

The Archetypes. When using the archetypes, or the classic stories in systems thinking, keep it simple and general. If the group wants to learn more about an individual archetype, you can then go into more detail. Don’t try to “sell” the archetypes; people will learn more if they see for themselves the parallels between the archetypes and their own problems. You can, however, try to demystify the archetypes by relating them to common experiences we all share.

How Do We Know That We’ve “Got It”?

Here’s how you can tell you’ve gotten a handle on systems thinking:

• You’re asking different kinds of questions than you asked before.
• You’re hearing “catchphrases” that raise cautionary flags. For example, you find yourself refocusing the discussion when someone says, “The problem is we need more (sales staff, revenue).”
• You’re beginning to detect the archetypes and balancing and reinforcing processes in stories you hear or read.
• You’re surfacing mental models (both your own and those of others).
• You’re recognizing the leverage points for the classic systems stories.

Once you’ve started to use systems thinking for inquiry and diagnosis, you may want to move on to more complex ways to model systems-accumulator and flow diagrams, management flight simulators, or simulation software. Or you may find that adopting a systems thinking perspective and using causal loop diagrams provide enough insights to help you tackle problems. However you proceed, systems thinking will forever change the way you think about the world and approach issues. Keep in mind the tips we’ve listed here, and you’re on your way!

Michael Goodman is principal at Innovation Associates Organizational Learning

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Student Researcher Examines Effectiveness of 'Systems Thinking' Teaching Approach in Chemical Education

New approach aims to amplify students' critical thinking powers and tie learning to real-world applications.

August 8, 2024 | By Brenda Gillen

In his second semester in the University of Northern Colorado's Chemical Education Ph.D. program , Navid Ahmed Sadman has already discovered his passion. He's researching the effectiveness of educating future chemists differently using a "systems thinking" approach. Systems thinking is both a philosophical and practical method that views problems holistically and considers the interconnectedness of a system's components.

It's far from the culture of rote memorization method Sadman experienced as a chemistry undergraduate in Bangladesh.

"...in systems thinking, instead of discrete components, it's looking at our whole world and how all its parts work together. The next generation of policymakers or scientists need that more complex picture." — Navid Ahmed Sadman

"The focus was on memorizing the answers to the questions that would repeat year after year in the examination. I think that despite being taught by well-trained faculty, only the top students in my country can get the mental scope of understanding the concepts after they have memorized them. For most others, perhaps cramming before an examination is only as far as they could or would go. Don't get me wrong, students emerging from this culture are still pursuing higher studies in droves, but still, our education policymakers should critically appraise and improve the country’s education system while being aware of the current culture, students' accessibility to resources, and their financial capabilities.

"This emphasis on memorization bothered me as a student; and now, as an instructor, I see that memorization makes students question chemistry's relevance. We need to train chemistry students better at the undergraduate level. That's why I am more and more invested in the chemistry education field," he said.

He believes a systems thinking approach to teaching chemistry will amplify students' critical thinking powers and tie learning to real-world applications.

"If students are learning about global warming, in general chemistry they are taught about carbon dioxide and its environmental implications. In industrial chemistry, carbon capture and human interventions are covered. In environmental chemistry, topics finally include climate change and its impacts. But in systems thinking, instead of discrete components, it's looking at our whole world and how all its parts work together. The next generation of policymakers or scientists need that more complex picture," Sadman said.

He offered the example of electric vehicles (EVs). While EVs are a promising solution to reducing carbon emissions, he noted that mining for metals like cobalt and rare earth elements, essential for EV batteries, can have significant social and environmental impacts if not properly monitored. A systems thinking approach will enable scientists to address these issues adequately, ensuring EVs' benefits are realized while mitigating negative consequences.

Such changes to chemical education would have a wide-ranging impact because different fields, e.g., pre-med, pre-nursing, health, biology and physics majors all take chemistry courses. As part of a graduate-level introduction to qualitative research course at UNC, he completed a mini-project to better understand student perceptions of systems thinking in chemistry education (STICE), which is an identified research gap. Next, he'll test the premises for incorporating STICE using a mixed-methods approach that includes quantitative and qualitative data.

"I'm also planning a systematic review of the literature on STICE. This will be a more comprehensive study, which would add depth to the growing body of literature," he said.

Sadman received feedback from his peers when he shared his early findings on this systematic review at the December 2023 Graduate Research Symposium. He believes the statistics, psychology and science education courses required for his Ph.D. will shape his understanding and development of his doctoral research project.

He's working as a research assistant this summer. For most of the year, he's a teaching assistant in the Department of Chemistry and Biochemistry for Assistant Professor Corina Brown .

"I'm learning a lot from working with Dr. Brown. She's kind and personable," he said.

Brown said Sadman's enthusiasm, motivation and sincere desire to learn have made mentoring enjoyable

"Even though Navid is in the beginning stages of his doctoral studies, he's working on a cutting-edge topic. The interdisciplinary nature of the systems thinking approach could allow students to comprehend and apply chemical concepts in novel ways. His research contributes to expanding the understanding, application and assessment of systems thinking in chemical education. I think he has a promising journey ahead with the potential to make significant contributions to research and education," Brown said.

After he graduates in 2027, Sadman hopes to pursue a post-doctoral degree. Eventually, he'd like to join academia as a chemistry education researcher or work at a research institute focused on chemistry education.

"I also feel I owe it to my country to return with the knowledge I have gathered here and contribute there. Ask me again in three years about my future plans," he said.

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Systems leadership case study: workplanning using systems thinking.

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Thomas Lim is the Vice-Dean of Centre for Systems Leadership at SIM Academy. He is an AI+Web3 practitioner & author of Think.Coach.Thrive!

Workplanning usually involves a confluence of top-down and bottom-up approaches in many organizations. Some broad annual guidance is given by the CEO, with Finance providing a budget forecast based on historical data and the strategic imperatives for the new fiscal year. The line divisions then prepare and present a list of initiatives that purportedly contribute to these imperatives and justify their budget-ask.

This generally works in stable environments where the workplanning objectives are incremental as part of a longer five-year duration, but it may be inadequate in managing transformation efforts with the need for new systemic structures due to the merging or dissolving of functional areas within the organization.

Systems thinking provides a holistic approach to understanding and managing complex systems from the current reality to a desired outcome, making it an ideal tool for recasting workplans to enhance efficiency and effectiveness.

In the case of Client X, they aimed to leverage systems leadership practices to transform internally and propagate these practices first across its internal divisions, with the goal of taking it to the ecosystem at large. This article outlines a high-level approach to recasting the workplan using systems thinking tools, which has helped Client X align its initiatives, identify gaps and overlaps and achieve strategic objectives.

Best High-Yield Savings Accounts Of 2024

Best 5% interest savings accounts of 2024, what is systems thinking.

Systems thinking is an approach to problem-solving that views "problems" as parts of a unified whole. It involves understanding how different parts of a system interact and influence each other within the system. Unlike traditional linear thinking, systems thinking considers the broader context and the interconnections within the system and provides a systems map wherein these interactions are perceived as system-to-system, subsystem-to-subsystem or component-to-component.

In the case of Client X, adopting systems thinking means moving away from siloed operations and toward a more integrated and cohesive approach whereby a division’s work is mapped against another for synergistic outcomes. This can help the organization address complex challenges, improve decision-making and foster innovation by removing duplication and identifying implementation gaps.

Recasting The Workplan

The workplan recasting effort begins with "taking apart" the current work streams, not along the divisions’ lines of work but from an overall organizational lens. The leaders participating in this exercise have already been trained in the fundamentals of systems thinking tools. The three-day effort is about applying the systems concepts to model Client X’s journey from its current reality to its desired outcome through its articulated theory of success. The three-day session revolves around these workpieces both at the organizational level and at each strategic level:

1. Align And Select Tools/Models: Select the appropriate systems models and frameworks to guide the recasting process.

2. Apply Systems Thinking Practices: Rework existing work streams of the workplan as layers of interaction across nested hierarchies for each strategy.

3. Identify Interconnectedness: Understand how various initiatives are interconnected and the causal loops that would guide the process.

4. Identify Gaps And Overlaps: Detect any gaps and overlaps in the initiatives to optimize efforts and budgetary choices.

The specific steps that the team undertook during the three-day process included the following.

Step 1: Articulate Vision And Current Reality

Begin by clearly defining the vision and the current reality of the organization. This involves understanding the structural gap between where Client X is and where it wants to be. This step helps in identifying the key challenges and opportunities.

Step 2: Recast Workplan As A Nested Hierarchy Of Choices

Recast the workplan as a nested hierarchy of choices to ensure that decisions at every level are aligned and relevant. This helps in clarifying the strategic intent and who is responsible for what and aids in surfacing gaps and duplications, enabling better resource allocation and prioritization.

Step 3: Cluster Use Cases, And Prioritize Challenge Statements

Cluster the use cases, and prioritize the top three challenge statements that need to be addressed. This focuses the efforts on the most critical issues and ensures that resources are used effectively.

Step 4: Work On Chosen Challenge Statements

The selected challenge statements are put through using the levels of perspective "walk-up" framework to surface and test mental models for diagnosis. This helps in understanding the underlying assumptions and beliefs that drive current behaviors and outcomes.

Step 5: Create A Theory Of Success

Develop a theory of success that identifies the key levers at higher leverage for achieving the desired outcomes from key success factors. This provides a clear road map for action and helps in aligning efforts across the organization.

Step 6: Co-Create A Walk-Down Of The Levels Of Perspective

Collaborate with stakeholders to create a walk-down of the levels of perspective. This step aligns the challenge statement and diagnosis with a related growth strategy, ensuring that all efforts are coherent and strategic.

By integrating systems thinking into the recasting of its workplan, Client X was able to achieve a more cohesive, efficient and effective approach to its initiatives. The workplan was still central in execution, but it is now reinforced and streamlined for internal alignment in a way that was not possible before overlaying the systems thinking perspectives.

This approach can be extrapolated to enable other organizations to address complex challenges, optimize resource allocation and drive strategic outcomes. A coaching reinforcement can additionally be put in place to ensure that these practices are deeply embedded within the organization, leading to sustained transformation and growth.

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Research Article

Research on comprehensive evaluation & development of aesthetic education based on PCA and CEM model

Roles Writing – original draft

Affiliation School of Art, Anhui University of Finance and Economics, Bengbu, China

Roles Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

Roles Conceptualization, Data curation, Funding acquisition

Affiliation Graduate School, Hankuk University of Foreign Studies, Seoul, Korea

Roles Investigation, Methodology, Project administration

Affiliation School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, China

Roles Project administration, Resources, Software

• Xin-Hong Xu, 
• Yu-Ting Niu, 
• Zhi-Min Li, 
• Yue-Yang Xu, 
• Ke-Wang Cao

• Published: August 9, 2024
• https://doi.org/10.1371/journal.pone.0308446
• Reader Comments

Aesthetic education, conveyed through public art courses, serves as a vital form of humanistic literacy education. It represents an effective approach to fostering innovative and creative thinking among college students. In order to effectively analyze the aesthetic education work of 46 universities, an aesthetic education index evaluation system is constructed, involving indicators including faculty strength, curriculum setting, teaching management, artistic practice, and teaching support. The secondary indicators corresponding to the five indicators are statistically analyzed, and a comprehensive evaluation analysis of the current development status of aesthetic education in 46 universities in Anhui Province is conducted by combining theoretical analysis with empirical analysis. Based on principal component analysis, an integrated evaluation model for the development of aesthetic education in universities in Anhui Province is further constructed. The model designed quantifies the influence weight of each aesthetic education index on the development of aesthetic education in Anhui Province, and forges a theoretical basis for determining the precursors of rapid development of aesthetic education in Anhui Province. Additionally, a novel approach is introduced to gauge the progression of aesthetic education within universities in Anhui Province, considering the dispersion of aesthetic education index data across the province. The comprehensive evaluation model for the development of aesthetic education in Anhui Province exhibits an overall declining trend. Hence, it is suggested to utilize the maximum value of the first derivative of the comprehensive evaluation model as an indicator of the imminent rapid development of aesthetic education in Anhui Province. On this basis, the probability equation of sustainable development of aesthetic education in Anhui Province is defined. Overall, the research results lay a theoretical foundation for the development of aesthetic education in Anhui Province.

Citation: Xu X-H, Niu Y-T, Li Z-M, Xu Y-Y, Cao K-W (2024) Research on comprehensive evaluation & development of aesthetic education based on PCA and CEM model. PLoS ONE 19(8): e0308446. https://doi.org/10.1371/journal.pone.0308446

Editor: Mc Rollyn Daquiado Vallespin, Far Eastern University - Manila, PHILIPPINES

Received: April 11, 2024; Accepted: July 23, 2024; Published: August 9, 2024

Copyright: © 2024 Xu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data are fully available without restriction.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Aesthetic education, also referred to as aesthetic or art education, holds significant importance within higher education. It typically pertains to undergraduate programs lasting four or five years, excluding vocational and technical colleges, as well as graduate education for the time being. Based on the National General Art Education Curriculum Guidelines 2006 and the Opinions on Solidly Improving the Aesthetic Education Work in Colleges and Universities in the New Era 2020 [ 1 , 2 ], the results of aesthetic education in colleges and universities over the past 15 years indicate that on the one hand, aesthetic education in colleges and universities is still in the stage of theoretical exploration and practical education, while on the other, there is no feasible evaluation system available for the actual effect of aesthetic education. This results in an imbalance between excessive aesthetic education theory and the lack of evaluation system.

According to relevant documents such as China’s National Medium-to-Long-Term Education Reform and Development Plan 2010–2020 [ 3 ], Opinions on Comprehensively Strengthening and Improving Art Education in Schools [ 4 ], and Regulations on Art Education Work in Schools [ 5 ], this article examines 46 undergraduate universities in Anhui Province, adhering to principles of scientificity, comprehensiveness, and hierarchy. Meanwhile, it employs reverse reasoning and considers multiple observation points such as faculty strength, curriculum design, teaching management, artistic practice, and teaching support. Through the utilization of methods like principal component analysis, entropy weight method, and BP neural network method, the article offers a comprehensive evaluation of the current state of aesthetic education in universities in Anhui Province. Additionally, it highlights future challenges that need to be addressed.

2. Literature review

Aesthetic education is an education that cultivates people’s aesthetic perception, appreciation, creativity, and judgment. It holds irreplaceable significance in the higher education system, and presents long-term effectiveness, strong infectiousness, and transcends time, space, and ethnic and national aesthetic universality. Plato advocated for the cultivation of citizens in both body and mind as the ultimate goal of education, while Confucius emphasized the importance of poetry and music education as primary avenues for aesthetic education. Indeed, aesthetic education is an emotional education that concerns people mentality and personality development. When individuals are in crisis and pressure, aesthetic education can furnish them with a balanced, stable, and positive attitude to life [ 6 ]. Filipović and Vojvodić [ 7 ] believed that aesthetic education provides opportunities for students’ creative ability, creative communication ability, and aesthetic ability development, thereby affecting their personality emancipation and all-round development. In this way, art education makes people the most humanized and complete individual [ 8 ]. The implementation of aesthetic education in universities primarily involves utilizing public art courses as the foundation of art education. It centers on art works within the context of art history as the core content of the educational process. Art education refers to the education of music, dance, drama and visual arts disciplines [ 9 ]. Specifically, art encompasses various forms, including visual arts such as painting, drawing, sculpture, filmmaking, architecture, photography, and ceramic art. Additionally, it includes literary arts such as poetry, drama, prose, and novels, as well as performing arts like drama, dance, and music [ 10 ]. According to the National Common Propaganda on Public Art Education in Colleges and Universities in China , public art courses refer to those emphasizing aesthetics, art history and theory, art appreciation, and artistic practice represented by music, dance, painting, calligraphy, drama, film and television.

From the perspective of function and method of aesthetics, reconstructing STEM education by integrating art education is a way to implant art education [ 11 ]. STEAM combines science, technology, engineering, art, and mathematics education [ 12 ]. Meanwhile, art education can enhance students’ innovation ability and promote the cultivation of comprehensive innovative talents [ 13 ]. Scientific work requires creativity and critical thinking, while art and science mutually inspire each other in a subtle and covert way [ 14 ]. Wang and Zeng [ 15 ] believed that imaginative thinking ability is a kind of creative thinking ability, which is not only the core of art but also the key to scientific research. However, it is a challenge to scientifically evaluate the actual function of art in STEAM education from the student-centered perspective [ 16 ]. Teachers should have good adaptive teaching abilities to ensure that the aesthetic effect of public art courses is achieved [ 17 ]. In order to shift from the traditional aesthetic evaluation model centered on teachers, classrooms, and textbooks, a more student-centered approach can be adopted. This involves conducting aesthetic ability evaluations based on indicators such as artistic cultural knowledge and skills, artistic abilities, and artistic achievements. However, despite these efforts, the evaluation may still exhibit some bias towards a student-centered perspective [ 18 ]. In 2018, in order to construct a comprehensive evaluation system for higher education aesthetic education, Shandong Province established an evaluation index system for higher education aesthetic education work from five dimensions of curriculum design, teaching management, teacher team, artistic practice, and condition guarantee [ 19 ]. Only by adopting a more student-centered approach to aesthetic education evaluation can the aesthetic development of universities in the province truly benefit.

3. Comprehensive evaluation analysis

3.1 construction of the comprehensive evaluation index.

Aesthetic education as an educational phenomenon can be described, measured, calculated, and analyzed to help depict the quality of aesthetic education. Observing, describing, or researching the development of aesthetic education in various universities in Anhui Province aids in cultivating a reasoned comprehension of its status, distinctive features, and operational mechanisms. Comprehensive evaluation serves as a quantitative empirical method enabling the comparison of research objects through evaluation outcomes. Evaluating and comparing the progress of aesthetic education in universities across Anhui Province necessitates the establishment of a viable comprehensive evaluation index system, which should adhere to the following four principles:

The first principle is systematicity, where various indicators have logical relationships, reflecting the main characteristics and status of the overall system of aesthetic education from different aspects. The second is the principle of typicality, which emphasizes that indicators should possess certain representative characteristics to comprehensively reflect the current development status of aesthetic education. Selected indicators should have the capacity to guide the evaluation process effectively. The third principle involves independence, where the interaction of indicators within the system manifests as the characteristics of subsystems. The evaluation index system of aesthetic education includes independent subsystems reflecting teacher conditions, curriculum settings, teaching management, practical results, and teaching guarantees. The fourth principle encompasses comparability, operability, and quantifiability. The index system utilizes existing data and standards, ensuring consistency in the calculation methods and measurement of indicators. The indicators should be as concise as possible, with strong micro-level characteristics, easy to collect, and quantifiable.

Aesthetic education quality evaluation entails a comprehensive assessment and acknowledgment of the situation, processes, methods, objectives, and outcomes of education. This contributes significantly to the management, supervision, and enhancement of the quality and standard of education [ 20 ]. The evaluation of aesthetic education involves complexity and multidimensionality. A single indicator is far from sufficient to comprehensively and typically reflect its characteristics. Therefore, constructing a comprehensive evaluation index system requires decomposition, summarization, and refinement from multiple attributes, perspectives, and features [ 21 ]. Drawing on normative documents and prior scholarly research, an evaluation index system for the advancement of aesthetic education in universities within Anhui Province is hereby formulated, which comprises five sub-dimensions, i.e., teacher qualifications, curriculum design, teaching management, artistic practice, and teaching support, as delineated in Table 1 .

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https://doi.org/10.1371/journal.pone.0308446.t001

3.2 Data source and processing

To measure the development of aesthetic education in universities in Anhui Province, while ensuring the authenticity, validity, and accessibility of data, a variety of sources can be utilized. These may include annual reports on art development from each university, public documents from the Anhui Provincial Department of Education, official documents from each university’s website, and publications like the China Education Statistical Yearbook . These sources can be organized and compiled to form original cross-sectional data with a time variable set to 2020 for empirical analysis.

In a multi-indicator evaluation system, each indicator often varies in units and magnitudes due to their different nature. To address this, raw data undergo preprocessing, involving standardization and quantification of qualitative indicators. This ensures that all indicator values are on a uniform scale, facilitating comprehensive evaluation analysis.

This formula standardizes the raw data x nm , k for each indicator across all schools and years, ensuring comparability across different indicators.

3.3 Method description

In comprehensive evaluations, utilizing different methods provides analyses from various perspectives. To overcome the many differences in preference and adaptability inherent in single comprehensive evaluation methods, employing multiple evaluation methods is essential, followed by the integration of results [ 22 ]. This paper takes the 46 universities in Anhui Province as samples, constructs an indicator system, and summarizes and analyzes the development of aesthetic education in each university. Methods such as the entropy method, BP neural network method, and principal component analysis method are employed, followed by a combined evaluation approach.

The Back Propagation (BP) neural network comprehensive evaluation method offers a comprehensive and interactive approach. It effectively bypasses the inaccuracies associated with manually assigning weights and the complexities of solving correlation coefficients. Moreover, it enables comprehensive evaluation of instances with large quantities and numerous indicators [ 24 ]. The BP neural network is an artificial neural network composed of input, hidden, and output layers. The input layer nodes only receive signal inputs, while the output layer nodes perform linear weighting, and the hidden layer nodes primarily handle the most significant mathematical processing of information. During forward propagation, training samples traverse through the input layer, followed by the hidden layer, and finally to the output layer. If the output results fail to meet the expected output, the process will enter the backpropagation stage. Herein, the weights and thresholds of each neuron are continuously adjusted based on the set prediction error until approaching the expected output. The aesthetic education development in Anhui Province’s universities is assessed by inputting indicators from teacher qualifications, curriculum design, teaching management, artistic practice, and teaching support subsystems into Python. Leveraging the potent nonlinear mapping capability of BP neural networks, the data undergo iterative learning and optimization for a comprehensive evaluation.

Principal Component Analysis (PCA) is a multivariate statistical analysis method that reduces the dimensionality of data by linear transformation to select a smaller number of important variables. The basic idea is to recombine the original set of correlated indicators into a smaller set of uncorrelated composite indicators F m to replace the original indicators.

The above equation satisfies that F i and F j are uncorrelated, that is, cov( F i , F j ) = 0, and have nonzero covariances. F i is the linear combination of X 1 , X 2 , X 3 …. X p with the largest variance, that is, it is the combination of all linear combinations that are uncorrelated with each other and have the largest variance. It is constructed as the new variable indicator, namely the first, second,…, mth principal component of the original variable indicators. In practical applications, the specific steps of using Principal Component Analysis (PCA) are as follows: to standardize the original data; to calculate the covariance matrix; to find the eigenvalue λ i of R and the corresponding eigenvector a i of the orthogonalized unit; and to select principal components: through m in F 1 , F 2 , F 3 ….. F m is determined by the cumulative variance contribution rate G m .

Scores of aesthetic education in universities in Anhui Province are calculated, Principal Component Analysis is conducted using the Sklearn toolkit in Python, with the cumulative variance contribution rate set to be greater than 80%, and the scores for each university are finally computed.

3.4 Result interpretation

The entropy method, BP neural network and principal component analysis method are used to calculate the development scores of aesthetic education in 46 universities in Anhui Province. The weights of each index are shown in Table 2 :

https://doi.org/10.1371/journal.pone.0308446.t002

The weights of the indicators calculated by the three methods vary. The high rankings of both the number of teaching and research papers published by teachers and the number of art inheritance bases underscore their significance in supporting the development of aesthetic education. Research papers serve as vital data supporting the advancement of aesthetic education, while art inheritance bases enable schools, associations, and enterprises to leverage their strengths. They facilitate the discovery and cultivation of aesthetic education models and help standardize and guide aesthetic education behavior effectively. Hence, it is not difficult to understand that these two indicators occupy a large weight. In addition, significant weight is placed on the number of teachers participating in discipline competitions rated B or above, the ratio of traditional cultural associations to school associations, investment in aesthetic education funds, and the number of awards received in the previous National College Students Art Performance in Anhui Province.

After calculating the weights, the development scores of aesthetic education in 46 universities in Anhui Province are calculated according to three methods and evaluated jointly. Python software is used to draw the heat map, and the results are presented in visual form. The results are shown in Fig 1 .

https://doi.org/10.1371/journal.pone.0308446.g001

Fig 1 obviously reveals that darker colors correspond to higher scores, indicating a higher ranking in the development of aesthetic education. Observation over the last column of color blocks indicates that following the comprehensive evaluation, Anhui University, Anhui Normal University, Anqing Normal University, Chuzhou University, Anhui University of Finance and Economics, Fuyang Normal University, Anhui Academy of Fine Arts, Huangshan University, Anhui University of Engineering, and Bengbu University rank among the top ten. Reasons behind this include the fact that these universities offer five or more arts-related majors. Among them, Anhui Normal University, Anhui University, and Anqing Normal University offering over ten such majors. With sufficient funding and effective support for artistic venues, these universities prioritize professional faculty, thereby fostering comprehensive development in art courses, artistic heritage sites, and practical art endeavors. Additionally, institutions like Anhui Academy of Fine Arts specialize in cultivating artistic talents, positioning these universities at the forefront of aesthetic education development in the province.

4. Further analysis

Fig 2 illustrates a comparison of weighted indicators between research paper publications and the number of awards for artistic exhibitions across 46 universities in Anhui Province. From 2005 to 2022, in terms of the total number of awards at the national university art exhibitions organized by the Ministry of Education, universities with art schools, fine arts colleges, design colleges, and music colleges ranked prominently. A strong correlation between the quantity of research paper publications and the number of awards for artistic exhibitions is suggested by a calculated correlation coefficient of 0.899. Anhui Normal University, Anhui University, Suzhou University, Hefei Normal University, Anhui University of Finance and Economics, along with several other universities, exhibit a notable trend of both higher quantities of research paper publications related to aesthetic education and a greater number of awards for artistic exhibitions. This pattern implies the establishment of a systematic mechanism for nurturing talents, encompassing aspects such as faculty allocation, curriculum design, practical teaching methods, artistic practice, and participation in artistic exhibitions.

https://doi.org/10.1371/journal.pone.0308446.g002

In terms of overall statistical award results, participation in artistic exhibitions and subject competitions serves as a dual-purpose platform. It not only allows universities to showcase their achievements in aesthetic education but also serves as an observation point for assessing the degree to which universities prioritize efforts in aesthetic education. Through retrospective analysis, with a focus on professional settings, faculty allocation, and curriculum design for aesthetic education, it becomes evident that certain universities excel in constructing flagship or advantageous disciplines. However, this specialization may lead to fewer entries in exhibitions and competitions, consequently resulting in fewer awards. This situation could potentially relegate aesthetic education to a subsidiary or even marginal position within these universities.

An analysis is conducted on research papers regarding aesthetic education with significant weightage. Based on statistics from the China National Knowledge Infrastructure (CNKI) from 1990 to 2020, 624 research papers are examined. Python is employed for text segmentation and word frequency analysis to generate a word cloud, as shown in Fig 3 . The word cloud demonstrates "aesthetic education," "curriculum," and "art" as the three most frequently occurring terms, suggesting that art education, primarily focusing on public art courses, holds a dominant position. Among these, music and dance often occupy the forefront of aesthetic education. However, courses such as art appreciation, film and television appreciation, drama appreciation, calligraphy appreciation, and traditional Chinese opera appreciation are relatively marginalized. This is attributed to the prevalence of music and dance education at the primary and secondary school levels. Statistics also reveal that 26% of universities do not offer courses related to calligraphy, Chinese folk art, paper cutting, or intangible cultural heritage. Notably, Chinese calligraphy education appears to lack prominence, accounting for only 0.048% of research paper contributions. Furthermore, through a parallel comparison of public art courses, the structural imbalance in course offerings highlights the uneven distribution of such courses among the 46 universities.

https://doi.org/10.1371/journal.pone.0308446.g003

Differences in aesthetic education development in teaching management among the 46 universities in Anhui Province are further explored. Considering the small sample size and the teaching management indicators being categorical variables, a systematic cluster analysis method is adopted. The Ward method is used to calculate the distances between clusters using the squared Euclidean distance, and the number of clusters is determined based on the constructed pseudo-F statistic and pseudo-t 2 statistic. According to the statistics in Table 3 , nine clusters are finally obtained, as shown in Fig 4 .

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https://doi.org/10.1371/journal.pone.0308446.t003

The aesthetic education evaluation index system encompasses both basic statistics and variables. Hard indicators in teaching management include the presence of specialized public art course management departments, the number of teaching institutions, and the count of full-time staff in aesthetic education institutions or teaching departments. They have specific data requirements and are highly operational. The aesthetic management departments of the 46 universities vary widely, involving departments such as Art Education Centers, Cultural Arts and Quality Education Departments, Public Art Education Centers, Aesthetic Teaching Departments, Undergraduate Art Research Offices, Undergraduate Art Education Centers, Sports and Art Clubs, Public Art Education Clubs, Aesthetic Research Offices, etc. The diversity of management departments implies the flexibility of aesthetic education work, indicating an exploratory and practical stage in aesthetic education at universities. First, professional faculty and aesthetic education faculty may share resources, but this arrangement is uncertain and does not form a fixed teaching team. At the same time, soft indicators include the teaching syllabus of public art courses, the methods of public art course evaluation and assessment, public art course evaluations, awards, and teaching observation activities. Among these, cultural courses offered by engineering and medical universities occupy a relatively high proportion, but they are somewhat related to aesthetic education. The absence of standardized indicators among provincial universities limits the effectiveness of assessing procedural soft indicators, making it challenging to operationalize. The convergence of hard and soft indicators leads to a diverse range of teaching management approaches.

As shown in Fig 4 , a cluster analysis is conducted on the 46 universities in Anhui Province based on teaching management. The results indicate that Anqing Normal University, Chuzhou University, Anhui University of Finance and Economics, Tongling University, and Anhui Academy of Fine Arts are grouped into one cluster; Anhui University, Anhui Normal University, Anhui Agricultural University, Huangshan University, Bozhou University, Anhui Science and Technology University, and Hefei Normal University form another cluster; Bengbu Medical College, Wannan Medical College, Anhui Wenyi Information Engineering College, Fuyang Normal University School of Information Engineering, Anhui Medical University Clinical Medicine College, and Huaibei Normal University constitute a third cluster. The distribution of different types can be attributed to the setup of teaching management institutions. Specifically, 10 universities have dedicated institutions solely responsible for aesthetic education, supported by full-time staff. In contrast, 36 universities lack such dedicated staff, resulting in the delegation of aesthetic education responsibilities to various management departments. Regarding the establishment of art-related majors, six universities have more than 10 art-related majors, eight have between 7 and 9 art-related majors, 13 have between 4 and 6 art-related majors, 10 have between 1 and 3 art-related majors, and eight do not have any art-related majors. In terms of the student-teacher ratio for aesthetic education, according to the Guidelines for Public Art Courses in National Regular Higher Education Institutions , the number of teachers responsible for teaching public art courses in each school should account for 0.15% to 0.2% of the total number of students, with full-time teachers taking up 50% of the total number of art teachers. Based on the given ratio, certain medical and science/engineering universities have only one-third the necessary number of instructors for public art classes. Furthermore, universities with adequate faculty often fail to differentiate between art educators dedicated to specialized training and those teaching public art courses, thereby not offering a comprehensive array of public art courses. In terms of teaching management, responsibilities and personnel regarding faculty, courses, and practical activities should be further refined.

5. Aesthetic education comprehensive evaluation model

5.1 establishment of the model.

Herein, multiple indicators of aesthetic education development are selected to analyze and evaluate the status of aesthetic education in universities in Anhui Province. However, it remains challenging to quantitatively analyze aesthetic education development. The difficulty arises partly from some indicators being binary outcomes and the potential for the research conclusions to be limited to specific scenarios if only intuitive analysis of aesthetic education indicators is conducted. Therefore, five nonlinear indicators are hereby selected, which include the number of teacher publications on aesthetic education, the frequency of organizing school-level and above art activities, the number of awards in Anhui University Student Art Exhibition, the number of awards in provincial-level arts competitions, and the proportion of funding for cultural and folk heritage activities on campus-as the benchmark indicators for principal component analysis. A comprehensive evaluation model for aesthetic education development, considering data dispersion, is established. If the original variables are denoted as x 1 , x 2 ,⋅⋅⋅⋅, x n , and the new variables after principal component analysis are denoted as F 1 , F 2 ,⋅⋅⋅⋅, F m , where m < n, the new variables are linear combinations of the original variables. The new variable coordinate system is derived by translating and rotating the original one. The resulting space, comprising the new variables, is termed the m-dimensional principal hyperplane. On this plane, the first principal component F 1 corresponds to the direction of the largest data variation (contribution rate e1), while for F, there are e 2 ≥ e 3 ≥ ⋅⋅⋅≥ e m in sequence. As a result, the new variables effectively encapsulate the essence of the original data, while the m-dimensional hyperplane holds the utmost information content. Despite the possible presence of a slight loss of data information, this method effectively captures the primary contradictions, extracting the majority of variance from the original variables. By reducing the number of variables and focusing on the essential information, it facilitates problem analysis and processing, streamlining the overall approach.

Through principal component analysis, some of the original data information with minor contributions to the final results can be eliminated, while the main characteristic information of aesthetic education development indicators is retained. This is conducive to the analysis and processing of aesthetic education development in Anhui Province. The calculation process of the comprehensive evaluation model for aesthetic education is illustrated in Fig 5 .

https://doi.org/10.1371/journal.pone.0308446.g005

5.2 Precursors of rapid development in art education

The weight analysis in Principal Component Analysis (PCA) establishes a theoretical foundation for pinpointing sensitive indicators that mirror the advancement of art education in Anhui Province. Through PCA, a comprehensive evaluation model of art education development in Anhui Province is constructed, which incorporates multiple parameters such as the number of published papers on art education by teachers, the frequency of organizing arts events at the school and higher levels, the number of awards won by university students in the Anhui division of art exhibitions, the number of awards won in arts competitions at the provincial level and above, and the proportion of funding allocated to cultural heritage and folk art projects entering campuses. This model streamlines a comprehensive analysis of art education development in Anhui Province. Its essence lies in summing the product of each indicator and its corresponding weight across different dimensions of art education in higher education institutions within the province. A thorough investigation into the precursors of rapid development in art education aids in understanding the influence of various factors such as societal, policy, and technological factors on art education. It provides a basis for devising more effective strategies for art education development and lays the theoretical groundwork for the sustainable development of art education in Anhui Province.

Fig 6 depicts the evolution curve of the comprehensive evaluation model of art education development in Anhui Province as a function of funding input. As illustrated in the figure, the curve of the comprehensive evaluation model for art education development in Anhui Province exhibits an overall decreasing trend, with values ranging from -0.8 to 0.2. Despite the variations in numerical values and diverse changing trends among different art education indicators, indicating a certain degree of dispersion, this study takes into account the dispersion of data across these indicators. Polynomial fitting is applied to the curve of the comprehensive evaluation model for art education development in Anhui Province, using logarithmic, exponential, and polynomial functions. It is found that the correlation coefficient of the fitting curve reaches its highest value of 0.999 when a third-degree term is used, indicating a near-complete overlap between the fitting curve and the comprehensive evaluation model curve. Subsequently, the equation of the fitting curve is differentiated once and twice. The first derivative’s significance lies in indicating the rate of change of the curve in the comprehensive evaluation model for art education development in Anhui Province. It indirectly reflects the model’s sensitivity to changes in art education funding. Extreme values of the first derivative signify transitions in sensitivity states. The derivative curve of the comprehensive evaluation model for art education development in Anhui Province is shown in Fig 6 , which exhibits an overall increasing followed by decreasing trend. As art education funding increases, the first derivative peaks, with the second derivative reaching 0. Herein, the authors pinpoint this maximum of the first derivative as the precursor to rapid development in art education. At this juncture, funding input for art education in Anhui Province stands at 1,331,000 RMB, presenting a corresponding comprehensive evaluation model value of -0.502.

https://doi.org/10.1371/journal.pone.0308446.g006

5.3 Sustainable development probability of aesthetic education

Art education holds considerable significance in the sustainable development of society, emphasizing the cultivation of students’ creative thinking and innovation skills, both essential components for the enduring development of society. Creativity is a key factor driving social progress and problem-solving. Art education stimulates individuals’ independent thinking, fostering creativity and providing ongoing momentum for societal innovation. It helps to inherit and promote local culture while also facilitating communication and integration between different cultures. Art facilitates a deeper understanding and respect for multiculturalism, fostering a more harmonious and inclusive society. Besides, art education emphasizes cultivating students’ aesthetic tastes and cultural literacy, enriching individuals in the arts and enhancing their overall comprehensive qualities. Additionally, participation in artistic activities cultivates skills in interpersonal communication, cooperation, and collaboration, which are also crucial for societal sustainable development. The cultural and creative industries are integral components of modern society’s economy. Also, art education nurtures creative talents like artists, designers, and cultural professionals, fostering the development of the creative industry and establishing a cultural and economic foundation for societal sustainability. Moreover, it cultivates environmental awareness by drawing attention to environmental issues. At the same time, artworks serve as powerful tools for conveying environmental concepts, arousing concern through visual and aesthetic means, and advocating for sustainable environmental development.

When t = T, the art education funding input in Anhui Province reaches its peak. Hence, the probability value of sustainable development of art education at the peak state is 1. By computing the probability density curve of sustainable development of art education in Anhui Province based on Eq (16) , Fig 7 illustrates the evolutionary trend of the probability density of sustainable development of art education in Anhui Province. As shown in the figure, the probability density curve of sustainable development of art education in Anhui Province exhibits an overall trend of accelerating increase. The probability value of sustainable development corresponding to the precursor point of rapid development of art education in Anhui Province is 0.388. The probability values of sustainable development of art education corresponding to art education funding of 1.85 million yuan and 1.95 million yuan are 0.8 and 0.9, respectively. Examining the probability curve of sustainable art education development in Anhui Province provides access to probability values for sustainable development across different levels of art education funding.

https://doi.org/10.1371/journal.pone.0308446.g007

6. Discussions and recommendations

In Anhui Province, 10 colleges and universities offer one to three art majors, while 8 lack any art programmes. Some medical and scientific institutions have a mere one-third of the public art faculty compared to the program’s needs. Additionally, colleges with adequate faculty do not segregate those focused on professional art education from public art teachers, resulting in an incomplete public art curriculum. The authors believe that a sound teaching management organisation should be established. On the basis of the 10 colleges and universities that already have had an organisation specifically responsible for aesthetic education, it is recommended that a specialised aesthetic education management organisation with full-time staff also be established in the remaining colleges and universities. This ensures a specialised team is dedicated to overseeing and advancing aesthetic education. Secondly, the setting of art majors should be optimised. For the 8 colleges and universities without art majors, more relevant majors should be gradually set up to enrich the disciplines. Meanwhile, institutions with a limited number of art majors should be motivated to expand their offerings and evolve towards a more diverse and holistic approach. This strategy aims to accommodate the varied demands of society for artistic talent and to bolster the overall competitiveness of these colleges and universities. Colleges and universities, particularly those focused on medical and technical fields, should bolster their recruitment efforts for public art programs. This is to ensure that the faculty count meets the necessary standards, thereby enhancing the quality and breadth of aesthetic education. In addition, it is recommended that full-time art teachers and public art course teachers be divided to undertake the teaching tasks of professional education and public art courses, respectively. This ensures that the courses are fully opened. In terms of teacher management, the teacher training and assessment mechanism should be strengthened, and art teachers should be organised to participate in training and exchange activities on a regular basis, thereby improving their teaching ability and professionalism. At the same time, a scientific teacher appraisal system can be established to evaluate the teaching effectiveness and performance, so as to motivate the teachers for consistent self-improvement and optimisation of the teaching quality. In terms of curriculum, the public art curriculum system should be enriched and improved. In alignment with the distinct profiles of colleges and universities and the varied interests of their students, a diverse curriculum of art courses, spanning music, visual arts, dance, theater, and other disciplines, should be established. This curriculum is designed to cater to the broad artistic learning needs of students, enrich their practical experience, and enhance their practical skills and overall quality through a combination of campus-based and extramural internships and art practice activities.

Finally, delineating clear responsibilities and assigning specific roles is essential. Create a personalized responsibility system to ensure that the task of aesthetic education work is decomposed into specific posts and individuals, so that every task has a responsible person in charge and is subject to proper supervision. By clearly defining roles and enforcing accountability, work efficiency is enhanced, ensuring the seamless execution of aesthetic education initiatives. For example, by adding a number of art majors and actively bringing in high-calibre teachers, Zhejiang University has rapidly formed a competitive cluster of art disciplines and increased the university’s influence in the field of art education. Meanwhile, the Chinese University of Hong Kong has significantly enhanced students’ artistic qualities and practical abilities through the provision of diversified art courses and the organisation of rich art practice activities. However, the above proposal also faces challenges on various fronts, including problems in funding, resources, time and management co-ordination. Specifically, the introduction of additional specialisations necessitates considerable financial and resource investment, potentially burdening HEIs with scarce resources. Recruiting and training adequate faculty, notably in medical and polytechnic institutions, is a protracted process. Crafting and launching a varied curriculum demands significant time and resources, potentially overwhelming current educational capacities. Moreover, organizing and overseeing practical sessions involves multi-party resource coordination, presenting logistical challenges. In order to achieve an overall improvement in aesthetic education, successful implementation of these recommendations requires detailed planning and step-by-step progress by the universities according to their own specific conditions, balancing short-term goals with long-term development.

The comprehensive evaluation model established in this paper serves as a novel method for quantitatively analysing the development degree of aesthetic education. Its theoretical basis relies on the discrete characteristics of aesthetic education metrics, utilizing mathematical curve-fitting techniques, along with the application of primary and secondary derivatives for analysis. The model can effectively analyse the relationship between the input of aesthetic education and the degree of development. The primary derivative reflects the sensitivity of the comprehensive evaluation model to changes in the funding of aesthetic education, while the point of extreme value indicates a shift in the state of sensitivity. The extreme value point of the primary derivative is considered the precursor point of rapid development of aesthetic education, similar to the inflection point in the theory of marginal effect, revealing the rapid growth of aesthetic education input funding upon reaching a certain degree. In order to measure the sustainable development characteristics of aesthetic education, the authors have integrated the concept of probability value. They have delineated the probability of sustainable development in aesthetic education, grounded in a comprehensive evaluation model.

In terms of practical application, the model proposed in this paper can assist policy makers and educational administrators in identifying the key points of investment in aesthetic education, optimising the funding allocation strategy, and ensuring the effective use of resources. Analysing the derivative curves enables educational administrators to dynamically evaluate the responsiveness of aesthetic education development to inputs and the effectiveness of those inputs. This provides data support for the continuous improvement of the effectiveness of the aesthetic education teaching and learning. By identifying the precursor points of rapid development, the model can facilitate colleges and government departments to formulate long-term planning and predict the future trend of aesthetic education development. The points at which both the first and second derivatives’ extreme values equal zero signify a pivotal shift in the sensitivity of funding inputs to the advancement of aesthetic education. These points corroborate the hypothesis that the field is poised for rapid development. In terms of model validation, in future studies, the authors will apply the model to the data on aesthetic education in other provinces to validate the generalisability of the model. In addition, the accuracy of the model predictions will be verified by tracking the actual data on the development of aesthetic education in Anhui Province over time. This paper constructs a comprehensive evaluation model of aesthetic education in universities in Anhui Province based on principal component analysis. Besides, it identifies the precursor points for the rapid development of aesthetic education, and defines the probability value of the sustainable development of aesthetic education in Anhui Province. The paper’s model excels by accommodating the discrete nature of data, making it versatile for comprehensive aesthetic education evaluations across diverse datasets. Yet, its efficacy is critically dependent on the quality and completeness of aesthetic education indicator data.

In addition, the model mainly analyses the relationship between the investment in aesthetic education and the development degree, failing to comprehensively consider other factors affecting the development of aesthetic education, such as cultural background, policy environment, and students’ interests. As artificial intelligence advances rapidly, the authors intend to leverage AI technology in their forthcoming research for mining and analysing aesthetic education big data. This will encompass a broader spectrum of data related to aesthetic education, including student feedback, assessments of teaching quality, and the social impact of these educational efforts. More comprehensive analytical support will be provided. Furthermore, the authors aim to employ deep learning models to assess the collective impact of various factors on the progression of aesthetic education. These models will predict how the field may evolve under diverse conditions, thereby enhancing the precision of decision-making support. On this basis, natural language processing technology will also be utilized to analyse literature, policy documents and expert opinions related to aesthetic education. Valuable information can be extracted for model optimisation and strategy formulation, while an intelligent recommendation system can be developed to recommend optimal aesthetic education development strategies and resource allocation plans according to the specific conditions of universities. In this case, the efficiency and effectiveness of aesthetic education work can be comprehensively enhanced. The paper’s research contribution is exemplified through the case study of Anhui Province, where it introduces a comprehensive evaluation model for aesthetic education. Besides, it defines the probability value of sustainable development of aesthetic education in Anhui Province. The paper’s model stands out for its ability to handle the discrete nature of data, making it suitable for conducting comprehensive evaluations of aesthetic education across a range of data scenarios. However, the size of the data volume may affect the analysis scope of the model, yet this limitation does not impact data accuracy or the model’s predictive trends and policy suggestions for aesthetic education. The authors plan to collect a larger volume of data in future studies to enhance the comprehensive evaluation model’s analysis capabilities.

7. Conclusion

Following a thorough evaluation of art education development across 46 universities in Anhui Province utilizing a construction of 25 indicators, it becomes evident that there are variations in the development of art education among these universities. For instance, Anhui University and Anhui Normal University, representing comprehensive and normal universities respectively, rank higher in terms of overall strength and university rankings. However, universities such as the University of Science and Technology of China, Hefei University of Technology, and Anhui Medical University, despite their high overall strength, do not necessarily lead in art education. Despite advancements in higher education, art education continues to be a weak aspect within the system. However, universities such as Chuzhou University and Huangshan University, while ranking average in overall university standings, demonstrate relatively advanced development in art education.

In summary, several observations arise: Firstly, universities housing art colleges boast advantages in faculty expertise. However, there is still a need to differentiate between specialized courses for art students and those for the general public. Secondly, universities without art colleges generally offer public arts courses in literature and culture. Thirdly, while some universities offer distinctive interdisciplinary courses such as Contemporary Science and Technology Arts (USTC), Medical Humanities Film (BBMC), High-tech Ceramic Materials (AHUT), and Architectural Aesthetics (AHJZU), there is still a relative scarcity of courses focusing on interdisciplinary studies and fostering students’ innovative thinking.

According to the undergraduate talent training regulations of the 46 universities, students must complete 2 credits of public arts courses to graduate during their school years. However, most universities have not fully offered public arts courses, leading to varying degrees of imbalance between supply and demand. Consequently, students may not necessarily fulfill their 2-credit art education based on their interests, hobbies, and specialties. Art education may even become utilitarian education driven by credit orientation, neglecting the importance of aesthetic consciousness, personality development, and innovative thinking, making it necessarily important to strengthen faculty construction and curriculum system development for public arts courses.

Among the forty-six universities in the province, the total number of student art groups and art-related clubs ranges from 5 to 30. However, a higher quantity of literary and art clubs does not necessarily indicate more artistic practice activities, as some clubs may be dormant. Indeed, art education extends beyond formal coursework in public arts courses; it encompasses practical experiences like visiting art galleries, museums, and attending art exhibitions. Additionally, various professional education programs also incorporate elements of art education. Therefore, the construction of a comprehensive evaluation index system for faculty strength, curriculum design, teaching management, artistic practice, and teaching support matters considerably for improving the quality of higher education. The next step in enhancing art education involves focusing on faculty quality, uniqueness, practicality, and innovation in the reform of public arts course teaching.

Herein, a comprehensive evaluation model for the development of art education in Anhui Province is constructed based on principal component analysis. This model quantifies the impact weights of various art education indicators on the development of art education in Anhui Province, and also provides a theoretical basis for identifying the precursors of rapid development of art education in Anhui Province. Furthermore, a new method for determining the development of art education in Anhui Province is also proposed, which takes into account the discreteness of art education indicator data in Anhui Province. The comprehensive evaluation model curve for art education development in Anhui Province exhibits an overall declining trend. Building upon this observation, the authors suggest utilizing the maximum value of the first derivative of the comprehensive evaluation model as the precursor point for rapid art education development in Anhui Province. This very approach leads to the definition of a probability equation for the sustainable development of art education in the province, forging a theoretical foundation for its future development.

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• 15. Wang M, Zeng FR (2017). The Modern Construction of a Large Aesthetic Education System in Colleges and Universities. Chinese Higher Education, no.7, (General Serial 583), pp.7-10.
• 18. Shi CX (2020). Research on the Evaluation System and Promotion Strategies of College Students’ Artistic Quality under the Background of Aesthetic Education. China University Teaching, no.6 (General Serial 358), pp.60-63.
• 19. Shandong Provincial Department of Education. Evaluation Index System of Aesthetic Education Work in Higher Education Institutions in Shandong Province. https://edu.shandong.gov.cn . Accessed 24 March, 2022.
• 21. Yin YX (2020). Research on the Current Situation and Countermeasures of Aesthetic Education in Science and Engineering Colleges and Universities. Nanjing University of Technology. https://doi.org/10.27238/d.cnki.gnjhu.2020.000064
• 24. Wang XH, Li TJ, Ding LL (2010). Evaluation Theory and Techniques for Complex Large Systems. Jinan: Shandong University Press, pp. 80–89.
• 25. Yuan YC (2017) Evolution Law of Precursor Information of Sudden Water Influx in Tunnels and Fusion Warning Method and Engineering Application [D]. Jinan: Shandong University.
• 28. Sheng Z, Xie SQ, Pan CY (2008). Probability Theory and Mathematical Statistics[M]. Beijing: Higher Education Press.

Ask an MIT Professor: What Is System Thinking and Why Is It Important?

Prof. edward crawley considers system thinking “ the cognitive skill of the 21st century”.

By: MIT xPRO

“System Thinking is the cognitive skill of the 21st century.”

Look around you, and you’ll see: life as we know it is becoming more and more complex.

From the iPhone in your pocket to the organizations driving public health, national defense, finance, criminal justice, and [insert just about anything else you can imagine], the world is powered by increasingly intricate systems working behind the scenes to integrate countless moving pieces into a meaningful whole.

“One of the characteristics of the 21st century is that we’re investing more in complexity, and things are just getting damn complicated,” says Professor Edward Crawley , Ford Department of Engineering, Department of Aeronautics and Astronautics, MIT.

Crawley is one of the MIT lead faculty instructors for MIT xPRO’s online course on system thinking  , a skill that helps organizations examine and simplify complexity, recognize patterns, and create effective solutions to challenges. He considers system thinking “ the cognitive skill of the 21st century.” We recently sat down with him to discuss system thinking and what learners can expect from his course.

What is system thinking?

Prof. Crawley explains that “system thinking is simply thinking about something as a system: the existence of entities-the parts, the chunks, the pieces-and the relationships between them.”

There are measures of both performance and complexity in system thinking. “Complexity is what we invest in: more parts, more sophisticated parts, more parts talking to more parts,” Crawley states. “Performance is the benefit that emerges.”

Who uses system thinking, and how might they use it?

“System thinking is for everyone on this side of the life-death line,” Prof. Crawley jokes. Anyone who has taken a course he teaches will tell you that he has an excellent sense of humor.

More specifically, system thinking is broadly used by:

• Leaders who have a high-level view of how different parts of a system fit together and need to be able to step back and see how all the pieces connect.
• Individual contributors who want to understand how the part they’re responsible for fits into the bigger picture so that they can perform at their highest potential.

While it’s true that system thinking is prevalent in STEM fields, Crawley stresses that a tremendous amount of system thinking occurs outside of science, technology, engineering, and mathematics. He rattles off a list of examples to illustrate his point: “The legal system is a system , the Constitution is a system , public health is a system , national defense is a system , finance is a  system .”

In a professional setting, leaders and individual contributors use system thinking all the time to understand:

• How organizations work ( e.g. , team dynamics)
• Complex technologies ( e.g. , smartphones and other devices)
• The optimal ways to track, organize, and utilize information ( e.g. , medical records)
• Intricate processes ( e.g. , the tax system: who pays taxes, how much they pay, and how the revenue is distributed)

Crawley specializes in using system thinking to understand the space system, exploring the answers to questions like: Who builds the satellites? What orbits are they in? How do they communicate with each other? How can humans produce brilliant images like those from the James Webb Space Telescope  ? “Those images are an example of an emergent value proposition that resulted from NASA’s multi-year effort on the James Webb Space Telescope,” remarks Crawley.

What pedagogical methods and tools do you use to get learners comfortable with system thinking?

The big challenge in being one of the faculty instructors for MIT xPRO’s system thinking course, explains Prof. Crawley, is using examples that exhibit just the right amount of complexity. The systems need to be complicated enough that the answers aren’t too obvious but not so complicated that no one can understand how they work, even after learning the tools for system thinking.

Crawley prefers using examples that he categorizes as “middle-complexity systems that people commonly encounter in their lives.” One example is a bicycle. If a rollerblade is too simple and an automobile is overly complex, a bicycle is just right. “You want to train your mind and train your methodology to think about automobiles, but it’s a hard place to start,” says Crawley. “So you start with the middle-complexity system.”

Crawley uses these types of examples to teach students:

• The principles underlying the system
• The methods used to think about the system
• The concrete tools that system thinkers activate each day

What are some challenges learners face during a system thinking course?

Nevertheless, getting comfortable with system thinking can be extraordinarily challenging for learners! Why? Because system thinking is, in essence, an entirely new way of thinking.

“You’re literally neurologically tuning up your brain. You’re creating connections between neurons that didn’t exist before because you’re developing new neural pathways that allow you to think about things differently,” states Crawley.

“I tell my class at MIT at the beginning of the term, ‘I predict that within a week or two, you’ll have headaches,’” he says with a grin. “They look at me and laugh. But sure enough, I check in with them two weeks later, and I’m right.”

What would you say to someone considering enrolling in a system thinking course?

“You’ll get over the headaches once the brain is rewired,” Prof. Crawley jokes.

On a serious note, Crawley encourages students to take a system thinking course because learning a new way of thinking about the world is of vital importance in the 21st century.

“Life is only getting more complex,” he says. If you see him in person, ask him to tell the story about how he and a colleague — two actual rocket scientists — couldn’t figure out how to make a photocopy. “That was two decades ago, and already technology was so complex that you had to be trained to operate it!” he exclaims.

With devices and organizations becoming ever more complicated, system thinking can give learners the skills to succeed.

Those skills include being able to engage in the unknown and think differently about the relationships between the parts that make up a system; ultimately, learners evolve from reductionist thinkers to integrative thinkers ready to face a limitless future.

If you’d like the opportunity to learn from Professor Crawley, as well as Professors John Sterman, Daniela Rus, and Hasma Balakrishnan, enroll in MIT xPRO’s 5-week online system thinking course  .

Originally published at http://curve.mit.edu on September 14th, 2022.

Ask an MIT Professor: What Is System Thinking and Why Is It Important? was originally published in MIT Open Learning on Medium, where people are continuing the conversation by highlighting and responding to this story.

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How to cite ChatGPT

Use discount code STYLEBLOG15 for 15% off APA Style print products with free shipping in the United States.

We, the APA Style team, are not robots. We can all pass a CAPTCHA test , and we know our roles in a Turing test . And, like so many nonrobot human beings this year, we’ve spent a fair amount of time reading, learning, and thinking about issues related to large language models, artificial intelligence (AI), AI-generated text, and specifically ChatGPT . We’ve also been gathering opinions and feedback about the use and citation of ChatGPT. Thank you to everyone who has contributed and shared ideas, opinions, research, and feedback.

In this post, I discuss situations where students and researchers use ChatGPT to create text and to facilitate their research, not to write the full text of their paper or manuscript. We know instructors have differing opinions about how or even whether students should use ChatGPT, and we’ll be continuing to collect feedback about instructor and student questions. As always, defer to instructor guidelines when writing student papers. For more about guidelines and policies about student and author use of ChatGPT, see the last section of this post.

Quoting or reproducing the text created by ChatGPT in your paper

If you’ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or in a comparable section of your paper. For literature reviews or other types of essays or response or reaction papers, you might describe how you used the tool in your introduction. In your text, provide the prompt you used and then any portion of the relevant text that was generated in response.

Unfortunately, the results of a ChatGPT “chat” are not retrievable by other readers, and although nonretrievable data or quotations in APA Style papers are usually cited as personal communications , with ChatGPT-generated text there is no person communicating. Quoting ChatGPT’s text from a chat session is therefore more like sharing an algorithm’s output; thus, credit the author of the algorithm with a reference list entry and the corresponding in-text citation.

When prompted with “Is the left brain right brain divide real or a metaphor?” the ChatGPT-generated text indicated that although the two brain hemispheres are somewhat specialized, “the notation that people can be characterized as ‘left-brained’ or ‘right-brained’ is considered to be an oversimplification and a popular myth” (OpenAI, 2023).

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

You may also put the full text of long responses from ChatGPT in an appendix of your paper or in online supplemental materials, so readers have access to the exact text that was generated. It is particularly important to document the exact text created because ChatGPT will generate a unique response in each chat session, even if given the same prompt. If you create appendices or supplemental materials, remember that each should be called out at least once in the body of your APA Style paper.

When given a follow-up prompt of “What is a more accurate representation?” the ChatGPT-generated text indicated that “different brain regions work together to support various cognitive processes” and “the functional specialization of different regions can change in response to experience and environmental factors” (OpenAI, 2023; see Appendix A for the full transcript).

Creating a reference to ChatGPT or other AI models and software

The in-text citations and references above are adapted from the reference template for software in Section 10.10 of the Publication Manual (American Psychological Association, 2020, Chapter 10). Although here we focus on ChatGPT, because these guidelines are based on the software template, they can be adapted to note the use of other large language models (e.g., Bard), algorithms, and similar software.

The reference and in-text citations for ChatGPT are formatted as follows:

• Parenthetical citation: (OpenAI, 2023)
• Narrative citation: OpenAI (2023)

Let’s break that reference down and look at the four elements (author, date, title, and source):

Author: The author of the model is OpenAI.

Date: The date is the year of the version you used. Following the template in Section 10.10, you need to include only the year, not the exact date. The version number provides the specific date information a reader might need.

Title: The name of the model is “ChatGPT,” so that serves as the title and is italicized in your reference, as shown in the template. Although OpenAI labels unique iterations (i.e., ChatGPT-3, ChatGPT-4), they are using “ChatGPT” as the general name of the model, with updates identified with version numbers.

The version number is included after the title in parentheses. The format for the version number in ChatGPT references includes the date because that is how OpenAI is labeling the versions. Different large language models or software might use different version numbering; use the version number in the format the author or publisher provides, which may be a numbering system (e.g., Version 2.0) or other methods.

Bracketed text is used in references for additional descriptions when they are needed to help a reader understand what’s being cited. References for a number of common sources, such as journal articles and books, do not include bracketed descriptions, but things outside of the typical peer-reviewed system often do. In the case of a reference for ChatGPT, provide the descriptor “Large language model” in square brackets. OpenAI describes ChatGPT-4 as a “large multimodal model,” so that description may be provided instead if you are using ChatGPT-4. Later versions and software or models from other companies may need different descriptions, based on how the publishers describe the model. The goal of the bracketed text is to briefly describe the kind of model to your reader.

Source: When the publisher name and the author name are the same, do not repeat the publisher name in the source element of the reference, and move directly to the URL. This is the case for ChatGPT. The URL for ChatGPT is https://chat.openai.com/chat . For other models or products for which you may create a reference, use the URL that links as directly as possible to the source (i.e., the page where you can access the model, not the publisher’s homepage).

Other questions about citing ChatGPT

You may have noticed the confidence with which ChatGPT described the ideas of brain lateralization and how the brain operates, without citing any sources. I asked for a list of sources to support those claims and ChatGPT provided five references—four of which I was able to find online. The fifth does not seem to be a real article; the digital object identifier given for that reference belongs to a different article, and I was not able to find any article with the authors, date, title, and source details that ChatGPT provided. Authors using ChatGPT or similar AI tools for research should consider making this scrutiny of the primary sources a standard process. If the sources are real, accurate, and relevant, it may be better to read those original sources to learn from that research and paraphrase or quote from those articles, as applicable, than to use the model’s interpretation of them.

We’ve also received a number of other questions about ChatGPT. Should students be allowed to use it? What guidelines should instructors create for students using AI? Does using AI-generated text constitute plagiarism? Should authors who use ChatGPT credit ChatGPT or OpenAI in their byline? What are the copyright implications ?

On these questions, researchers, editors, instructors, and others are actively debating and creating parameters and guidelines. Many of you have sent us feedback, and we encourage you to continue to do so in the comments below. We will also study the policies and procedures being established by instructors, publishers, and academic institutions, with a goal of creating guidelines that reflect the many real-world applications of AI-generated text.

For questions about manuscript byline credit, plagiarism, and related ChatGPT and AI topics, the APA Style team is seeking the recommendations of APA Journals editors. APA Style guidelines based on those recommendations will be posted on this blog and on the APA Style site later this year.

Update: APA Journals has published policies on the use of generative AI in scholarly materials .

We, the APA Style team humans, appreciate your patience as we navigate these unique challenges and new ways of thinking about how authors, researchers, and students learn, write, and work with new technologies.

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

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