Abstract

This article describes an open-development approach to collaboratively refine and expand a meta-framework (a framework used to organize frameworks) called The CURIOUS Educator. The work seeks to provide educators and researchers in science education with a means to organize advancements in science teaching along stages of learning in the human brain. To engage, readers are encouraged to select text segments and comment on feedback or ask the author questions. Significant contributions from these interactions will result in an update to the meta-framework, new releases of this article, and updates to the acknowledgments or authorship of the work.

Introduction

Could the key to revolutionizing science education lie in aligning our teaching methods with the brain's innate learning processes? This introduction confronts this question head-on, dissecting advancements in science education, reshaping pedagogical strategies, and addressing the challenges and opportunities they present.

Education Research: From What Works to Why and How

Science education has traditionally favored lecture-based instruction for delivering content to large student cohorts. While lectures can efficiently transmit information, they often result in passive learning, hindering knowledge retention and application.[1][2] This can result in a cognitive bias known as the illusion of competence,[3][4] manifesting, for example, as students forgetting what they thought they learned soon after an assessment.[5] Thus, while lectures remain prevalent in science education, there is a growing recognition of the need to enhance their effectiveness through innovative teaching methods.

Evidence-based instructional practices emphasize student engagement over traditional methods that deliver institutional efficiency. This shift acknowledges the diverse learning styles of today’s students,[6] highlighting the need to incorporate active learning activities to enhance student engagement and academic performance.[7] Scores of research studies are represented in meta-analyses demonstrating the positive impact of active learning or evidence-based pedagogies, including 225 studies in STEM overall [8], 166 in science and engineering at the postsecondary level,[9] 96 in chemistry education,[10] and 38 related to Asian students’ performance.[11] Given this remarkable amount of evidence, one could reasonably argue that we (educators) know that active learning pedagogies could be more effective than passive alternatives.

However widespread the evidence supporting active learning, there is a significant contrast in its barriers to implementation. From student resistance[12], negative evaluations [13], ill-defined constructs of what constitutes active learning [14], and a systemic lack of supporting infrastructure[15], it's understandable why instructors’ knowledge about active learning and the results instructors achieve following their implementations vary substantially.[16] Additionally, the rapid pace of these advancements has made it challenging for educators to stay current and effectively implement these practices.[17][18]

Auerbach and colleagues (2018) conclude:

The potential positive impact of active-learning instruction on student learning and retention in undergraduate STEM has not been widely realized. High-profile calls for incorporating active-learning instruction have not been accompanied by high-profile calls to fundamentally transform how we prepare and support college STEM instructors.

Staying abreast of and effectively integrating the latest research findings into teaching practices demands a proactive and adaptable approach that institutional structures may rarely incentivize. Moreover, the wealth of evidence supporting the efficacy of instructional practices (the what) should not obscure the essential insights into why or how these methods succeed. Such understanding is critical for their practical application and addressing systemic support issues.

Indeed, the divide between research findings and practical implementation may hinge less on educators' awareness of the benefits of contemporary pedagogies and more on a clear articulation of the cognitive principles that underpin their effectiveness. Therefore, it is essential to investigate the efficacy of active learning and understand its cognitive foundations so that educators can promote it and institutions can make necessary changes. This understanding, in turn, illuminates the way forward, as I would argue the most significant strides in science education share a common thread – an intrinsic alignment with the brain's natural learning processes.

Is it Engaging, Effective, or Brain-Based?

Advancements in science education are closely linked to our expanding knowledge of how the brain learns. As we better understand the brain's learning processes, we can make strides in instructional methodology that aligns with those processes. This has led to developing a brain-based learning paradigm, which evidence supports improvements in student motivation, engagement, and retention.[19][20][21] In the following examples, I will demonstrate how these advancements in science education have echoed our understanding of the brain's learning processes.

Active Learning and Neuroplasticity

Active learning is a cornerstone of modern education, deeply rooted in neuroplasticity—the brain's remarkable ability to form new neural connections in response to learning. Problem-based learning and collaborative group work are practical manifestations of this concept, mirroring the brain's active engagement and adaptation to new challenges.[22] For example, interactive simulations in physics classes allow students to experiment with variables in real time, fostering a deeper understanding of complex theories. Research has consistently shown that these active learning strategies surpass traditional passive learning models, promoting a more immersive and effective learning experience.[23]

Emotional Engagement and Memory Formation

The role of emotions in learning represents another significant stride in science education. Neuroscience has shed light on how emotional engagement amplifies attention and fortifies memory formation.[24][25] Emotionally charged learning experiences, such as case-based scenarios in medical education, can forge stronger and more lasting neural connections. These narratives, steeped in personal and relatable challenges, not only aid in retaining complex concepts but also cultivate empathy and a holistic understanding of medical practice.[26]

Howard Gardner's theory of multiple intelligences reinforces the value of emotional engagement, suggesting that interpersonal and intrapersonal intelligences are as vital as traditional logical and linguistic skills in learning.[27] This theory, alongside Mind, Brain, and Education (MBE) science, advocates for educational strategies that integrate cognitive and emotional aspects to optimize learning.[28]

Cognitive Load Theory and Instructional Design

Cognitive load theory's application to instructional design is a third essential advancement. It posits that effective learning occurs when instructional design respects the brain's working memory limits. By segmenting complex information into smaller units, educators can enhance knowledge transition from working memory to long-term memory. The 'flipped classroom' model exemplifies this principle, where students initially engage with new material independently, followed by in-class activities that deepen understanding and facilitate application, thereby optimizing cognitive load.

Cognitive science principles such as activating prior knowledge, segmenting information, employing visual aids, and interleaving subjects are instrumental in designing profound learning experiences. These principles, aligned with the brain's cognitive architecture, significantly enhance knowledge encoding and retrieval.[29][30][31]

By focusing on these cognitive principles, we demystify the success behind modern advancements in science education and pave the way for its practical application. This knowledge equips educators with the tools to revolutionize teaching and student learning. The following section will explore how frameworks serve as conduits between theory and practice, enabling educators to translate neuroscience research into actionable classroom strategies.

Frameworks: Bridging Theory and Practice

In response to the challenges of integrating brain-based learning principles into science education, research-based frameworks have emerged as essential tools. These frameworks offer educators a structured methodology for translating insights from neuroscience, cognitive psychology, and education research into a coherent and actionable guide for classroom practice. By synthesizing complex findings into a clear set of principles and strategies, frameworks bridge the gap between theory and practice, enabling educators to implement brain-based learning approaches in various educational contexts effectively.[32][33]

One of the key benefits of using frameworks is that they provide a common language and conceptual understanding for educators, researchers, and policymakers.[34] This shared understanding facilitates collaboration and communication across stakeholders, allowing for a more coordinated and practical approach to improving science education. Frameworks also guide curriculum development, helping educators design learning experiences aligned with the latest research on how the brain learns.[35]

Moreover, frameworks can be used to evaluate the effectiveness of existing instructional practices and identify areas for improvement.[36] By providing a clear set of criteria for effective brain-based learning, frameworks enable educators to critically examine their teaching methods and make evidence-based decisions about optimizing student learning.[37] This continuous reflection and improvement process is essential for ensuring that science education remains responsive to the evolving needs of students and society.

However, it is crucial to recognize that frameworks are not a panacea for all science education challenges. The successful implementation of brain-based learning principles requires more than just a well-designed framework; it also requires ongoing professional development, resources, and support for educators. Additionally, frameworks must be flexible enough to accommodate the diverse needs and contexts of different learners and educational settings.[38]

Despite these challenges, the potential benefits of using frameworks to bridge theory and practice in science education are significant. By providing a clear and actionable roadmap for implementing brain-based learning principles, frameworks can help educators create more engaging, effective, and equitable learning experiences for all students. As we continue to deepen our understanding of how the brain learns, we can use this knowledge to inform and transform educational practice by developing and applying research-based frameworks.

The CURIOUS Educator Meta-Framework

The CURIOUS Educator is an evidence-based meta-framework designed to bridge the gap between research and practice in science education (see Figure 1).

This figure contains a visual overview of the frameworks mapping the three stages of brain learning to seven steps of brain-based teaching in a sequence designed to promote neural connections, storage, and retrieval. — **Figure 1**
*The CURIOUS Educator* meta-framework [Infographic]

Developed as a cornerstone project of the nonprofit teaching cooperative Cuvette Empowered, the meta-framework synthesizes key advancements across cognitive psychology, neuroscience, and science education research. It provides a scaffold to organize future advancements and offers a structured approach to designing learning experiences that align with the brain's natural processes of encoding, storing, and retrieving information. Intended as a resource, no datasets were generated or analyzed during the current study; therefore, data sharing does not apply to this article.

Three Stages of Brain-Based Learning

The CURIOUS Educator meta-framework is grounded in a growing body of research emphasizing the importance of aligning teaching strategies with the brain's natural learning processes. Recent research in cognitive neuroscience has provided insights into the neural mechanisms underlying information encoding, storage, and retrieval.[39] These findings reflect the three stages of the meta-framework and emphasize aligning science teaching strategies with the brain's natural learning processes.[40]

Encoding relates to the sensory experiences learners translate into usable signals in the brain mediated by attention and intrigue.[41]
Storage refers to transferring sensory memories into working memory to be developed and refined and then into long-term memory via repeated use or emotional value.[42][43]
Retrieval is about using repeated and spaced practice to recover long-term memories and apply them to examine and understand new problems and phenomena.[44][45]

Seven Steps, Practices, or Categories

The CURIOUS Educator meta-framework is designed to integrate with the brain's learning processes. It achieves this by starting with engaging and relevant content to capture attention (encoding), structuring learning activities that deepen understanding and facilitate memory consolidation (storage), and encouraging practices that enhance the recall and application of knowledge (retrieval). Whether the meta-framework is used to design curricula and lessons or organize new advancements in science education, these steps, practices, or categories are listed below.

Encoding: Sensory Experiences Translated into Usable Brain Signals

The first two steps of The CURIOUS Educator meta-framework align with the principles of brain-based learning, particularly in how the encoding process can be facilitated. Encoding refers to the brain's ability to translate sensory experiences into neural signals that can be processed, stored, and retrieved from memory.[41]

Connect: Engaging learners with an intriguing story, phenomenon, problem, or question is a powerful way to capture attention. Numerous studies have shown that attention is crucial for encoding sensory information.[46][47] By presenting content in a novel, emotionally engaging, or personally relevant way, educators can activate the brain's attentional systems, priming it to receive and process new information.[48] This aligns with the brain-based learning principle that "emotions are critical to patterning."[49]
Uncover: Encouraging students to ask questions taps into the brain's innate curiosity and desire to explore.[50] Curiosity-driven learning has deep evolutionary roots; our ancestors' survival depended on the drive to seek new knowledge about their environment.[51][52] Modern neuroscience research has revealed that curiosity activates the brain's reward circuitry, which modulates the hippocampus, a key brain region for forming new memories.[53][54] By stimulating students' curiosity, educators can leverage this neural circuitry to enhance the encoding of new information.

Moreover, the inquiry-based approach reflected in the "Uncover" step has garnered substantial empirical support, particularly in science education. Numerous studies have found that inquiry-based learning promotes critical thinking, problem-solving skills, and deeper conceptual understanding compared to passive instructional methods.[55][56] Engaging students in active questioning and exploration enhances their ability to find meaning and patterns in new information, another key principle of brain-based learning.

Storage: Consolidating Information for Long-Term Retention

The "Reveal," "Integrate," and "Organize" steps align with key principles of brain-based learning, particularly in how they facilitate the storage process. Storage refers to the brain's ability to consolidate and maintain information over time, allowing for later retrieval and use.[42][43]

Reveal: Introducing fundamental concepts through real-world examples and case studies reflects the principles of situated learning. This approach emphasizes the importance of learning in authentic contexts and has been shown to enhance knowledge transfer and application.[57][58] Educators help students connect new information with existing knowledge frameworks by presenting content through relevant scenarios. This alignment with prior experiences and knowledge is crucial for adequate storage, as the brain is more likely to retain meaningful and relevant information.
Integrate: Examining the similarities, differences, and applications of new and prior knowledge is essential for creating a permanent record of the encoded information in long-term memory. This integration process, or elaborative rehearsal, involves actively processing and connecting new learning with existing knowledge networks. Numerous studies have shown that elaborative rehearsal leads to better long-term retention than passive strategies like rote memorization.[59][60] By exploring connections and applying new learning, students engage in the type of deep processing that facilitates durable memory formation.
Organize: Organizing information into meaningful categories and patterns is another critical aspect of practical storage. The brain naturally seeks to identify patterns and relationships among pieces of information, which is enhanced when knowledge is structured logically and coherently. This aligns with cognitive load theory, which emphasizes managing the mental demands placed on learners to facilitate learning and memory.[61] By helping students organize knowledge into clear, interconnected frameworks, educators can reduce extraneous cognitive load and promote more efficient storage and retrieval.[62]

In summary, the "Reveal," "Integrate," and "Organize" elements are firmly grounded in our current understanding of how the brain stores and consolidates new information. Presenting content in authentic contexts, promoting elaborative rehearsal, and facilitating effective knowledge organization creates optimal conditions for transforming new learning into durable, long-term memories that can be flexibly retrieved and applied in future situations.

Retrieval: Memories Recovered & Applied to Understand New Experiences

Self-assessment and reflection align with metacognition and self-regulated learning research. These skills are essential for academic success and lifelong learning.[63][64] This emphasis on continuous self-assessment and application of knowledge reflects the principles of spaced retrieval practice. This technique involves revisiting and applying learned information at increasing intervals, enhancing long-term retention and retrieval.[65][66]

Unify: The sixth step involves consolidating knowledge and creating resources that can be tested against new learning experiences. Unifying and applying knowledge strengthens neural connections and improves information retrieval.[67] By actively using what they have learned in various contexts, students deepen their understanding and develop the ability to transfer their knowledge to novel situations.[58]
Self-Assessment: The seventh and final step of The CURIOUS Educator meta-framework involves continuous self-assessment and reflection, supporting retrieval by reinforcing memory and understanding of the content. By engaging in metacognitive practices, students become more aware of their learning processes, strengths, and areas for growth.[68] This self-awareness enables them to take greater ownership of their learning and develop strategies for improvement.[69]

Studies have shown that the brain's ability to reorganize and form new neural connections (neuroplasticity) is crucial for learning and memory.[70][71] The framework's focus on active engagement, knowledge integration, and learning application aligns with the principles of neuroplasticity.[72]

In conclusion, The CURIOUS Educator meta-framework is grounded in the principles of brain-based learning and supported by a growing body of research in cognitive psychology and neuroscience. By aligning instructional practices with the brain's natural processes of encoding, storage, and retrieval, educators can create optimal conditions for learning and long-term retention. By leveraging the brain's inherent plasticity and capacity for growth, this framework offers a powerful approach to teaching and learning that can help students develop a deeper, more enduring understanding of complex concepts and skills. As educators continue to refine and apply these principles in their practice, they can play a vital role in unlocking the full potential of every learner's brain.

Applying the Meta-Framework

While helpful in developing educational content, another intended use of The CURIOUS Educator meta-framework is to serve as a tool for science educators and researchers to categorize and integrate the latest developments in pedagogical techniques and teaching frameworks.

iframe 1 (interactive) maps the advancements in science education onto the meta-framework to demonstrate how it could be used to organize them. If you prefer to read these advancements in another format, see Table 1.

iframe 1

About iframe 1 and Table 1, Vanessa Rosa (author) notes:

These are just a few examples of how advancements and frameworks in science education could map onto The CURIOUS Educator meta-framework; however, I encourage readers to track and design their own or contribute to this example by selecting the pertinent text and commenting. Please include citable references to the work or scholars you contribute to, and thank you for helping improve this framework. New versions will be released once substantial updates have been made to improve its quality and comprehensiveness.

Discussion

The CURIOUS Educator meta-framework represents a significant step towards bridging the gap between research and practice in science education. By synthesizing critical advancements across cognitive psychology, neuroscience, and science education research, this framework provides a structured approach for designing learning experiences that align with the brain's natural processes of encoding, storing, and retrieving information. Through ongoing refinement and collaboration with educators and researchers, this framework can be valuable for advancing science education practice and promoting student success.

Unique Contributions and Comparative Advantages

The CURIOUS Educator meta-framework offers several unique perspectives and advantages compared to existing approaches. First, it synthesizes contemporary research across multiple disciplines, including cognitive psychology, neuroscience, and science education, into a coherent and actionable guide for classroom practice. This interdisciplinary approach ensures the framework is grounded in the latest scientific understanding of how the brain learns.

Second, the meta-framework provides a comprehensive and coherent approach that aligns learning activities with the brain's natural processes of encoding, storing, and retrieving information. By organizing instructional strategies and innovations according to these stages (see iframe 1), the framework offers a systematic way to design learning experiences that optimize cognitive processing and promote long-term retention.

Third, the CURIOUS Educator meta-framework offers a unique meta-level organization of best practices in science education. Rather than focusing on specific pedagogical techniques, the framework provides a high-level structure for categorizing and integrating various evidence-based strategies. This allows educators to flexibly adapt and apply the framework based on their specific teaching context and student needs.

Finally, the meta-framework has the potential to serve as a tool for organizing and integrating future research advancements in science education. As new evidence-based strategies and innovations emerge, they can be mapped onto the appropriate framework stages, ensuring that The CURIOUS Educator approach remains up-to-date and relevant.

In conclusion, The CURIOUS Educator meta-framework offers a unique and valuable perspective on science education by synthesizing contemporary research, aligning learning activities with brain processes, and providing a flexible structure for organizing best practices. As we continue to refine and develop the framework through collaboration with educators and researchers, we are confident that it will become an increasingly powerful tool for advancing science education practice and promoting student success.

Feasibility and Practical Implementation

One of the key strengths of The CURIOUS Educator meta-framework is its user-friendly, step-by-step approach designed for easy adoption by educators. Prior developments in science education suggest that the framework's seven steps - Connect, Uncover, Reveal, Integrate, Organize, Unify, and Self-Assessment - may provide a clear roadmap for designing and delivering brain-based learning experiences (see Figure 1).

For example, Owens and Tanner (2017) examine the relationship between neuroscience and innovative teaching, highlighting the significance of integrating instructional practices with the brain's natural learning processes.[17] The step-by-step approach of the CURIOUS Educator meta-framework facilitates seamless integration into existing lesson plans and curricula, enabling teachers to enhance their teaching practices by incorporating brain-based learning principles without causing significant disruption.

The CURIOUS Educator meta-framework aligns with common curricular standards and instructional constraints. The Next Generation Science Standards (NGSS), created by the National Research Council, emphasize engaging students in science and engineering practices, which involve asking questions, defining problems, and planning and executing investigations.[73] The "Connect" and "Uncover" steps of the CURIOUS Educator meta-framework align with these practices by encouraging educators to capture students' attention with captivating phenomena and promote student-led inquiry.

Dubinsky, Roehrig, and Varma (2013) discuss the importance of infusing neuroscience into teacher professional development to help educators understand and apply brain-based learning principles in their classrooms.[74] While the CURIOUS Educator meta-framework may benefit from some initial training to help educators fully grasp its principles, it is designed to be accessible without extensive resources, making it a practical tool for science educators to implement.

In conclusion, The CURIOUS Educator meta-framework offers a practical and feasible approach for science educators to align their teaching practices with the latest research on brain-based learning. By providing a clear, step-by-step guide and aligning with existing curricular standards, the framework is designed for easy adoption and implementation in diverse educational settings.

Addressing Student Variability and Diversity

One of the key strengths of The CURIOUS Educator meta-framework is its potential for differentiating instruction and learning activities. Tomlinson's work on differentiated instruction emphasizes the importance of adapting teaching strategies to meet the diverse needs of learners.[75] The CURIOUS Educator meta-framework's adaptability and flexibility in differentiating instruction and learning activities align with Tomlinson's principles. The framework's seven steps - Connect, Uncover, Reveal, Integrate, Organize, Unify, and Self-Assessment - can be tailored to individual students' or groups' specific needs and abilities. For example, during the "Connect" stage, educators can present phenomena or problems at varying levels of complexity, allowing students to engage with the content at their current level of understanding. Similarly, the "Integrate" and "Organize" stages allow students to process and structure new information in ways that align with their cognitive abilities and learning preferences.

The framework also emphasizes the importance of activating students' diverse prior knowledge and experiences. By beginning with the "Connect" stage, educators can draw upon students' existing understanding and cultural backgrounds to create meaningful connections to new learning. Strategies such as KWL charts (What I Know, What I Want to Know, What I Learned),[76] anticipation guides, or cultural storytelling can help elicit students' prior knowledge and experiences, making the learning process more relevant and engaging for all students.

The CURIOUS Educator meta-framework emphasizes the importance of multimodal learning, which recognizes that students have various learning styles and preferences. Universal Design for Learning (UDL), a book by Meyer, Rose, and Gordon in 2014, also emphasizes the importance of providing multiple means of representation, engagement, and expression to accommodate diverse learning styles and preferences.[77] The CURIOUS Educator meta-framework's focus on multimodal learning opportunities aligns with UDL and supports students' understanding and engagement across diverse cognitive and cultural backgrounds. Educators can achieve this by incorporating visuals, discussions, hands-on activities, and varied content representations. For example, in the "Reveal" stage, educators can use a combination of case studies, simulations, and graphic organizers to introduce new concepts, catering to students' preferences for visual, auditory, and kinesthetic learning.

In conclusion, The CURIOUS Educator meta-framework is well-equipped to address student variability and diversity in the science classroom. By emphasizing flexibility, differentiation, activation of prior knowledge, and multimodal learning opportunities, the framework enables educators to create inclusive and equitable learning experiences that meet the needs of all students, regardless of their background or ability level.

Limitations and Future Research

The CURIOUS Educator meta-framework offers a promising approach to aligning science education with brain-based learning principles. However, it is crucial to acknowledge its potential limitations and identify areas for future research to fully realize its potential in enhancing faculty engagement, support, development, and student outcomes.

Over-Emphasis on Brain-Based Principles

While The CURIOUS Educator meta-framework's focus on cognitive processes is a strength, it may inadvertently overshadow other important factors contributing to effective teaching and learning, such as environmental, social, and emotional contexts related to student engagement and motivation.[78] To mitigate this risk, educators should adopt a balanced approach that integrates brain science with pedagogical practices they have established as beneficial for their students in their given learning environments, considering the framework as a complementary tool rather than a replacement for what has demonstrably worked for their students in the past.

Lack of Empirical Testing

The framework is based on thorough cognitive psychology, neuroscience, and science education research. However, its practical effectiveness and impact on student outcomes have not been thoroughly evaluated. This limitation emphasizes the need for future classroom-based studies to assess the framework's effectiveness in different educational settings.

Future research should include classroom-based studies that assess the framework's effectiveness in various educational settings to address the lack of empirical testing. These studies could employ a range of methodologies, such as:

Pre- and post-assessments to measure changes in student knowledge, understanding, and application of key concepts,
Performance-based tasks to evaluate the framework's effectiveness in promoting knowledge transfer and problem-solving skills and
Student and teacher surveys to gather qualitative data on learning experiences, engagement, and perceived growth

Conducting studies that compare student outcomes in classrooms implementing The CURIOUS Educator meta-framework with those using traditional instructional approaches can help establish the framework's efficacy. These studies can fill the gap in the research literature for science higher education by providing evidence of the framework's impact on student learning and engagement.

Further, tracking student progress over time can provide valuable insights into the framework's long-term impact on academic performance, retention, and future learning success. Longitudinal studies can help researchers understand how the CURIOUS Educator meta-framework contributes to students' long-term success in science education and beyond.

Another crucial area for future research is investigating the framework's impact on faculty engagement, support, and development. Owens and Tanner (2017) emphasize the importance of exploring connections between neuroscience and innovative teaching, highlighting the need for professional development that helps educators understand and apply brain-based learning principles in their classrooms.[17] Investigating The CURIOUS Educator meta-framework's impact on faculty engagement, support, and development aligns with this call for research on the intersection of neuroscience and teaching practices. Studies could explore how the framework influences faculty members' teaching practices, job satisfaction, and professional growth. This research can provide insights into the framework's potential to foster a culture of continuous improvement and collaboration among science educators.

Adopting an iterative, evidence-based approach is essential as The CURIOUS Educator meta-framework is further developed and refined. Dubinsky, Roehrig, and Varma (2013) discuss the importance of infusing neuroscience into teacher professional development, emphasizing an iterative, evidence-based approach to refining and improving educational practices based on insights from the learning sciences.[74] As The CURIOUS Educator meta-framework is further developed, adopting this collaborative, iterative approach will ensure that the framework remains a dynamic and relevant tool for advancing science education practice. Ongoing collaboration between educators and researchers will be crucial for identifying areas of improvement, addressing challenges, and incorporating new insights from the learning sciences. By fostering a culture of continuous improvement and open dialogue, researchers can ensure that the framework remains a dynamic and relevant tool for advancing science education practice.

Conclusion

The CURIOUS Educator meta-framework represents a significant step towards bridging the gap between research and practice in science education. The meta-framework's unique contributions lie in its synthesis of contemporary research across multiple disciplines, its comprehensive approach to aligning learning activities with brain processes, and its potential to categorize and integrate future research advancements. While The CURIOUS Educator meta-framework holds significant promise, it is essential to acknowledge potential limitations, such as the risk of overemphasizing brain-based principles at the expense of other fundamental factors and the current lack of empirical testing in science classrooms. This highlights the need for future classroom-based studies to evaluate its effectiveness. As an open-development initiative, The CURIOUS Educator meta-framework invites science educators and researchers to collaborate on refining and expanding this cutting-edge approach. Through empirical testing, iterative refinement, and ongoing collaboration, we can work towards realizing the full potential of this brain-based framework for enhancing student learning and engagement in the sciences.

If you’d like to join the collaborative development team for The CURIOUS Educator meta-framework, click the image below:

Figure 2

Click the image to join the development team! All are welcome.

Contribute to data collection and future research as to the utility of the meta-framework by completing this index:

The image is entitled "The CURIOUS Educator" with a subtitle of "Benchmark your capacity to inspire curiosity in your science classroom."

There's a colorful donut chart with a button that says "Are you CURIOUS?" followed by this text:
"As educators, success is measured in the lifelong learners we inspire. Without curiosity, our capacity to inspire our students is limited. Take the quiz to discover which aspects to expand your impact as a science educator." — **Figure 3**
Get your CURIOUS-ity Index!

Appendix

The CURIOUS Educator meta-framework aims to synthesize and organize the latest advancements in science education, cognitive psychology, and neuroscience into a comprehensive guide for designing compelling learning experiences. To illustrate the framework's ability to categorize and integrate diverse research findings, we have mapped a wide range of evidence-based teaching strategies and innovations onto the different stages of the framework below in Table 1.

Table 1
Stage	Step	Advancement	Description	Example(s)	Innovations & Innovators
ENCODING	Connect	Active (Science) Learning	Student-centered, emphasizing hands-on exploration and investigation to construct understanding.[55]	Students physically manipulate 3D models of molecules to explore chemical structures and properties.	Tom Wenzel transformed undergraduate chemistry education by incorporating active learning strategies.[79] Joi Walker has significantly contributed to studying and implementing Course-based Undergraduate Research Experiences.[80] Carl Wieman's interactive PhET simulations allow students to manipulate variables and observe outcomes in virtual environments.[81]
		Context- or Project-Based Learning	Situates scientific concepts and practices within real-world social, technological, and environmental contexts relevant to students by proximity or project.[82]	Context-Based: Students investigate the environmental impact of different energy sources, analyzing data from their local community. Project-Based Learning: Students work in teams to create educational videos explaining a scientific concept to a lay audience, developing communication and media skills.	Angela Calabrese Barton has pioneered youth-led participatory action research projects that empower students to investigate and address local environmental justice issues, integrating science learning with community engagement.[83] Judith Bennett and her colleagues have developed and researched context-based approaches in chemistry education, demonstrating increased student engagement and understanding of the relevance of science.[84] Joseph Krajcik and his colleagues developed and studied project-based science curricula that engage students in authentic scientific practices while learning core concepts.[85]
		Phenomenon-Based Learning or Anchoring Phenomena	Anchors instruction in real-world observable events that spark student curiosity and drive further inquiry to uncover scientific explanations.[86]	Students observe a discrepant event (such as a color change in a chemical reaction) and generate questions to investigate the underlying principles.	The 5E Model (Engage, Explore, Explain, Elaborate, Evaluate) effectively scaffolds active learning experiences from phenomena.[87] Joseph Krajcik developed the Three Dimensional Learning framework that emphasizes starting with phenomena and designing solutions to problems, influencing the Next Generation Science Standards.[88] Okhee Lee focuses on equity and inclusion, promoting "knowledge-in-use" approaches where students apply knowledge to explain real-world phenomena.[89] Atkin and Black begin units with demonstrations, hands-on activities, or real-world observations that students can experience through their senses, influencing curricular reform in science education.[90]
	Uncover	Inquiry-Based Learning	This approach emphasizes student autonomy, choice, and responsibility in pursuing answers to their questions.[91]	Students design and conduct experiments to test factors affecting an organism’s growth and develop scientific process skills.	The Smithsonian Science Education Center developed the Leadership and Assistance for Science Education Reform program to build capacity for effectively implementing inquiry-based science curricula in schools.[92] Robyn Gillies has extensively researched the effects of inquiry-based, collaborative learning on students' learning in science, finding improvements in learning.[93] The National Research Council has also been influential, stating [94] that inquiry: …refers to the activities of students in which they develop knowledge and understanding of scientific ideas, as well as an understanding of how scientists study the natural world.
		Socratic Questioning	A teaching strategy that uses a series of questions to guide students' inquiry and promote critical thinking.[95]	An instructor engages students in a dialogue about the ethical implications of genetic engineering, stimulating critical thinking through probing questions.	Mortimer Adler, a prominent philosopher and educator, was a strong proponent of using Socratic seminars in the classroom, founding the National Paideia Center in 1988 to promote this method.[96] The center provides extensive materials on using Socratic seminars, which they describe as "collaborative, intellectual dialogue facilitated with open-ended questions about a text."
		Conceptual Change Model	This model recognizes that students often have preexisting ideas about scientific phenomena, some of which may be misconceptions.[97] By eliciting these ideas through questioning and presenting contradictory evidence, teachers can guide students to confront and revise their thinking.[98]	Students predict the outcome of a counterintuitive physics demonstration, confront their misconceptions, and construct new mental models.	Louis Nadelson highlights the need for instructional approaches that directly address and build upon learners' prior knowledge to facilitate conceptual change.[99] Michelene Chi further elaborated on the cognitive processes involved in conceptual change, proposing that it requires a fundamental shift in the categorical structure of a concept.[100] Stella Vosniadou developed the framework theory approach to conceptual change, which views students' intuitive ideas as coherent structures grounded in everyday experience.[101] Gale Sinatra and colleagues have investigated the role of motivation, emotion, and engagement in the conceptual change process.[102][103]
	Reveal	Case-Based Learning	Fundamental concepts are introduced through real-world case studies. Students explore authentic scenarios to learn how scientific principles manifest in actual situations.[104] Cases provide concrete illustrations of abstract ideas, making content more relevant and memorable.[105]	Students analyze a case study about a community facing a water pollution crisis. As they investigate the causes and impacts, they learn key concepts in environmental science, chemistry, and ecology.	Clyde Freeman Herreid has pioneered the promotion of case study teaching in science.[106] Herreid established The National Center for Case Study Teaching in Science, offering a peer-reviewed collection of cases for educators.[107] Jill Elizabeth Thistlethwaite et al. (2012) conducted a systematic review demonstrating the effectiveness of case-based learning in health professional education for improving critical thinking and application of knowledge.[108]
		Guided Inquiry	Students explore case studies and scenarios under teacher guidance, allowing them to discover key concepts and principles.[109] Teachers provide scaffolding and support in guided inquiry as students examine case studies or problems.[110]	In a guided inquiry lesson on interpreting geological maps, the instructor provides scaffolded questions to help students analyze the features and formations. Students work in small groups to discuss their observations and inferences, with the teacher offering prompts and feedback to guide their thinking.	Thomas Greenbowe introduced guided inquiry materials for exploring chemistry concepts, enhancing students' understanding through structured investigation. Greenbowe’s work has shown that guided inquiry can improve student learning outcomes and attitudes toward chemistry.[111] David Hanson's Process Oriented Guided Inquiry Learning (POGIL) approach has been widely adopted in undergraduate science education.[112] POGIL materials guide students through constructing understanding, with the teacher as a facilitator.[113] Gaddis and Schoffstall (2007) found that guided inquiry labs in organic chemistry led to better student performance and increased confidence compared to traditional verification labs.[114]
		Storytelling in Science	Teachers incorporate narratives and stories to explain complex scientific concepts, making them more accessible and memorable. Storytelling in science education has deep roots in Indigenous ways of knowing and sharing knowledge.[115][116]	An instructor could recount the personal struggles and triumphs of a diverse scientist, humanizing the scientific process and inspiring students. For example, a teacher might tell how fossil hunter Mary Anning discovered ichthyosaur and plesiosaur skeletons that challenged prevailing ideas about Earth's history. Through Anning's narrative, students learn about geology, paleontology, and the nature of scientific discovery in a memorable way.	Ananda Marin and Megan Bang emphasize the importance of "story work" in designing pedagogies for Indigenous science education, recognizing the power of narratives to convey scientific understanding in culturally relevant ways.[115] David Boje, a leading scholar in organizational storytelling, highlights the transformative potential of Indigenous ontological antinarratives in evoking meaningful conversations and problem-solving. Boje's work underscores the value of Indigenous storytelling traditions in contemporary educational contexts.[116] Michael Clough and Joanne Olson (2011) argue that using stories in science teaching can enhance student understanding, motivation, and attitudes toward science. He provides strategies for incorporating storytelling into science lessons.[117]
STORAGE	Integrate	Concept Mapping	Students create visual representations of the relationships between ideas, helping them organize and integrate new information with existing knowledge. Concept maps promote meaningful learning by explicitly connecting new concepts to prior understanding.	After learning about energy transfer in ecosystems, students create a concept map linking this new knowledge to what they previously learned about matter cycling and food webs. Students integrate their understanding of these related ecological concepts by visually representing these connections.	Joseph Novak, a pioneer in concept mapping, emphasized its role in meaningful learning. Novak’s work showed that concept mapping helps students organize knowledge hierarchically, leading to better comprehension and retention.[118] David Ausubel's Meaningful Learning Theory underscores the importance of integrating new knowledge with existing cognitive structures.[119] Nesbit and Adesope conducted a meta-analysis of 55 studies, finding that concept mapping improves knowledge retention and transfer across various educational levels and subject areas.[120]
		Analogical Reasoning	Teachers use familiar concepts as analogies to help students understand new ideas. By comparing the similarities between a known concept and a new one, students can leverage their existing knowledge to construct new understanding.	The instructor uses a factory assembly line analogy to help students understand the sequential steps of protein synthesis. Students relate the familiar process of car manufacturing to the abstract concept of gene expression, seeing how codons (assembly instructions) are translated by ribosomes (workers) into proteins (finished products).	Shawn Glynn's Teaching With Analogies (TWA) model provides a framework for using analogies effectively in science instruction.[121] Dedre Gentner's Structure-Mapping Theory explains how analogical reasoning works cognitively. According to Gentner, when we use analogies, we align the relational structures between two domains, mapping knowledge from a base domain to a target domain.[122] Orgill and Bodner (2004) found that using analogies in college chemistry courses helped students understand abstract concepts and correct misconceptions. However, they cautioned that students may overgeneralize or misinterpret analogies if not used carefully.[123]
		Interdisciplinary Learning	Educators connect science and other subjects, helping students see the relevance and applications of scientific concepts across domains. Interdisciplinary learning promotes transferring knowledge and skills between disciplines, leading to a more integrated understanding.	In a unit on the physics of sound, students explore how musicians use their understanding of sound waves to create music. By connecting physics concepts to music theory and practice, students see how scientific principles apply in real-world contexts and integrate their learning across subjects.	The STEAM (Science, Technology, Engineering, Arts, and Mathematics) framework exemplifies an interdisciplinary approach. STEAM education integrates the arts into STEM subjects, fostering creativity, problem-solving, and critical thinking skills.[124] Veronica Boix Mansilla, a leading researcher in interdisciplinary education, defines interdisciplinary understanding as the capacity to integrate knowledge and modes of thinking from two or more disciplines to produce cognitive advancement.[125]
	Organize	Chunking	Teachers break down complex information into smaller, more manageable units or "chunks." Educators help students process and store information more effectively by organizing content into meaningful groups.	When teaching about the periodic table, a teacher groups elements into categories based on their properties (e.g., metals, nonmetals, noble gases) and highlights patterns within each group. By chunking the information in this way, students can better understand and remember the organization and trends in the periodic table.	George Miller's classic paper "The Magical Number Seven, Plus or Minus Two" introduced the concept of chunking, which suggests that the human working memory can hold around seven chunks of information at a time.[126] This finding has important implications for presenting and organizing information in educational settings. Robert Gagné's Nine Events of Instruction model emphasizes the importance of organizing and chunking information for optimal learning, stating that presenting content in a structured, logical sequence and breaking it down into manageable parts helps students process and retain new knowledge more effectively.[127] Gobet et al. (2001) review the literature on chunking and expert memory, arguing that chunking is a fundamental mechanism for learning and memory and plays a crucial role in developing expertise across various domains, including science.[128]
		Graphic Organizers	Students use visual tools such as Venn diagrams, flowcharts, and concept maps to organize and represent knowledge. These graphic organizers help students see the relationships between ideas and create a structured framework for understanding.	After a unit on cell biology, students create a Venn diagram comparing and contrasting plant and animal cells. Students organize their knowledge meaningfully by visually representing the similarities and differences, deepening their understanding of cell structure and function.	Ausubel's Meaningful Learning Theory emphasizes that students must actively construct knowledge by connecting new information to prior learning. [129][130] Graphic organizers support this process by providing a framework for organizing and integrating ideas, facilitating meaningful learning. Bromley, Irwin-DeVitis, and Modlo (1995) describe graphic organizers as visual representations of knowledge that structure information by arranging essential aspects of a concept or topic into a pattern using labels.[131]
		Mnemonic Devices	Teachers use memory aids such as acronyms, rhymes, or visual associations to help students remember important information. These devices provide a structure for organizing and retrieving knowledge.	To help students remember the order of taxonomic classifications (Domain, Kingdom, Phylum, Class, Order, Family, Genus, Species), a teacher introduces the mnemonic device "Dear King Philip Came Over For Good Soup."	Bellezza (1981) defines mnemonic devices as learning strategies that organize and integrate new information with existing knowledge, facilitating retrieval through cuing. These devices can benefit students learning complex subjects like science, as they help make abstract concepts more concrete and memorable.[132] Carney and Levin (2000) reviewed the research on mnemonic strategies and found that they can significantly enhance student learning and memory, particularly for low-achieving students and those with learning disabilities. This suggests that mnemonic devices can be a valuable tool for making science content more accessible and memorable for many learners.[133]
ENCODING	Unify	Problem-Based Learning	Students work collaboratively to solve complex, real-world problems, applying their knowledge and skills in authentic contexts. Problem-based learning promotes deep learning and practical application by engaging students in active, self-directed inquiry.	In an environmental science unit, students are presented with a scenario about a community facing water scarcity. They must apply their water conservation, ecology, and sustainability knowledge to develop and propose solutions, learning to unite and use their understanding in a meaningful context.	Howard Barrows, a physician and medical educator, developed Problem-Based Learning in the 1960s to prepare medical students for the complex challenges of clinical practice.[134] Cindy Hmelo-Silver has extensively researched problem-based learning in science education, demonstrating its effectiveness in promoting deep understanding and knowledge transfer.[135][136] George M. Bodner has extensively studied and promoted problem-based learning in chemistry education to enhance students' critical thinking and problem-solving skills.[137][138]
	Unify	Authentic Assessment	Teachers evaluate student learning through tasks and projects resembling real-world challenges and applications. Authentic assessments promote more profound understanding and transfer of learning by engaging students in meaningful, complex tasks that require applying knowledge and skills.	As a culminating project for a unit on genetics, students create educational materials (e.g., brochures, videos, or presentations) to inform the public about a genetic disorder. This authentic task requires students to synthesize and apply their knowledge of genetics concepts in a relevant, real-world context.	Grant Wiggins, a proponent of authentic assessment, argued that traditional tests often fail to measure the complex thinking and problem-solving skills most important for success in the real world.[139] Darling-Hammond and Snyder (2000) argue that authentic assessments provide a more comprehensive picture of student learning by requiring the integration and application of knowledge, skills, and dispositions in context. They highlight the importance of using multiple sources of evidence and involving students in the assessment process.[140] Gulikers, Bastiaens, and Kirschner (2004) propose a five-dimensional framework for authentic assessment, which includes task, physical context, social context, assessment result or form, and assessment criteria. They argue that aligning these dimensions with real-world practice enhances the authenticity and impact of the assessment.[141]
		Retrieval Practice	Students engage in activities that require them to actively recall and use information they have learned, strengthening their memory and understanding. Retrieval practice enhances long-term retention and transfer of learning by challenging students to retrieve knowledge from memory and apply it in various contexts.	After a lesson on Newton's laws of motion, students complete a series of practice problems and quizzes that require them to retrieve and apply their understanding of these principles. Students reinforce their learning and develop fluency in applying these concepts by actively recalling and using their knowledge.	Jeffrey Karpicke and Henry Roediger III have conducted extensive research demonstrating the powerful effects of retrieval practice on long-term retention.[65][142] Agarwal et al. (2012) conducted a series of experiments in a middle school science classroom, demonstrating that retrieval practice through quizzing improved students' performance on a final test compared to a control group that engaged in concept mapping. This study provides evidence for the effectiveness of retrieval practice in authentic educational settings.[143] McDaniel et al. (2007) found that frequent testing with short-answer questions improved students' learning and retention of science content compared to studying a concept map or reading the material. This study highlights the benefits of retrieval practice over other common study strategies.[144]
	Self-Assess	Metacognitive Reflection	Students engage in activities that prompt them to think about their thinking and learning processes. Metacognitive reflection helps students develop self-awareness, monitor their understanding, and regulate their learning strategies.	After completing a project on sustainable energy, students write a reflective journal entry about their learning experiences. They consider questions such as: What strategies did I use to learn about this topic? What challenges did I encounter, and how did I overcome them? What new insights or perspectives did I gain? By reflecting on their learning process, students develop greater self-awareness and can monitor and regulate their learning.	John Flavell, a pioneer in metacognition research, defined metacognition as "knowledge and cognition about cognitive phenomena" and emphasized the importance of helping students develop metacognitive knowledge (understanding of their thinking processes) and metacognitive regulation (ability to control and adapt their learning strategies).[145][63] Schraw and Dennison developed the Metacognitive Awareness Inventory (MAI) to assess adults' metacognitive awareness. The MAI has been widely used in educational research to measure students' metacognitive knowledge and regulation.[68] John Hattie's Visible Learning framework emphasizes the importance of making learning visible to teachers and students.[146] By engaging in regular self-assessment and reflection, students develop a clearer understanding of their learning and can take more targeted steps to improve.[147]
		Formative Assessment	Teachers use ongoing, low-stakes assessments to gather evidence of student learning and provide feedback for improvement. Formative assessment helps teachers identify students' strengths and weaknesses, adapt instruction, and support student progress.	During a unit on chemical reactions, a teacher uses quick checks for understanding, such as exit tickets or mini-quizzes, to assess students' grasp of key concepts. Based on the results, the teacher provides targeted feedback and adjusts instruction to meet students' needs.	Formative Assessment, as researched by Dylan Wiliam and Paul Black, involves using evidence of student learning to adjust instruction and provide feedback that moves learning forward.[148] Metacognitive reflection is a critical component of formative assessment, as it helps students identify areas for improvement and develop strategies for progress.[149] Nicol and Macfarlane-Dick (2006) propose a framework for practical formative assessment and feedback in higher education. They highlight the importance of engaging students in self-assessment, providing high-quality feedback, and fostering dialogue about learning.[150]
		Self-Regulated Learning	Students actively plan, monitor, and evaluate their learning, setting goals and strategies for improvement. Self-regulated learning helps students develop metacognitive skills, take ownership of their knowledge, and become more independent and effective learners.	As part of a long-term research project, students create a learning plan outlining their goals, timeline, and strategies for completing the project. They regularly assess their progress, adjust their plans as needed, and seek feedback from peers and the teacher.	Barry Zimmerman, a leading researcher in self-regulated learning, developed a cyclical model of self-regulated learning that includes three phases: forethought (goal setting and planning), performance (monitoring and self-control), and self-reflection (self-evaluation and adaptation).[151][64] Paul Pintrich (2000) proposed a framework for understanding self-regulated learning that includes four phases: planning, monitoring, control, and reflection.[152] Pintrich argues that self-regulated learning is a constructive process in which students set goals, monitor their progress, and adapt their strategies based on feedback. Schunk and Ertmer (2000) review the research on self-regulated learning and its implications for classroom practice. They discuss strategies for promoting self-regulated learning, such as goal setting, self-monitoring, and self-evaluation, and highlight the importance of providing students with opportunities to practice and develop these skills.[153]

While this mapping is extensive, spanning multiple pages, we have included the entire table in this appendix to ensure proper attribution and credit is given to the researchers whose work is referenced. In the main text, we have provided a condensed version of this mapping to highlight the framework's unique contributions and comparative advantages (iframe 1).

The CURIOUS Educator: A Meta-Framework for Science Communication