Donald S. Coon

Teaching is one of my favorite activities. It’s like giving someone building blocks, showing them how they interact, and watching them build. While I may guide their understanding of the blocks, what they build is entirely their own creation. This metaphor reflects a core aspect of my teaching philosophy: fostering independent thinking by gradually moving students from linear to systems thinking. In doing so, I help them cross a critical threshold in their intellectual development: understanding the complexity of and how to approach real-world problems.

This philosophy has evolved through my past teaching experiences; participation in Center for the Integration of Research, Teaching, and Learning courses; industry experience; and in-depth discussions with colleagues and mentors about effective pedagogy. Each of these experiences has contributed to my pedagogical philosophy, leading to a range of strategies that are both flexible and evidence based. My classrooms empower students to become independent thinkers and problem-solvers through experiential learning and metacognitive development.

Artificial Intelligence in Education

The rise of large language models (LLMs) is recent, but I have been fortunate enough to be a student during this time and witness the early stages of this development. While LLMs such as ChatGPT can provide quick answers, there is a potential for creating a passive learning experience when relied upon heavily. I firmly believe in the need for developing artificial intelligence (AI) literacy (Laupichler et al. 2022) enabling students to master the use of AI but also grasp the limitations, biases and ethical considerations of its use.

In my courses, students are encouraged to experience problem-solving without AI initially, building a foundation of critical thinking and problem-solving skills. Later, they are introduced to LLMs as a tool, but with structured reflection tasks. For instance, I have asked students to attempt writing a program using AI for analyzing a given dataset, already knowing how and why the AI solutions will fail. Reflection tasks in this experience guided them to identify the weaknesses of AI and describe how using their own skills in combination with AI can yield better results. Students who reflect on their learning process often show enhanced learning (Ryan 2013). By guiding them to approach AI critically, I ensure that LLMs serve as an aid rather than a crutch.

Project Based Learning

Experiential learning is key to my philosophy because during my education the strongest skill development and knowledge transfer occurred with projects that mirrored real-world tasks. However, it is not just my own learning that has benefited from this practice. It has been shown that engaging students through project-based learning (PBL) enhances their creativity, high level information acquisition, and collaborative skills (Alacapinar, n.d.).

I incorporated PBL while designing lessons for high school agriculture classes covering a wide range of skills from drafting landscapes, welding practical objects of their choice, to creating posters about livestock diseases. Despite diverse subject matter, they all promoted self-management (Kokotsaki, Menzies, and Wiggins 2016) and featured authentic assessment (Wiggins, n.d.) to educationally maximize and reward the time and effort they dedicated to the projects. In doing so, I saw students push beyond the minimum requirements because they feel that their work is relevant and impactful – confirming again how meaningful, authentic projects increase student engagement and ownership over learning (Hmelo-Silver, Duncan, and Chinn 2007).

Metacognitive Development

Metacognition is a complex subject ranging from awareness to regulation of cognitive processes (Schraw and Dennison 1994). I find it important to emphasize metacognition to develop lifelong learning skills in my students through a better understanding of what they do and don’t know along with how their thought processes occur. I challenge students to reflect on their thinking and learning by embedding microlessons and demonstrating heuristics and biases into my curriculum along with methodology to overcome those. One method I have found successful is a series of simple questions that promote both the acquisition of knowledge and regulation of cognitive processes (Rivas, Saiz, and Ossa 2022):

• What don’t you know?
• How would you learn what you don’t know?
• How would you know if you were wrong?

With projects or in lab settings there is always a potential for mistakes that need to be corrected. Watching my students struggle in these situations is not easy when I know the answer, but implementing these processes helps them master current knowledge, build troubleshooting skills, and improve their ability to adapt to the unforeseen beyond the classroom. The sense of achievement I see in them makes it worth it.

Conclusion

Teaching, to me, is not just about imparting knowledge; it’s about empowering students to think critically, explore new ideas, and adapt to challenges. My methods—rooted in PBL, metacognitive development, and AI literacy—are designed to equip students with the tools they need to succeed in an increasingly complex world. When I encourage students to take control of their own learning process, I do so in hopes of not only teaching them my specialty, but also giving them the tools to get the most out of all their classrooms, whether I am in it or not. After all, it’s like giving someone building blocks, showing them how to use them, and sitting back to see what structures arise out on the horizon as they continue with their education.  

References

Alacapinar, F. n.d. “Effectiveness of Project Based Learning.” Egitim Arastirmalari-Eurasian Journal of Educational Research, 33:17–34.

Hmelo-Silver, Cindy E., Ravit Golan Duncan, and Clark A. Chinn. 2007. “Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, and Clark (2006).” Educational Psychologist 42 (2): 99–107. https://doi.org/10.1080/00461520701263368.

Kokotsaki, Dimitra, Victoria Menzies, and Andy Wiggins. 2016. “Project-Based Learning: A Review of the Literature.” Improving Schools 19 (3): 267–77. https://doi.org/10.1177/1365480216659733.

Laupichler, Matthias Carl, Alexandra Aster, Jana Schirch, and Tobias Raupach. 2022. “Artificial Intelligence Literacy in Higher and Adult Education: A Scoping Literature Review.” Computers and Education: Artificial Intelligence 3:100101. https://doi.org/10.1016/j.caeai.2022.100101.

Rivas, Silvia F., Carlos Saiz, and Carlos Ossa. 2022. “Metacognitive Strategies and Development of Critical Thinking in Higher Education.” Frontiers in Psychology 13 (June):913219. https://doi.org/10.3389/fpsyg.2022.913219.

Ryan, Mary. 2013. “The Pedagogical Balancing Act: Teaching Reflection in Higher Education.” Teaching in Higher Education 18 (2): 144–55. https://doi.org/10.1080/13562517.2012.694104.

Schraw, Gregory, and Rayne Sperling Dennison. 1994. “Assessing Metacognitive Awareness.” Contemporary Educational Psychology 19 (4): 460–75. https://doi.org/10.1006/ceps.1994.1033.

Wiggins, Grant. n.d. “The Case for Authentic Assessment. – Practical Assessment, Research & Evaluation.”

 BONUS: Hidden philosophy for you! https://xkcd.com/1053/

Proudly written without large language models.

©Donald Coon 2024 available at https://doi.org/10.5281/zenodo.14584993

This work is licensed under CC BY 4.0