Learning Theories Through the Lens of Physics and Mathematics

Before reading about behaviorism, cognitivism, constructivism, and connectivism, I assumed that effective learning relied on a single “best” approach. Working through the readings challenged this assumption and helped me realize that different learning theories become useful at different stages of learning, especially in fields like physics and mathematics.

In my experience, behaviorism plays an important role at the very basic stage of learning. When beginning a new physics or math topic, there is little room for interpretation. Learning fundamental rules, formulas, units, and standard procedures often requires repetition, practice, and immediate feedback. At this stage, reinforcement helps ensure accuracy and fluency. Trying to approach these foundations without structure can lead to confusion rather than understanding.

The most central theory for my learning, however, is cognitivism. Physics and mathematics are heavily focused on problem solving, which requires organizing information, building mental models, and applying concepts to new situations. Cognitivist approaches support this by emphasizing how learners process information and connect ideas. When solving problems, I am not simply recalling formulas; I am reasoning through relationships, visualizing systems, and selecting strategies. This aligns strongly with how I learn in STEM courses.

At the same time, constructivism plays a significant role when writing lab reports. While calculations and experimental procedures rely on cognitive understanding, the discussion section requires interpretation and reflection. Making sense of experimental results, explaining sources of error, and addressing unexpected outcomes involve constructing meaning based on personal experience with the experiment. Two students can complete the same lab and obtain similar data, yet produce very different discussions. This meaning-making process reflects constructivist learning.

In many STEM courses at UVic, connectivism is especially present before lectures. Pre-lecture videos, online quizzes, and independent searching encourage me to explore concepts in advance using a network of resources. Before attending class, I often search for explanations, simulations, or alternative perspectives online to familiarize myself with the topic. This process helps me build initial connections and prepares me to engage more deeply during lectures. In this way, learning is distributed across videos, online platforms, and digital tools rather than located in a single source.

Based on these experiences, I disagree with the idea that newer or more open learning theories automatically replace structured approaches. Instead, effective learning particularly in scientific disciplines depends on using the right theory at the right time. My instructional mindset is primarily cognitivist, supported by behaviorism at foundational stages, constructivism in reflective tasks such as lab writing, and connectivism in pre-lecture and exploratory learning.