Abstract:

Teaching Newton’s Laws represents a fundamental chapter in the physics curriculum, but at the same time, it constitutes one demanding area of school Physics, as students often retain alternative conceptions and struggle to connect theory with real-life situations. Research suggests that the use of digital representations plays a critical role in students’ understanding. However, the effectiveness of each medium remains a subject of debate, particularly when examined under authentic classroom conditions.

In this study, three distinct types of representations—static (graphs), animated, and dynamic (simulations)—were compared across separate, equivalent classes to examine which most effectively supports student learning.

According to Cognitive Load Theory (CLT), instructional effectiveness depends on managing intrinsic, extraneous, and germane cognitive load. Different representations impose different cognitive demands: simulations externalize variables, reducing extraneous load; graphs increase germane load by requiring relational reasoning; and videos leverage dual channels but may risk redundancy. Comparing these formats across classes enables evaluation of representation-specific cognitive demands.

In addition to cognitive load considerations, the study employs a guided inquiry framework to structure learner engagement with each representational form. By providing strategic prompts and scaffolds, guided inquiry supports metacognitive regulation and promotes meaningful engagement with representations. In digital contexts, the combination of guided inquiry with simulations, graphs, or videos fosters active construction of understanding rather than passive reception of information.

By comparing these modalities, the study provides empirical evidence on how to structure complex Newtonian concepts to prevent cognitive overload and enhance conceptual understanding. It explores whether different representations require different levels of scaffolding to help students transition from abstract laws to concrete physical phenomena. The outcomes of this research have practical implications for curriculum designers and physics teachers. By identifying the most effective representation for Newton's Laws, the study offers a blueprint for developing digital learning materials that are both pedagogically sound and cognitively efficient for Grade 10 students.

Although the full analysis is still in progress, emerging qualitative patterns suggest that the simulation-based representation may offer a modest advantage in supporting conceptual understanding, a trend that will be examined more thoroughly in the complete study.

Keywords:

Cognitive Load Theory, Newton’s Laws, Digital Representations, Guided Inquiry, Physics Education, Instructional Design, Simulations.