In recent decades, the integration of technology in education has transformed traditional learning environments, leading to the emergence of a new paradigm: Technology-Enhanced Learning (TEL), which refers to the use of digital tools, platforms, and resources to enhance the teaching and learning process. The adoption of TEL offers several potential benefits, including increased access to education, personalized learning experiences, and the fostering of digital literacy.

Pedagogical Agents (PAs) emerged as a promising approach, simulating human-like interaction to provide real-time guidance and scaffold learning. By enhancing student motivation and engagement, PAs have been shown to positively impact learning outcomes, as confirmed by multiple meta-analyses.

Although digital learning tools have transformed education, significant challenges remain, particularly in developing higher order cognitive skills. One such challenge is the interpretation of graphs, a crucial competency for analyzing information, identifying patterns, and making informed decisions. Graphs summarize complex data in a visual format, making them a widely used tool in the Information Age. However, research suggests that even university students encounter difficulties in extracting meaningful insights from data visualizations, especially when relying on traditional instructional methods. These challenges not only hinder problem-solving skills but also limit students' ability to critically engage with real-world information. Addressing this gap requires innovative instructional approaches that move beyond passive knowledge transmission and actively support learners in developing graphical reasoning skills.

This pilot study examines the impact of a Pedagogical Agent (PA) on high school students' understanding of graphs using a quasi-experimental pre-test and post-test design. The intervention was conducted in a typical classroom setting, aligned with the national curriculum for Linear Motion in the first year of high school (10th grade). A total of 52 High School students (15 years old) participated in the study were divided into two groups: one using a PA, the other without. Both groups received typical face-to-face instruction and had access to additional resources in a Learning Management System (LMS). The effectiveness of the intervention was assessed using the Test of Understanding Graphs in Kinematics 2 (TUG-K2), a validated instrument for measuring students’ comprehension of graphs in physics. The study compares students' performance across conditions to evaluate the effectiveness of the Pedagogical Agent. Results confirm that learners benefit from the designed Pedagogical Agent.

Keywords: Pedagogical Agents (PAs), Test of Understanding Graphs in Kinematics (TUG-K2), High School, Quasi-Experimental Design, Graph Interpretation, Technology-Enhanced Learning (TEL), Physics Education.