TITLE:
Design of Teaching Activities for Cultivating Algorithmic Thinking in Middle School Students Based on Teaching Agents
AUTHORS:
Xiulin Ma, Yizibasar Rawa, Fei Wu, Yu Fan
KEYWORDS:
Teaching Intelligent Agent, Algorithmic Thinking, Activity Design
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.14 No.4,
April
30,
2026
ABSTRACT: Algorithmic thinking is an essential core competency for middle school students in the digital age, but its cultivation faces practical difficulties such as “emphasizing code over thinking” and insufficient personalized teaching support. The unrestrained use of AIGC tools may also exacerbate students’ cognitive inertia. In view of this, this study explores teaching agents and their activity design for cultivating algorithmic thinking in middle school students, and will focus on three major objectives: 1) designing an agent for cultivating algorithmic thinking in middle school students; 2) designing teaching activities centered on this agent to promote the development of algorithmic thinking in middle school students; and 3) verifying the effect of the activity design on the development of algorithmic thinking in middle school students. In order to achieve the above objectives, the “Intelligent Computing Partner” agent was developed based on the Coze platform, and a three-element collaborative activity system of “teacher-student-agent” was constructed. The sorting algorithm teaching activities were designed by combining the 5E teaching model with strategies such as situational teaching and cognitive conflict, forming an effective activity model for the development of algorithmic thinking in middle school students based on the agent. The model was optimized through multiple rounds of iterations by expert review and other means to ensure its effectiveness.