Cognitive Features of Developing Basic Algorithmic Thinking in Students: Based on Formative Algorithms of Assessment and Feedback in the Digital Environment

Vollständiger Abstract

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In the context of digital transformation in education, formative assessment, along with acquiring new qualities through technological tools, contributes to improving the quality of education. This work is dedicated to studying the characteristics of formative assessment in the digital educational environment, focusing on the role of algorithmic feedback systems in developing students' self-management skills. The evolution of feedback from one-time expert reviews to a continuous, individualized, and data-driven process provided by algorithms is analyzed. It examines how automated, timely, and diagnostically enriched feedback contributes to the formation of metacognitive skills in students: goal setting, selfcontrol, correction of learning directions, and reflection. Particular attention is paid to the dialectics of interaction between external, technologically organized assessment processes and internal self-regulation processes. The study is theoreticalmethodological in nature and involves a combination of pedagogical, digital didactics, and cognitive psychology rules. It was concluded that the effectiveness of digital feedback algorithms is determined not by their technical complexity, but by their ability to initiate and maintain conscious learning activities, transitioning formative assessment into a subject-subject mutually regulated process, which is a key factor in the development of academic independence in the digital age.