This article examines issues related to the early identification of the risk of academic underperformance among students and the enhancement of clinical competency assessment within the credit-module system of higher medical education institutions. The author proposes a digital “Early Warning System” based on the Moodle platform, along with an adaptive “Smart Tutoring” technology that uses 3D-visualized clinical cases. By analyzing the dynamics of student activity on the platform, this technology automatically categorizes students into three risk zones—green, yellow, and red—in real time and establishes a differentiated learning trajectory.
| Mualliflar | Ibragimova, Venera, Ибрагимова, Венера, Ibragimova, Venera |
|---|---|
| Jurnal | Жамият ва инновациялар / Общество и инновации / Society and innovations |
| Nashr sanasi | 2026-07-25 |
| Jild | 7 |
| Son | 7/S |
| Betlar | 252-257 |
| Til | O‘zbek |
| DOI | 10.47689/2181-1415-vol7-iss7/s-pp252-257 |
DOI: 10.47689/2181-1415-vol7-iss7/s-pp252-257 · Maqolaning asl sahifasi
кредитно-модульная система, интеллектуальное тьюторство, система раннего оповещения, когнитивная нагрузка, медицинское образование, система GPA, Moodle, клиническая компетентность, самостоятельное обучение, цифровой мониторинг, credit-module system, Smart Tutoring, Early Warning System, cognitive load, medical education, GPA system, Moodle, clinical competence, independent study, digital monitoring, kredit-modul tizimi, Smart-Tutoring, Erta ogohlantirish tizimi, kognitiv yuklama, tibbiy ta’lim, GPA tizimi, Moodle, klinik kompetensiya, mustaqil ta’lim, raqamli monitoring
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