Yuliya V Vainshtein
Biographic Data
| ID | 9979159 |
|---|---|
| NAME | Yuliya V Vainshtein |
| GIVEN NAMES | Yuliya V |
| FAMILY NAME | Vainshtein |
| SIGNATURE | VAINSHTEIN Y V |
| AFFILIATIONS | Siberian Federal University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Scenarios of Pedagogical Support to Promote Subject Learning Success Among University Students Based on Academic Risk Analysis
The paper considers a strategy for shifting from predicting academic risks to implementing personalized measures of pedagogical support in the context of the digital transformation of education. This study is aimed at developing and testing scenarios for providing this support to university students based on learning analytics data. It is based on the outcomes of a predictive model implemented in the Pythia early warning system. This system has b…
Hybrid Approach to Predicting Learning Success Based on Digital Educational History for Timely Identification of At-Risk Students
Student retention is a significant challenge for higher education institutions (HEIs). The fact that a considerable number of dropouts from universities are primarily due to academic underperformance motivates universities to develop learning analytics tools based on models for predicting learning success. However, the scalability of such models is limited since students’ academic performance and engagement, as well as the factors influencing the…
No prominent works on this page.
Hybrid Approach to Predicting Learning Success Based on Digital Educational History for Timely Identification of At-Risk Students
Student retention is a significant challenge for higher education institutions (HEIs). The fact that a considerable number of dropouts from universities are primarily due to academic underperformance motivates universities to develop learning analytics tools based on models for predicting learning success. However, the scalability of such models is limited since students’ academic performance and engagement, as well as the factors influencing the…
Scenarios of Pedagogical Support to Promote Subject Learning Success Among University Students Based on Academic Risk Analysis
The paper considers a strategy for shifting from predicting academic risks to implementing personalized measures of pedagogical support in the context of the digital transformation of education. This study is aimed at developing and testing scenarios for providing this support to university students based on learning analytics data. It is based on the outcomes of a predictive model implemented in the Pythia early warning system. This system has b…
Online Learning and Analytics (2 works) · Academic achievement (1 work) · At-risk students (1 work) · Computer Science (1 work) · Educational Innovations and Challenges (1 work) · Educational technology (1 work) · Higher education (1 work) · Innovations in Education and Learning Technologies (1 work) · Innovative Teaching Methods (1 work) · Knowledge management (1 work)