Machine Learning Predictions of Student Outcomes: The Role of
Educational Structure and Social Stressors in Czech
Municipalities

J 2026

Machine Learning Predictions of Student Outcomes: The Role of Educational Structure and Social Stressors in Czech Municipalities

FLEGL, Martin; Markéta MATULOVÁ a Kristyna VLTAVSKA

Základní údaje

Originální název

Machine Learning Predictions of Student Outcomes: The Role of Educational Structure and Social Stressors in Czech Municipalities

Autoři

FLEGL, Martin; Markéta MATULOVÁ a Kristyna VLTAVSKA

Vydání

Journal on Efficiency and Responsibility in Education and Science, PRAGUE 6, Czech University of Life Sciences Prague, 2026, 2336-2375

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

50300 5.3 Education

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 1.300 v roce 2024

Označené pro přenos do RIV

Ano

Organizační jednotka

Ekonomicko-správní fakulta

Klíčová slova anglicky

Czech municipalities; educational responsibility; educational structure; machine learning; predictive analytics; social stressors

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 8. 6. 2026 12:45, Mgr. Jaroslava Králová

Anotace

V originále

Persistent disparities in student learning outcomes across Czech municipalities highlight the challenge of ensuring equitable access to quality education. These disparities are not only associated with demographic and economic conditions but also with the responsibility of municipalities and institutions to address structural inequalities. This study applies machine learning and SHAP analysis to predict student learning outcomes across municipalities with extended jurisdiction (MEJs), using demographic, economic, social, and housing indicators. Results highlight the dominant role of educational structure, with the share of people without secondary education and the proportion of younger adults holding college degrees emerging as the most influential predictors. Social and housing stressors, including parental executions, poverty destabilization, and housing allowances, further moderate outcomes, revealing nonlinear threshold effects that refine the explanatory narrative. The combined model achieved an R2 of 0.629, confirming that while demographic and educational indicators explain most of the variance, contextual vulnerabilities add interpretive richness by identifying vulnerable subgroups. These findings underscore the dual influence of structural educational attainment and social stressors on student performance, while emphasizing educational responsibility as a key dimension in promoting equity and sustainable development.

Přiložené soubory

machine_learning_prediction_of_student_outcomes_matulova_final.pdf

Citovat

FLEGL, Martin; Markéta MATULOVÁ a Kristyna VLTAVSKA. Machine Learning Predictions of Student Outcomes: The Role of Educational Structure and Social Stressors in Czech Municipalities. Journal on Efficiency and Responsibility in Education and Science. PRAGUE 6: Czech University of Life Sciences Prague, 2026, roč. 19, č. 1, s. 40-56. ISSN 2336-2375. Dostupné z: https://doi.org/10.7160/eriesj.2026.190104.

@article{2571979,
   author = {Flegl, Martin and Matulová, Markéta and Vltavska, Kristyna},
   article_location = {PRAGUE 6},
   article_number = {1},
   doi = {https://doi.org/10.7160/eriesj.2026.190104},
   keywords = {Czech municipalities; educational responsibility; educational structure; machine learning; predictive analytics; social stressors},
   language = {eng},
   issn = {2336-2375},
   journal = {Journal on Efficiency and Responsibility in Education and Science},
   title = {Machine Learning Predictions of Student Outcomes: The Role of Educational Structure and Social Stressors in Czech Municipalities},
   url = {https://www.eriesjournal.com/index.php/eries/article/view/2203},
   volume = {19},
   year = {2026}
}

TY  - JOUR
ID  - 2571979
AU  - Flegl, Martin - Matulová, Markéta - Vltavska, Kristyna
PY  - 2026
TI  - Machine Learning Predictions of Student Outcomes: The Role of Educational Structure and Social Stressors in Czech Municipalities
JF  - Journal on Efficiency and Responsibility in Education and Science
VL  - 19
IS  - 1
SP  - 40-56
EP  - 40-56
PB  - Czech University of Life Sciences Prague
SN  - 23362375
KW  - Czech municipalities
KW  - educational responsibility
KW  - educational structure
KW  - machine learning
KW  - predictive analytics
KW  - social stressors
UR  - https://www.eriesjournal.com/index.php/eries/article/view/2203
N2  - Persistent disparities in student learning outcomes across Czech municipalities highlight the challenge of ensuring equitable access to quality education. These disparities are not only associated with demographic and economic conditions but also with the responsibility of municipalities and institutions to address structural inequalities. This study applies machine learning and SHAP analysis to predict student learning outcomes across municipalities with extended jurisdiction (MEJs), using demographic, economic, social, and housing indicators. Results highlight the dominant role of educational structure, with the share of people without secondary education and the proportion of younger adults holding college degrees emerging as the most influential predictors. Social and housing stressors, including parental executions, poverty destabilization, and housing allowances, further moderate outcomes, revealing nonlinear threshold effects that refine the explanatory narrative. The combined model achieved an R2 of 0.629, confirming that while demographic and educational indicators explain most of the variance, contextual vulnerabilities add interpretive richness by identifying vulnerable subgroups. These findings underscore the dual influence of structural educational attainment and social stressors on student performance, while emphasizing educational responsibility as a key dimension in promoting equity and sustainable development.
ER  -

FLEGL, Martin; Markéta MATULOVÁ a Kristyna VLTAVSKA. Machine Learning Predictions of Student Outcomes: The Role of Educational Structure and Social Stressors in Czech Municipalities. \textit{Journal on Efficiency and Responsibility in Education and Science}. PRAGUE 6: Czech University of Life Sciences Prague, 2026, roč.~19, č.~1, s.~40-56. ISSN~2336-2375. Dostupné z: https://doi.org/10.7160/eriesj.2026.190104.

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