University entrance scores as department-level indicators of English preparatory program outcomes in a Turkish state University

Despite the widespread use of centralized examination systems globally, institutions lack evidence-based frameworks to inform program-level decision-making and resource allocation in intensive English preparatory programs. This study examines whether university entrance examination scores serve as institutional-level indicators of these decisions. Analysis of aggregate departmental data from 15 departments ( N = 443 students) at a Turkish state university revealed a strong department-level correlation between average entrance scores and preparatory program success rates ( r = 0.83, p < 0.001), accounting for 69% of the variance in departmental outcomes. The regression model (Success Rate = − 46.76 + 0.207 × Entrance Score) illustrates the nature of this institutional-level relationship. Substantial faculty-level differences emerged: Engineering departments achieved 44.4% success compared with 11.1% in Health Sciences (d = 1.24), suggesting that uniform program delivery may warrant further institutional review. The Academic Preparedness Transfer Model is proposed as a conceptual framework consistent with these findings, identifying cognitive, metacognitive, and motivational transfer as potential pathways warranting direct investigation in future research. These findings suggest that existing entrance data may inform institutional-level decisions regarding program differentiation and resource allocation, though individual-level applications require further validation with student-level data.

Authors

Institutions

Publication Details

Journal
Discover Education
Published
2026-07-17
DOI
https://doi.org/10.1007/s44217-026-01930-y
Primary Topic
EFL/ESL Teaching and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

University entrance scores as department-level indicators of English preparatory program outcomes in a Turkish state University

Ayşegül Daloğlu, Seçkin CAN
Discover Education
EFL/ESL Teaching and Learning
article

University entrance scores as department-level indicators of English preparatory program outcomes in a Turkish state University

Ayşegül Daloğlu, Seçkin CAN
article en

Abstract

Despite the widespread use of centralized examination systems globally, institutions lack evidence-based frameworks to inform program-level decision-making and resource allocation in intensive English preparatory programs. This study examines whether university entrance examination scores serve as institutional-level indicators of these decisions. Analysis of aggregate departmental data from 15 departments ( N = 443 students) at a Turkish state university revealed a strong department-level correlation between average entrance scores and preparatory program success rates ( r = 0.83, p < 0.001), accounting for 69% of the variance in departmental outcomes. The regression model (Success Rate = − 46.76 + 0.207 × Entrance Score) illustrates the nature of this institutional-level relationship. Substantial faculty-level differences emerged: Engineering departments achieved 44.4% success compared with 11.1% in Health Sciences (d = 1.24), suggesting that uniform program delivery may warrant further institutional review. The Academic Preparedness Transfer Model is proposed as a conceptual framework consistent with these findings, identifying cognitive, metacognitive, and motivational transfer as potential pathways warranting direct investigation in future research. These findings suggest that existing entrance data may inform institutional-level decisions regarding program differentiation and resource allocation, though individual-level applications require further validation with student-level data.

Discover Education
Middle East Technical University (TR), Ondokuz Mayıs University (TR)
Quality Education
Openalex Percentile: Top 3%
EFL/ESL Teaching and Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.