School-Level Insights on Innovation in Saudi Public Education: An Employee-Centered Approach

The study aimed to identify effective innovation indicators in public education schools in the Kingdom of Saudi Arabia. A mixed-method sequential exploratory design was used starting with interviews of fourteen experts in the fields of talent, creativity and educational excellence. A questionnaire was developed that consisted of seven main innovation indicators, divided into 78 sub-indicators based on the results of these interviews. The questionnaire was administered to a sample of 694 participants including school principals, deputies and teachers. The findings revealed that the overall achievement of innovation indicators in public education schools was moderate. These results suggest that there is a moderate level of implementation of innovation indicators. Further efforts are needed to enhance their effectiveness in Saudi public schools. The study provides a valuable framework for educational policymakers and school administrators to promote innovation within educational environments. This framework can serve as a guide for future efforts to improve the innovative capacity of public schools and enhance their ability to achieve educational excellence. The study offers practical insights for fostering a culture of innovation that supports continuous improvement in the Saudi education system by focusing on strengthening the identified indicators.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-16
DOI
https://doi.org/10.5281/zenodo.15229395
Primary Topic
Socioeconomic Development in MENA
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

School-Level Insights on Innovation in Saudi Public Education: An Employee-Centered Approach

Zenodo (CERN European Organization for Nuclear Research)
Socioeconomic Development in MENA
article

School-Level Insights on Innovation in Saudi Public Education: An Employee-Centered Approach

article en

Abstract

The study aimed to identify effective innovation indicators in public education schools in the Kingdom of Saudi Arabia. A mixed-method sequential exploratory design was used starting with interviews of fourteen experts in the fields of talent, creativity and educational excellence. A questionnaire was developed that consisted of seven main innovation indicators, divided into 78 sub-indicators based on the results of these interviews. The questionnaire was administered to a sample of 694 participants including school principals, deputies and teachers. The findings revealed that the overall achievement of innovation indicators in public education schools was moderate. These results suggest that there is a moderate level of implementation of innovation indicators. Further efforts are needed to enhance their effectiveness in Saudi public schools. The study provides a valuable framework for educational policymakers and school administrators to promote innovation within educational environments. This framework can serve as a guide for future efforts to improve the innovative capacity of public schools and enhance their ability to achieve educational excellence. The study offers practical insights for fostering a culture of innovation that supports continuous improvement in the Saudi education system by focusing on strengthening the identified indicators.

Zenodo (CERN European Organization for Nuclear Research)
King Faisal University (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 41%
Socioeconomic Development in MENA
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.