Bulletin of Educational Management and Innovation

The boundary role of motivation in the relationship between competence, leadership, work environment, and teachers’ continuance commitment

2026-08-17T05:38:57+07:00

Background: Keeping highly qualified teaching staff demands comprehensive insight into the mental and structural drivers shaping an educator's choice to stay at their current school. While professional capability, administrative guidance, and workplace conditions are established predictors of institutional loyalty, it is still unclear how professional drive acts as a moderator within these dynamics.

Purpose: The current inquiry explores the capacity of occupational motivation to serve as an interacting variable, specifically examining its influence on the pathways linking competence, leadership styles, and school climate with continuous institutional loyalty amid escalating job demands.

Method: This research employed a cross-sectional explanatory design involving 250 state junior high educators in Salatiga City, Indonesia. Participants were chosen via a proportional randomized sampling approach. To gather information, we distributed standardized, independently completed surveys based on validated metrics. Responses were measured on a 5-level rating format to capture participant viewpoints. Finally, the empirical data underwent evaluation via Partial Least Squares Structural Equation Modeling (PLS-SEM).

Findings: The structural model explained 76.6% of the variance in teachers’ continuance commitment. Competence, leadership, work environment, and work motivation each had positive effects on continuance commitment. However, work motivation demonstrated differential moderating effects: it weakened the relationship between leadership and continuance commitment, strengthened the relationship between work environment and continuance commitment, and did not significantly moderate the relationship between competence and continuance commitment. These findings suggest that work motivation operates as a context-dependent mechanism rather than uniformly strengthening organizational influences, highlighting its importance in developing effective teacher retention strategies.

Google Sites-based statistics learning: Integrating Tri-N ethnopedagogy and cognitive load theory

2026-08-08T22:13:38+07:00

Background: Google Sites is commonly used as a static repository for learning materials, limiting its potential to foster meaningful cognitive engagement in mathematics education. Moreover, few studies have integrated Ki Hadjar Dewantara's Tri-N philosophy (Niteni, Nirokke, Nambahi) with Cognitive Load Theory (CLT) to design culturally responsive and cognitively structured e-learning, particularly for junior high school statistics.

Purpose: This study aimed to develop and validate a Google Sites-based e-learning platform grounded in Tri-N philosophy and CLT for Grade VIII statistics learning.

Method: This Research and Development (R&D) study employed a modified 3D development model adapted from Thiagarajan's 4D model, consisting of the Define, Design, and Develop stages. Participants included 32 Grade VIII students and one mathematics teacher. Data were gathered through observations, interviews, expert validation questionnaires, and student response questionnaires. Specific instruments were used to measure CLT aspects (e.g., intrinsic, extraneous, and germane cognitive load items) and Tri-N integration (e.g., items assessing niteni–observation, nirokke–imitation, and nambahi–creation activities). Data were analyzed using descriptive qualitative and quantitative techniques.

Findings: The developed e-learning product showed high validity and practicality. Content expert validation yielded a mean score of 4.05 (Valid), and media expert validation reached 4.44 (Highly Valid). Student practicality assessments indicated Practical levels, with overall means of 3.61 (limited trial) and 3.93 (large-scale trial). These findings suggest that integrating Tri-N with CLT provides a culturally responsive and cognitively optimized framework that enhances meaningful digital learning. This approach offers practical implications for designing local wisdom-based e-learning and warrants further research on its effectiveness in broader educational contexts and longer implementation periods

Digital literacy, low-code pedagogical ecosystems, and innovative teaching in primary education

2026-07-01T06:26:57+07:00

Background: Digital transformation in elementary schools continues to advance alongside the increasing use of technology in learning. However, the presence of technology has not always been accompanied by the emergence of innovative teaching practices, as the mechanisms explaining the relationship between teachers’ digital literacy, the technological environment, and pedagogical competence are not yet fully understood.

Purpose: This study aims to analyze the relationship between digital literacy, a low-code-based pedagogical ecosystem via microsites, Technological Pedagogical Content Knowledge (TPACK), and innovative teaching practices among elementary school teachers.

Method: This study employed a quantitative explanatory survey involving 83 elementary school teachers in Jepara Regency, Indonesia, selected through proportional stratified random sampling. Data were collected using a structured questionnaire measuring digital literacy, low-code pedagogical ecosystems, TPACK, and innovative teaching practices. Structural Equation Modeling–Partial Least Squares (SEM-PLS) was employed to examine the direct and indirect relationships among the proposed constructs.

Findings: The findings reveal that digital literacy strongly promotes the use of low-code pedagogical ecosystems, which subsequently strengthen teachers’ TPACK competencies. TPACK emerged as the primary mechanism underlying innovative teaching practices, with significant indirect effects observed for Digital Literacy → TPACK → Innovative Teaching Practice (β = 0.231, p = 0.001), Low-Code Pedagogical Ecosystem → TPACK → Innovative Teaching Practice (β = 0.266, p < 0.001), and the sequential pathway Digital Literacy → Low-Code Pedagogical Ecosystem → TPACK → Innovative Teaching Practice (β = 0.167, p = 0.001). The proposed model explained 67.8% of the variance in innovative teaching practices (R² = 0.678). Moreover, Digital Literacy demonstrated a large effect on the Low-Code Pedagogical Ecosystem (f² = 0.649), while TPACK exerted the strongest effect on innovative teaching practices (f² = 0.702), confirming its central role in digital pedagogical transformation.