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Validation of Students' Green Behavior Instrument Based on Local Potential Using Structural Equation Modeling With Smart Partial Least Squares
instrument validation green behavior local potential structural equation modeling smart partial least squares...
This study aims to develop and validate a green behavior instrument based on local potential using structural equation modeling (SEM) with smart partial least squares (SmartPLS). The instrument consists of 40 statements covering five main indicators: environmental maintenance, waste reduction, saving natural resources, sustainable mobility and consumption, and community education. This study addresses a gap in existing research by creating a context-specific tool for assessing green behavior, incorporating local cultural and ecological factors. While prior studies emphasize global sustainability principles, they often overlook the significance of local practices and values, which are essential for effective environmental education. By integrating local potential, this instrument bridges global sustainability goals with regional contexts, enabling meaningful and practical student engagement. The instrument was validated through content validity testing, exploratory and confirmatory factor analyses, and construct validity and reliability testing using SEM with SmartPLS. The results indicate strong content validity, with content validity index (CVI) values ranging from .80 to .90. After analysis, 34 valid items were retained from the initial 40. This study contributes to the literature by developing an instrument that aligns with global sustainability goals while integrating local cultural practices and ecological contexts. It offers insights into how local knowledge enhances sustainability education, providing a holistic framework for assessing green behavior across diverse regions.
Leadership Education in Finland: A Critical Examination of Well-Being Management Approaches
adult education course descriptions leadership education well-being management...
This study examines how work well-being is addressed in Finnish leadership education programs. The data consist of 91 publicly available course descriptions from Finnish leadership education programs in 2023, including those for master’s degrees from universities of applied sciences, traditional university-level leadership programs, and specialist vocational qualifications in leadership and business management. The study uses content analysis to examine the role of work well-being in leadership training. The results indicate that work well-being is often linked to organizational performance and treated as a tool for achieving economic goals, with less emphasis on the inherent value of employee well-being. This instrumental approach is prevalent across the different types of leadership training programs, including those found in the universities of applied sciences, traditional universities, and programs for specialist vocational qualifications in leadership and business management. The study also finds that leadership training programs often emphasize self-leadership and personal development, which can perpetuate a culture of individual responsibility for well-being and may lead to superficial leadership practices. The study concludes that Finnish leadership educators should prioritize holistic approaches to work well-being in leadership training, emphasizing its intrinsic value alongside its role in organizational performance, while researchers could explore methods to integrate and evaluate these balanced perspectives in diverse educational contexts.
Evaluating Student Knowledge, Performance, and Satisfaction with the Integration of the Sustainable Development Goals into a First-Year Social Education Methodology Course
academic performance knowledge satisfaction social education students sustainable development goals...
To ensure a sustainable future, it is important to align educational practices with global sustainability goals. This study examines the impact of integrating the United Nations’ Sustainable Development Goals (SDGs) into a first-year social education methodology course. Using a survey of 70 students, the relationships between students’ knowledge of the SDGs, their academic performance, and their satisfaction with the integration of the SDGs into their course curriculum were analysed. Findings indicated a significant correlation between enhanced understanding of the SDGs and improved academic performance. The incorporation of the SDGs into the course received somewhat mixed evaluations, however, with most students reporting high overall satisfaction but identifying specific aspects as in need of improvement. Despite this, a greater increase in knowledge of the SDGs by the end of the course appeared to enhance students’ overall satisfaction with the teaching project. These outcomes emphasise the complexity of embedding sustainability in higher education, suggesting that while direct academic improvements may be subtle, cultivating knowledge of the SDGs is pivotal for fostering better educational outcomes and greater student satisfaction. Future research should consider longitudinal and qualitative studies to further explore these dynamics and provide deeper insights into the long-term effects and experiential aspects of integrating the SDGs into university education.
Validity of Measurement and Causal Model of Online Scam Protection Behavior Among Risk Thai Students
causal model confirmatory factor analysis high school student online scam protection behavior...
This research investigated the validity of measurement and causal model of online scam protection behavior (OSPB) among at risk Thai students. The sample comprised 286 high school students from three demonstration schools under the University. Data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The factor loadings for all items satisfied the standard criteria with scores ranging from .40 to .80, item-total correlations ranging from .405 to .718, and Cronbach’s alpha coefficients ranging from .773 to .928. The modified model demonstrated a better fit with the empirical data (χ² = 47.62, df = 37, p = .113, χ²/df = 1.287, RMSEA = .032, SRMR = .028, GFI = .97, CFI = 1.00, NFI = .99). All factors: a) awareness of online risks, b) inhibitory control, c) game-based learning, d) social support, and e) motivation to prevent online scams can predict 81% of OSPB. The motivation to prevent online scams strongly influenced OSPB, with an effect size of .60. Additionally, all factors can predict 88% of the motivation for online scam prevention, suggesting that Protection Motivation Theory (PMT) is a suitable framework for understanding and evaluating Thai students' preventive behaviors in online deception scenarios. This newly developed instrument is highly reliable and can be effectively used by researchers and educators to assess the risk of online fraud victimization among high school students.
Intermediality in Student Writing: A Preliminary Study on The Supportive Potential of Generative Artificial Intelligence
artificial intelligence automated writing evaluation chatgpt intermedia transmedia...
The proliferating field of writing education increasingly intersects with technological innovations, particularly generative artificial intelligence (GenAI) resources. Despite extensive research on automated writing evaluation systems, no empirical investigation has been reported so far on GenAI’s potential in cultivating intermedial writing skills within first language contexts. The present study explored the impact of ChatGPT as a writing assistant on university literature students’ intermedial writing proficiency. Employing a quasi-experimental design with a non-equivalent control group, researchers examined 52 undergraduate students’ essay writings over a 12-week intervention. Participants in the treatment group harnessed the conversational agent for iterative essay refinement, while the reference group followed traditional writing processes. Utilizing a comprehensive four-dimensional assessment rubric, researchers analyzed essays in terms of relevance, integration, specificity, and balance of intermedial references. Quantitative analyses revealed significant improvements in the AI-assisted group, particularly in relevance and insight facets. The findings add to the research on technology-empowered writing learning.