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The growing prominence of China in the global art market contrasts with the relatively limited engagement of art students with abstract art, highlighting an important gap in understanding the determinants of abstract art perception. Existing studies have primarily focused on cognitive or stylistic interpretations, with insufficient attention to the combined influence of socio-personal and psychological factors. This conceptual paper develops an integrated framework to explain how individual characteristics shape the appreciation and interpretation of abstract art among university art students. Specifically, the model incorporates personal art-making experience, self-assessed artistic knowledge, socioeconomic status, and peer pressure as key antecedents, with openness to artistic experimentation positioned as a central psychological mechanism. Drawing on the Theory of Aesthetic Ability, Social Cognitive Theory, and the Big Five personality framework, the paper proposes that openness to artistic experimentation mediates the relationship between socio-personal factors and abstract art perception. By synthesizing insights from art education, psychology, and social influence literature, the study advances a socio-psychological perspective on art appreciation that moves beyond traditional approaches. The proposed framework offers theoretical contributions by integrating multiple domains into a unified model of aesthetic perception, and provides practical implications for art educators and policymakers seeking to foster inclusive and exploratory learning environments that enhance student engagement with abstract art.

The study aimed to identify the impact of applying deep learning strategies and adaptive learning systems (ALS) on enhancing algebraic proficiency among eigh^th-grade students in the Jerash Directorate of Education. The study tools and materials were prepared, including the development of a proposed instructional unit within the algebra curriculum based on the application of deep learning strategies and adaptive learning systems (ALS), as well as an algebraic proficiency test and verification of its psychometric properties. The study sample consisted of (60) female students selected through purposive sampling. The sample was divided into two groups: an experimental group comprising (30) students who were trained according to the instructional unit, and a control group comprising (30) students who did not undergo training. The study instrument was administered to the sample, and the results were recorded and analyzed, revealing statistically significant differences in favor of the experimental group in enhancing the dimensions of algebraic proficiency in accordance with deep learning strategies and Adaptive Learning Systems (ALS). In light of the study’s findings, the researcher recommends the importance of pedagogical and technical diversity in the teaching of mathematical content to enhance algebraic proficiency, thereby contributing to the achievement of the intended outcomes.

The research evaluates Task-Based Learning (TBL) effectiveness for enhancing listening skills of first-semester students who study English as a Foreign Language (EFL). Despite the importance of listening comprehension in second language acquisition, many EFL learners struggle to understand spoken English due to limited vocabulary knowledge, fast speech rate, and insufficient exposure to authentic listening activities. The research study investigates task-based listening activities which help students develop active listening skills through their participation in practical communication exercises. The study used a pre-experimental one-group pretest–posttest design which tested fourteen students who studied English Education at an Indonesian university. The researchers collected data using listening comprehension tests which were given to students at two different times along with classroom observations and a student perception questionnaire. The instructional treatment included eight sessions of task-based listening training. The results demonstrated a major improvement in student listening abilities. The mean listening score rose from 57.14 in the pre-test to 78.57 in the post-test. A paired-sample t-test confirmed that the improvement showed statistical significance with a t-value of 10.82 and a p-value of less than 0.001 and the result achieved a large effect size according to Cohen’s d value of 3.05. The research findings demonstrate that task-based listening instruction improves student participation while it helps students build their listening comprehension abilities. The researchers recommend conducting additional research with larger participant groups and experimental study methods.

Although previous studies on green transformation mainly emphasize macro-level policies and environmental management, empirical analyses focusing on industrial clusters in Vietnam remain limited. This paper investigates the factors affecting green transformation in industrial clusters in Hanoi, Vietnam. Based on the theoretical framework of institutional theory and resource-based view, a structural equation modeling (SEM) approach was applied to identify and measure the effects of key determinants, including institutional framework, human resources, financial resources, innovation capacity, and environmental regulation. Data were collected from 300 valid responses across 8 industrial clusters in Hanoi. The measurement model was validated using Cronbach’s Alpha, EFA, and CFA, with good reliability and fit indices (GFI = 0.917, CFI = 0.959, RMSEA = 0.043). SEM results indicate that financial resources exert the most substantial positive influence on the effectiveness of green transformation policies, followed by human resources. The study contributes empirical evidence to the understanding of micro-level dynamics driving green transformation within Vietnam’s industrial clusters and offers managerial and policy implications for promoting sustainable industrial development.

This study investigates the effectiveness of state management of green credit in Vietnam’s commercial banks through a structural model based on survey data from 335 respondents. The findings reveal that all factors positively influence management effectiveness, with the data system having the most substantial impact, followed by inspection and supervision mechanisms, and the institutional and legal framework. Meanwhile, international standards, strategic commitment to green credit, and appraisal governance capacity show more minor yet positive effects. The results highlight the importance of enhancing data infrastructure, improving supervision quality, and consolidating institutional coordination to strengthen policy implementation and promote sustainable finance in Vietnam.