The use of theory of planned behavior to systemically study the integrative-qualitative intentional behavior in Romanian preschool education with network analysis.

Predicting preschool teachers' intention to adopt qualitative and inclusive early childhood intentional behaviors represents an important research field. The objective of this research is first to develop and validate a scale to assess the integrative-qualitative intentional behavior (IQIB-ECEC) of preschool teachers in order to achieve SDG4.2's objective of ensuring that all children have access to high-quality pre-primary education and then to systemically analyze the relationship between variables with Network Analysis.

The Mediation Role of an Individual's and Couple's Psychological Factors, Including Parenting in the Prediction of Relational and Marital Satisfaction.

The goal of this study was to widen the scope of the social component of family sustainability. The fundamental goal of this non-experimental, quantitative study was to look at the links between parenting correlates, personality characteristics, marital satisfaction, and well-being in couples, as well as to construct explanatory prediction models for relational and marital satisfaction. The study focused on the effects of personality traits, parental self-efficacy, and attachment to marital and relational satisfaction.

Pathways to inclusive and equitable quality early childhood education for achieving SDG4 goal-a scoping review.

According to Sustainable Development Goal 4.2 (SDG 4.2), Equal Access to Quality Pre-primary Education, governments throughout the world are working to ensure that all children have access to high-quality early childhood development, care, and pre-primary education by 2030.

A Radial Basis Function Neural Network Approach to Predict Preschool Teachers' Technology Acceptance Behavior.

With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function (RBF) neural network (NN) modeling technique to predict preschool instructors' technology usage in classes based on recognized determinant characteristics of technology acceptance.