Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.

This study examines the impact of structured cultural educational activities on various dimensions of student well-being in primary education. Using a randomized controlled trial design, 120 third- and fourth-grade students from Arad County, Romania, were assigned to either an experimental group, which participated in cultural educational activities, or a control group, which received no intervention. Well-being and social behavior were assessed using the Strengths and Difficulties Questionnaire (SDQ) and the EPOCH Measure of Adolescent Well-Being, administered before and after the intervention. The SDQ evaluated emotional symptoms, hyperactivity, conduct problems, peer relationship issues, and prosocial behavior, while the EPOCH scale measured engagement, perseverance, optimism, connectedness, and happiness. Analysis revealed statistically significant improvements (p < 0.05) in the experimental group compared to the control group. Students in the experimental group exhibited reduced hyperactivity and peer relationship problems, alongside notable increases in engagement, perseverance, optimism, connectedness, and happiness. These findings highlight the efficacy of integrating cultural educational activities into the primary school curriculum as a strategy for enhancing emotional and social development. The study underscores the importance of such interventions in fostering positive developmental outcomes and offers a foundation for further research into their long-term effects and adaptability across diverse educational contexts.

In regard to national development (ND), this review article (which is basically a perspective approach) presents retroactive and forward-looking perspectives on university education in Nigeria. In the past, particularly during the 1970s, the Nigerian university (NU) sector was among the most outstanding in Africa as well as globally. The best institutions drew students from around Africa, who flocked to Nigeria to study. The NU structure evidently contained four essential components for an international and effective university system, viz., world-class instructors, world-class students, a conducive learning environment, and global competitiveness. The NU structure, nevertheless, has undergone some neglect over the past thirty years and lost its distinctive identity, which raises questions about its function and applicability at the current stage of ND. Hence, some retrospective and forward-looking observations on university education in Nigeria in connection to ND are conveyed in this perspective article uses basically published articles and other relevant literature, as well as other sources and data from available literature. Hitherto, there is an urgent need for reinforcement of the university system in order to give it the desired and comparable international quality and functionality needed to meet the demands of current issues and the near future. However, this article conveys an intense belief and conviction that the NU system is still important for both the political and socioeconomic development (growth) of the nation. The article concludes by recommending the way forward in this regard.

Higher education (HE) consists of both conventional and non-conventional methods of learning. Open and Distance Learning (ODL) is a non-conventional system where teachers (often referred to as facilitators) are physically not present. The conduct of practical in engineering and science education using ODL remains a challenge due to inadequate technology and the dispersion of the students, which results in a graduate skills gap in ODL programs. There is a possibility of using a cloud computing set-up, as well as platforms for the creation of simulated virtual practical settings (virtual laboratories-VLs), which could be accessible by ODL engineering and science and education-based students notwithstanding their locations. This paper adds to existing knowledge on VLs and discusses these inadequacies in engineering and science education with emphasis on the enhancement of online and collaborative learning, as well as the possible laboratory (lab) requirements. In addition, the paper highlights contemporary trends and some issues in VLs and remote labs.

This study conducts a comparative analysis of various machine learning and deep learning models for predicting order quantities in supply chain tiers. The models employed include XGBoost, Random Forest, CNN-BiLSTM, Linear Regression, Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), Bidirectional LSTM (BiLSTM), Bidirectional GRU (BiGRU), Conv1D-BiLSTM, Attention-LSTM, Transformer, and LSTM-CNN hybrid models. Experimental results show that the XGBoost, Random Forest, CNN-BiLSTM, and MLP models exhibit superior predictive performance. In particular, the XGBoost model demonstrates the best results across all performance metrics, attributed to its effective learning of complex data patterns and variable interactions. Although the KNN model also shows perfect predictions with zero error values, this indicates a need for further review of data processing procedures or model validation methods. Conversely, the BiLSTM, BiGRU, and Transformer models exhibit relatively lower performance. Models with moderate performance include Linear Regression, RNN, Conv1D-BiLSTM, Attention-LSTM, and the LSTM-CNN hybrid model, all displaying relatively higher errors and lower coefficients of determination (R²). As a result, tree-based models (XGBoost, Random Forest) and certain deep learning models like CNN-BiLSTM are found to be effective for predicting order quantities in supply chain tiers. In contrast, RNN-based models (BiLSTM, BiGRU) and the Transformer show relatively lower predictive power. Based on these results, we suggest that tree-based models and CNN-based deep learning models should be prioritized when selecting predictive models in practical applications.

Environmental Education (EE) programs are of crucial importance. EE are aimed at global citizenship to generate new knowledge and new, more participatory and conscious ways of acting in the environment. This study, therefore, wants to verify the effectiveness of a training intervention that is based on education on climate change issues and on the active participation of subjects in the dimension of the small psychological group. At the intervention 309 students took part, equally distributed by gender (52.1% males), 64.4% enrolled in primary school, 35.6% enrolled in lower secondary school. A quantitative protocol was administered to evaluate the effectiveness of the intervention. The study shows an increase in pro-environmental behaviors and their stability even after 15–30 days. The intervention seems to be effective in triggering pro-environmental behaviors and maintaining them in the following weeks. The results of this study highlight the need to develop environmental education pro-grams in schools to increase levels of knowledge and awareness on the issue of climate change.