This study evaluates the effectiveness of human resources (HR) practices on teaching and learning outcomes in primary education. The research was guided by four research questions and two research hypotheses. The study utilized a survey design via Google Forms for efficient data collection on human resources practices’ effectiveness in primary education. The questionnaire, validated by experts, garnered 60 responses within a month. Data analysis in Statistical Package for the Social Sciences (SPSS) included descriptive statistics and analysis of variance (ANOVA) techniques, adhering to ethical standards. The findings highlight the importance of HR practices that accommodate diversity, support inclusivity, and foster a sense of belonging for all students. Challenges in implementing inclusive HR practices are also identified, emphasizing the need for ongoing efforts to promote inclusivity and equity in primary education. The study concludes by advocating for the development and implementation of effective HR strategies to enhance teaching and learning outcomes in primary education.

The progress of a country can be directly related to the education level of its countrymen. Over a time period, the internet has become a game changer for the world of disseminating education. From 2000 onwards, the scale of online courses has increased manyfold. The main reason for this growth in online learning can be attributed to the flexibility in course delivery and scheduling. Through this study, the authors analyzed the challenges in adopting Online degree programs in higher education in management in India. The authors used Focus Group discussions, semi-structured interviews, and in-depth interviews to collect the data from the various stakeholders. Thematic analysis was used to analyze the responses. Considering the challenges and constraints in India, the authors proposed a sustainable model for implementation. Based on the viewpoints of the different stakeholders, the authors find that online degrees can be instrumental in bringing inclusivity in higher education. There are obvious constraints like a lack of IT infrastructure, the inexperience of faculty in online pedagogy, and the need for more expertise in the administration of online programs by existing universities. However, using SWAYAM as a platform can overcome most of these constraints, as it reduces the burden on individual universities. Hence, the authors proposed models where SWAYAM (technology platform) and Universities (academic partners) can come together to provide a sustainable education model.

Data literacy is an important skill for students in studying physics. With data literacy, students have the ability to collect, analyze and interpret data as well as construct data-based scientific explanations and reasoning. However, students’ ability to data literacy is still not satisfactory. On the other hand, various learning strategies still provide opportunities to design learning models that are more directed at data literacy skills. For this reason, in this research a physics learning model was developed that is oriented towards physics objects represented in various modes and is called the Object-Oriented Physics Learning (OOPL) Model. The learning model was developed through several stages and based on the results of the validity analysis; it shows that the OOPL model is included in the valid category. The OOPL model fulfils the elements of content validity and construct validity. The validity of the OOPL model and its implications are discussed in detail in the discussion.

Gamification is an active methodology of great value that, in a quality educational environment, provides students with the necessary motivation to participate in their teaching-learning process. An emerging active methodology, which is based on the use of information and communication technologies (ICT) and requires an educational space that guarantees greater flexibility in the pedagogical dynamics in favor of academic achievement. This increase in interest in active methodologies, and specifically in gamification, has raised doubts about whether current educational spaces are prepared to host a renewal in methodology or if, on the contrary, they could undermine the attitude of change. For this reason, this research seeks to analyze whether current educational spaces are facilitating elements for the incorporation of gamification in the classroom. The methodological cut of the research is quantitative, specifically in two phases. On the one hand, a descriptive analysis of the results is carried out, obtaining information on the trend of each item. On the other hand, an inferential analysis is carried out around different variables to verify their possible influence on the evaluations of the participants. The results obtained, in the sample made up of 210 teachers distributed in the different centers and who carry out their educational activity from 3rd to 6th grade of primary school, indicate that teachers believe it is relevant to take into account the educational space when incorporating active methodologies in class.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

The study aims to explore the impact of examination-oriented education on Chinese English learners and the importance of cultural intelligence in second language acquisition. Through a questionnaire administered to postgraduate students majoring in English in China, the research discovered that the emphasis on test scores and strategies in China’s higher English education system has led to a neglect of cultural backgrounds and cross-cultural communication. The findings underscore the necessity for reforms in English teaching within Chinese higher education to cultivate students’ intercultural intelligence and enhance their readiness for international careers in the era of globalization.