AI Chatbot: A Teaching Tool to Support the Development of Self-learning capacity in Chemistry for High School Students

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In the context of digital transformation and the rapid development of artificial intelligence (AI), the use of AI technology in general and AI Chatbot in particular in education has become a significant trend. There is an increasing number of studies and practical applications of AI Chatbot in teaching and learning. Research indicates that AI Chatbot bring numerous benefits to the teaching process of subjects such as foreign languages, mathematics, science, chemistry, and more. This paper analyzes the potential of AI Chatbot in supporting the self-learning process of high school students in Chemistry. By integrating artificial intelligence technology, AI Chatbot not only provide instant information but also personalize the learning process, helping students enhance their self-learning capacity more effectively. Specifically, the study focuses on identifying the relationship between AI Chatbot and the self-learning process in Chemistry, while also proposing methods to implement AI Chatbot in Chemistry education to improve self-learning capacity for high school students in particular and for other subjects and levels of education in general.

Influence of Teachers’ Assessment Procedures on Student Achievements in Public Junior Schools in Langata Sub County Nairobi, Kenya

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This study investigated the influence of teachers’ assessment procedures on student learning achievements in public junior schools in Langata Sub County, Nairobi City County, Kenya. It was guided by the hypothesis H01: There is no significant relationship between teachers’ assessment procedures and student achievements in these schools. The research employed Howard Gardner’s (1983) Multiple Intelligences Theory, which posits that intelligence consists of various dimensions and educators can enhance learning by addressing these diverse intelligences. A descriptive survey research design targeted 159 public junior secondary schools, 159 head teachers, 480 teachers, and 2 Curriculum Support Officers (CSOs). The sampling included 32 schools, 32 head teachers, 2 CSOs, and 96 teachers. Data was collected using interview schedules and questionnaires and analyzed through the Statistical Package for Social Sciences (SPSS) version 28. Quantitative data was analyzed using descriptive statistics such as frequencies, percentages, means, and standard deviation, while qualitative data was processed using content analysis. Findings revealed a significant relationship between teachers’ assessment procedures and students’ learning achievement (Chi-square = 106.222, p = 0.000). The study concluded that assessment procedures significantly influenced student achievement and recommended that teachers adopt assessments that evaluate core competencies like creativity and problem-solving. The Ministry of Education, KICD, and school leaders should review and track the effectiveness of assessment practices to ensure alignment with national education goals.

The Future of E-Waste Recycling: Emerging Technologies and Practices Evaluating the Social and Economic Benefits of Advanced E-Waste Recycling Technologies

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The exponential development in electronic waste (e-waste) has become an urgent global concern, necessitating new and sustainable recycling solutions. Emerging technologies, including bioleaching, robots, and artificial intelligence (AI)-driven material recovery, present prospects to transform e-waste management by enhancing resource recovery, minimizing environmental impact, and boosting social and economic growth. This study assesses the effectiveness of these sophisticated recycling technologies, concentrating on their economic viability, environmental sustainability, and societal advantages. A mixed-methods approach, integrating quantitative data analysis and qualitative insights, gives a full appraisal of the revolutionary potential of these technologies in the context of a circular economy.

Female Sexual Disfunction in Teachers and Nurses of Productive Age in Lampung, Indonesia

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Sexual function is an important part of an individual’s physical and emotional well-being that can be influenced by various factors, including the type of work. Vocational high school (SMK) teachers and nurses are faced with different working conditions, with levels of stress, social interactions, and workloads that may impact their sexual lives. This study aims to analyze sexual function based on the type of work of female teachers and nurses in Indonesia. This study used a cross sectional study 82 people consisting of 41 nurses at Ryacudu Hospital and 41 teachers at SMK 01 Kotabumi, SMK YPIB Kotabumi, SMK Muhammadiah Abung Timur, North Lampung, Indonesia. The sample were selected by purposive sampling from July to December 2024. Data were collected through a questionnaire that measured aspects of sexual function such as sexual satisfaction, sexual desire, and sexual disorders experienced. Data analysis using Mann-Whitney test to determine the differences in sexual function in nurses and teachers. The results show that there is no difference in sexual function in female nurses at HM Ryacudu Hospital Kotabumi and female teachers at SMK 01 Kotabumi, SMK YPIB Kotabumi, SMK Muhammadiah Abung Timur (p-value = 0.745). Female teachers and nurses are expected to pay more attention to their sexual function so that it does not affect their performance at work.

The Influence of Service Quality and Telemedicine Convenience on Patient Trust and Its Impact on Elderly Patient Satisfaction at Siloam Hospital Bekasi Sepanjang Jaya

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This study aims to analyze the influence of service quality and the convenience of telemedicine on patient trust and its impact on the satisfaction of elderly patients at Siloam Hospital Bekasi Sepanjang Jaya. The research employs a quantitative method with an associative approach. The population in this study consists of all elderly patients treated at Siloam Hospital Bekasi Sepanjang Jaya from January to September 2024, totaling 859 patients. A sample of 136 elderly patients was used. The analytical method applied is the SEM using SmartPLS (Partial Least Square). The findings indicate that service quality affects patient trust, telemedicine affects patient trust, service quality affects patient satisfaction, and telemedicine affects patient satisfaction, trust influences patient satisfaction, service quality mediated by trust influences patient satisfaction, and telemedicine mediated by trust influences the satisfaction of elderly patients at Siloam Hospital Bekasi Sepanjang Jaya.

Development of Physics Learning Devices with Group Investigation Type Cooperative Model to Improve Students Logistics Thinking Ability in Senior High School

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This research is a development research that aims to develop Physics Learning Tool with Cooperative Model of Group Investigation Type to Improve Students’ Logical Thinking Ability in High School. This research uses the ADDIE development model which consists of five stages: Analysis, Design, Development, Implementation, and Evaluation. Validation of Learning Devices was carried out by involving three validators who assessed the feasibility of media, material, and educator responses. The sample in this study was class XI consisting of 25 students who were given a pretest and post test. Data analysis techniques were carried out based on the stages of the ADDIE development model. The results showed that the learning tools developed have a high level of validity, practical, and effective in improving students’ logical thinking skills. The use of this learning tool has a positive impact in improving students’ understanding of physics learning on temperature and heat material as well as improving students’ logical thinking skills in physics learning.

An Explainable Artificial Intelligence (XAI) Methodology for Heart Disease Classification

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Heart disease continues to be one of the predominant contributors to morbidity and mortality on a global scale, underscoring the imperative for early and precise diagnosis to enhance patient outcomes. Machine Learning (ML) has emerged as a formidable instrument in the classification of cardiovascular diseases, utilizing intricate clinical datasets to discern patterns that conventional statistical methodologies may fail to detect. Nevertheless, notwithstanding their robust predictive capabilities, numerous machine learning models function as black-box systems, exhibiting a deficiency in transparency regarding their decision-making processes. The absence of interpretability presents a considerable challenge in clinical environments, where trust, accountability, and elucidation are of utmost importance for medical professionals. In order to tackle this issue, we propose a methodology for heart disease classification that is grounded in Explainable Artificial Intelligence (XAI). This approach incorporates interpretable machine learning models to improve diagnostic transparency and reliability. Our framework conducts an evaluation of various classifiers, including Support Vector Machine (SVM), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), Multi-Layer Perceptron (MLP), and LightGBM. This assessment is based on essential performance metrics, namely accuracy, precision, recall, F1-score, and AUC-ROC. Furthermore, SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations) have been integrated to enhance the interpretability of the model. The experimental findings indicate that XGBoost surpasses alternative models, attaining the highest classification accuracy of 92% and an AUC-ROC score of 0.93, all while preserving interpretability. This study underscores the significance of incorporating Explainable Artificial Intelligence (XAI) techniques within medical AI applications. It advocates for the adoption of transparent, interpretable, and clinically dependable machine learning methodologies to enhance clinical decision-making and optimize patient outcomes.

Challenges in Quality and Quality Assessment in Education: Subjectivity, Ambiguity, and Professional Deficiencies in the Bulgarian Context: A Case Study

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This research critically examines the dismal state of the quality assessment framework in the Bulgarian education system, revealing a “tangled eclectic educational patchwork” that fails to yield any meaningful improvements. Through an incisive analysis of key official documents—namely, the “Framework for Assessing the Quality of Education,” the “Inspection Guide,” and the “Analysis of the Quality of Education Provided by Schools”—the study exposes a system “riddled with vagueness, subjectivity, meretricious practices of no in-depth value and real positive results and significant limitations in the current assessment approach. Specifically, the findings indicate a pervasive subjectivity linked to personal impressions of inspectors, a lack of clear and standardized indicators, and insufficient stakeholder involvement, which collectively undermine the reliability and validity of quality assessments which create a “blurry picture” that lacks reliable benchmarks. The absence of real feedback from essential stakeholders—students, parents, and teachers—leaves the entire framework detached from reality, with desultory emphasis on compliance over genuine improvement that resulted in a culture that prioritizes procedural adherence instead of stimulating an environment conducive to educational excellence. The disconnect with international benchmarks (as given PISA) further exacerbates these issues, highlighting rough discrepancies between reported data and actual performance outcomes. This study aims to provide insights into the systemic challenges facing Eastern European and especially Bulgarian education, along with practical recommendations for enhancing the quality assessment framework to more effectively support student learning and institutional development.

Contemporary Pedagogical “Global Epidemic Maladies” Disrupting and Distorting VET: Survey on the Pedagogical Diseases of the 21st Century

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The article explores the contemporary pedagogical maladies affecting vocational education and training (VET) processes in the 21st century. It identifies a range of systemic issues that hinder immensely effective learning and teaching, including a focus on short-term outcomes, administrative constraints, market-driven approaches, cultural irrelevance, outdated curricula, and a lack of evidence-based practices. The author summarizes and categorizes the educational “diseases” with the most intense effects in VET. In addition to the broadly discussed educational issues, such as pedagogical myopia, the overemphasis on credentialism, and the commodification of education (and others)—which treats learning as a product and prioritizes profit over quality—the author provides definitions for several other negative educational phenomena that are increasingly prevalent in contemporary discourse. In operational terms are given proposals and author’ definitions of new maladies, such as “educational Lisenkovism,” “educational Bufosynchronism,” “pluralism of educational Ersatz-Models,” “pedagogical Pharisaism,” “pedagogical solipsism,” and “factoid-like Jactitation”. The core reason for all the identified pedagogical maladies can be attributed to a systemic often deliberate misalignment between educational practices, institutional policies, and the evolving needs of learners and the labour market. The survey is structured based on the origins of the phenomena and their likely future pernicious effects.

Transforming Lesson Study with PHP Learning Application: It’s Impact on Students’ Digital Literacy

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Improving the digital literacy of educators and students is an important element in educational reform to support the achievement of students’ academic achievement. This study aims to identify alternative solutions through the development of Hypertext Preprocessor (PHP) application-based learning to improve students’ digital literacy. The study used a quasi-experimental method with a one-group pretest-posttest design involving 41 students of the Elementary School Teacher Education Study Program, Makassar Islamic University who were taking the Microteaching course. The study was conducted in eleven meetings, with digital literacy measurements using test instruments and questionnaires based on indicators compiled Referring to Caballé, Cervera, Esteve Mon (2020) and Wang Ng (2012). The results of the study showed a significant increase in digital literacy, with an average N Gain of 45% on the test results and 56% on the questionnaire. The implementation of PHP-based Lesson Study has also been shown to facilitate the implementation of the planning (plan), implementation (do), and reflection (see) stages, as measured by assessment instruments adapted from the UNY Lesson Study Team (2007) and Ibrohim (2009). With these results, the technology-based application shows its effectiveness in supporting the improvement of students’ digital literacy and can be implemented widely at various levels of education to improve the efficiency and quality of learning.