The aim of the study is to determine views of principals regarding assignment procedure. Data were gathered with the implementation of semi-structured interview forms from 14 administrators in the center of Konya according to ‘Purposive sampling’ method. The data were analyzed by content analysis and the following findings have been reached. There should be criteria such as an examination (written and verbal), developing projects related with the school, receiving academic or in-service training in administration, having experience as assistant principal, preparation of evaluation forms aiming at objectivity and improvement, election of the assistant principal by the principal without any intervention among the successful ones from the written exams, appointment of administrators instead of assignment, acceptance of school administration as a profession, regulations respecting of the objectivity, justice and equality. It is recommended that similar studies be conducted through quantitative research.

Mechanics, as a large part of physics, shows the most basic concepts we encounter in our daily lives. With this regard, we implemented the mechanics baseline test (MBT) to the University of Rwanda - College of Education before and after the teaching mechanics module to track students learning. About 38 students participated in this study. We found the instructional strategies used to fit in a model we named "teaching and learning bucket" (lecturer backing and learners owning learning) during data analysis. The results showed that the performance occurred only in 12 out of 26 MBT items at a p<.001, and Cohen's D effect size of 1.26. Such analysis also allowed us to identify areas of mechanics that need teaching improvement, such as (a) constant acceleration, (b) average velocity, (c) the first law of Newton, (d) work and energy, and (e) energy conservation. There was also a positive correlation (r=0.58) between students' confidence in answering questions and correct answers provided and vice versa. Therefore, the research significantly informs lecturers to use various teaching approaches to effectively employ the teaching and learning bucket (TLB) model.

This research aims to systematically review the integration of artificial intelligence (AI) in English language teaching and learning. It specifically seeks to analyze the current literature to identify how AI could be utilized in English language classrooms, the specific tools and pedagogical approaches employed, and the challenges faced by educators. Using the PRISMA-guided Systematic Literature Review (SLR) methodology, articles were selected from Scopus, Science Direct, and ERIC, and then analyzed thematically with NVivo software. Findings reveal that AI enhances English teaching through tools like grammar checkers, chatbots, and language learning apps, with writing assistance being the most common application (54.55% of studies). Despite its benefits, challenges such as academic dishonesty, over-reliance on AI (27.27% of studies), linguistic issues, and technical problems remain significant. The study emphasizes the need for ethical considerations and teacher training to maximize AI’s potential. It also highlights societal concerns, including the digital divide, underscoring the importance of equitable access to AI-powered education for learners of all socioeconomic backgrounds.