This study aims to examine the 9th-grade 2018 physics curriculum according to various criteria. A cross-sectional survey model was used. The sample consists of 36 physics teachers working in various high schools in 12 regions of Turkey in the 2022-2023 academic year. The data of the study were collected via the “9th-grade 2018 physics curriculum Evaluation Form”. The data collected via the evaluation form were determined with the multilevel Rasch analysis program. The results of the research revealed that the criteria determined in the evaluation of the 9th-grade physics curriculum differed in terms of strictness and generosity. In addition, the quantitative data analysis revealed that the physics teachers mostly comply with the criteria set in the program while they disapprove of some criteria. The physics teachers reported some deficiencies in the objectives, content, and educational status of the elements included in the program. In this context, it is recommended that the achievements of the 9th-grade 2018 physics curriculum be reviewed in line with the evaluations of the stakeholders related to the subject.

The main thrust of the study was to explore the third-year English student’s sentiments on the application of the artificial intelligence (AI)-integrated paraphrasing tools. Specifically, it aimed to investigate the benefits and drawbacks brought by AI paraphrasing tools towards the writing skills of the students. The investigation utilized a semi-structured interviews with an open-ended questionnaire using an audio-video recorder. The data gathered were interpreted using the Thematic Analysis of Braun and Clarke. The study was carried out at one of the campuses of a state university located at Candijay, Bohol, Philippines. Using the Purposive sampling technique, twelve (12) respondents provided information on the research endeavor. The findings revealed that students had a positive opinion of AI-integrated paraphrase tools: they saw them as helpful resources that significantly improve their academic writing process; it includes plagiarism reduction, efficiency, and timesaving, and aids in rephrasing text. The findings also revealed the risks and issues of using AI-integrated paraphrasing tools, such as Prone to plagiarism, automated suggestions dependency, and loss of original meaning and context. With that, the students showed how they deal with those risks and issues, including as responsible users and thorough editing and reviewing. In accordance with the study, students are encouraged not to rely excessively on AI-integrated paraphrase tools, even though they can improve their writing abilities. This research emphasizes that students play a pivotal role in ensuring the appropriateness of texts generated by AI-integrated paraphrasing tools by mastering the art of proper paraphrasing.

There are studies in the learning management literature examining the measure of system usage, but few explore how users apply the software tools to achieve specific work tasks, which in turn leads to perceived benefits. In the context of distance education, this study focuses on how Learning Management Systems (LMS) are fully used by faculty for their instructional needs. It extends existing research on LMS adoption by investigating how faculty members or instructors use the LMS tools for effective class teaching to achieve educational outcomes. Four usage patterns were identified: communication, content management, assessment, and class management. A model is presented to examine how these usage patterns interplay to achieve the perceived benefits. Data were collected from 544 instructors using LMS, such as Blackboard Learn, etc. Structural equation modeling using LISREL was employed to assess the research model. The results suggest that the usage for communication, content, and assessment activities positively impacts the usage for class management. In turn, the usage for class management influences the net benefits perceived by the instructors, and the usage for content also impacts perceived net benefits directly. These results provide practical guidelines for LMS developers’ design improvements and institutions’ policies, such as training instructors to fully utilize LMS features to achieve the maximum benefits of distance education.

The personalization of learning and teaching processes represents an advanced approach to education that adapts content, pace, and teaching methods to the individual needs and preferences of students. This approach relies on analyzing diverse student characteristics, such as their knowledge level, progress, learning style, and interests. Achieving these goals is significantly supported by the use of information and communication technology, which facilitates and enhances the implementation of personalization in technology-enhanced learning (TEL). The primary objective of personalization is to increase student engagement, motivation, and support in achieving learning outcomes through individualized learning paths, real-time progress tracking, and feedback. This systematic literature review examines existing personalization approaches in secondary and higher education, supported by technology. The study investigates their effectiveness and provides recommendations for future research. Results reveal that personalized teaching methods—primarily through recommender systems, adaptive learning platforms, and algorithm-driven models—are effective in tailoring educational experiences by leveraging diverse student data, such as demographics, prior achievements, learning styles, and digital engagement. The review shows a predominant focus on higher education, particularly in subjects related to computer science and digital technologies. Quantitative evaluations complemented by qualitative insights, consistently indicate that personalization enhances content mastery, motivation, and overall satisfaction, with no significant negative effects identified.