Articles

This study investigates whether the Feedback Literacy Scale (FLS) can be developed and validated to measure student teachers’ feedback literacy in teacher education in Myanmar. Based on the Feedback Literacy Scale (FLS) by Yildiz et al. (2020) [1], the Student Feedback Literacy Scale (SFLS) developed by Liao (2021) [2], and the Student Feedback Literacy (SFL) scale by Woitt et al. (2023) [3], the Feedback Literacy Scale was validated. Firstly, the item pool for the feedback literacy scale contained 76 items. The participants of this study were 1550 from 360 first-year, 367 second-year, 378 third-year and 445 fourth-year student teachers. The exploratory factor analysis resulted in a four-factor structure, and the final confirmatory factor analysis indicated acceptable model fit. The final scale demonstrated strong internal consistency and acceptable validity and reliability for use with Myanmar student teachers in teacher education. Therefore, the Feedback Literacy Scale (FLS) was found to be valid and reliable for measuring feedback literacy of student teachers of the teacher education program in Myanmar. This study indeed helps student teachers, school administrators and education policymakers improve their understanding of feedback and application of feedback in their learning for future professional teaching in the Myanmar teacher education program.

Preference learning plays a crucial role in AI applications, particularly in recommender systems and personalized services. Traditional pairwise comparisons, while foundational, present scalability challenges in large-scale systems. This study explores alternative elicitation methods such as ranking, numerical ratings, and natural language feedback, alongside a novel hybrid framework that dynamically integrates these approaches. The proposed methods demonstrate improved efficiency, reduced cognitive load, and enhanced accuracy. Results from simulated user studies reveal that hybrid approaches outperform traditional methods, achieving a 40% reduction in user effort while maintaining high predictive accuracy. These findings open pathways for deploying user-centric, scalable preference learning systems in dynamic environments.

This study aimed to examine students' perceptions of the usefulness of formative feedback in mathematics lessons at Sagnerigu Municipality in the Northern Region of Ghana. Quantitatively, this study employed a descriptive non-experimental survey design. The population comprises all pupils of public Junior High Schools in the Sagnerigu Municipality. A purposive sampling technique was used to select the Junior High School students for the study. The criterion purposive sampling technique was used to select 518 final-year students for the 2022 Basic education certificate examination from 14 schools in Sagnerigu Municipality. The chosen schools comprised 291 students from high-performing schools and 227 students from low-performing schools. The primary tool for the study was the Student Feedback Perception Questionnaire (SFPQ), administered to the student participants. The Descriptive statistical tool was used to analyse the mean and standard deviation of the data. The study's examination of students' perceptions of feedback revealed a moderate level of perceived usefulness. This emphasises the importance of feedback as a tool for student growth and development. However, the findings also suggest the need for further support and guidance to optimise the impact of feedback on student learning outcomes. The findings also suggest that students value feedback that helps them improve their skills and strategies in Mathematics and keeps them on track to succeed. It also highlights the importance of providing different types of feedback to cater to the diverse learning needs of students. Educators can create a conducive environment that promotes student engagement and achievement by equipping teachers with effective feedback techniques, emphasising constructive comments and avoiding grades.

There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare appointments and hospital settings. In this review, the current gap in clinical care for real-time feedback and guidance with pain management decision-making for chronic and post-operative pain treatment is defined. We examine the recent and future applications for predictive analytics of opioid use after surgery and implementing real-time neural networks for personalized pain management goal setting for particular individuals on the path to discharge to normal function. Integration of personalized neural networks with longitudinal data may enable the development of future treatment personalizations paired with electrical simulations.

Seamless integration of information in organizations promotes not only the operational efficiency but also the quality of decisions made by managers. Real-time decision support systems enable organizations to evaluate organizational changes immediately and ideally gives a hint of problems before they even appear in the organization. Such real time systems are nowadays regarded as the front-line solutions for managing organizations effectively. The technological possibilities seem not to conquer management. For most companies the data is still dealt with traditional solutions, data is collected and reports are generated to evaluate the past occurrences which only gives information on what has happened in the organization. The problem with these non-real-time systems is the reflection of organizational condition very late. These are the common rear-mirror descriptions for what already has been. Managers are receiving information from their organizations too late and often too little to make optimal decisions. Is it not possible to manage operations in real-time? Is real-time decision support really needed? If so, why most organizations still rely on traditional reporting systems.

<b>Background and aim:</b> Developing clinical skills and its assessment is one of the most important components in nursing education which prepares the student for the reality of practice. Objective structured clinical examination (OSCE) is extensively used and widely accepted by nurse educators across the globe to assess the competency skills of nursing students. The present study aimed at identifying the attitude and perceptions of faculty, and exploring their feedback and experience in conducting OSCE as an assessment tool. <b>Methods:</b> A triangulation research approach was used with convenience sampling. Data collection was carried out using questionnaires and semi-structured interviews. Participants were ten faculty members who were involved in conducting OSCE for students. <b>Results and conclusion</b>: Most of the faculty felt that OSCE reflected the skills of delivery of safe patient care, and the structure reflected mastery of knowledge and skills, which are related to course objectives. OSCE was regarded by the faculty as a consistent, reliable, valid, and objective measure to assess students’ performance and to improve students’ confidence in clinical skills. Concerns were raised about a high level of stress in students, the time required for the proper performance of tasks, OSCE scenarios lacking real-life situations in assessment, and the need for repeated practice and intensive mock training sessions. The applicability of OSCE in terms of limitations in human and material resources with a large number of students would necessitate rethinking in developing other assessment strategies to improve the overall process.