رعنا رحیمی

This study builds on previous reviews of technology-mediated feedback up to 2020 to provide an updated account of research conducted from 2020 onwards. It offers an overview of contextual trends, feedback focus, and the types of technology and software used. The analysis focuses on peer-reviewed studies examining technology-mediated corrective feedback on writing in EFL or ESL contexts, using quantitative or mixed methods approaches. Data were coded using an Excel sheet, and frequencies were reported as percentages. The major findings indicate that technology-mediated feedback is more prevalent in higher education, emphasizing the importance of leveraging technology for enhancing feedback practices. Additionally, half of the publications employed a mixed-methods approach, contributing to a more comprehensive understanding of the topic. However, some studies lacked methodological transparency; therefore, the study highlights the need for stricter reporting guidelines. Furthermore, the findings reveal that teachers and computers are the primary sources of feedback in technology-mediated settings, aligning with their significant roles in traditional and online learning environments. According to the findings, educators are encouraged to adopt technology-mediated feedback in higher education and engage in training and professional development in this area. Moreover, researchers are recommended to continue conducting mixed-methods studies by following more rigorous transparency guidelines.

Using Kane's interpretive argument model and Messick's validity argument approach, this study rigorously examined faculty and PhD candidate’s perspectives on PhD admission interviews in Iranian universities. We interviewed 10 professors and PhD interviewees which provided comprehensive insight into nuanced perspectives. We conducted rigorous content analysis to identify prevalent themes, forming a strong foundation for our analysis. This study emphasizes the vital requirement for standardized evaluation criteria, robust support systems, and an enhanced interview process to ensure fair and inclusive admission systems. Additionally, our development of guidelines based on Toulmin's reasoning model underscores the originality of our contribution and its potential to benefit stakeholders and the Ministry of Science, Research, and Technology (MSRT) in Iran. The findings highlighted the importance of standardized criteria, support, and a stronger interview process for fairness and inclusivity in selecting PhD candidates. Faculty stressed clear guidelines to remove subjectivity, while candidates voiced concerns about unclear expectations and proposed added support like mentoring and preparation programs. Based on Toulmin's reasoning model, the study crafted validity argument guidelines for this context. As a result, these proposed changes will impact stakeholders and the MSRT by enhancing the PhD candidate evaluation process and ensuring a fairness and inclusivity. This study provides valuable insights to improve PhD admission procedures at Iranian universities by integrating standardized criteria, enhancing support mechanisms, and fostering fairness in decision-making.