or more than two decades, university professors at the institute of study have implemented group oral examinations as a summative assessment strategy within their courses. This essay offers a critical reflection on the pedagogical benefits of this format, examining its impact on both instructors and students, while also addressing the practical and logistical challenges encountered in its sustained use. In the context of the rapid proliferation of artificial intelligence and the corresponding complications it introduces for traditional assessment practices, the authors argue that group oral examinations have gained renewed significance. Specifically, they highlight the capacity of this approach to promote authentic demonstration of student learning and to cultivate communication, collaboration, and critical thinking skills that are essential for post-graduate professional contexts.
From Reflection to Confidence: Student Career Self-Efficacy in Course-Embedded Career Learning at a Minority-Serving Institution Abstract This study examines undergraduate students’ career decision-making self-efficacy and related performance indicators within course-integrated career readiness assignments at a Hispanic- and minority-serving institution. As higher education institutions seek scalable approaches to workforce preparation, embedding career development into credit-bearing coursework may offer more equitable access to professional learning opportunities, particularly for students at Minority-Serving Institutions. Guided by Bandura’s theory of self-efficacy and the career decision-making self-efficacy framework, this evaluation study analyzes descriptive data from faculty-rated rubric summaries across multiple course-integrated assignments (assignment-level sample sizes varied) and student self-reported surveys (n = 55 respondents). Three embedded assignments were examined: a career reflection essay, a résumé and career research project, and a mock interview and presentation. Results indicated that most students met established performance benchmarks and reported moderate to high confidence across career goal articulation, job search preparedness, and transition readiness. Consistent with the study’s exploratory design, findings are interpreted as associative rather than causal and are discussed in relation to self-efficacy mechanisms and instructional assessment practices. The study offers a transferable example of how routine classroom assessments can serve as scholarship of teaching and learning evidence for evaluating embedded career development.
This paper examines the use of generative artificial intelligence in the development of teaching cases for MBA programs. The study introduces the Lecturer Oversight and Verification of AI (LOV AI) Co-Creation Approach, which integrates the ChatGPT 5.2 Thinking Deep Research model with structured subject expert supervision to produce teaching extended case studies and related teaching materials. The model is implemented through a multi-step process. First, specific prompts are used to identify and select potential case topics that align with required syllabus objectives. Next, the AI model generates extensive drafts that include narratives, background information, and supporting data for each case. These outputs are then reviewed in detail by a subject expert who verified the accuracy of the information, corrected any inconsistencies, and adjusted the content to meet pedagogical standards. This process involves constant iterative improvements and co-creation actions by the lecturer to ensure that the final materials reflect both current business developments and academic rigor. Preliminary findings indicate that the integration of AI reduces the time required to produce high-quality teaching cases while maintaining the depth and complexity necessary for graduate-level education. However, the study also highlights the importance of continuous human intervention of subject experts to address potential factual errors and to ensure the educational integrity of the cases. The paper contributes a practical framework for AI-assisted case study development, offering insights into the benefits and limitations of merging automated tools with expert oversight in the context of business education. Further research is recommended to evaluate the model’s long-term impact on teaching effectiveness and student learning outcomes.
In recent years, Australian universities have intensified efforts to respond to the growing demand for remote and online study. This shift has underscored the need for academics who are appropriately prepared to design, develop, deliver, and evaluate high-quality online courses. Mentoring represents a key practice that can support the development of such expertise. However, formalized and well-established mentoring practices are not consistently present across Australian higher education institutions. In contrast, most universities maintain academic development units tasked with enhancing teaching capacity, particularly in relation to online learning. This paper conceptualizes aspects of academic development practice as a form of mentoring. Drawing on the authors’ experiences as academic developers, it critically examines how academic development initiatives can function as mentoring mechanisms. Two illustrative cases from Australian universities engaged in online education are presented to demonstrate this alignment. The paper concludes by proposing strategies for fostering mentoring through the intentional leveraging of academic development practices and discusses the broader implications for institutions seeking to strengthen online teaching capacity.
In South African universities, multilingual students whose first language is not English face distinct challenges that impact academic participation and success. This qualitative study examines how second language (L2) anxiety shapes first-year students’ classroom and clinical experiences at the University of Cape Town. Drawing on open-ended survey data, the study reveals that fear of negative evaluation, communicative apprehension, and prevailing language ideologies contribute to students’ reluctance to speak, feelings of invisibility, and withdrawal from engagement. Although anxiety tends to lessen over time, it rarely disappears completely. Notably, students experienced anxiety differently across settings: classroom discussions elicited greater fear and self-censorship, while clinical interactions, often involving shared linguistic and cultural backgrounds, felt less intimidating. Findings highlight the need for systemic, structural interventions that validate diverse English varieties and promote inclusive, low-anxiety learning environments through pedagogical and institutional reform.
