This study examines if Pacific students’ academic background and engagement in a student support programme was associated with first-year students’ academic success, and retention. This is a cohort study of linked administrative and attendance data for Pacific students (N=1532) enrolled in a first-year Health Sciences programme, at a New Zealand university, between 2013 and 2025. Statistical regression models were used to test associations between engagement or preparation with academic outcomes. We found engagement in support programmes was significantly associated with first-year success independent of students’ academic background. However, arriving at university with the best possible academic preparation had the greatest influence on their academic success. These findings reinforce the need for early, targeted interventions that address both academic and cultural dimensions of student success, particularly for those who are less prepared upon arrival. Strengthening collaboration with secondary schools, improving early academic preparation, and ensuring adequate resourcing of support programmes are essential to achieving equity in health professional pathways for Pacific students.
Early assessment (EA) is a key component of learning, providing students with opportunities to receive feedback, clarify expectations, and build confidence. This is particularly important for first-year students transitioning to university. This study considers whether EA performance is a reliable predictor of future performance, and whether this depends on student group or EA format. Results indicate that for high-performing students, EA is a reliable predictor of future success; however, other groups have mixed results. The ability of EA to predict future performance also depends on EA format, particularly for lower-performing groups. Where EA is not a reliable predictor of future performance, we suggest that it instead, in some cases, serves as a useful catalyst, leading to improved performance. These findings highlight the importance of EA, and the careful consideration required when determining EA format and associated support strategies, to effectively scaffold student success, particularly for lower-performing and at-risk students.
This research explores the critical intersection of consistency, standards and complexity in academic assessment integrity using focus groups consisting of academic staff and undergraduate nursing students. While academic quality standards are mandated by accreditation bodies to ensure accountability and skill acquisition, the marking process remains a complex, intuitive task heavily reliant on a marker's experience and practicality. Significant challenges arise when marking becomes overly criteria-driven at the expense of core assessment goals, leading to variability in judging relevant student ideas or specific technical skills such as referencing. Such variability undermines the reliability and objectivity essential for assessment fairness. To mitigate these risks, pre-marking meetings are identified as essential for establishing shared requirements and expectations among staff. Strategic timing of these supports, ideally pre-semester, provides the necessary framework for quality assurance and enables markers to make meaningful and accurate judgements regarding a student’s true knowledge and performance. Keywords: student/ marking/ assessment/ quality/consistency/ tertiary education
The objective of this study was to analyse the inclusive culture in the Faculty of Engineering of a private university in Lima. The research focused on teaching staff and student perceptions regarding the value of student diversity and the barriers that hinder academic performance. The approach was qualitative with a phenomenological design and included a sample of 10 university teachers and six students. The instruments used were a semi-structured interview guide for university teachers and a focus group guide for students. The data analysis procedure was conducted using ATLAS.ti (version 23). The results demonstrate a gap between the valuation of diversity and inclusive practice, whereby Universal Design for Learning (UDL) is not incorporated into session planning. Likewise, a lack of learning supports is recognised as a result of institutional deficiencies.
Early identification of students experiencing academic difficulty is critical to supporting student success and retention in their first year of university. This study examines an interpretable learning analytics framework designed to support timely intervention in a first-year introductory statistics unit. Data from 566 students across three cohorts were used to develop and evaluate predictive models using assessment results collected during the teaching period and enrolment characteristics. The selected model demonstrated strong predictive performance and was validated on a subsequent cohort. To support practical implementation, predictions were translated into a colour-coded risk report that enables educators to quickly identify and prioritise students requiring academic support. SHapley Additive exPlanations (SHAP)-based explanations were incorporated to provide transparency and assist educators in understanding the factors contributing to individual risk classifications. Findings indicate that formative assessments are the strongest indicators of academic success, highlighting opportunities for proactive and targeted intervention. The framework demonstrates how interpretable learning analytics can support evidence-informed decision-making and student success in large first-year units.
