A large-scale investigation into the relationship between attendance and attainment: a study using an innovative, electronic attendance monitoring system, Studies in Higher Education, 33:6, 699-717,The literature available on the relationship between student attendance and attainment is inconsistent. Nevertheless, there is some empirical evidence to suggest that attendance is a determinant of academic performance and progression. Colby published results of a study which examined the relationship within a single year 1 undergraduate module, and his findings showed a strongly significant relationship between attendance and attainment. However, Colby's article, along with countless other attendance studies, suffers inherent data collection limitations that are associated with paper-based attendance monitoring and manual data entry. UniNanny® is an electronic attendance monitoring system developed at the University of Glamorgan, which boasts high-quality data and minimises disadvantages associated with paper-based methods. The purpose of this study was to corroborate, or otherwise, the findings of Colby, though on a much larger scale, evaluating 22 first year modules within four separate award programmes, using attendance data gathered and stored electronically. The results of this study show a strong, statistically significant correlation between learning event attendance and academic attainment, thereby substantiating Colby's findings. Data revealed that the more a student attends classes, the less chance they have of failing academic assessments, and the more chance they have of attaining high grades. Attendance was found to decline considerably over time, though early morning lectures were not associated with significantly worse attendance. IntroductionStudent motivation, effective note-taking, time-management, endeavour, participation in the educational programme, attitudes about learning and reading the correct materials are likely determinants of academic achievement. However, undergraduates are often looking for additional factors to aid their chances of success on a course. In the past academics have attempted to use personality traits and other subjective factors to predict students' academic attainment. For example, Barney, Fredericks, and Fredericks (1984) investigated the impact of personality, stress, social norms, anxiety and social class on student grades. Similarly, Baird (1984) investigated how well personality, aptitude and scores on an intelligence test can be used to predict assessment outcomes. Despite producing interesting results, studies such as these are incapable of providing students with information on what they can do to enhance their own educational performance.Every student is in command of their own attendance; a course-related behaviour that can be easily and precisely measured. It would make sense to suggest that the more a student attends learning events, such as lectures or tutorials, the more information they acquire and

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.ACCORDING to the National Audit Office (NAO), 2007, higher education participation has increased and widened from 39% of 18-to 30-year-olds in 1999-2000 to 43% in 2005-06. However, they also stated that there is a need to achieve a balance between increasing participation and bearing down on rates of non-completion. Performance indicators reveal that one in six students drop out of higher education, at a cost to the taxpayer of at least £450m per year in wasted fees and subsidised loans (Baty, 2006). NAO (2007) figures show that more than 100,000 students who dropped out of their courses did so during their first year of study. Failure and poor attainment during the first year significantly contribute to the overall statistics for non-progression (Scott and Graal, 2007). Nevertheless, whilst considerable attention has been directed towards researching factors associated with first-year dropout (eg Christie et al, 2004), less attention has been dedicated to students who fail academically.At the University of Glamorgan, both retention and attainment are of particular concern. The University's attrition figures have compared unfavourably with other UK institutions. The average dropout rate for all first-degree students over all courses and all levels is 22.4%. The average dropout rate between year 1 and year 2 is 30%. The Higher Education Statistics Agency (HESA, 2007) figures, based on the 2005-06 academic year, highlight attainment issues specific to the University: 29.4% of Glamorgan undergraduates are from low participation neighbourhoods (against a benchmark of Abstract THE NUMBER of people engaging in higher education (HE) has increased considerably over the past decade. However, there is a need to achieve a balance between increasing access and bearing down on rates of non-completion. It has been argued that poor attainment and failure within the first year are significant contributors to the overall statistics for non-progression and that, although research has concentrated on factors causative of student withdrawal, less attention has focused on students who fail academically. This study investigated the effects of a number of factors on the academic attainment of first-year und...

The popularity of engineering degrees among undergraduates is in decline. There are many barriers affecting the supply of engineering undergraduates and the School of Technology at the University of Glamorgan has identified lack of awareness of what engineering entails and lack of mathematical preparedness as two principal barriers to potential students studying engineering in higher education. To show how the School of Technology overcame these barriers, the role of the Network75 Recruitment and SupportOfficer will be explained along with the subsequent development of a remedial summer mathematics programme entitled 'Bridging Technology with Mathematics'. These two initiatives are outlined and their success evaluated in terms of increasing engineering undergraduate enrolments for the academic year 2005/06.

This study reports on the progress of undergraduate students who, during the summer of 2005, participated in a top-up mathematics programme at the University of Glamorgan. Bridging Technology with Mathematics was developed to improve the mathematical preparedness of prospective students for the mathematical demands of engineering in Higher Education (HE). The course was designed in response to a serious decline in students' mastery of basic mathematical skills and level of preparation for mathematics-based degree courses. This paper evaluates whether the course was able to provide students with sufficient mathematical competence/ understanding to successfully complete the mathematical elements of their degree courses. Opinions and experiences regarding the Bridging Technology with Mathematics programme were also sought from engineering lecturers and the students themselves. Findings show that students who entered engineering degree programmes through the Bridging Technology with Mathematics route performed better than their fellow students in both mathematical and non-mathematical module assessments. The programme provided the additional benefits of improving students' mathematical competence and confidence, academic motivation, preparedness for HE and conviction that they had chosen the correct course.

The Making Assessment Count (MAC) project started at the University of Westminster in 2008. It sought to align staff and student expectations of feedback and support greater use of feed-forward approaches. A baseline analysis of staff views in the School of Life Sciences suggested that students did not make strategic use of the feedback they received. A similar analysis of the student position revealed that as a group they felt that the feedback provided to them was often insufficiently helpful. To address this dichotomy, a MAC process was developed in the School of Life Sciences and trialled with a cohort of about 350 first year undergraduate students. The process was based on a student-centred, three-stage model of feedback: Subject specific, Operational, and Strategic (SOS model). The student uses the subject tutor's feedback on an assignment to complete an online self-review questionnaire delivered by a simple tool. The student answers are processed by a web application called e-Reflect to generate a further feedback report. Contained within this report are personalised graphical representations of performance, time management, satisfaction and other operational feedback designed to help the student reflect on their approach to preparation and completion of future work. The student then writes in an online learning journal, which is shared with their personal tutor to support the personal tutorial process and the student's own development plan (PDP). Since the initial development and implementation of the MAC process within Life Sciences at Westminster, a consortium of universities has worked together to maximise the benefits of the project outcomes and collaboratively explore how the SOS model and e-Reflect can be exploited in different institutional and subject contexts. This paper presents and discusses an evaluation of the use of the MAC process within Life Sciences at Westminster from both staff and student perspective. In addition, the paper will show how the consortium is working to develop a number of scenarios for utilisation of the process as a whole as well as the key individual process components, the SOS model and e-Reflect.