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31 December 2018 | Story Charlene Stanley
Advising pic
Aligning your study field with your career aspirations can be challenging. Academic advising provides solutions.

Over the past few years, institutions of higher learning have experienced an explosive growth in student numbers. Student volumes are often more than campus administrations can effectively deal with. On the students’ side, coming to grips with and transitioning into university and navigating the academic-content processes and technology can be an overwhelming experience – especially for so-called ‘first-generation’ students. Many students often have fixed career dreams, but not a clear knowledge of what they need to get there. This is where academic advising can be a guiding light.

 How Academic Advising works

 Academic advising fosters the development, engagement, and support of students and provides guidance towards academic, personal, and career success. “Through academic advising we basically make sure that students’ career prospects align with their academic programme,” explains Prof Francois Strydom, Senior Director of the Centre for Teaching and Learning (CTL), which houses the UFS Academic Advisement Unit. It is also not only the academic needs of students that are addressed. He describes advising as a ‘hub of the wheel’ that connects students to different departments and services across campus, depending on their needs.

Evolution of Academic Advising

Prof Strydom explains that some type of advising has always existed on university campuses in the form of career counsellors and faculty managers assisting with student queries. But with many institutions virtually doubling in size over the past few years, many students started ‘falling through the cracks’. “There’s been a great need to professionalise this service and to have a clearly defined structure in place with dedicated advisers to assist students quickly and efficiently,” he says. The UFS academic advising team has been playing a leading role in securing a seven-institution collaborative University Capacity Development Grant (UCDG) in 2017 to professionalise the practice in South Africa. 

“We focus on communicating with and serving Kovsie students in ways that really speaks to them, for instance through the Academic Advising Facebook page, email (advising@ufs.ac.za), the electronic magazine (Kovsie Advice), plus face-to-face interactions in the faculties, the Sasol Library in Bloemfontein, and in the TK Mopeli Building on our Qwaqwa Campus,” says Gugu Tiroyabone, who heads the Academic Advisement Unit within CTL. She emphasises that advising is a shared responsibility. “Advisers can never decide for the students but are there to assist them to make informed decisions themselves.”

Data collected from the 1 456 students who utilised continuous academic advising services at the UFS during 2017, has irrefutably shown that these students have a higher probability of passing most of their modules with over 70% – a clear indication that academic advising really works.

Paving a professional path for advisers

Drawing on eight years of ongoing development in academic advising, the UFS piloted the first nationally contextualised Short Learning Programme for advisers in order to guide the development of this practice.

The pilot of the fully accredited Academic Advising Professional Development (AAPD) Short Learning Programme (SLP), which will be presented twice a year, was presented by the CTL early in October 2018 and represented all seven institutions forming part of the UCDG collaboration (UFS, NMU, Wits, UCT, DUT, MUT, and UP).

With the SLP’s ultimate goal to build and cultivate the practice and its practitioners, this national initiative is likely to be one of the enablers for the development and enhancement of student success in South Africa.

 

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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