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12 May 2023 | Story Kekeletso Takang | Photo Supplied
Faculty of Education shapes learners’ dreams
Stakeholders forming the multidisciplinary team and a learner from Kgotsofalo Primary School at the event on 21 April 2023, are from the left: Dina Mashiyane, Dr Vusiwana Babane, Ronet Vrey, a learner from Kgotsofalo Primary School, and Prof Bekithemba Dube.

There has been a clarion call within the education sector for primary school intervention strategies. As an institution that invests in education in its surrounding areas and beyond, the University of the Free State (UFS) has heeded the call to impactfully support societal development as outlined in its Vision 130. Through its Faculty of Education, the UFS has adopted the Kgotsofalo Primary School in the Free State to help shape the minds of the learners in this rural school.    

Dr Vusiwana Babane, Lecturer in the Faculty of Education, identified the school – situated about 46 km from the UFS Bloemfontein Campus – as part of a community engagement project that aims to transform the lives of children in low-income communities, in order to eradicate and break the vicious cycle of poverty in their families and communities. The project also seeks to inform stakeholders about the role that higher education institutions can play in supporting farm and rural schools.

Multidisciplinary approach

Prof Bekithemba Dube, acting Head of the Department of Education Foundations in the Faculty of Education, says the initiative with Kgotsofalo Primary School is a culmination of efforts to engage the community around the UFS. “Dr Babane and I visited the school in March 2023 to establish the needs of the school, which could help in planning and exploring intervention strategies. We established that, among others, their needs included motivation for learners, career guidance, library and sports resources. This implied that we needed a multidisciplinary approach. We invited Grade 7 learners from the school to attend motivational and career guidance sessions. We then started collaborating with colleagues from the Education Science Centre, KovsieSport, and the UFS Library and Information Services (Sasol Library) to co-host the learners and for further interventions at the school.”

On 21 April 2023, the learners, teachers, and representatives of the school governing body (SGB) visited the UFS. Hosted at the newly built UFS Education Science Centre, the learners participated in and explored various science experiments. A visit to the UFS library was also part of the package and the learners were treated to motivation, career guidance, and souvenirs from the Faculty of Education, before concluding their visit with a tour to KovsieSport. 

Masontaha Mosuoe, one of the learners who delivered an acceptance speech that brought many to tears, thanked the UFS for the experience. “Today, I would like to thank the UFS for giving our school the opportunity to be here; as you all know, education on the farms is not like the ones in the city. On the farms, children struggle to go to school because the schools are not enough. Thank you for giving us the experience of varsity life and shaping our dreams at a very young age.” 

The Principal of Kgotsofalo Primary School, Mmadikeledi Seepamore, also expressed her gratitude to the university. “Seed was sown and will continue to grow. The experience was educational, fun, and good and changed my learners’ way of thinking.”

Click here for more information on the programmes and other offerings and initiatives in the Faculty of Education.

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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