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2020 NSFAS Funding at Universities

04 March 2020

What does the bursary cover?

• Accommodation
• Transport (up to 40 km from institution)
• Meal allowance (including incidental allowance)
• Book allowance
• Registration
• Tuition
• Funded students with disabilities need to submit claims for assistive devices and human support directly to the university’s Centre for Universal Access and Disability Support (CUADS)/Financial Aid office.

Who qualifies for NSFAS allowances?

STUDENTS STAYING IN A RESIDENCE:
• Books up to a maximum of R5 200
• Actual accommodation cost
• Meals (including incidental allowance) up to a maximum of R15 000

STUDENTS LIVING OFF CAMPUS IN FAMILY ACCOMMODATION

• Books up to a maximum of R5 200
• Meals (including incidental allowance) up to a maximum of R15 000
• Transport up to a maximum of R7 500

STUDENTS LIVING OFF CAMPUS IN ACCREDITED and NON-ACCREDITED ACCOMMODATION:

• Books up to a maximum of R5 200
• Private accommodation amount to a maximum of R34 400
• Meals (including incidental allowance) up to a maximum of R15 000

DISTANCE-LEARNING STUDENTS:

• Books based on the number of modules registered, up to a maximum of R5 200

Please note that students who were registered for the first time at a tertiary institution before 2018 are subject to a maximum NSFAS amount for the year. The maximum NSFAS amount for 2020 is R93 400.
According to NSFAS policy, payments must be made in the following order of priority if your qualifying NSFAS costs exceed the maximum amount:
1. Tuition
2. Books
3. Accommodation
4. Meals
5. Transport
This means that the amount by which you exceeded the maximum NSFAS amount must be deducted from your allowances, starting with the transport and meal allowances. Therefore, you might not receive the full allowances.

How will NSFAS allowances be paid?

NSFAS allowances will be paid in cash to the student via the Fundi system. Once the allowances are debited to your student class-fee account, you will receive an SMS message from Fundi to upload your banking details. Fundi will confirm your banking details and payment will follow.

Please note that no payments will be made to a third party.
You only need to upload your banking details once. If you experience any problems with uploading your banking details, please contact Fundi at 086 055 5544.

When will I receive my NSFAS allowances?

NSFAS allowances will be paid during the first week of each month over a period of 10 months. Please note that due to several variables, a specific date for payment cannot be provided.

How do I apply for NSFAS private accommodation?

Please visit the UFS website for a complete guide:
Students
Financial Aid

When will I receive my private accommodation payment?

You must apply online for your private accommodation. It is compulsory to upload your rental agreement and proof of home address. If your private accommodation application is approved by the 25th of a month, you will receive payment from your move-in date up to date during the first week of the following month, and thereafter you will receive your monthly payments until November.

How will I know if my private accommodation application status has changed?

You will immediately receive an email on your ufs4life email address when your status changes.

What should I do if my private accommodation application is incomplete?

Please log in on your Student Self-Service. The reasons for your incomplete application will be listed under your private accommodation application. Please correct the application and resubmit. Please do not resubmit if the application was not corrected.
Please visit the website for clear explanations on the reasons for incomplete applications if you are unsure of what is expected of you.

Please note that no payment will be made before your private accommodation application is approved.

When is the closing date for NSFAS private accommodation applications?
The closing date for private accommodation applications is 11 September 2020. Please note that no extension will be granted.

News Archive

Researcher works on finding practical solutions to plant diseases for farmers

2017-10-03

Lisa Ann Rothman, researcher in the Department of
Plant Sciences.
Photo: Supplied

Plant disease epidemics have wreaked havoc for many centuries. Notable examples are the devastating Great Famine in Ireland and the Witches of Salem.

Plant diseases form, due to a reaction to suitable environments, when a susceptible host and viable disease causal organism are present. If the interactions between these three factors are monitored over space and time the outcome has the ability to form a “simplification of reality”. This is more formally known as a plant disease model. Lisa Ann Rothman, a researcher in the Department of Plant Sciences at the University of the Free State (UFS) participated in the Three Minute Thesis competition in which she presented on Using mathematical models to predict plant disease.

Forecast models provide promise fighting plant diseases
The aim of Lisa’s study is to identify weather and other driving variables that interact with critical host growth stages and pathogens to favour disease incidence and severity, for future development of risk forecasting models. Lisa used the disease, sorghum grain mold, caused by colonisation of Fusarium graminearum, and concomitant mycotoxin production to illustrate the modelling process.

She said: “Internationally, forecasting models for many plant diseases exist and are applied commercially for important agricultural crops. The application of these models in a South African context has been limited, but provides promise for effective disease intervention technologies.

Contributing to the betterment of society
“My BSc Agric (Plant Pathology) undergraduate degree was completed in combination with Agrometeorology, agricultural weather science. I knew that I wanted to combine my love for weather science with my primary interest, Plant Pathology.
“My research is built on the statement of Lord Kelvin: ‘To measure is to know and if you cannot measure it, you cannot improve it’. Measuring the changes in plant disease epidemics allows for these models to be developed and ultimately provide practical solutions for our farmers. Plant disease prediction models have the potential ability to reduce the risk for famers, allowing the timing of fungicide applications to be optimised, thus protecting their yields and ultimately their livelihoods. I am continuing my studies in agriculture in the hope of contributing to the betterment of society.”

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