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02 October 2019 | Story Anneri Meintjes | Photo Charl Devenish
Anneri Meintjes
Anneri Meintjes from the Centre for Teaching and Learning at the UFS.

The #FeesMustFall student-led movement started in 2015 to protest against increasing student fees and to call for increased government funding of universities. At the end of 2016, the protests led to mass disruption of academic activities in higher-education institutions countrywide. Some universities, including the University of the Free State (UFS), suspended academic activities for extended periods which necessitated online and blended learning approaches (the combination of face-to-face and online learning) to complete the academic year. In most cases, these methods were unplanned and unstructured, and knowledge gaps in good blended learning practice were identified.

The Carnegie Corporation of New York funded a two-year research project in collaboration with the University of Pretoria, UFS, University of Cape Town and University of Johannesburg to investigate the use of blended learning at the end of 2016, during the campus disruptions, as well as how these respective institutions used blended learning in 2017.

The prohibitive cost of data in South Africa means few of our students have access to the internet off-campus. The most recent data on UFS student digital identity shows that only 21% have consistent, reliable access to the internet at home. This is a challenge not only for the UFS but for all universities in the country.

“For technology to be used in a way that contributes to learning and teaching, we needed to investigate what works well and what does not, considering our contextual challenges” says Anneri Meintjes from the Centre for Teaching and Learning, who was the principal researcher for the UFS on this project. In the first phase of the research, she wrote a case study on the UFS’ approach to blended learning during and after the protests in 2016. The findings of this phase of the research were presented at a national convening of higher-education institutions across South Africa.

In the second phase of the research, the four participating universities produced open educational resources on good, blended learning practice to share with universities countrywide. The UFS was responsible for the development of online assessment resources and general best-practice guidelines for the use of blended learning. Anneri says: “While we had laid solid foundations for the effective use of online assessment at the UFS prior to 2016 through the investment in online assessment software and staff development in online assessment design, we learnt many valuable lessons during that time. It provided momentum for the establishment of formal online assessment procedures and refinement of best-practice guidelines. This research project gave us an opportunity to share our work on a national platform.” The number of lecturers that use online assessment in their modules has grown considerably at the UFS since 2016. In 2016, 211 online assessments were completed on Questionmark (UFS online assessment programme) and in 2018, this number had grown to 743. Institutional Blackboard use data shows that at least one online assessment tool is used in 47% of all modules on Blackboard.

Resources developed by the other participating institutions include a self-evaluation app that academics can use to reflect on their existing blended learning practices, and an online utility that assists lectures and course designers to plan blended learning modules.

Anneri also coordinated the development of the national website, which was launched at the Flexible Futures conference hosted by the University of Pretoria on 9-10 September 2019. The website and resources were praised at the conference for being a timely response to a critical need in the higher education community in South Africa.

News Archive

Researcher works on finding practical solutions to plant diseases for farmers
2017-10-03

 Description: Lisa read more Tags: Plant disease, Lisa Ann Rothman, Department of Plant Sciences, 3 Minute Thesis,  

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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