ArticleThe South African journal of communication disorders = Die Suid-Afrikaanse tydskrif vir Kommunikasieafwykings2022
Application of machine learning approaches to analyse student success for contact learning and emergency remote teaching and learning during the COVID-19 era in speech-language pathology and audiology.
Article in The South African journal of communication disorders = Die Suid-Afrikaanse tydskrif vir Kommunikasieafwykings, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- AI applications in disaster governance with health approach: A scoping review.Archives of public health = Archives belges de sante publique · 2025Pooled it
- Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.Sensors (Basel, Switzerland) · 2024Article
- We need a decolonized appropriation of AI in Africa.Nature human behaviour · 2023Article
- The impact of COVID-19 on speech-language and hearing professions in low- and middle-income countries: Challenges and opportunities explored.The South African journal of communication disorders = Die Suid-Afrikaanse tydskrif vir Kommunikasieafwykings · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe onset of the COVID-19 pandemic across the globe resulted in countries taking several measures to curb the spread of the disease. One of the measures taken was the locking down of countries, which entailed restriction of movement both locally and internationally. To ensure continuation of the academic year, emergency remote teaching and learning (ERTL) was launched by several institutions of higher learning in South Africa, where the norm was previously face-to-face or contact teaching and learning. The impact of this change is not known for the speech-language pathology and audiology (SLPA) students. This motivated this study.
objectivesThis study aimed to evaluate the impact of the COVID-19 pandemic on SLPA undergraduate students during face-to-face teaching and learning, ERTL and transitioning towards hybrid teaching and learning.
methodUsing course marks for SLPA undergraduate students, K means clustering and Random Forest classification were used to analyse students' performance and to detect patterns between students' performance and the attributes that impact student performance.
resultsAnalysis of the data set indicated that funding is one of the main attributes that contributed significantly to students' performance; thus, it became one of the priority features in 2020 and 2021 during COVID-19.
conclusionThe clusters of students obtained during the analysis and their attributes can be used in identification of students that are at risk of not completing their studies in the minimum required time and early interventions can be provided to the students.
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