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On providing feedback to students

3 minute read

Published:

Enye yezinto endinomdla ngazo zii-theory zokwakha nokunikezela iingxelo kubafundi bakho. Emaxesheni amaninzi xa ufundisa, uye wakhe iingxaki okanye uzithathe kwincwadi onayo, uzenze kunye nabafundi bakho eklasini. Ngoku ndandifunda kubamanga abantsi, ootishala babesenza le nto amaxesheni amaninzi (ayekhona amaxesha apho kulindeleke ingxaki uyisombulule ngowakho njengomfundi). Eyona nto ndiyikhumbulayo ngelixesha kukuba kwakulula kwaye kumnandi ukuzama ukusombulula ezo ngxaki, eklasini ninonke kunye notishala. Kwaye, le nto yayinjalo kuzo zonke izifundo, ukuqala kwisiXhosa (e.g., xa sihlalutya imibongo umzekelo) ukuya kwiMathematika.

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publications

OWLSIZ: An isiZulu CNL for structured knowledge validation

Published in WebNLG, 2020

In iterative knowledge elicitation, engineers are expected to be directly involved in validating the already captured knowledge and obtaining new knowledge increments, thus making the process time consuming. Languages such as English have controlled natural languages than can be repurposed to generate natural language questions from an ontology in order to allow a domain expert to independently validate the contents of an ontology without understanding a ontology authoring language such as OWL. IsiZulu, South Africa’s main L1 language by number speakers, does not have such a resource, hence, it is not possible to build a verbaliser to generate such questions. Therefore, we propose an isiZulu controlled natural language, called OWL Simplified isiZulu (OWLSIZ), for producing grammatical and fluent questions from an ontology. Human evaluation of the generated questions showed that participants’ judgements agree that most (83%) questions are positive for grammaticality or understandability,

Recommended citation: Mahlaza et al. 2020

talks

teaching

Compilers I @ UCT

Honours course, University of Cape Town, Department of Computer Science, 2021

This course introduced students to the inner mechanics of a modern programming language compiler or interpreter. Students learnt to appreciate why programming languages are designed in particular ways, how to develop compilers and compiler-related tools. Course content included: language classes, formal grammars, parsing, and abstract syntax trees.

Advanced Programming (INF272) @ UP

Second year course, University of Pretoria, Department of Informatics, 2021

This course introduces students to advanced concepts that are required to create web applications using the C# programming language. It covers various topics from html, css, bootstrap, OOP, databases, entity framework (MS’ ORM), etc.

Applied Data Science (INF791) @ UP

Honours course, University of Pretoria, Department of Informatics, 2021

This course introduces students to a variety of concepts within data science using a visual programming environment called RapidMiner. Specifically, the course introduces students to correlation, regression, various clustering models, association rule mining, neural networks, etc. Afterwards, students are expected to be able to use the CRISP-DM methodology to solve a number of problems that one would encounter in-the-wild.

Advanced Programming (INF272) @ UP

Second year course, University of Pretoria, Department of Informatics, 2022

This course introduces students to advanced concepts that are required to create web applications using the C# programming language. It covers various topics from html, css, bootstrap, OOP, databases, entity framework (MS’ ORM), etc.

Advanced Programming (INF354) @ UP

Third year course, University of Pretoria, Department of Informatics, 2022

This course introduces students to a variety of topics aimed at mastering full-stack development. The main topics focus on getting students to learn how to develop Angular web and Ionic mobile applications that interact with independent APIs. Students are also expected to learn how to create APIs using the .Net Core cross-platform framework.

Applied Data Science (INF791) @ UP

Honours course, University of Pretoria, Department of Informatics, 2022

This course introduces students to a variety of concepts within data science using a visual programming environment called RapidMiner. Specifically, the course introduces students to correlation, regression, various clustering models, association rule mining, neural networks, etc. Afterwards, students are expected to be able to use the CRISP-DM methodology to solve a number of problems that one would encounter in-the-wild.