Research Publications

We explore how machine learning (ML) and Bayesian networks (BNs) can be combined in a personal health agent (PHA) for the detection and interpretation of electrocardiogram (ECG) characteristics. We propose a PHA that uses ECG data from wearables to monitor heart activity, and interprets and explains the observed readings. We focus on atrial fibrillation (AF), the commonest type of arrhythmia. The absence of a P-wave in an ECG is the hallmark indication of AF. Four ML models are trained to classify an ECG signal based on the presence or absence of the P-wave: multilayer perceptron (MLP), logistic regression, support vector machine, and random forest. The MLP is the best performing model with an accuracy of 89.61% and an F1 score of 88.68%. A BN representing AF risk factors is developed based on expert knowledge from the literature and evaluated using Pitchforth and Mengersen’s validation framework. The P-wave presence or absence as determined by the ML model is input into the BN. The PHA is evaluated using sample use cases to illustrate how the BN can explain the occurrence of AF using diagnostic reasoning. This gives the most likely AF risk factors for the individual

@inbook{478,
  author = {Tezira Wanyana and Mbithe Nzomo and C. Sue Price and Deshen Moodley},
  title = {Combining Machine Learning and Bayesian Networks for ECG Interpretation and Explanation},
  abstract = {We explore how machine learning (ML) and Bayesian networks (BNs) can be combined in a personal health agent (PHA) for the detection and interpretation of electrocardiogram (ECG) characteristics. We propose a PHA that uses ECG data from wearables to monitor heart activity, and interprets and explains the observed readings. We focus on atrial fibrillation (AF), the commonest type of arrhythmia. The absence of a P-wave in an ECG is the hallmark indication of AF. Four ML models are trained to classify an ECG signal based on the presence or absence of the P-wave: multilayer perceptron (MLP), logistic regression, support vector machine, and random forest. The MLP is the best performing model with an accuracy of 89.61% and an F1 score of 88.68%. A BN representing AF risk factors is developed based on expert knowledge from the literature and evaluated using Pitchforth and Mengersen’s validation framework. The P-wave presence or absence as determined by the ML model is input into the BN. The PHA is evaluated using sample use cases to illustrate how the BN can explain the occurrence of AF using diagnostic reasoning. This gives the most likely AF risk factors for the individual},
  year = {2022},
  journal = {Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE},
  pages = {81-92},
  publisher = {SciTePress},
  address = {INSTICC},
  isbn = {978-989-758-566-1},
  doi = {https://doi.org/10.5220/0011046100003188},
}

Stock markets are dynamic systems that exhibit complex intra-share and inter-share temporal dependencies. Spatial-temporal graph neural networks (ST-GNN) are emerging DNN architectures that have yielded high performance for flow prediction in dynamic systems with complex spatial and temporal dependencies such as city traffic networks. In this research, we apply three state-of-the-art ST-GNN architectures, i.e. Graph WaveNet, MTGNN and StemGNN, to predict the closing price of shares listed on the Johannesburg Stock Exchange (JSE) and attempt to capture complex inter-share dependencies. The results show that ST-GNN architectures, specifically Graph WaveNet, produce superior performance relative to an LSTM and are potentially capable of capturing complex intra-share and inter-share temporal dependencies in the JSE. We found that Graph WaveNet outperforms the other approaches over short-term and medium-term horizons. This work is one of the first studies to apply these ST-GNNs to share price prediction.

@article{443,
  author = {Kialan Pillay and Deshen Moodley},
  title = {Exploring Graph Neural Networks for Stock Market Prediction on the JSE},
  abstract = {Stock markets are dynamic systems that exhibit complex intra-share and inter-share temporal dependencies. Spatial-temporal graph neural networks (ST-GNN) are emerging DNN architectures that have yielded high performance for flow prediction in dynamic systems with complex spatial and temporal dependencies such as city traffic networks. In this research, we apply three state-of-the-art ST-GNN architectures, i.e. Graph WaveNet, MTGNN and StemGNN, to predict the closing price of shares listed on the Johannesburg Stock Exchange (JSE) and attempt to capture complex inter-share dependencies. The results show that ST-GNN architectures, specifically Graph WaveNet, produce superior performance relative to an LSTM and are potentially capable of capturing complex intra-share and inter-share temporal dependencies in the JSE. We found that Graph WaveNet outperforms the other approaches over short-term and medium-term horizons. This work is one of the first studies to apply these ST-GNNs to share price prediction.},
  year = {2022},
  journal = {Communications in Computer and Information Science},
  volume = {1551},
  pages = {95-110},
  publisher = {Springer},
  address = {Cham},
  isbn = {978-3-030-95070-5},
  url = {https://link.springer.com/chapter/10.1007/978-3-030-95070-5_7},
  doi = {10.1007/978-3-030-95070-5_7},
}

This research proposes an architecture and prototype implementation of a knowledge-based system for automating share evaluation and investment decision making on the Johannesburg Stock Exchange (JSE). The knowledge acquired from an analysis of the investment domain for a value investing approach is represented in an ontology. A Bayesian network, developed using the ontology, is used to capture the complex causal relations between different factors that influence the quality and value of individual shares. The system was found to adequately represent the decision-making process of investment professionals and provided superior returns to selected benchmark JSE indices from 2012 to 2018.

@{442,
  author = {Rachel Drake and Deshen Moodley},
  title = {INVEST: Ontology Driven Bayesian Networks for Investment Decision Making on the JSE},
  abstract = {This research proposes an architecture and prototype implementation of a knowledge-based system for automating share evaluation and investment decision making on the Johannesburg Stock Exchange (JSE). The knowledge acquired from an analysis of the investment domain for a value investing approach is represented in an ontology. A Bayesian network, developed using the ontology, is used to capture the complex causal relations between different factors that influence the quality and value of individual shares. The system was found to adequately represent the decision-making process of investment professionals and provided superior returns to selected benchmark JSE indices from 2012 to 2018.},
  year = {2022},
  journal = {Second Southern African Conference for AI Research (SACAIR 2022)},
  pages = {252-273},
  month = {06/12/2021-10/12/2021},
  address = {Online},
  isbn = {978-0-620-94410-6},
  url = {https://protect-za.mimecast.com/s/OFYSCpgo02fL1l9gtDHUkY},
}

Within complex societies, social communities are distinguishable based on social interactions. The interactions can be between members or communities and can range from simple conversations between family members and friends to complex interactions that represent the flow of money, information, or power. In our modern digital society, social media platforms present unique opportunities to study social networks through social network analysis (SNA). Social media platforms are usually representative of a specific user group, and Twitter, a microblogging platform, is characterised by the fast distribution of news and often provocative opinions, as well as social mobilizing, which makes it popular for political interactions. The nature of Twitter generates a valuable SNA data source for investigating political conversations and communities, and in related research, specific archetypal conversation patterns between communities were identified that allow for unique interpretations of conversations about a topic. This paper reports on a study where social network analysis (SNA) was performed on Twitter data about political events in 2021 in South Africa. The purpose was to determine which distinct conversation patterns could be detected in datasets collected, as well as what could be derived from these patterns given the South African political landscape and perceptions. The results indicate that conversations in the South African political landscape are less polarized than expected. Conversations often manifest broadcast patterns from key influencers in addition to tight crowds or community clusters. Tight crowds or community clusters indicate intense conversation across communities that exhibits diverse opinions and perspectives on a topic. The results may be of value for researchers that aim to understand social media conversations within the South African society.

@article{434,
  author = {Aurona Gerber},
  title = {The Detection of Conversation Patterns in South African Political Tweets through Social Network Analysis},
  abstract = {Within complex societies, social communities are distinguishable based on social interactions. The interactions can be between members or communities and can range from simple conversations between family members and friends to complex interactions that represent the flow of money, information, or power. In our modern digital society, social media platforms present unique opportunities to study social networks through social network analysis (SNA). Social media platforms are usually representative of a specific user group, and Twitter, a microblogging platform, is characterised by the fast distribution of news and often provocative opinions, as well as social mobilizing, which makes it popular for political interactions. The nature of Twitter generates a valuable SNA data source for investigating political conversations and communities, and in related research, specific archetypal conversation patterns between communities were identified that allow for unique interpretations of conversations about a topic. This paper reports on a study where social network analysis (SNA) was performed on Twitter data about political events in 2021 in South Africa. The purpose was to determine which distinct conversation patterns could be detected in datasets collected, as well as what could be derived from these patterns given the South African political landscape and perceptions. The results indicate that conversations in the South African political landscape are less polarized than expected. Conversations often manifest broadcast patterns from key influencers in addition to tight crowds or community clusters. Tight crowds or community clusters indicate intense conversation across communities that exhibits diverse opinions and perspectives on a topic. The results may be of value for researchers that aim to understand social media conversations within the South African society.},
  year = {2022},
  journal = {Communications in Computer and Information Science},
  volume = {1551},
  pages = {15-31},
  publisher = {Springer},
  address = {Cham},
  isbn = {978-3-030-95070-5},
  url = {https://link.springer.com/chapter/10.1007/978-3-030-95070-5_2},
  doi = {10.1007/978-3-030-95070-5_2},
}

Knowledge representation and reasoning (KRR) is an approach to artificial intelligence (AI) in which a system has some information about the world represented formally (a knowledge base), and is able to reason about this information. Defeasible reasoning is a non-classical form of reasoning that enables systems to reason about knowledge bases which contain seemingly contradictory information, thus allowing for exceptions to assertions. Currently, systems which support defeasible entailment for propositional logic are ad hoc, and few and far between, and little to no work has been done on improving the scalability of defeasible reasoning algorithms. We investigate the scalability of defeasible entailment algorithms, and propose optimised versions thereof, as well as present a tool to perform defeasible entailment checks using these algorithms. We also present a knowledge base generation tool which can be used for testing implementations of these algorithms.

@{428,
  author = {Joel Hamilton and Joonsoo Park and Aidan Bailey and Thomas Meyer},
  title = {An Investigation into the Scalability of Defeasible Reasoning Algorithms},
  abstract = {Knowledge representation and reasoning (KRR) is an approach to artificial intelligence (AI) in which a system has some information about the world represented formally (a knowledge base), and is able to reason about this information. Defeasible reasoning is a non-classical form of reasoning that enables systems to reason about knowledge bases which contain seemingly contradictory information, thus allowing for exceptions to assertions. Currently, systems which support defeasible entailment for propositional logic are ad hoc, and few and far between, and little to no work has been done on improving the scalability of defeasible reasoning algorithms. We investigate the scalability of defeasible entailment algorithms, and propose optimised versions thereof, as well as present a tool to perform defeasible entailment checks using these algorithms. We also present a knowledge base generation tool which can be used for testing implementations of these algorithms.},
  year = {2022},
  journal = {Second Southern African Conference for Artificial Intelligence},
  pages = {235-251},
  month = {06/12-10/12},
  publisher = {SACAIR 2021 Organising Committee},
  address = {Online},
  isbn = {978-0-620-94410-6},
  url = {https://2021.sacair.org.za/proceedings/},
}

Belief revision and belief update are approaches to represent and reason with knowledge in artificial intelligence. Previous empirical studies have shown that human reasoning is consistent with non-monotonic logic and postulates of defeasible reasoning, belief revision and belief update. We extended previous work, which tested natural language translations of the postulates of defeasible reasoning, belief revision and belief update with human reasoners via surveys, in three respects. Firstly, we only tested postulates of belief revision and belief update, taking the position that belief change aligns more with human reasoning than non-monotonic defeasible reasoning. Secondly, we decomposed the postulates of revision and update into material implication statements of the form “If x is the case, then y is the case”, each containing a premise and a conclusion, and then translated the premises and conclusions into natural language. Thirdly, we asked human participants to judge each component of the postulate for plausibility. In our analysis, we measured the strength of the association between the premises and the conclusion of each postulate. We used Possibility theory to determine whether the postulates hold with our participants in general. Our results showed that our participants’ reasoning is consistent with postulates of belief revision and belief update when judging the premises and conclusion of the postulate separately.

@{427,
  author = {Clayton Baker and Tommie Meyer},
  title = {Belief Change in Human Reasoning: An Empirical Investigation on MTurk},
  abstract = {Belief revision and belief update are approaches to represent and reason with knowledge in artificial intelligence. Previous empirical studies have shown that human reasoning is consistent with non-monotonic logic and postulates of defeasible reasoning, belief revision and belief update. We extended previous work, which tested natural language translations of the postulates of defeasible reasoning, belief revision and belief update with human reasoners via surveys, in three respects.
Firstly, we only tested postulates of belief revision and belief update, taking the position that belief change aligns more with human reasoning than non-monotonic defeasible reasoning. Secondly, we decomposed the postulates of revision and update into material implication statements of the form “If x is the case, then y is the case”, each containing a premise
and a conclusion, and then translated the premises and conclusions into natural language. Thirdly, we asked human participants to judge each component of the postulate for plausibility. In our analysis, we measured the strength of the association between the premises and the conclusion of each postulate. We used Possibility theory to determine whether the postulates hold with our participants in general. Our results showed that our participants’ reasoning is consistent with postulates of belief
revision and belief update when judging the premises and conclusion of the postulate separately.},
  year = {2022},
  journal = {Second Southern African Conference for AI Research (SACAIR 2022)},
  pages = {218-234},
  month = {06/12/2021-10/12/2021},
  publisher = {SACAIR 2021 Organising Committee},
  address = {Online},
  isbn = {978-0-620-94410-6},
  url = {https://2021.sacair.org.za/proceedings/},
}

Explanation services are a crucial aspect of symbolic reasoning systems but they have not been explored in detail for defeasible formalisms such as KLM. We evaluate prior work on the topic with a focus on KLM propositional logic and find that a form of defeasible explanation initially described for Rational Closure which we term weak justification can be adapted to Relevant and Lexicographic Closure as well as described in terms of intuitive properties derived from the KLM postulates. We also consider how a more general definition of defeasible explanation known as strong explanation applies to KLM and propose an algorithm that enumerates these justifications for Rational Closure.

@inbook{426,
  author = {Lloyd Everett and Emily Morris and Tommie Meyer},
  title = {Explanation for KLM-Style Defeasible Reasoning},
  abstract = {Explanation services are a crucial aspect of symbolic reasoning systems but they have not been explored in detail for defeasible formalisms such as KLM. We evaluate prior work on the topic with a focus on KLM propositional logic and find that a form of defeasible explanation initially described for Rational Closure which we term weak justification can be adapted to Relevant and Lexicographic Closure as well as described in terms of intuitive properties derived from the KLM postulates. We also consider how a more general definition of defeasible explanation known as strong explanation applies to KLM and propose an algorithm that enumerates these justifications for Rational Closure.},
  year = {2022},
  journal = {Artificial Intelligence Research. SACAIR 2021.},
  edition = {1551},
  publisher = {Springer},
  address = {Cham},
  isbn = {978-3-030-95069-9},
  url = {https://link.springer.com/book/10.1007/978-3-030-95070-5},
  doi = {10.1007/978-3-030-95070-5_13},
}

We investigate the use of silhouette coefficients in cluster analysis for speaker diarisation, with the dual purpose of unsupervised fine-tuning during domain adaptation and determining the number of speakers in an audio file. Our main contribution is to demonstrate the use of silhouette coefficients to perform per-file domain adaptation, which we show to deliver an improvement over per-corpus domain adaptation. Secondly, we show that this method of silhouette-based cluster analysis can be used to accurately determine more than one hyperparameter at the same time. Finally, we propose a novel method for calculating the silhouette coefficient of clusters using a PLDA score matrix as input.

@{482,
  author = {Lucas Van Wyk and Marelie Davel and Charl Van Heerden},
  title = {Unsupervised fine-tuning of speaker diarisation pipelines using silhouette coefficients},
  abstract = {We investigate the use of silhouette coefficients in cluster analysis for speaker diarisation, with the dual purpose of unsupervised fine-tuning during domain adaptation and determining the number of speakers in an audio file. Our main contribution is to demonstrate the use of silhouette coefficients to perform per-file domain adaptation, which we show to deliver an improvement over per-corpus domain adaptation. Secondly, we show that this method of silhouette-based cluster analysis can be used to accurately determine more than one hyperparameter at the same time. Finally, we propose a novel method for calculating the silhouette coefficient of clusters using a PLDA score matrix as input.},
  year = {2021},
  journal = {Southern African Conference for Artificial Intelligence Research},
  pages = {202 - 216},
  month = {06/12/2021 - 10/12/2021},
  address = {South Africa},
  isbn = {978-0-620-94410-6},
  url = {https://2021.sacair.org.za/proceedings/},
}

We investigate the effect of a reduced modulation scheme pool on a CNN-based automatic modulation classifier. Similar classifiers in literature are typically used to classify sets of five or more different modulation types [1] [2], whereas our analysis is of a CNN classifier that classifies between two modulation types, 16-QAM and 8-PSK, only. While implementing the network, we observe that the network’s classification accuracy improves for lower SNR instead of reducing as expected. This analysis exposes characteristics of such classifiers that can be used to improve CNN classifiers on larger sets of modulation types. We show that presenting the SNR data as an extra data point to the network can significantly increase classification accuracy.

@{481,
  author = {Andrew Oosthuizen and Marelie Davel and Albert Helberg},
  title = {Exploring CNN-based automatic modulation classification using small modulation sets},
  abstract = {We investigate the effect of a reduced modulation scheme pool on a CNN-based automatic modulation classifier. Similar classifiers in literature are typically used to classify sets of five or more different modulation types [1] [2], whereas our
analysis is of a CNN classifier that classifies between two modulation types, 16-QAM and 8-PSK, only. While implementing the network, we observe that the network’s classification accuracy improves for lower SNR instead of reducing as expected. This analysis exposes characteristics of such classifiers that can be used to improve CNN classifiers on larger sets of modulation types. We show that presenting the SNR data as an extra data point to the network can significantly increase classification accuracy.},
  year = {2021},
  journal = {Southern Africa Telecommunication Networks and Applications Conference},
  pages = {20 - 24},
  month = {21/11/2021 - 23/11/2021},
  address = {South Africa},
  url = {https://www.satnac.org.za/proceedings},
}

The COVID-19 pandemic and the subsequent response by governments to introduce national lockdown regulations have confined individuals to their residential premises. As a result, no recreational or sport activities are allowed outside the (often small) boundaries of family homes, a situation often rapidly introducing social isolation. Research has proven that emotional coping mechanisms, such as sport, can lower the stressful and uncertainty burden on individuals. However, without the availability of this coping mechanism, many individuals have been forced to use virtual sport training technology to keep active. This preliminary quantitative study investigated the role of technology, in particular virtual sport training technology (if any) by cyclists as emotional coping mechanism during a period of national lockdown. The results of an online survey indicated that sport, in general, has always been an emotional coping mechanism during normal challenging situations but that slightly more respondents used sport as mechanism during the lockdown period. Respondents indicated that virtual cycling training technology enabled them to continue with using their normal coping mechanism even in a period of national lockdown. One of the benefits of a virtual training environment is the ability to socialize by riding with virtual team members. Surprisingly, the number of cyclists who preferred riding alone in the virtual cycling environment was slightly more than the cyclists who preferred to join scheduled rides with virtual team members. The research is the first step towards an in-depth investigation into the adoption of technology as an emotional coping mechanism in stressful environments.

@article{439,
  author = {Sunet Eybers and Aurona Gerber},
  title = {A Preliminary Investigation into the Role of Virtual Sport Training Technology as Emotional Coping Mechanism During a National Pandemic Lockdown},
  abstract = {The COVID-19 pandemic and the subsequent response by governments to introduce national lockdown regulations have confined individuals to their residential premises. As a result, no recreational or sport activities are allowed outside the (often small) boundaries of family homes, a situation often rapidly introducing social isolation. Research has proven that emotional coping mechanisms, such as sport, can lower the stressful and uncertainty burden on individuals. However, without the availability of this coping mechanism, many individuals have been forced to use virtual sport training technology to keep active. This preliminary quantitative study investigated the role of technology, in particular virtual sport training technology (if any) by cyclists as emotional coping mechanism during a period of national lockdown. The results of an online survey indicated that sport, in general, has always been an emotional coping mechanism during normal challenging situations but that slightly more respondents used sport as mechanism during the lockdown period. Respondents indicated that virtual cycling training technology enabled them to continue with using their normal coping mechanism even in a period of national lockdown. One of the benefits of a virtual training environment is the ability to socialize by riding with virtual team members. Surprisingly, the number of cyclists who preferred riding alone in the virtual cycling environment was slightly more than the cyclists who preferred to join scheduled rides with virtual team members. The research is the first step towards an in-depth investigation into the adoption of technology as an emotional coping mechanism in stressful environments.},
  year = {2021},
  journal = {Lecture Notes in Networks and Systems},
  volume = {186},
  pages = {186-194},
  publisher = {Springer},
  address = {Cham},
  isbn = {978-3-030-66093-2},
  url = {https://link.springer.com/chapter/10.1007/978-3-030-66093-2_18},
  doi = {10.1007/978-3-030-66093-2_18},
}

Social communities play a significant role in understanding complex societies, from communities formed by support interactions between friends and family to community structures that depict the flow of information, money and power. With the emergence of the internet, the nature of social networks changed because communities could form disassociated from physical location, and social network analysis (SNA) on social media such as Twitter and Facebook emerged as a distinct research field. Studies suggest that Twitter feeds have a significant influence on the views and opinions of society, and subsequently the formation of communities. This paper reports on a study where social network analysis was performed on Twitter feeds in South Africa around the 2019 elections to detect distinct patterns within the overall network. In the datasets that were analysed, a specific network pattern namely Broadcast Networks were observed. A Broadcast Network typically reflects central hubs such as media houses, political parties or influencers whose messages are repeated without interaction or discussion. Our results indicate that there were few discussions and interactions and that messages were broadcasted from central nodes even though the general experience of Twitter users during this time was of intense discussions and differences in opinion.

@article{438,
  author = {Aurona Gerber and Stephanie Strachan},
  title = {Network Patterns in South African Election Tweets},
  abstract = {Social communities play a significant role in understanding complex societies, from communities formed by support interactions between friends and family to community structures that depict the flow of information, money and power. With the emergence of the internet, the nature of social networks changed because communities could form disassociated from physical location, and social network analysis (SNA) on social media such as Twitter and Facebook emerged as a distinct research field. Studies suggest that Twitter feeds have a significant influence on the views and opinions of society, and subsequently the formation of communities. This paper reports on a study where social network analysis was performed on Twitter feeds in South Africa around the 2019 elections to detect distinct patterns within the overall network. In the datasets that were analysed, a specific network pattern namely Broadcast Networks were observed. A Broadcast Network typically reflects central hubs such as media houses, political parties or influencers whose messages are repeated without interaction or discussion. Our results indicate that there were few discussions and interactions and that messages were broadcasted from central nodes even though the general experience of Twitter users during this time was of intense discussions and differences in opinion.},
  year = {2021},
  journal = {Lecture Notes in Networks and Systems},
  volume = {186},
  pages = {3-13},
  publisher = {Springer},
  address = {Cham},
  isbn = {978-3-030-66093-2},
  url = {https://link.springer.com/chapter/10.1007/978-3-030-66093-2_1},
  doi = {10.1007/978-3-030-66093-2_1},
}

Many organisations turn to enterprise architecture (EA) to assist with the alignment of business and information technology. While some of these organisations succeed in the development and implementation of EA, many of them fail to manage EA after implementation. Because of the specific focus on the management of EA during and after the initial implementation, the enterprise architecture management (EAM) field is developed. EAM is characterised by many dimensions or elements. It is a challenge to select the dimensions that should be managed and that are vital for successful EA practice. In this study, we executed a systematic literature review (SLR) of primary EA and EAM literature with the aim of identifying dimensions regarded as key areas of EAM. The main contribution of this work is a concept map of the essential EAM dimensions with their relationships. The results of the SLR indicate that dimensions that used to be considered important or seemed to be the most essential for EA, such as frameworks, EA principles and reference models, are no longer emphasised as strongly and more focus is placed on people, skills, communication and governance when considering EAM literature and EAM maturity.

@article{437,
  author = {Trishan Marimuthu and Alta van der Merwe and Aurona Gerber},
  title = {A systematic literature review of essential enterprise architecture management dimensions},
  abstract = {Many organisations turn to enterprise architecture (EA) to assist with the alignment of business and information technology. While some of these organisations succeed in the development and implementation of EA, many of them fail to manage EA after implementation. Because of the specific focus on the management of EA during and after the initial implementation, the enterprise architecture management (EAM) field is developed. EAM is characterised by many dimensions or elements. It is a challenge to select the dimensions that should be managed and that are vital for successful EA practice. In this study, we executed a systematic literature review (SLR) of primary EA and EAM literature with the aim of identifying dimensions regarded as key areas of EAM. The main contribution of this work is a concept map of the essential EAM dimensions with their relationships. The results of the SLR indicate that dimensions that used to be considered important or seemed to be the most essential for EA, such as frameworks, EA principles and reference models, are no longer emphasised as strongly and more focus is placed on people, skills, communication and governance when considering EAM literature and EAM maturity.},
  year = {2021},
  journal = {Lecture Notes in Networks and Systems},
  volume = {235},
  pages = {381-391},
  publisher = {Springer},
  address = {Singapore},
  isbn = {978-981-16-2377-6},
  url = {https://link.springer.com/chapter/10.1007/978-981-16-2377-6_36},
  doi = {10.1007/978-981-16-2377-6_36},
}

The global Covid-19 pandemic caused havoc in higher education teaching routines and several residential institutions encouraged instructors to convert existing modules to flipped classrooms as part of an online, blended learning strategy. Even though this seems a reasonable request, instructors straightaway encountered challenges which include a vague concept of what an online flipped classroom entails within a higher education context, a lack of guidelines for converting an existing module, facilitating learner engagement as well as unique challenges for inclusion of all learners in a digitally divided developing country in Covid-19 lockdown. In order to respond, we embarked on a study to identify the distinguishing characteristics of flipped classrooms to understand the as-is and to-be scenarios using a systematic literature review. The characteristics were used to develop of design considerations to convert to an online flipped classroom for higher education taking our diverse learner profiles into account. We subsequently converted a short module in an information systems department and shortly report on our experience.

@article{436,
  author = {Aurona Gerber and Sunet Eybers},
  title = {Converting to Inclusive Online Flipped Classrooms in Response to Covid-19 Lockdown},
  abstract = {The global Covid-19 pandemic caused havoc in higher education teaching routines and several residential institutions encouraged instructors to convert existing modules to flipped classrooms as part of an online, blended learning strategy. Even though this seems a reasonable request, instructors straightaway encountered challenges which include a vague concept of what an online flipped classroom entails within a higher education context, a lack of guidelines for converting an existing module, facilitating learner engagement as well as unique challenges for inclusion of all learners in a digitally divided developing country in Covid-19 lockdown. In order to respond, we embarked on a study to identify the distinguishing characteristics of flipped classrooms to understand the as-is and to-be scenarios using a systematic literature review. The characteristics were used to develop of design considerations to convert to an online flipped classroom for higher education taking our diverse learner profiles into account. We subsequently converted a short module in an information systems department and shortly report on our experience.},
  year = {2021},
  journal = {South African Journal of Higher Education},
  volume = {35},
  pages = {34-57},
  issue = {4},
  isbn = {1753-5913},
  url = {https://journals.co.za/doi/10.20853/35-4-4285},
  doi = {10.20853/35-4-4285},
}

Blockchain is the underlying technology behind Bitcoin, the first digital currency, and due to the rapid growth of Bitcoin, there is significant interest in blockchain as the enabler of digital currencies due to the consensus distributed ledger model. The rise and the success of alternative cryptocurrencies such as Ethereum and Ripple has supported the development of blockchain technology, but the performance of blockchain applications has been documented as a significant obstacle for adoption. At the core of blockchain is a consensus protocol, which plays a key role in maintaining the safety, performance and efficiency of the blockchain network. Several consensus protocols exist, and the use of the right consensus protocol is crucial to ensure adequate performance of any blockchain application. However, there is a lack of documented overview studies even though there is agreement in the literature about the importance and understanding of blockchain consensus protocols. In this study, we adopt a systematic literature review (SLR) to investigate the current status of consensus protocols used for blockchain together with the identified limitations of these protocols. The results of this study include an overview of different consensus protocols as well as consensus protocol limitations and will be of value for any practitioner or scholar that is interested in blockchain applications.

@article{435,
  author = {Sikho Luzipo and Aurona Gerber},
  title = {A Systematic Literature Review of Blockchain Consensus Protocols},
  abstract = {Blockchain is the underlying technology behind Bitcoin, the first digital currency, and due to the rapid growth of Bitcoin, there is significant interest in blockchain as the enabler of digital currencies due to the consensus distributed ledger model. The rise and the success of alternative cryptocurrencies such as Ethereum and Ripple has supported the development of blockchain technology, but the performance of blockchain applications has been documented as a significant obstacle for adoption. At the core of blockchain is a consensus protocol, which plays a key role in maintaining the safety, performance and efficiency of the blockchain network. Several consensus protocols exist, and the use of the right consensus protocol is crucial to ensure adequate performance of any blockchain application. However, there is a lack of documented overview studies even though there is agreement in the literature about the importance and understanding of blockchain consensus protocols. In this study, we adopt a systematic literature review (SLR) to investigate the current status of consensus protocols used for blockchain together with the identified limitations of these protocols. The results of this study include an overview of different consensus protocols as well as consensus protocol limitations and will be of value for any practitioner or scholar that is interested in blockchain applications.},
  year = {2021},
  journal = {Lecture Notes in Computer Science},
  volume = {12896},
  pages = {580-595},
  publisher = {Springer},
  address = {Cham},
  isbn = {978-3-030-85447-8},
  url = {https://link.springer.com/chapter/10.1007/978-3-030-85447-8_48},
  doi = {10.1007/978-3-030-85447-8_48},
}

We extend the expressivity of classical conditional reasoning by introducing context as a new parameter. The enriched conditional logic generalises the defeasible conditional setting in the style of Kraus, Lehmann, and Magidor, and allows for a refined semantics that is able to distinguish, for example, between expectations and counterfactuals. In this paper we introduce the language for the enriched logic and define an appropriate semantic framework for it. We analyse which properties generally associated with conditional reasoning are still satisfied by the new semantic framework, provide a suitable representation result, and define an entailment relation based on Lehmann and Magidor’s generally-accepted notion of Rational Closure.

@{430,
  author = {Giovanni Casini and Tommie Meyer and Ivan Varzinczak},
  title = {Contextual Conditional Reasoning},
  abstract = {We extend the expressivity of classical conditional reasoning by introducing context as a new parameter. The enriched
conditional logic generalises the defeasible conditional setting in the style of Kraus, Lehmann, and Magidor, and allows for a refined semantics that is able to distinguish, for example, between expectations and counterfactuals. In this paper we introduce the language for the enriched logic and define an appropriate semantic framework for it. We analyse which properties generally associated with conditional reasoning are still satisfied by the new semantic framework, provide a suitable representation result, and define an entailment relation based on Lehmann and Magidor’s generally-accepted notion of Rational Closure.},
  year = {2021},
  journal = {35th AAAI Conference on Artificial Intelligence},
  pages = {6254-6261},
  month = {02/02/2021-09/02/2021},
  publisher = {AAAI Press},
  address = {Online},
}

We extend the KLM approach to defeasible reasoning to be applicable to a restricted version of first-order logic. We describe defeasibility for this logic using a set of rationality postulates, provide an appropriate semantics for it, and present a representation result that characterises the semantic description of defeasibility in terms of the rationality postulates. Based on this theoretical core, we then propose a version of defeasible entailment that is inspired by Rational Closure as it is defined for defeasible propositional logic and defeasible description logics. We show that this form of defeasible entailment is rational in the sense that it adheres to our rationality postulates. The work in this paper is the first step towards our ultimate goal of introducing KLM-style defeasible reasoning into the family of Datalog+/- ontology languages.

@{429,
  author = {Giovanni Casini and Tommie Meyer and Guy Paterson-Jones},
  title = {KLM-Style Defeasibility for Restricted First-Order Logic},
  abstract = {We extend the KLM approach to defeasible reasoning to be applicable to a restricted version of first-order logic. We describe defeasibility for this logic using a set of rationality postulates, provide an appropriate semantics for it, and present a representation result that characterises the semantic description of defeasibility in terms of the rationality postulates. Based on this theoretical core, we then propose a version of defeasible entailment that is inspired by Rational Closure as it is defined for defeasible propositional logic and defeasible description logics. We show that this form of defeasible entailment is rational in the sense that it adheres to our rationality postulates. The work in this paper is the first step towards our ultimate goal of introducing KLM-style defeasible reasoning into the family of Datalog+/- ontology languages.},
  year = {2021},
  journal = {19th International Workshop on Non-Monotonic Reasoning},
  pages = {184-193},
  month = {03/11/2021-05/11/2021},
  address = {Online},
  url = {https://drive.google.com/open?id=1WSIl3TOrXBhaWhckWN4NLXoD9AVFKp5R},
}

The abductive theory of method (ATOM) was recently proposed to describe the process that scientists use for knowledge discovery. In this paper we propose an agent architecture for knowledge discovery and evolution (KDE) based on ATOM. The agent incorporates a combination of ontologies, rules and Bayesian networks for representing different aspects of its internal knowledge. The agent uses an external AI service to detect unexpected situations from incoming observations. It then uses rules to analyse the current situation and a Bayesian network for finding plausible explanations for unexpected situations. The architecture is evaluated and analysed on a use case application for monitoring daily household electricity consumption patterns.

@inbook{425,
  author = {Tezira Wanyana and Deshen Moodley},
  title = {An Agent Architecture for Knowledge Discovery and Evolution},
  abstract = {The abductive theory of method (ATOM) was recently proposed to describe the process that scientists use for knowledge discovery. In this paper we propose an agent architecture for knowledge discovery and evolution (KDE) based on ATOM. The agent incorporates a combination of ontologies, rules and Bayesian networks for representing different aspects of its internal knowledge. The agent uses an external AI service to detect unexpected situations from incoming observations. It then uses rules to analyse the current situation and a Bayesian network for finding plausible explanations for unexpected situations. The architecture is evaluated and analysed on a use case application for monitoring daily household electricity consumption patterns.},
  year = {2021},
  journal = {KI 2021: Advances in Artificial Intelligence},
  edition = {volume 12873},
  pages = {241-256},
  publisher = {Springer International Publishing},
  address = {Cham},
  isbn = {978-3-030-87626-5},
  doi = {https://doi.org/10.1007/978-3-030-87626-5_18},
}

Universities supply free Wi-Fi to registered students on campus to access learning materials. Many issues could reduce the quality of students' Wi-Fi use, e.g., devices using different Wi-Fi standards than those used on campus, and numerous students accessing Wi-Fi through a single access point simultaneously. Understanding where, when and how students use Wi-Fi on campus can help IT administrators to provide an adequate Wi-Fi service. This pre-COVID study adopted a mixed method approach. Questionnaires were completed by a representative sample of 373 students on the Westville campus of the University of KwaZulu-Natal, South Africa. Two Information Communication Services (lCS) staff members were interviewed to gain insights into how the Wi-Fi was set up, and their perspectives on how students utilise the Wi-Fi. The questionnaire data were analysed statistically, and interview results were used to explain results. The students' most used venues, and the places they encountered poor and best Wi-Fi signal quality, are presented, along with the durations of use and problems encountered. When analysing these results by students' residence type, each category showed a different pattern of use. These results can help IT administrators understand where to improve the Wi-Fi quality, if necessary. It is particularly useful if some categories of students return to campus, while others do not, e.g. as COVID-19 lockdowns ease.

@{424,
  author = {V. Mbonye and C. Sue Price},
  title = {Students’ use of on-campus wireless networks: Analysis by residence type},
  abstract = {Universities supply free Wi-Fi to registered students on campus to access learning materials. Many issues could reduce the quality of students' Wi-Fi use, e.g., devices using different Wi-Fi standards than those used on campus, and numerous students accessing Wi-Fi through a single access point simultaneously. Understanding where, when and how students use Wi-Fi on campus can help IT administrators to provide an adequate Wi-Fi service. This pre-COVID study adopted a mixed method approach. Questionnaires were completed by a representative sample of 373 students on the Westville campus of the University of KwaZulu-Natal, South Africa. Two Information Communication Services (lCS) staff members were interviewed to gain insights into how the Wi-Fi was set up, and their perspectives on how students utilise the Wi-Fi. The questionnaire data were analysed statistically, and interview results were used to explain results. The students' most used venues, and the places they encountered poor and best Wi-Fi signal quality, are presented, along with the durations of use and problems encountered. When analysing these results by students' residence type, each category showed a different pattern of use. These results can help IT administrators understand where to improve the Wi-Fi quality, if necessary. It is particularly useful if some categories of students return to campus, while others do not, e.g. as COVID-19 lockdowns ease.},
  year = {2021},
  journal = {2021 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD)},
  month = {5-6/08},
  publisher = {IEEE},
  address = {Durban, South Africa},
  isbn = {978-1-7281-8591-0},
  url = {https://ieeexplore.ieee.org/document/9519327},
  doi = {https://doi.org/10.1109/icABCD51485.2021.9519327},
}

Abstract dialectical frameworks (in short, ADFs) are one of the most general and unifying approaches to formal argumentation. As the semantics of ADFs are based on three-valued interpretations, the question poses itself as to whether some and which monotonic three-valued logic underlies ADFs, in the sense that it allows to capture the main semantic concepts underlying ADFs. As an entry-point for such an investigation, we take the concept of model of an ADF, which was originally formulated on the basis of Kleene’s three-valued logic. We show that an optimal concept of a model arises when instead of Kleene’s three-valued logic, possibilistic logic is used. We then show that in fact, possibilistic logic is the most conservative three-valued logic that fulfils this property, and that possibilistic logic can faithfully encode all other semantical concepts for ADFs. Based on this result, we also make some observations on strong equivalence and introduce possibilistic ADFs.

@misc{422,
  author = {Jesse Heyninck and Matthias Thimm and Gabriele Kern-Isberner and Tjitze Rienstra and Kenneth Skiba},
  title = {On the Relation between Possibilistic Logic and Abstract Dialectical Frameworks},
  abstract = {Abstract dialectical frameworks (in short, ADFs) are one of the most general and unifying approaches to formal argumentation. As the semantics of ADFs are based on three-valued interpretations, the question poses itself as to whether some and which monotonic three-valued logic underlies ADFs, in the sense that it allows to capture the main semantic concepts underlying ADFs. As an entry-point for such an investigation, we take the concept of model of an ADF, which was originally formulated on the basis of Kleene’s three-valued logic. We show that an optimal concept of a model arises when instead of Kleene’s three-valued logic, possibilistic logic is used. We then show that in fact, possibilistic logic is the most conservative three-valued logic that fulfils this property, and that possibilistic logic can faithfully encode all other semantical concepts for ADFs. Based on this result, we also make some observations on strong equivalence and introduce possibilistic ADFs.},
  year = {2021},
  url = {https://sites.google.com/view/nmr2021/home?authuser=0)},
}

Abstract dialectical frameworks (in short, ADFs) are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. This idea is generalized by letting acceptance conditions being assigned to complex formulas, resulting in conditional abstract dialectical frameworks (in short, cADFs). We define the semantics of cADFs in terms of a non-truth-functional four-valued logic, and study the semantics in-depth, by showing existence results and proving that all semantics are generalizations of the corresponding semantics for ADFs.

@misc{421,
  author = {Jesse Heyninck and Matthias Thimm and Gabriele Kern-Isberner and Tjitze Rienstra and Kenneth Skiba},
  title = {Arguing about Complex Formulas: Generalizing Abstract Dialectical Frameworks},
  abstract = {Abstract dialectical frameworks (in short, ADFs) are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. This idea is generalized by letting acceptance conditions being assigned to complex formulas, resulting in conditional abstract dialectical frameworks (in short, cADFs). We define the semantics of cADFs in terms of a non-truth-functional four-valued
logic, and study the semantics in-depth, by showing existence results and proving that all semantics are generalizations of the corresponding semantics for ADFs.},
  year = {2021},
  url = {https://sites.google.com/view/nmr2021/home?authuser=0},
}

Approximation fixpoint theory (AFT) constitutes an abstract and general algebraic framework for studying the semantics of nonmonotonic logics. It provides a unifying study of the semantics of different formalisms for nonmonotonic reasoning, such as logic programming, default logic and autoepistemic logic. In this paper we extend AFT to non-deterministic constructs such as disjunctive information. This is done by generalizing the main constructions and corresponding results to non-deterministic operators, whose ranges are sets of elements rather than single elements. The applicability and usefulness of this generalization is illustrated in the context of disjunctive logic programming.

@{420,
  author = {Jesse Heyninck and Ofer Arieli},
  title = {Approximation Fixpoint Theory for Non-Deterministic Operators and Its Application in Disjunctive Logic Programming},
  abstract = {Approximation fixpoint theory (AFT) constitutes an abstract and general algebraic framework for studying the semantics of nonmonotonic logics. It provides a unifying study of the semantics of different formalisms for nonmonotonic reasoning, such as logic programming, default logic and autoepistemic logic. In this paper we extend AFT to non-deterministic constructs such as disjunctive information. This is done by generalizing the main constructions and corresponding results to non-deterministic operators, whose ranges are sets of elements rather than single elements. The applicability and usefulness of this generalization is illustrated in the context of disjunctive logic programming.},
  year = {2021},
  journal = {18th International Conference on Principles of Knowledge Representation and Reasoning},
  pages = {334-344},
  month = {03/11-12/11},
  publisher = {IJCAI Organization},
  address = {Online},
  isbn = {978-1-956792-99-7},
  url = {https://proceedings.kr.org/2021/32/},
  doi = {10.24963/kr.2021/32},
}

For propositional beliefs, there are well-established connections between belief revision, defeasible conditionals and nonmonotonic inference. In argumentative contexts, such connections have not yet been investigated. On the one hand, the exact relationship between formal argumentation and nonmonotonic inference relations is a research topic that keeps on eluding researchers despite recently intensified efforts, whereas argumentative revision has been studied in numerous works during recent years. In this paper, we show that similar relationships between belief revision, defeasible conditionals and nonmonotonic inference hold in argumentative contexts as well. We first define revision operators for abstract dialectical frameworks, and use such revision operators to define dynamic conditionals by means of the Ramsey test. We show that such conditionals can be equivalently defined using a total preorder over three-valued interpretations, and study the inferential behaviour of the resulting conditional inference relations.

@{418,
  author = {Jesse Heyninck and Gabriele Kern-Isberner and Tjitze Rienstra and Kenneth Skiba and Matthias Thimm},
  title = {Revision and Conditional Inference for Abstract Dialectical Frameworks},
  abstract = {For propositional beliefs, there are well-established connections between belief revision, defeasible conditionals and
nonmonotonic inference. In argumentative contexts, such connections have not yet been investigated. On the one hand, the exact relationship between formal argumentation and nonmonotonic inference relations is a research topic that keeps on eluding researchers despite recently intensified efforts, whereas argumentative revision has been studied in numerous works during recent years. In this paper, we show that similar relationships between belief revision, defeasible conditionals and nonmonotonic inference hold in argumentative contexts as well. We first define revision operators for abstract dialectical frameworks, and use such revision operators to define dynamic conditionals by means of the Ramsey test. We show that such conditionals can be equivalently defined using a total preorder over three-valued interpretations, and study the inferential behaviour of the resulting conditional inference relations.},
  year = {2021},
  journal = {18th International Conference on Principles of Knowledge Representation and Reasoning},
  pages = {345-355},
  month = {03/11-12/11},
  publisher = {IJCAI Organization},
  address = {Online},
  isbn = {978-1-956792-99-7},
  url = {https://proceedings.kr.org/2021/33/},
  doi = {10.24963/kr.2021/33},
}

Up to 70% of all watch time on YouTube is due to the suggested content of its recommender system. This system has been found, by virtue of its design, to be promoting conspiratorial content. In this paper, the author firstly critiques the value neutrality thesis regarding technology, showing it to be philosophically untenable. This means that technological artefacts can influence what people come to value (or perhaps even embody values themselves) and change the moral evaluation of an action. Secondly, he introduces the concept of an affordance, borrowed from the literature on ecological psychology. This concept allows him to make salient how technologies come to solicit certain kinds of actions from users, making such actions more or less likely, and in this way influencing the kinds of things one comes to value. Thirdly, he critically assesses the results of a study by Alfano et al. He makes use of the literature on affordances, introduced earlier, to shed light on how these technological systems come to mediate our perception of the world and influence action.

@article{415,
  author = {Fabio Tollon},
  title = {Designed to Seduce: Epistemically Retrograde Ideation and YouTube's Recommender System},
  abstract = {Up to 70% of all watch time on YouTube is due to the suggested content of its recommender system. This system has been found, by virtue of its design, to be promoting conspiratorial content. In this paper, the author firstly critiques the value neutrality thesis regarding technology, showing it to be philosophically untenable. This means that technological artefacts can influence what people come to value (or perhaps even embody values themselves) and change the moral evaluation of an action. Secondly, he introduces the concept of an affordance, borrowed from the literature on ecological psychology. This concept allows him to make salient how technologies come to solicit certain kinds of actions from users, making such actions more or less likely, and in this way influencing the kinds of things one comes to value. Thirdly, he critically assesses the results of a study by Alfano et al. He makes use of the literature on affordances, introduced earlier, to shed light on how these technological systems come to mediate our perception of the world and influence action.},
  year = {2021},
  journal = {International Journal of Technoethics (IJT)},
  volume = {12},
  issue = {2},
  publisher = {IGI Global},
  isbn = {9781799861492},
  url = {https://www.igi-global.com/gateway/article/281077},
  doi = {10.4018/IJT.2021070105},
}

In this paper I critically evaluate the value neutrality thesis regarding technology, and find it wanting. I then introduce the various ways in which artifacts can come to influence moral value, and our evaluation of moral situations and actions. Here, following van de Poel and Kroes, I introduce the idea of value sensitive design. Specifically, I show how by virtue of their designed properties, artifacts may come to embody values. Such accounts, however, have several shortcomings. In agreement with Michael Klenk, I raise epistemic and metaphysical issues with respect to designed properties embodying value. The concept of an affordance, borrowed from ecological psychology, provides a more philosophically fruitful grounding to the potential way(s) in which artifacts might embody values. This is due to the way in which it incorporates key insights from perception more generally, and how we go about determining possibilities for action in our environment specifically. The affordance account as it is presented by Klenk, however, is insufficient. I therefore argue that we understand affordances based on whether they are meaningful, and, secondly, that we grade them based on their force.

@article{386,
  author = {Fabio Tollon},
  title = {Artifacts and affordances: from designed properties to possibilities for action},
  abstract = {In this paper I critically evaluate the value neutrality thesis regarding technology, and find it wanting. I then introduce the various ways in which artifacts can come to influence moral value, and our evaluation of moral situations and actions. Here, following van de Poel and Kroes, I introduce the idea of value sensitive design. Specifically, I show how by virtue of their designed properties, artifacts may come to embody values. Such accounts, however, have several shortcomings. In agreement with Michael Klenk, I raise epistemic and metaphysical issues with respect to designed properties embodying value. The concept of an affordance, borrowed from ecological psychology, provides a more philosophically fruitful grounding to the potential way(s) in which artifacts might embody values. This is due to the way in which it incorporates key insights from perception more generally, and how we go about determining possibilities for action in our environment specifically. The affordance account as it is presented by Klenk, however, is insufficient. I therefore argue that we understand affordances based on whether they are meaningful, and, secondly, that we grade them based on their force.},
  year = {2021},
  journal = {AI & SOCIETY Journal of Knowledge, Culture and Communication},
  volume = {36},
  issue = {1},
  publisher = {Springer},
  url = {https://link.springer.com/article/10.1007%2Fs00146-021-01155-7},
  doi = {https://doi.org/10.1007/s00146-021-01155-7},
}

Design science research (DSR) is a popular research approach used in information systems for the design, development and evaluation of artefacts. There is some guidance in the literature on how to conduct DSR as an approach to find solutions for wicked problems. Some of the areas with which students who are involved in DSR struggle are the confirmation of the problem and design and evaluation of the artefact. Hevner et al. [1] presented their conceptual model for DSR in 2004 and in this paper we use this seminal work as guidance to illustrate where there is potential for inclusion of data collection activities to address these three areas of concern. We also indicate the nature of the data collection that can be used during these phases. Lastly, we use some cases studies to map the areas that we have identified to these case studies as illustration.

@{452,
  author = {Alta van der Merwe and Hanlie Smuts and Aurona Gerber},
  title = {Data Collection in an Information Systems Design Science Research Project},
  abstract = {Design science research (DSR) is a popular research approach used in information systems for the design, development and evaluation of artefacts. There is some guidance in the literature on how to conduct DSR as an approach to find solutions for wicked problems. Some of the areas with which students who are involved in DSR struggle are the confirmation of the problem and design and evaluation of the artefact. Hevner et al. [1] presented their conceptual model for DSR in 2004 and in this paper we use this seminal work as guidance to illustrate where there is potential for inclusion of data collection activities to
address these three areas of concern. We also indicate the nature of the data collection that can be used during these phases. Lastly, we use some cases studies to map the areas that we have identified to these case studies as illustration.},
  year = {2020},
  journal = {49th Annual Conference of the Southern African Computer Lecturers' Association (SACLA)},
  pages = {36-48},
  month = {06/07-09/07},
  publisher = {SACLA 2020 Organising Committee, Rhodes University, South Africa},
  address = {Online},
  isbn = {978-1-990964-40-4},
  url = {https://sacla2020.ru.ac.za/docs/SACLA2020Proceedings.pdf},
}