An investigation of how a visual teaching approach can possibly address issues of mathematics anxiety at a selected school in the Oshikoto region of Namibia

This Namibian case study aimed to explore a visual teaching approach (VTA) used by three selected teachers to address issues of mathematics anxiety (MA). The three teachers took part in an intervention program that was looking at how a VTA could be grown in the context of an after-school club (ASC) at my school. The selected teachers were the senior primary teachers at my school. The focus of the research was on how they taught mathematics using visuals after participating in an intervention programme. Their VTA made use of manipulatives, visuals, and concrete materials. The learners of the participating teachers completed a big MA pre-test, small MA tests, and a big MA post-test to determine their levels of MA as the teaching programme unfolded. The study hoped to create awareness amongst teachers and education researchers about the significant use of a VTA in the teaching and learning of mathematics to address issues of MA among the learners. It aimed to answer three research questions. One was on teachers’ use of a VTA in the context of an ASC; the second one was on comparisons of learners’ MA big pre and post-tests to detect any change of MA, and the last was on the enabling and constraining factors encountered when using a VTA. The main argument was that a VTA can encourage learners to be more confident and less anxious about doing mathematics. This study was framed by a constructivist perspective and its design and methodology were underpinned by an interpretive paradigm. This mixed-method research study employed video-recorded observations and stimulated recall interviews, learners’ MA test results, and the teachers’ focus group interviews as the means of collecting data. To generate rich data and support validity, four lessons per selected teacher were observed and video recorded; 54 learners completed the MA tests of 16 questions, and three teachers answered seven questions each in the focus group interview (FGI) after the stimulus recall interviews (SRI) which were done immediately after the lesson presentations. The study found that the participating teachers incorporated a variety of visuals into their lessons to make the mathematics fun, inspiring, visible, hands-on, and activity-oriented. They engaged the learners and also found that the use of visuals motivated learners and reduced their MA.Thesis (MED) -- Faculty of Education, Education, 202

An investigation of how a visual teaching approach can possibly address issues of mathematics anxiety at a selected school in the Oshikoto region of Namibia

This Namibian case study aimed to explore a visual teaching approach (VTA) used by three selected teachers to address issues of mathematics anxiety (MA). The three teachers took part in an intervention program that was looking at how a VTA could be grown in the context of an after-school club (ASC) at my school. The selected teachers were the senior primary teachers at my school. The focus of the research was on how they taught mathematics using visuals after participating in an intervention programme. Their VTA made use of manipulatives, visuals, and concrete materials. The learners of the participating teachers completed a big MA pre-test, small MA tests, and a big MA post-test to determine their levels of MA as the teaching programme unfolded. The study hoped to create awareness amongst teachers and education researchers about the significant use of a VTA in the teaching and learning of mathematics to address issues of MA among the learners. It aimed to answer three research questions. One was on teachers’ use of a VTA in the context of an ASC; the second one was on comparisons of learners’ MA big pre and post-tests to detect any change of MA, and the last was on the enabling and constraining factors encountered when using a VTA. The main argument was that a VTA can encourage learners to be more confident and less anxious about doing mathematics. This study was framed by a constructivist perspective and its design and methodology were underpinned by an interpretive paradigm. This mixed-method research study employed video-recorded observations and stimulated recall interviews, learners’ MA test results, and the teachers’ focus group interviews as the means of collecting data. To generate rich data and support validity, four lessons per selected teacher were observed and video recorded; 54 learners completed the MA tests of 16 questions, and three teachers answered seven questions each in the focus group interview (FGI) after the stimulus recall interviews (SRI) which were done immediately after the lesson presentations. The study found that the participating teachers incorporated a variety of visuals into their lessons to make the mathematics fun, inspiring, visible, hands-on, and activity-oriented. They engaged the learners and also found that the use of visuals motivated learners and reduced their MA.Thesis (MED) -- Faculty of Education, Education, 202

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Template-based Question Answering over RDF Data

Unger C, Bühmann L, Lehmann J, Ngomo A-CN, Gerber D, Cimiano P. Template-based Question Answering over RDF Data. In: Association for Computing Machinery, ed. Proceedings of the 21 World Wide Web Conference 2012. ACM Digital Library. New York, NY: ACM Press; 2012: 639-648

Sorry, I don't speak SPARQL – Translating SPARQL Queries into Natural Language

Ngonga Ngomo A-C, Bühmann L, Unger C, Lehmann J, Gerber D. Sorry, I don't speak SPARQL – Translating SPARQL Queries into Natural Language. Presented at the WWW'13: 22nd International World Wide Web Conference.Over the past years, Semantic Web and Linked Data technologies have reached the backend of a considerable number of applications. Consequently, large amounts of RDF data are constantly being made available across the planet. While experts can easily gather information from this wealth of data by using the W3C standard query language SPARQL, most lay users lack the expertise necessary to proficiently interact with these applications. Consequently, non-expert users usually have to rely on forms, query builders, question answering or keyword search tools to access RDF data. However, these tools have so far been unable to explicate the queries they generate to lay users, making it difficult for these users to i) assess the correctness of the query generated out of their input, and ii) to adapt their queries or iii) to choose in an informed manner between possible interpretations of their input. This paper addresses this drawback by presenting SPARQL2NL, a generic approach that allows verbalizing SPARQL queries, i.e., converting them into natural language. Our framework can be integrated into applications where lay users are required to understand SPARQL or to generate SPARQL queries in a direct (forms, query builders) or an indirect (keyword search, question answering) manner. We evaluate our approach on the DBpedia question set provided by QALD-2 within a survey setting with both SPARQL experts and lay users. The results of the 115 filled surveys show that SPARQL2NL can generate complete and easily understandable natural language descriptions. In addition, our results suggest that even SPARQL experts can process the natural language representation of SPARQL queries computed by our approach more efficiently than the corresponding SPARQL queries. Moreover, non-experts are enabled to reliably understand the content of SPARQL queries

Defacto - deep fact validation

Abstract. One of the main tasks when creating and maintaining knowledge bases is to validate facts and provide sources for them in order to ensure correctness and traceability of the provided knowledge. So far, this task is often addressed by human curators in a three-step process: issuing appropriate keyword queries for the statement to check using standard search engines, retrieving potentially relevant documents and screening those documents for relevant content. The drawbacks of this process are manifold. Most importantly, it is very time-consuming as the experts have to carry out several search processes and must often read several documents. In this article, we present DeFacto (Deep Fact Validation) -an algorithm for validating facts by finding trustworthy sources for it on the Web. DeFacto aims to provide an effective way of validating facts by supplying the user with relevant excerpts of webpages as well as useful additional information including a score for the confidence DeFacto has in the correctness of the input fact

Keyword-Driven SPARQL Query Generation Leveraging Background Knowledge

The search for information on the Web of Data is becoming increasingly difficult due to its dramatic growth. Especially novice users need to acquire both knowledge about the underlying ontology structure and proficiency in formulating formal queries (e. g. SPARQL queries) to retrieve information from Linked Data sources. So as to simplify and automate the querying and retrieval of information from such sources, we present in this paper a novel approach for constructing SPARQL queries based on user-supplied keywords. Our approach utilizes a set of predefined basic graph pattern templates for generating adequate interpretations of user queries. This is achieved by obtaining ranked lists of candidate resource identifiers for the supplied keywords and then injecting these identifiers into suitable positions in the graph pattern templates. The main advantages of our approach are that it is completely agnostic of the underlying knowledge base and ontology schema, that it scales to large knowledge bases and is simple to use. We evaluate 17 possible valid graph pattern templates by measuring their precision and recall on 53 queries against DBpedia. Our results show that 8 of these basic graph pattern templates return results with a precision above 70%. Our approach is implemented as a Web search interface and performs sufficiently fast to return instant answers to the user even with large knowledge bases