Tristan Kneisel, Marko Schmellenkamp, Fabian Vehlken
et al.
This paper explores how natural-language descriptions of formal languages can be compared to their formal representations and how semantic differences can be explained. This is motivated from educational scenarios where learners describe a formal language (presented, e.g., by a finite state automaton, regular expression, pushdown automaton, context-free grammar or in set notation) in natural language, and an educational support system has to (1) judge whether the natural-language description accurately describes the formal language, and to (2) provide explanations why descriptions are not accurate. To address this question, we introduce a representation language for formal languages, Nile, which is designed so that Nile expressions can mirror the syntactic structure of natural-language descriptions of formal languages. Nile is sufficiently expressive to cover a broad variety of formal languages, including all regular languages and fragments of context-free languages typically used in educational contexts. Generating Nile expressions that are syntactically close to natural-language descriptions then allows to provide explanations for inaccuracies in the descriptions algorithmically. In experiments on an educational data set, we show that LLMs can translate natural-language descriptions into equivalent, syntactically close Nile expressions with high accuracy - allowing to algorithmically provide explanations for incorrect natural-language descriptions. Our experiments also show that while natural-language descriptions can also be translated into regular expressions (but not context-free grammars), the expressions are often not syntactically close and thus not suitable for providing explanations.
Benjamin Quarshie, Vanessa Willemse, Macharious Nabang
et al.
Generative artificial intelligence (GenAI) tools are increasingly adopted in education, yet many educators lack structured guidance on responsible and context sensitive prompt engineering, particularly in African and other resource constrained settings. This case report documents a three day online professional development programme organised by Generative AI for Education and Research in Africa (GenAI-ERA), designed to strengthen educators and researchers capacity to apply prompt engineering ethically for academic writing, teaching, and research. The programme engaged 468 participants across multiple African countries, including university educators, postgraduate students, and researchers. The training followed a scaffolded progression from foundational prompt design to applied and ethical strategies, including persona guided interactions. Data sources comprised registration surveys, webinar interaction records, facilitator observations, and session transcripts, analysed using descriptive statistics and computationally supported qualitative techniques. Findings indicate that participants increasingly conceptualised prompt engineering as a form of AI literacy requiring ethical awareness, contextual sensitivity, and pedagogical judgement rather than technical skill alone. The case highlights persistent challenges related to access, locally relevant training materials, and institutional support. The report recommends sustained professional development and the integration of prompt literacy into curricula to support responsible GenAI use in African education systems.
Stroke is a leading cause of disability worldwide, with low- and middle-income countries (LMICs), particularly in Africa, experiencing an increasing burden due to rising incidences driven by urbanization, lifestyle changes, and non-communicable diseases. This scoping review maps stroke rehabilitation interventions in Africa, identifying barriers to implementation and adherence, and highlighting research gaps to inform future policy and clinical practices. A literature search was conducted across PubMed, Scopus, Web of Science, Embase, and African Journals Online (AJOL), supplemented by grey literature from WHO reports and government publications. Inclusion criteria focused on studies of stroke rehabilitation interventions in African countries, targeting adults diagnosed with stroke, and included randomized controlled trials, cohort studies, qualitative studies, and systematic reviews. Findings indicate that stroke rehabilitation interventions in Africa, including physical therapy, task-specific training, psychoeducational programs, tele-rehabilitation, mobile phone-supported interventions, and programs targeting activities of daily living (ADLs), are implemented in some settings to enhance functional independence, motor, cognitive, and speech functions, and psychological well-being. However, adherence to these protocols is often limited by significant barriers, including financial constraints, geographical and transportation challenges, a shortage of skilled rehabilitation professionals, cultural and language barriers, and patient-related factors such as cognitive impairments and lack of social support. The review also reveals variability in the availability of standardized rehabilitation protocols across African settings, with some regions lacking consistent implementation. Research gaps include insufficient epidemiological data, limited evaluation of cost-effective and culturally appropriate rehabilitation models, and underexplored caregiver burden. This review advocates further studies on technology integration, community-based rehabilitation, and culturally tailored interventions to improve adherence and accessibility. It also emphasizes addressing systemic and infrastructural barriers to ensure equitable access to rehabilitation services for stroke survivors across Africa. Future research should focus on optimizing rehabilitation strategies, reducing long-term disability, and improving quality of life for stroke survivors in Africa.
I. Sumartana, P. D. Hudiananingsih, Abdur Rouf
et al.
In the era of educational globalization, the preservation of mother tongues has become a critical concern for educators, linguists, and policymakers. The dominance of global languages such as English in educational curricula and academic discourse often leads to the marginalization of indigenous and minority languages. This study aims to explore the challenges and opportunities associated with preserving mother tongues within globalized educational frameworks. It seeks to highlight the implications of language loss on cultural identity, intergenerational communication, and linguistic diversity. The research employs a qualitative descriptive method, utilizing literature review, case studies, and interviews with educators and language activists from multilingual communities. The analysis reveals that while globalization facilitates access to international knowledge and collaboration, it also pressures educational institutions to prioritize global languages, often at the expense of local linguistic heritage. Case studies from regions such as Southeast Asia, Sub-Saharan Africa, and Latin America demonstrate how communities are attempting to integrate mother tongues into formal education through bilingual or multilingual education models. Interviews indicate that successful preservation efforts often depend on community involvement, governmental support, and curriculum integration that values both global and local knowledge systems. The study concludes that preserving mother tongues in education is not only a matter of linguistic justice but also of cultural sustainability. It emphasizes the need for inclusive language policies that balance global communication demands with the rights of communities to maintain their linguistic identities. Educational institutions must embrace multilingualism as an asset rather than a hindrance to progress. Further research is recommended to develop scalable models of mother-tongue-based multilingual education that can be adapted across diverse educational settings.
Jay L. Cunningham, Adinawa Adjagbodjou, Jeffrey Basoah
et al.
This scoping literature review examines how fairness, bias, and equity are conceptualized and operationalized in Automatic Speech Recognition (ASR) and adjacent speech and language technologies (SLT) for African American English (AAE) speakers and other linguistically diverse communities. Drawing from 44 peer-reviewed publications across Human-Computer Interaction (HCI), Machine Learning/Natural Language Processing (ML/NLP), and Sociolinguistics, we identify four major areas of inquiry: (1) how researchers understand ASR-related harms; (2) inclusive data practices spanning collection, curation, annotation, and model training; (3) methodological and theoretical approaches to linguistic inclusion; and (4) emerging practices and design recommendations for more equitable systems. While technical fairness interventions are growing, our review highlights a critical gap in governance-centered approaches that foreground community agency, linguistic justice, and participatory accountability. We propose a governance-centered ASR lifecycle as an emergent interdisciplinary framework for responsible ASR development and offer implications for researchers, practitioners, and policymakers seeking to address language marginalization in speech AI systems.
Irene Tafani, Ola Ali, Rafael Prieto-Curiel
et al.
Migration patterns are complex and context-dependent, with the distances migrants travel varying greatly depending on socio-economic and demographic factors. While global migration studies often focus on Western countries, there is a crucial gap in our understanding of migration dynamics within the African continent, particularly in West Africa. Using data from over 60,000 individuals from eight West African countries, this study examines the determinants of migration distance in the region. Our analysis reveals a bimodal distribution of migration distances: while most migrants travel locally within a hundred km, a smaller yet significant portion undertakes long-distance journeys, often exceeding 3,000 km. Socio-economic factors such as employment status, marital status and level of education play a decisive role in determining migration distances. Unemployed migrants, for instance, travel substantially farther (1,467 km on average) than their employed counterparts (295 km). Furthermore, we find that conflict-induced migration is particularly variable, with migrants fleeing violence often undertaking longer and riskier journeys. Our findings highlight the importance of considering both local and long-distance migration in policy decisions and support systems, as well as the need for a comprehensive understanding of migration in non-Western contexts. This study contributes to the broader discourse on human mobility by providing new insights into migration patterns in Western Africa, which in turn has implications for global migration research and policy development.
Tafiti mbalimbali zinaonesha kwamba, baadhi ya lahaja za Kiswahili zinaelekea kupoteza uasili wake kutokana na sababu mbalimbali zikiwamo za kijamii na kihistoria. Kupotea kwa maneno chanzi katika lahaja ni tatizo linalohitaji umakini wa haraka kwa sababu huenda kizazi kijacho kisiweze kuyatambua kabisa maneno hayo. Pamoja na ukweli huo, hakujawa na uchunguzi wa kina unaoonesha mifano kuntu ya maneno chanzi ambayo yanaonekana kupotea katika lahaja mbalimbali za Kiswahili ikiwamo lahaja ya Kipemba. Hivyo, makala hii inachunguza mifano ya maneno chanzi yanayoanza kupotea katika lahaja hiyo. Kwa hakika uchunguzi huu utasaidia kuyaweka bayana maneno hayo ili yabaki hai na yaendelee kutumiwa na watafiti pamoja na waandishi mbalimbali wa lugha ya Kiswahili na lahaja zake. Aidha, makala imechunguza sababu pamoja na athari za kupotea kwa maneno chanzi. Utafiti huu umeongozwa na Nadharia ya Umuundo iliyoasisiwa na De Saussure mwanzoni mwa karne ya 20. Data za makala hii zimekusanywa kupitia mbinu ya usomaji wa nyaraka, ushuhudiaji, usaili na hojaji. Makala imebaini kuwa kuna maneno chanzi mbalimbali ambayo yamepotea na mengine yanaendelea kupotea katika lahaja hiyo. Aidha, makala inatoa mchango mkubwa kwa taasisi za BAKITA na BAKIZA kwa kuwa zitaweza kuyatumia maneno hayo katika uundaji na usanifishaji wa istilahi za Kiswahili. Pia, watafiti na waandishi mbalimbali wa lahaja za Kiswahili wataweza kuyatumia maneno hayo katika tafiti zao. Makala imetoa mapendekezo ya kufanyika kwa uchunguzi zaidi wa maneno hayo katika lahaja nyingine mbalimbali za Kiswahili.
We report on an international scientific conference, where we brought together African and European academic astronomers. This aimed to bridge the gap between those in position of privilege, with ease of access to international events (i.e., the typical experience of academics in Western institutions), with those historically excluded (affecting the majority of African scientists/institutions). We describe how we designed the conference around cutting-edge research problems, but with a parallel focus on building networking and professional relationships. Significant effort went into: (1) ensuring a diversity of participants; (2) practically and financially supporting those who may never have attended an international conference and; (3) creating an inclusive and supportive environment through a careful programme of activities, both before and during the event. Maintaining scientific integrity was a core commitment throughout. We summarise successes, challenges and lessons learnt from organising this conference. We also present feedback obtained from participants immediately after the conference, and a discussion of some longer-term impacts, which we identified around 1 year later. We found an overall achievement of our objectives, and multiple longer-term benefits. With this report we provide some key recommendations for groups, from any research field, who may wish to lead similar initiatives.
Academic literature reviews have traditionally relied on techniques such as keyword searches and accumulation of relevant back-references, using databases like Google Scholar or IEEEXplore. However, both the precision and accuracy of these search techniques is limited by the presence or absence of specific keywords, making literature review akin to searching for needles in a haystack. We present vitaLITy 2, a solution that uses a Large Language Model or LLM-based approach to identify semantically relevant literature in a textual embedding space. We include a corpus of 66,692 papers from 1970-2023 which are searchable through text embeddings created by three language models. vitaLITy 2 contributes a novel Retrieval Augmented Generation (RAG) architecture and can be interacted with through an LLM with augmented prompts, including summarization of a collection of papers. vitaLITy 2 also provides a chat interface that allow users to perform complex queries without learning any new programming language. This also enables users to take advantage of the knowledge captured in the LLM from its enormous training corpus. Finally, we demonstrate the applicability of vitaLITy 2 through two usage scenarios. vitaLITy 2 is available as open-source software at https://vitality-vis.github.io.
End-user development allows everyday users to tailor service robots or applications to their needs. One user-friendly approach is natural language programming. However, it encounters challenges such as an expansive user expression space and limited support for debugging and editing, which restrict its application in end-user programming. The emergence of large language models (LLMs) offers promising avenues for the translation and interpretation between human language instructions and the code executed by robots, but their application in end-user programming systems requires further study. We introduce Cocobo, a natural language programming system with interactive diagrams powered by LLMs. Cocobo employs LLMs to understand users' authoring intentions, generate and explain robot programs, and facilitate the conversion between executable code and flowchart representations. Our user study shows that Cocobo has a low learning curve, enabling even users with zero coding experience to customize robot programs successfully.
This paper introduces LLAssist, an open-source tool designed to streamline literature reviews in academic research. In an era of exponential growth in scientific publications, researchers face mounting challenges in efficiently processing vast volumes of literature. LLAssist addresses this issue by leveraging Large Language Models (LLMs) and Natural Language Processing (NLP) techniques to automate key aspects of the review process. Specifically, it extracts important information from research articles and evaluates their relevance to user-defined research questions. The goal of LLAssist is to significantly reduce the time and effort required for comprehensive literature reviews, allowing researchers to focus more on analyzing and synthesizing information rather than on initial screening tasks. By automating parts of the literature review workflow, LLAssist aims to help researchers manage the growing volume of academic publications more efficiently.
Computer vision is a broad field of study that encompasses different tasks (e.g., object detection). Although computer vision is relevant to the African communities in various applications, yet computer vision research is under-explored in the continent and constructs only 0.06% of top-tier publications in the last ten years. In this paper, our goal is to have a better understanding of the computer vision research conducted in Africa and provide pointers on whether there is equity in research or not. We do this through an empirical analysis of the African computer vision publications that are Scopus indexed, where we collect around 63,000 publications over the period 2012-2022. We first study the opportunities available for African institutions to publish in top-tier computer vision venues. We show that African publishing trends in top-tier venues over the years do not exhibit consistent growth, unlike other continents such as North America or Asia. Moreover, we study all computer vision publications beyond top-tier venues in different African regions to find that mainly Northern and Southern Africa are publishing in computer vision with 68.5% and 15.9% of publications, resp. Nonetheless, we highlight that both Eastern and Western Africa are exhibiting a promising increase with the last two years closing the gap with Southern Africa. Additionally, we study the collaboration patterns in these publications to find that most of these exhibit international collaborations rather than African ones. We also show that most of these publications include an African author that is a key contributor as the first or last author. Finally, we present the most recurring keywords in computer vision publications per African region.
Anthony Biwott, Collins Kenga Mumbo, Robert Oduori
Propitiation is part of what it means to be human. Traditionally, propitiation has been studied from a broad sociocultural perspective with little consideration of the performance processes at play. Among the Nandi community in Kenya, propitiatory offering reconciliation forms the core of restoration of inter-communities relationships. It defines and enriches their culture, but what is propitiatory offering reconciliation? How is it performed? Are there any steps followed in its execution? Is there a specific place of performance? In this article we provide a framework to understand the Nandi propitiatory reconciliation through a literary perspective. We expound on the steps followed: investigation, interrogation, and cleansing, and the three features of performance: that is, place of performance, actions and signs, formulaic expression, costumes, and audience. The data collection took place in Kabiyet and Kipkaren Wards in Nandi county and was collected through participatory observation, interviews, and questionnaires. The sample population was 30 adults between the ages of 45–90 years who were selected using purposive and snowball sampling techniques. The data collected on performance in propitiatory reconciliation rites was analysed by use of functionalism theory as expounded by Foley. We found that the stages of propitiatory reconciliation must be religiously adhered to for its effectiveness and that the success of its performance heavily depends on the participation of its performers and audience. This article also brings out performance in form of particular acts, singing, and chanting.
A Twi-English parallel corpus is certainly an important resource for Machine Translation of Twi (ISO 639-3), a Low- Resource Language (LRL) which is mainly spoken in Ghana and Ivory Coast. Currently large-scale multidomain Twi- English parallel corpus is still unavailable partly due to the difficulties and the arduous efforts required in its design. A digital Twi lexicon curated purposely for linguistic research is also not available. In this paper, we present TWIENG – Twi English corpus, a large-scale multi-domain Twi-English parallel corpus and Twi lexicon, a digital Twi Dictionary. We discuss the data collection methodology, translation, alignment and compilation of the Twi-English parallel sentences and the technology we used to compile and host the corpus. Today’s parallel corpora are crawled from the web using web crawlers, the sentence pairs are processed, aligned, tokenized and compiled to create the corpus. We crawled English sentences from Ghanaian indigenous electronic news portals, Ghanaian Parliamentary Hansards, standard literature and also used crowdsourcing. The sentences are translated by professional translators and linguists, then aligned, tokenized and compiled. The corpus is curated using the sketch engine, a corpus manager and analysis software developed by Lexical Computing Limited. The corpus is manually evaluated by Twi professional linguists. The Corpus has 5,419 parallel sentences which were curled from local news portals, Ghana Parliament Hansard, The New Testament of the Twi Bible and through crowdsourcing via social media sites. CCS CONCEPTS • Computing Methodologies • Artificial Intelligence • Natural Language Processing
Norwegian Twitter data poses an interesting challenge for Natural Language Processing (NLP) tasks. These texts are difficult for models trained on standardized text in one of the two Norwegian written forms (Bokmål and Nynorsk), as they contain both the typical variation of social media text, as well as a large amount of dialectal variety. In this paper we present a novel Norwegian Twitter dataset annotated with POS-tags. We show that models trained on Universal Dependency (UD) data perform worse when evaluated against this dataset, and that models trained on Bokmål generally perform better than those trained on Nynorsk. We also see that performance on dialectal tweets is comparable to the written standards for some models. Finally we perform a detailed analysis of the errors that models commonly make on this data.
Women in the Bamenda Grassland have always been involved in different aspects of economic activities notably agriculture, local industry, and trade to sustain their households. Time and circumstances inevitably presented situations compelling them to take economic responsibility by complimenting men’s efforts and supplementing family income. This study examines women’s involvement in informal trade activities, particularly the petrol (commonly known as fingue or zoa-zoa) trade in Bamenda City. The article draws attention not only to the circumstances and contexts of women’s involvement in the informal petrol trade but also to the cutting-edge role they played in the business. The study makes use of written, oral as well as online sources to sustain its thesis.
History of Africa, African languages and literature
Background Schistosomiasis, a disease caused by blood flukes of the genus Schistosoma, belongs to the neglected tropical diseases. Left untreated, schistosomiasis can lead to severe health problems and even death. An estimated 800 million people are at risk of schistosomiasis and 250 million people are infected. The global strategy to control and eliminate schistosomiasis emphasizes large-scale preventive chemotherapy with praziquantel targeting school-age children. Other tools are available, such as information, education, and communication (IEC), improved access to water, sanitation, and hygiene (WASH), and snail control. Despite available evidence of the effectiveness of these control measures, analyses estimating the most cost-effective control or elimination strategies are scarce, inaccurate, and lack standardization. We systematically reviewed the literature on costs related to public health interventions against schistosomiasis to strengthen the current evidence-base. Methodology In adherence to the PRISMA guidelines, we systematically searched three readily available electronic databases (i.e., PubMed, WHOLIS, and ISI Web of Science) from inception to April 2019 with no language restrictions. Relevant documents were screened, duplicates eliminated, specific rules on studies to consider were defined, and the eligible studies fully reviewed. Costs of schistosomiasis interventions were classified in three groups: (i) preventive chemotherapy; (ii) preventive chemotherapy plus an individual diagnostic test to identify at-risk population; and (iii) test-and-treat interventions. Principal findings Fifteen articles met our inclusion criteria. In general, it was hard to compare the reported costs from the different studies due to different approaches used to estimate and classify the costs of the intervention assessed. Costs varied considerably from one study to another, ranging from US$ 0.06 to US$ 4.46 per person treated. The difference between financial and opportunity costs only played a minimal role in the explanation of the costs’ variation, even if delivery costs were two times higher in the analyses including economic costs. Most of the studies identified in our systematic review focused on sub-Saharan African countries. Conclusions/Significance The degree of transparency of most of the costing studies of schistosomiasis interventions found in the current review was limited. Hence, there is a pressing need for strategies to improve the quality of cost analyses, and higher reporting standards and transparency that should be fostered by peer-review journal policies. Cost information on these interventions is crucial to inform resource allocation decisions and those regarding the affordability of scaling-up interventions.