Automating question generation and marking of language learning exercises for isiZulu

Increase in isiZulu language learning is hampered by the predominantly manual approach to creating and marking homework and test exercises. Extant computer-assisted language learning platforms cannot handle the intricacies of agglutination in isiZulu and related languages. We seek to address this by designing a controlled natural language-based exercise generator and marker for isiZulu. This consists of question and answer sentence templates for exercise types, reusable algorithm snippets as grammar library, a small corpus of words and sentences to be used by the system, a constrained sentence generator to combine the right type of words, and finally the exercise creation and automated marking system. The preliminary evaluation shows encouraging results

Natural Language Generation Requirements for Social Robots in Sub-Saharan Africa

Robots are deployed in Africa mainly in manufacturing, yet they may assist in society as future oriented technologies as well. They may ameliorate, e.g., service delivery issues and skills shortages. In this discussion paper, several uses and use cases relevant to Sub-Saharan Africa are described and requirements identified. We zoom in on human-robot interaction in Niger-Congo B (‘bantu’) languages. Use cases for healthcare and education elucidate specific requirements for the natural language generation component of robots in society. In contrast to typical generation systems, it demands i) combining data-to-text and knowledge-to-text in one system, ii) generating different types of sentences so as to switch between written and spoken language, and iii) processing non-trivial numbers

A classification of grammar-infused templates for ontology and model verbalisation

Involving domain-experts in the development, maintenance, and use of knowledge organisation systems can be made easier through the introduction of easy-to-use interfaces that are based on natural language. Well resourced languages make use of natural language generation techniques to provide such interfaces. In particular, they often make use of templates combined with computational grammar rules to generate grammatically complex text. However, there is no model of pairing templates and computational grammar rules to ensure suitability for less-resourced languages. These languages require a modular design that ensures grammar detachability so as to allow grammar re-use across domains and applications. In this paper, we present a model and classification scheme for grammar-infused templates suited for less-resourced languages and classify existing systems that make use of them. We have found that of the 15 systems that pair templates and grammar rules, and their 11 distinct template types, 13 have support for detachable grammars

Automated Exercise Generation in Mobile Language Learning

The Language Lion is an Android application that teaches basic Dutch to English speakers. While mobile language learning has increased exponentially in popularity, course creation is still labor-intensive. By contrast, the Language Lion uses a map of Dutch to English lexemes, a context-free grammar, and a modified version of the SimpleNLG sentence realizer to automatically generate semi-random translation exercises for the student. Each component is evaluated individually to find and analyze the particular roadblocks in automated exercise generation for mobile language learning

An Architecture for Generating Questions, Answers, and Feedback from Ontologies

Automatically generating questions, answers, and feedback from ontologies and conceptual models is crucial for learning activities and knowledge validation. Existing proposals are limited to predefined types of questions and the modelling style that they are tailored to, lack feedback generation, and their core algorithm are dependent on those characteristics, therewith hampering maintainability and reusability. We designed a new architecture where the question, answer and feedback specifications, the core algorithm for selecting the contents from the ontology, and the verbaliser are modularised for resolving these problems. We instantiated the architecture as a proof-of-concept, examined three test cases, and showed that it compares favourably to related work

Surface realization architecture for low-resourced African languages

There has been growing interest in building surface realization systems to support the automatic generation of text in African languages. Such tools focus on converting abstract representations of meaning to text. Since African languages are low-resourced, economical use of resources and general maintainability are key considerations. However, there is no existing surface realizer architecture that possesses most of the maintainability characteristics (e.g., modularity, reusability, and analyzability) that will lead to maintainable software that can be used for the languages. Moreover, there is no consensus surface realization architecture created for other languages that can be adapted for the languages in question. In this work, we solve this by creating a novel surface realizer architecture suitable for low-resourced African languages that abide by the features of maintainable software. Its design comes after a granular analysis, classification, and comparison of the architectures used by 77 existing NLG systems. We compare our architecture to existing architectures and show that it supports the most features of a maintainable software product.Hasso Plattner Institute for Digital Engineering through the HPI Research School at UCT and the National Research Foundation (NRF) of South Africahttps://dl.acm.org/journal/tallipInformatic

The State of AI Ethics Report (June 2020)

These past few months have been especially challenging, and the deployment of technology in ways hitherto untested at an unrivalled pace has left the internet and technology watchers aghast. Artificial intelligence has become the byword for technological progress and is being used in everything from helping us combat the COVID-19 pandemic to nudging our attention in different directions as we all spend increasingly larger amounts of time online. It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions. This pulse-check for the state of discourse, research, and development is geared towards researchers and practitioners alike who are making decisions on behalf of their organizations in considering the societal impacts of AI-enabled solutions. We cover a wide set of areas in this report spanning Agency and Responsibility, Security and Risk, Disinformation, Jobs and Labor, the Future of AI Ethics, and more. Our staff has worked tirelessly over the past quarter surfacing signal from the noise so that you are equipped with the right tools and knowledge to confidently tread this complex yet consequential domain

Speculative Futures on ChatGPT and Generative Artificial Intelligence (AI): A Collective Reflection from the Educational Landscape

While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Education (AIEd) and possible adverse effects are identified and discussed which emerge from the narratives. It is argued that now is the best of times to define human vs AI contribution to education because AI can accomplish more and more educational activities that used to be the prerogative of human educators. Therefore, it is imperative to rethink the respective roles of technology and human educators in education with a future-oriented mindset

Semiotic machines : software in discourse

Includes abstract.Includes bibliographical references (p. 245-259).This study develops new theoretical and methodological approaches to the study of software as a medium of communication. This study analyses voting software, educational software, search engines, and combat and narrative in digital games. In each case it investigates how proprietary software affords discourse, and suggests a way of characterising users’ experience of this discourse. These affordances constitute the rules of communication, or ‘rules of speaking’, ‘rules of seeing’, and ‘writing-rights’ which proprietary software makes available to users, situating them within specific power-relations in the process

The Early Grade Reading Assessment

The Early Grade Reading Assessment (EGRA) measures students' progress towards reading. EGRA gauges early literacy skills through a 15-minute individual oral assessment of five fundamental reading skills. RTI worked with education experts to develop the EGRA in 2006, and it has been piloted and implemented in more than 40 countries. This volume aims to take stock of the substantial amount of information and experience generated through the use of EGRA, and to share this knowledge with practitioners, policymakers, and international donors. Chapters cover not only particular applications of the instrument but also put EGRA in the context of broader issues and developments in literacy and education.Publishe