Adults’ development of literacy and numeracy skills that can enable them to navigate the demands of contemporary life and be prepared for the future is central to their economic, social, and personal well-being and the functioning of society. This article discusses the role of literacy and numeracy in adult learning and education, beginning with the current status of literacy and numeracy skills in OECD countries and economies. Explored are the types of frameworks and standards that are used to guide adults’ acquisition of literacy and numeracy skills and approaches to delivering instructional and supportive services for those adults. The article concludes with challenges and considerations in strengthening literacy and numeracy as critical components of adult learning and education.
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Blended learning offers a learner-centred approach that employs both in-class learning and digital technology to facilitate online learning. Such an approach is especially advantageous to adult-learners in higher education as it meets their educational needs. However, adult-learners’ participation in blended learning programmes remains challenging due to a general lack of online interaction, and no clear teaching strategies that address this concern. Literature relating to adult-learners’ educational needs and online interaction was consulted in order to design teaching strategies that foster adult-learners’ online interaction. The aim of this study is to further validate these teaching strategies, hence a multiple case study was carried out using a mixed method approach. As such, eight teachers and sixteen students from four courses across three universities in Belgium and the Netherlands were interviewed. Additionally, a questionnaire testing a pre-defined set of variables was distributed to 84 students. The results lead to a set of validated teaching strategies that help teachers to further develop their professional skills and expertise. The teaching strategies can be grouped into three categories, namely 1) the teacher's online presence, 2) collaborative learning activities and preparatory learning activities, and 3) the distribution of learning content and learning activities across online and in-class learning. An elaborate set of validated teaching strategies is included. This study aids towards teacher professional development and adds evidence-based knowledge to teaching strategies and instructional frameworks for adult-learners in higher education.
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The main objective of this dissertation is to examine, both theoretically and empirically, the specific requirements of a blended learning instructional model aimed at facilitating higher education adult-learners into online interaction. Three objectives were formulated: Objective 1: to investigate adult-learners’ perceived satisfaction in relation to blended learning and the factors that foster their interaction with the ‘added’ online mode; and a thorough understanding of adult-learners’ educational needs and learning characteristics derived from theory. Objective 2: to understand the factors of social presence and convergence, and how these can be ingrained into design principles that foster online interaction. Objective 3: to explore the specifics of an instructional model for the design of a blended learning environment for adult-learners in higher education, both theoretically and empirically, and how said principles can be actualised in a validated model.
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CRYPTOPOLIS is a project supported by EU which focuses on the financial management knowledge of teachers and the emerging field of risk management and risk analysis of cryptocurrencies. Cryptocurrency has shown to be a vital and rapidly growing component in today’s digital economy therefore there is a need to include not just financial but also crypto literacy into the schools. Beside multiple investors and traders the market is attracting an increasing number of young individuals, viewing it as an easy way to make money. A large pool of teenagers and young adults want to hop on this train, but a lack of cryptocurrency literacy, as well as financial literacy in general amongst youth, together with their inexperience with investing makes them even more vulnerable to an already high-risk investment.Therefore, we aim to increase the capacity and readiness of secondary schools and higher educational institutions to manage an effective shift towards digital education in the field of crypto and financial literacy. The project will develop the purposeful use of digital technologies in financial and crypto education for teaching, learning, assessment and engagement.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
The growing use of digital media has led to a society with plenty of new opportunities for knowledge exchange, communication and entertainment, but also less desirable effects like fake news or cybercrime. Several studies, however, have shown that children are less digital literate than expected. Digital literacy has consequently become a key part within the new national educational policy plans titled Curriculum.nu and the Dutch research and policy agendas. This research project is focused on the role the game sector can play in the development of digital literacy skills of children. In concrete, we want to understand the value of the use of digital literacy related educational games in the context of primary education. Taking into consideration that the childhood process of learning takes place through playing, several studies claim that the introduction of the use of technology at a young age should be done through play. Digital games seem a good fit but are themselves also part of digital media we want young people to be literate about. Furthermore, it needs to be taken into account that digital literacy of teachers can be limited as well. The interactive, structured nature of digital games offers potential here as they are less dependent on the support and guidance of an adult, but at the same time this puts even more emphasis on sensible game design to ensure the desired outcome. The question is, then, if and how digital games are best designed to foster the development of digital literacy skills. By harnessing the potential of educational games, a consortium of knowledge and practice partners aim to show how creating theoretical and practical insights about digital literacy and game design can aid the serious games industry to contribute to the societal challenges concerning contemporary literacy demands.
