How Older Adults Learn ICT—Guided and Self-Regulated Learning in Individuals With and Without Disabilities

Learning to use information and communication technologies (ICT) may be more difficult for older people due to decreases in fluid intelligence, generational effects, and other age-related effects. Especially older people with intellectual disabilities (ID) are at a high risk of digital exclusion. To enable all older adults to use ICT, individualized technology training may be provided. However, little is known about the ICT learning preferences among older people with ID. Based on semi-structured interviews with older adults (n = 7, mean age = 76.6 years) and older adults with ID (n = 14, mean age = 62.4 years), this paper analyzes learning strategies, preferences, and learning settings. The results from content analysis show that guided learning with personal explanations in a one-to-one setting is the most preferred learning format in both groups of older adults. While many older adults without ID additionally favor self-regulated learning (i.e., learning with manuals or videos), older adults with ID mostly rely on guided learning with personal assistance. The differences can be explained by different abilities (e.g., reading skills) and social networks (e.g., living situation, having children). Not all older adults have a family or an institutional support network to help them learn ICT and community organizations may provide additional support. Researchers and practitioners should be aware of the diverse knowledge backgrounds and competencies in the group of older adults. ICT training in old age should be ideally composed in a modular way embedding self-regulated learning formats into guided learning modules.

The Characteristics of Instructional Systematic Design English Online Teaching Environment

The English online learning instructional model became contingent upon organised and guided learning practices by competent English lecturers as instructors in the online situation. There are a few concepts applied to the English instructional online pedagogy for Higher Education and Universities. The purposes of the examinations are to classify the relevance of online instructional learning to conform to English learning and present current or unexpected instructional design into the English online environment. The study employed a convergent parallel design method. This method of choice had depth-analysing and performing parallel analyses, which are considered alternative evidence for discussing the components of the online instructional model. The examination consisted of 52 English lecturers from various Higher Education and Universities. The survey questionnaires were addressed to participants, and interview strategies were identified to collect a distinctive angle and dept-involvement on the English online instructional. Findings of the study have revealed that English lecturers considered learner-centered intended course as very important for their teaching concept while emphasising real-world performance as important for the online environment material. Collaborative approach and concentrate on reliably and validly assessed outcomes become the second phase importance in the online instructional model. Interview protocols thematic analysis exposed that English lecturers should support and organise their particular English online instructional online environment. The general characterised adapted to engage in English online instructional online-based. The condition is because of English lecturers empathising with the appropriate material, approach to the learners’ flexibility, and individual accomplishment in every topic.

Learn2Write: Augmented Reality and Machine Learning-Based Mobile App to Learn Writing

Augmented reality (AR) has been widely used in education, particularly for child education. This paper presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing. The app has two main features: (i) guided learning to teach users how to write the alphabet and (ii) on-screen and AR-based handwriting testing using machine learning. A learner needs to write on the mobile screen in on-screen testing, whereas AR-based testing allows one to evaluate writing on paper or a board in a real world environment. We implement a novel approach to use machine learning for AR-based testing to detect an alphabet written on a board or paper. It detects the handwritten alphabet using our developed machine learning model. After that, a 3D model of that alphabet appears on the screen with its pronunciation/sound. The key benefit of our approach is that it allows the learner to use a handwritten alphabet. As we have used marker-less augmented reality, it does not require a static image as a marker. The app was built with ARCore SDK for Unity. We further evaluated and quantified the performance of our app on multiple devices.

Dual-Stream Guided-Learning via a Priori Optimization for Person Re-identification

The task of person re-identification (re-ID) is to find the same pedestrian across non-overlapping camera views. Generally, the performance of person re-ID can be affected by background clutter. However, existing segmentation algorithms cannot obtain perfect foreground masks to cover the background information clearly. In addition, if the background is completely removed, some discriminative ID-related cues (i.e., backpack or companion) may be lost. In this article, we design a dual-stream network consisting of a Provider Stream (P-Stream) and a Receiver Stream (R-Stream). The R-Stream performs an a priori optimization operation on foreground information. The P-Stream acts as a pusher to guide the R-Stream to concentrate on foreground information and some useful ID-related cues in the background. The proposed dual-stream network can make full use of the a priori optimization and guided-learning strategy to learn encouraging foreground information and some useful ID-related information in the background. Our method achieves Rank-1 accuracy of 95.4% on Market-1501, 89.0% on DukeMTMC-reID, 78.9% on CUHK03 (labeled), and 75.4% on CUHK03 (detected), outperforming state-of-the-art methods.

Model-based Damage Detection through Physics Guided Learning

Data-driven learning approaches have gained a lot of interest in evaluating and validating complex dynamic systems. One of the main challenges for developing a reliable learning model is the lack of training data covering a large range of various operational conditions. Extensive training data can be generated using a physics-based simulation model. On the other hand, the learning algorithm should be still tested with experimental data obtained from the actual system. Modeling errors may lead to a statistical divergence between the simulation training data and the experimental testing data, causing poor performance, especially for domain-agnostic black-box learning methods. To close the gap between the simulation and experimental domains, this paper proposes a physics-guided learning approach that combines the power of the neural network with domain-specific physics knowledge. Specifically, the proposed architecture integrates physical parameters extracted from the physics-based simulation model into the intermediate layers of the neural network to constrain the learning process. To demonstrate the effectiveness of the proposed approach, the architecture is adopted to a damage classification problem for a three-story structure. Our results show that the accuracy for localizing the damage correctly based on experimental data improves significantly over black-box models, especially under large modeling errors. In this paper, we also use the physics-based intermediate layers to analyze the interpretability of the classification results.

Self-Guided Learning Process in Preschool: Challenges of the Practice

The mandatory teaching/learning content of the preschool lays emphasis on the child’s most essential interests and needs, acquiring them in such a process that leads to the formation of literacy or competence. Self-guided learning in the teaching/learning process appears as the major method that helps the pre-schooler acquire the content of all domains. According to the preschool guidelines, values and morals, general or transversal skills, cognitive, emotional and social aspects of the child’s actions that help to acquire knowledge, understanding and key skills for man’s functioning in important spheres of life and these are the key skills in the domains of language, social and civic, understanding of culture and self-expression in art, science, mathematics, technology, health and physical activities that form the mandatory teaching/learning content of preschool education. When acquiring all the necessary skills and knowledge, the child has to reach the planned learning outcomes that are attained in a self-guided learning process. Self-guided learning is one of the most essential modern competences or the individual’s readiness to adjust and apply the knowledge, skills and attitudes when solving different situations. Are preschools ready for this, does this process take place and do preschool teachers understand the concept “self-guided learning process” – this is the topicality that definitely should be paid attention to relating it to teacher education, the development of the self-guided learning model and its piloting in the preschool environment. A self-guided learning process should not be taken for granted because the child does not have such skills – to know / to feel how and what to do to start, for example, exploration. The child has not acquired these skills if the adult has not demonstrated how to do this. The child since young age should be gradually directed towards that – what and in which way to learn. The participation of the adult or teacher in this significant process is critical.

Transversal Skills for the Implementation of Competence Approach during a Music Pedagogy Process at Primary School

Expertise-based (competence) approach is one of the approaches in pedagogy which in the 21st century can be applied to develop important value-based knowledge, skills and habits. Transversal skills help learners to use knowledge in a real-life context, be ready to take on responsibility for their own learning, constituting a complex achievement, and strengthening the link between knowledge and personal experience. These skills can be acquired by purposefully integrating them with the core skills in all subjects, music including. Transversal skills include such components as: cooperation, creative and entrepreneurial ability, civic participation, critical thinking and problem solving, digital literacy, and self-guided learning skills. It is essential to bring the above-mentioned skills into focus in music pedagogy – to substantiate them theoretically and give a practical guidance how they can be seen in a pedagogical reality and develop them within the frame of music teaching in primary school. Research aim: to describe and substantiate how to enhance the development of transversal skills by applying competence approach during a music pedagogy process at primary school. Materials and methods: this paper will provide the analysis of theoretical literature and education documents on the competence approach, examine possibilities of developing transversal skills in music at Music Primary School. Theoretical findings will be brought into foreground in connection with the pedagogical experience obtained while teaching at Jazeps Vitols Latvian Academy of Music and giving music lessons in general education institutions.