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Globally, teaching and learning in contact face-to-face universities had to transition to online learning during 2020, following the disruptions caused by COVID-19 pandemic lockdowns imposed in many countries around the world. The purpose of this paper is to provide insights from preliminary results of ongoing research focusing on students' personal concerns raised about online learning during the early stages of the COVID-19 pandemic in South Africa. Data were collected using a web-based survey in 2020, sampling one group of second-year university students. Internationally, the COVID-19 pandemic has led to an acceleration in digital transformation for teaching and learning in many face-to-face contact universities. The key findings from the survey reported in this paper are twofold: firstly, it was found that COVID-19 has fundamentally changed both teaching and learning space geographies with large proportions of university students having to study from their homes during the lockdown; secondly, students recognised that access to Information and Communication Technology (ICT) infrastructure and the unaffordability of internet connections were significant concerns for most respondents who took part in the study. The study seeks to highlight that even though the COVID-19 pandemic has led to an acceleration in the digital transformation underway in tertiary education and has drawn university teaching and learning more comprehensively into the digital era, the uneven distribution of ICT infrastructure accentuates the barriers to and inequalities that exist for students and for practical home studying. The study makes initial policy suggestions for assisting this acceleration into the digital world. Future research can build on this platform by analysing the post-COVID-19 effects in the university teaching and learning environment. [ABSTRACT FROM AUTHOR]

Traditional teaching methods have been bolstered by modern teaching methods and multimedia technology, allowing students to benefit from both new and old approaches to learning. Teaching and learning are evolving at an unprecedented rate because of the rise of online courses. Rapid advances in intelligent technologies and communication networks provide new opportunities for interactive technology innovation and technical support for hybrid teaching incorporating both on- and offline study. For this article to be helpful, it needs to examine how an intelligent mobile communication network's effective teaching combined with a hybrid teaching mode can improve the educational attainment of student teachers' English reading, among other things. This article should address these issues and more. According to this paper's findings from the experimental study, college students' desire for and capacity to learn independently in English reading courses has increased massively, and our English reading results will rise by at least 93%. • Teaching and learning are evolving at an unprecedented rate because to the rise of online courses. • On the basis of mastery of observational learning and constructivist teaching theory. • There is no longer a restriction on the amount of time or place in which individuals may communicate. • No longer any concerns regarding short-term single network lines thanks to the advent of mobile devices. [ABSTRACT FROM AUTHOR]

In a competitive game scenario, a set of agents have to learn decisions that maximize their goals and minimize their adversaries' goals at the same time. Besides dealing with the increased dynamics of the scenarios due to the opponents' actions, they usually have to understand how to overcome the opponent's strategies. Most of the common solutions, usually based on continual learning or centralized multi-agent experiences, however, do not allow the development of personalized strategies to face individual opponents. In this paper, we propose a novel model composed of three neural layers that learn a representation of a competitive game, learn how to map the strategy of specific opponents, and how to disrupt them. The entire model is trained online, using a composed loss based on a contrastive optimization, to learn competitive and multiplayer games. We evaluate our model on a pokemon duel scenario and the four-player competitive Chef's Hat card game. Our experiments demonstrate that our model achieves better performance when playing against offline, online, and competitive-specific models, in particular when playing against the same opponent multiple times. We also present a discussion on the impact of our model, in particular on how well it deals with on specific strategy learning for each of the two scenarios. [ABSTRACT FROM AUTHOR]

The aim of this integrative review is to explore how formative online multiple-choice tests used in nurse education promote self-regulated learning and report on pedagogies that support their design. Online multiple-choice tests are widely used as learning and formative assessment tools in a range of educational contexts. However, little is known about how these tools are used to promote patterns of learner self-regulation. It is important that nurses and nursing students develop the capability to self-regulate learning to be effective lifelong learners and navigate complex and unfamiliar practice environments. A five-stage approach guided this integrative review: problem identification, literature search, data evaluation, data analysis and presentation. A systematic search of ERIC, Web of Science, Ovid Medline, Scopus, PubMed, Embase and CINAHL was conducted in February 2021. Seventeen peer-reviewed papers were identified that discussed formative online multiple-choice tests in nurse education. Purposive sampling and ancestry searching identified an additional paper. Articles were analysed and sorted into themes of outcomes (presented as components of self-regulated learning theory) and pedagogy. Formative online multiple-choice tests are used with good effect in nurse education as measured by knowledge gain and exam performance, increased confidence and learner satisfaction. There was no literature that explored metacognitive outcomes and minimal literature considered behavioural outcomes. Pedagogy supporting the implementation of multiple-choice tests was lacking in most articles. Formative online multiple-choice tests are widely used with good effect in nurse education. However, opportunities for further research on how these tools can encourage metacognition and self-regulatory behaviours is warranted. [ABSTRACT FROM AUTHOR]

This paper reports on the online architectural learning experience at a university in the Kingdom of Saudi Arabia. The study surveyed students and faculty members regarding their experience of learning and assessment and proposed recommendations for future online education. The survey supported the study hypothesis that students generally believe that they had a positive online learning experience during the pandemic. However, the principal challenge was the lack of a physical interactive environment in studio-based courses, which resulted in a sense of isolation. Thus, the study recommends that online education in architecture could be used as a supportive tool rather than an alternative. In this context, design studio courses, especially at the beginning of a study programme, should not be given completely online unless this was essential. The use of blended learning is a balanced strategy that uses interactive online technologies to enhance traditional face-to-face learning in design studio courses. [ABSTRACT FROM AUTHOR]

Due to the outbreak of the new crown epidemic, online teaching is booming, but compared with traditional offline teaching, there are many problems, such as the difficulty of detecting the voice status of students. Therefore, the research on students' online status detection system is of great significance. In this paper, based on image processing, the detection method of online classroom students' learning behavior status is studied, and the learning status of students is detected from the perspective of face detection and face recognition fatigue detection. In this study, the students' learning status is detected by the facial expressions in the video during the students' learning process. When the students have negative emotions and become tired, the system can detect and record them in time and issue a warning. Therefore, this research can well solve the problems existing in online teaching, and to a certain extent, the teaching quality has been greatly improved. [ABSTRACT FROM AUTHOR]

Sensor-based human activity recognition (HAR), with the ability to recognise human activities from wearable or embedded sensors, has been playing an important role in many applications including personal health monitoring, smart home, and manufacturing. The real-world, long-term deployment of these HAR systems drives a critical research question: how to evolve the HAR model automatically over time to accommodate changes in an environment or activity patterns. This paper presents an online continual learning (OCL) scenario for HAR, where sensor data arrives in a streaming manner which contains unlabelled samples from already learnt activities or new activities. We propose a technique, OCL-HAR, making a real-time prediction on the streaming sensor data while at the same time discovering and learning new activities. We have empirically evaluated OCL-HAR on four third-party, publicly available HAR datasets. Our results have shown that this OCL scenario is challenging to state-of-the-art continual learning techniques that have significantly underperformed. Our technique OCL-HAR has consistently outperformed them in all experiment setups, leading up to 0.17 and 0.23 improvements in micro and macro F1 scores. [ABSTRACT FROM AUTHOR]