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Mobile apps have become indispensable for accessing and participating in various environments, especially for low-vision users. Users with visual impairments can use screen readers to read the content of each screen and understand the…

With the emergence of deep learning techniques, smartphone apps are now embedded on-device AI features for enabling advanced tasks like speech translation, to attract users and increase market competitiveness. A good interaction design is…

Logging is a common practice in traditional software development. Several research works have been done to investigate the different characteristics of logging practices in traditional software systems (e.g., Android applications, JAVA…

This paper introduces Aptly, a platform designed to democratize mobile app development, particularly for young learners. Aptly integrates a Large Language Model (LLM) with App Inventor, enabling users to create apps using their natural…

Using smartphones for mobile self-testing could provide easy access to speech intelligibility testing for a large proportion of the world population. The matrix sentence test (MST) is an ideal candidate in this context, as it is a…

This paper introduces the Word Synchronization Challenge, a novel benchmark to evaluate large language models (LLMs) in Human-Computer Interaction (HCI). This benchmark uses a dynamic game-like framework to test LLMs ability to mimic human…

Large language models (LLMs) are rapidly changing learning processes, as they are readily available to students and quickly complete or augment several learning-related activities with non-trivial performance. Such major shifts in learning…

Teens are using mobile devices for an increasing number of activities. Smartphones and a variety of mobile apps for communication, entertainment, and productivity have become an integral part of their lives. This mobile phone use has…

Deploying Large Language Models (LLMs) on mobile devices makes all the capabilities of natural language processing available on the device. An important use case of LLMs is question answering, which can provide accurate and contextually…

As large language models (LLMs) increasingly integrate into every aspect of our work and daily lives, there are growing concerns about user privacy, which push the trend toward local deployment of these models. There are a number of…

The more new features that are being added to smartphones, the harder it becomes for users to find them. This is because the feature names are usually short, and there are just too many to remember. In such a case, the users may want to ask…

Mobile notification systems have taken a major role in driving and maintaining user engagement for online platforms. They are interesting recommender systems to machine learning practitioners with more sequential and long-term feedback…

Emergence of latest technologies has diverted the focus of people form Computer-Supported Collaborative Learning (CSCL) to mobile supported collaborative learning. MCL is highly demanded in educational organizations to substantiate the…

Lifelong learning aims to accumulate knowledge and alleviate catastrophic forgetting when learning tasks sequentially. However, existing lifelong language learning methods only focus on the supervised learning setting. Unlabeled data, which…

Surveys in mobile learning developed so far have analysed in a global way the effects on the usage of mobile devices by means of general apps or apps already developed. However, more and more teachers are developing their own apps to…

Smartphone sensing offers an unobtrusive and scalable way to track daily behaviors linked to mental health, capturing changes in sleep, mobility, and phone use that often precede symptoms of stress, anxiety, or depression. While most prior…

Machine learning about language can be improved by supplying it with specific knowledge and sources of external information. We present here a new version of the linked open data resource ConceptNet that is particularly well suited to be…

Personalization plays a critical role in numerous language tasks and applications, since users with the same requirements may prefer diverse outputs based on their individual interests. This has led to the development of various…

Latest study shows that MCL is highly focusing paradigm for research particularity in distance and online education. MCL provides some features and functionalities for all participants to obtain the knowledge. Deployment of new emerging…

The fast advancements in Large Language Models (LLMs) are driving an increasing number of applications. Together with the growing number of users, we also see an increasing number of attackers who try to outsmart these systems. They want…