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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…
Computer-supported collaborative learning (CSCL) has been a steady topic of research since the early 1990s, and the trend has continued to this date. The basic benefits of CSCL in the classroom have been established in many fields of…
Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help…
Collaborations among various entities, such as companies, research labs, AI agents, and edge devices, have become increasingly crucial for achieving machine learning tasks that cannot be accomplished by a single entity alone. This is likely…
In the era of m-Learning, it is found that educational institutions have onus of incorporating the latest technological innovations that can be accepted and understood widely. While investigating the important theme of fast-paced…
The integration of new technologies in the classrooms opens new possibilities for the teaching and learning process. Technologies such as student response system (e.g. Clicker) are getting popularity among teachers due to its effects on…
This paper proposes a more comprehensive evaluation methodology to measure the usability and user experience qualities of accessible synchronous computer-mediated communication applications. The methodology goes beyond current practices by…
With rapid technological advancements, mobile learning (m-Learning) offers incredible opportunities, especially in the area of higher education. However, while interest in this area has been significant and several pilot studies have been…
Nowadays, real-world applications often face streaming data, which requires the learning system to absorb new knowledge as data evolves. Continual Learning (CL) aims to achieve this goal and meanwhile overcome the catastrophic forgetting of…
Mobile collaborative learning (MCL) is extensively recognized field all over the world. It demonstrates the cerebral approach combining the several technology to handle the problem of learning. MCL motivates the social and educational…
Teacher-Student Curriculum Learning (TSCL) is a curriculum learning framework that draws inspiration from human cultural transmission and learning. It involves a teacher algorithm shaping the learning process of a learner algorithm by…
With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities. Continual learning (CL) is a novel machine learning paradigm that…
Multi-Task Learning (MTL) is a powerful technique that has gained popularity due to its performance improvement over traditional Single-Task Learning (STL). However, MTL is often challenging because there is an exponential number of…
The phenomenon of the use of a mobile learning (m-Learning) platform in educational institutions is slowly gaining momentum. While this can be taken as an encouraging sign, the perplexing part is that the fervor with which mobile phones…
Usability evaluation is an essential method to support the design of effective and intuitive user interfaces (UIs). However, it commonly relies on resource-intensive, expert-driven methods, which limit its accessibility, especially for…
The paper reports on an ongoing research project into the development of "Mobile Academy", an Android-based mobile learning (mLearning) application (app). The project comprises three major phases: requirement analysis, application…
Controllability has become a crucial aspect of trustworthy machine learning, enabling learners to meet predefined targets and adapt dynamically at test time without requiring retraining as the targets shift. We provide a formal definition…
Multimodal Contrastive Learning (MCL) advances in aligning different modalities and generating multimodal representations in a joint space. By leveraging contrastive learning across diverse modalities, large-scale multimodal data enhances…
Continual learning (CL) aims to empower machine learning models to learn continually from new data, while building upon previously acquired knowledge without forgetting. As models have evolved from small to large pre-trained architectures,…
This paper studies the challenging continual learning (CL) setting of Class Incremental Learning (CIL). CIL learns a sequence of tasks consisting of disjoint sets of concepts or classes. At any time, a single model is built that can be…