相关论文: Blended e-Learning Training (BeLT): Enhancing Rail…

Embedded computing systems are pervasive in our everyday lives, imparting digital intelligence to a variety of electronic platforms used in our vehicles, smart appliances, wearables, mobile devices, and computers. The need to train the next…

Self-training approach for large language models (LLMs) improves reasoning abilities by training the models on their self-generated rationales. Previous approaches have labeled rationales that produce correct answers for a given question as…

We study the problem of inverse reinforcement learning (IRL) with the added twist that the learner is assisted by a helpful teacher. More formally, we tackle the following algorithmic question: How could a teacher provide an informative…

Query understanding plays a key role in exploring users' search intents and facilitating users to locate their most desired information. However, it is inherently challenging since it needs to capture semantic information from short and…

With the increasing prevalence of online learning, adapting education to diverse learner needs remains a persistent challenge. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), promise powerful…

Interest-based learning (IBL) is a paradigm of instruction in which educational content is contextualized using learners' interests to enhance content relevance. IBL has been shown to result in improved learning outcomes. Unfortunately,…

The topics of Artificial intelligence (AI) and especially Machine Learning (ML) are increasingly making their way into educational curricula. To facilitate the access for students, a variety of platforms, visual tools, and digital games are…

Transportation is the backbone of the economy and urban development. Improving the efficiency, sustainability, resilience, and intelligence of transportation systems is critical and also challenging. The constantly changing traffic…

Advancement in information system leads organizations to apply e-learning system to train their employees in order to enhance its performance. In this respect, applying web based training will enable the organization to train their…

With the rise of the gig economy, online language tutoring platforms are becoming increasingly popular. These platforms provide temporary and flexible jobs for native speakers as tutors and allow language learners to have one-on-one…

Mobile Learning (M-Learning) is an emerging discipline in the area of education and educational technology. So researchers are trying to optimize and expanding its application in the field of education. The aim of this paper is to…

Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which…

As a CDIO collaborating member, the School of Mechanical and Electrical Engineering of Sheridan maintains a curriculum that is deeply rooted in skills-based learning, experiential learning, and engineering design. To ensure our graduates…

The study introduces a new analysis scheme to analyze trace data and visualize students' self-regulated learning strategies in a mastery-based online learning modules platform. The pedagogical design of the platform resulted in fewer event…

E-learning in higher education is exponentially increased during the past decade due to its inevitable benefits in critical situations like natural disasters, and pandemic. The reliable, fair, and seamless execution of online exams in…

The shortage of people trained in STEM fields is becoming acute, and universities and colleges are straining to satisfy this demand. In the case of computer science, for instance, the number of US students taking introductory courses has…

The integration of large language models (LLMs) into computing education offers many potential benefits to student learning, and several novel pedagogical approaches have been reported in the literature. However LLMs also present…

Reinforcement learning (RL) offers a compelling data-driven paradigm for synthesizing controllers for complex systems when accurate physical models are unavailable; however, most existing control-oriented RL methods assume stationarity and,…

Learning-enabled control systems have demonstrated impressive empirical performance on challenging control problems in robotics, but this performance comes at the cost of reduced transparency and lack of guarantees on the safety or…

The discipline of Software Engineering (SE) allows students to understand specific concepts or problems while designing software. Empowering students with the necessary knowledge and skills for the software industry is challenging for…