相关论文: Handling Students Dropouts in an LLM-driven Intera…

Prompt engineering is critical for effective interaction with large language models (LLMs) such as ChatGPT. However, efforts to teach this skill to students have been limited. This study designed and implemented a prompt engineering…

Large language models (LLMs) are revolutionizing education, with LLM-based agents playing a key role in simulating student behavior. A major challenge in student simulation is modeling the diverse learning patterns of students at various…

Providing timely, consistent, and high-quality feedback in large-scale higher education courses remains a persistent challenge, often constrained by instructor workload and resource limitations. This study presents an LLM-powered, agentic…

Large language models (LLMs) have demonstrated the ability to generate formative feedback and instructional hints in English, making them increasingly relevant for AI-assisted education. However, their ability to provide effective…

While Large Language Models (LLMs) are often used as virtual tutors in computer science (CS) education, this approach can foster passive learning and over-reliance. This paper presents a novel pedagogical paradigm that inverts this model:…

Massive Open Online Courseware (MOOCs) appeared in 2008 and grew considerably in the past decade, now reaching millions of students and professionals all over the world. MOOCs do not replace other educational forms. Instead, they complement…

Artificial Intelligence (AI), especially cloud platforms and large language models (LLMs), is changing how engineering is taught by making learning more interactive and flexible. However, in electrical engineering and energy systems,…

The use of Large Language Models (LLMs) as automatic judges for code evaluation is becoming increasingly prevalent in academic environments. But their reliability can be compromised by students who may employ adversarial prompting…

As autonomous agents powered by large language models (LLMs) continue to demonstrate potential across various assistive tasks, ensuring their safe and reliable behavior is crucial for preventing unintended consequences. In this work, we…

Providing timely and personalized feedback to large numbers of students is a long-standing challenge in programming courses. Relying on human teaching assistants (TAs) has been extensively studied, revealing a number of potential…

This research is comparing learning environments to students dropout intentions. While using statistics I looked at data and the correlations between two articles to see how the two studies looked side to side. Learning environments and…

Diagnosing student problem behaviors requires teachers to synthesize multifaceted information, identify behavioral categories, and plan intervention strategies. Although fine-tuned large language models (LLMs) can support this process…

Generative Artificial Intelligence (GAI) can be seen as a double-edged weapon in education. Indeed, it may provide personalized, interactive and empowering pedagogical sequences that could favor students' intrinsic motivation, active…

Most AI-based educational tools today adopt a one-on-one tutoring paradigm, pairing a single LLM with a single learner. Yet decades of learning science research suggest that multi-party interaction -- through peer modeling, co-construction,…

Rapidly evolving cyberattacks demand incident response systems that can autonomously learn and adapt to changing threats. Prior work has extensively explored the reinforcement learning approach, which involves learning response strategies…

The advent of Large Language Models (LLMs) and Artificial Intelligence (AI) tools has revolutionized various facets of our lives, particularly in the realm of social media. For students, these advancements have unlocked unprecedented…

Massive Open Online Courses (MOOCs) offer a new scalable paradigm for e-learning by providing students with global exposure and opportunities for connecting and interacting with millions of people all around the world. Very often, students…

The ability of Large Language Models (LLMs) to extract context from natural language problem descriptions naturally raises questions about their suitability in autonomous decision-making settings. This paper studies the behaviour of these…

High dropout rates in engineering programmes are conventionally attributed to student deficits: lack of academic preparation or motivation. However, this view neglects the causal role of "normative friction": the complex system of…

An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussion, to potentially better engage students than standard…