This report examines the burgeoning generative artificial intelligence (GenAI) and foundation models landscape within the European Union, and analyses its impact, technological advancements, and regulatory implications. It details the GenAI value chain, identifying key players and investment trends, revealing a significant US dominance. The report…

This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain…

Artificial Intelligence (AI) is developing in a manner that blurs the boundaries between specific areas of application and expands its capability to be used in a wide range of applications. The public release of ChatGPT, a generative AI chatbot powered by a large language model (LLM), represents a significant step forward in this direction.…

Recent advances in Artificial Intelligence (AI) have paved the way for the integration of text-based and voice-enabled chatbots as adaptive virtual tutors in education. Despite the increasing use of AI-powered chatbots in language learning, there is a lack of studies exploring the attitudes and perceptions of teachers and students towards these…

Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…

Natural Language Generation (NLG) is the process of generating natural language text from an input, which is a communicative goal and a database or knowledge base. Informally, the architecture of a standard NLG system consists of the following modules (Reiter and Dale, 2000): content determination, sentence planning (or microplanning) and surface…

This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we…

The tremendous effectiveness of intelligent tutoring systems is due in large part to their interactivity. However, when learners are free to choose the extent to which they interact with a tutoring system, not all learners do so actively. This paper examines a study with a natural language tutorial dialogue system for computer science, in which…

In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose a principled framework that allows one to effectively incorporate knowledge into statistical machine learning models for…

While many studies have demonstrated that conversational tutoring systems have a positive effect on learning, the amount of manual effort required to author, design, and tune dialogue behaviors remains a major barrier to widespread deployment and adoption of these systems. Such dialogue systems must not only understand student speech, but must…

Presents principles of dialog cooperativity derived from a corpus of task-oriented spoken human-machine dialog. Analyzes the "corpus" to produce a set of dialog design principles intended to prevent users from having to initiate clarification and repair metacommunication that the system would not understand. Proposes a "more…

Describes a graphic modeling, natural language processing system, VerbalImage, which mimics features of human shape reasoning. Subjects read the same text description and were able to recognize the image generated by the computer from among a series of other computer-generated images. Performance on task was as good as for a control group…

This paper explores languages for communicating precise ideas within limited domains, which include mathematical notation and general purpose and high level computer programming languages. Low-level properties of such natural artificial languages are discussed, with emphasis on those in which names are chosen for concepts and symbols are chosen…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

In order to build robust natural language processing systems that can detect and recover from miscommunication, the investigation of how people communicate and how they recover from problems in communication described in this artificial intelligence report focused on reference problems which a listener may have in determining what or whom a…