Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…

This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key…

Efforts to utilize AI in education, and especially in language education, have their roots in the 60s with the appearance of the first rule-based systems. However, recent advances in Artificial Intelligence (AI) and more specifically the introduction of ChatGPT, have given a new perspective to language learning. The integration of AI, natural…

Intelligent computer-assisted language learning (ICALL) is a multidisciplinary area of research that combines natural language processing (NLP), intelligent tutoring system (ITS), second language acquisition (SLA), and foreign language teaching and learning (FLTL). Intelligent tutoring systems (ITS) are able to provide a personalized approach to…

The purpose of the study is to provide a literature review of the work done on sign language (SL) around the world and in Pakistan and to develop a translation tool of speech and text to Pakistan Sign Language (PSL) with bilingual subtitles. Information and communication technology and tools development for teaching and learning purposes improve…

Research on computer-supported collaborative learning has shown that students need support to benefit from collaborative activities. While classical collaboration scripts have been effective in providing such support, they have also been criticized for being coercive and not allowing students to self-regulate their learning. Adaptive collaboration…

Computers can help the range of ways learners build up their own perception. Students who collect data from the Internet can be self-directed and independent. They can select sources to study and the connections to follow. Relying on the bounds laid down by teachers, the students may be in full control of their subjects and their studies. Students…

This paper introduces Ontoolsearch, a new search system that can be employed by educators in order to find suitable tools for supporting collaborative learning settings. Current tool search facilities commonly allow simple keyword searches, limiting the accuracy of obtained results. In contrast, Ontoolsearch supports semantic querying of tool…

The role that affective states play in learning was investigated from the perspective of a constructivist learning framework. We observed six different affect states (frustration, boredom, flow, confusion, eureka and neutral) that potentially occur during the process of learning introductory computer literacy with AutoTutor, an intelligent…

CIRCSIM-Tutor is a computer tutor designed to carry out a natural language dialogue with a medical student. Its domain is the baroreceptor reflex, the part of the cardiovascular system that is responsible for maintaining a constant blood pressure. CIRCSIM-Tutor's interaction with students is modeled after the tutoring behavior of two experienced…