Educational chatbots (EC) have shown their promise in providing instructional support. However, limited studies directly explored the impact of EC on learners' emotional responses. This study investigated the induced emotions from interacting with micro-learning EC and how they impact learning motivation. In this context, the EC interactions…

Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenges for using such tools in college classrooms. To address this, an adaptable assignment called the…

In the field of education, ChatGPT has become a topic of debate for its usefulness as a learning tool. This article focuses on non-science majors' (n = 29) perceptions of a ChatGPT enabled final exam, where, prior to the exam, students wrote papers on science and sustainability and, during the final exam, students were asked to compare their paper…

Student performance on open-response calculations involving acid and base solutions before and after instruction in general chemistry and analytical chemistry courses was compared with the output from the artificial intelligence chatbot ChatGPT. Applying a theoretical model of expertise for problem solving that includes problem conceptualization,…

Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the…

This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…

In this paper we investigate how student disengagement relates to two performance metrics in a spoken dialog computer tutoring corpus, both when disengagement is measured through manual annotation by a trained human judge, and also when disengagement is measured through automatic annotation by the system based on a machine learning model. First,…

Pedagogical strategies are policies for a tutor to decide the next action when there are multiple actions available. When the content is controlled to be the same across experimental conditions, there has been little evidence that tutorial decisions have an impact on students' learning. In this paper, we applied Reinforcement Learning (RL) to…

It is often assumed that engaging in a one-on-one dialogue with a tutor is more effective than listening to a lecture or reading a text. Although earlier experiments have not always supported this hypothesis, this may be due in part to allowing the tutors to cover different content than the noninteractive instruction. In 7 experiments, we tested…

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…