5,397 research outputs found
Ruffle&Riley: Towards the Automated Induction of Conversational Tutoring Systems
Conversational tutoring systems (CTSs) offer learning experiences driven by
natural language interaction. They are known to promote high levels of
cognitive engagement and benefit learning outcomes, particularly in reasoning
tasks. Nonetheless, the time and cost required to author CTS content is a major
obstacle to widespread adoption. In this paper, we introduce a novel type of
CTS that leverages the recent advances in large language models (LLMs) in two
ways: First, the system induces a tutoring script automatically from a lesson
text. Second, the system automates the script orchestration via two LLM-based
agents (Ruffle&Riley) with the roles of a student and a professor in a
learning-by-teaching format. The system allows a free-form conversation that
follows the ITS-typical inner and outer loop structure. In an initial
between-subject online user study (N = 100) comparing Ruffle&Riley to simpler
QA chatbots and reading activity, we found no significant differences in
post-test scores. Nonetheless, in the learning experience survey, Ruffle&Riley
users expressed higher ratings of understanding and remembering and further
perceived the offered support as more helpful and the conversation as coherent.
Our study provides insights for a new generation of scalable CTS technologies.Comment: NeurIPS'23 GAIED, Camera-read
Towards the Use of Dialog Systems to Facilitate Inclusive Education
Continuous advances in the development of information technologies have currently led to the possibility
of accessing learning contents from anywhere, at anytime, and almost instantaneously. However,
accessibility is not always the main objective in the design of educative applications, specifically to
facilitate their adoption by disabled people. Different technologies have recently emerged to foster the
accessibility of computers and new mobile devices, favoring a more natural communication between
the student and the developed educative systems. This chapter describes innovative uses of multimodal
dialog systems in education, with special emphasis in the advantages that they provide for creating
inclusive applications and learning activities
Conversational Agents in Education â A Systematic Literature Review
Conversational Agents (CAs) are widely spread in a variety of domains, such as health and customer service. There is a recent trend of increasing publications and implementations of CAs in education. We conduct a systematic literature review to identify common methodologies, pedagogical CA roles, addressed target groups, the technologies and theories behind, as well as human-like design aspects. The initially found 3329 records were systematically reduced to 252 fully coded articles. Based on the analysis of the codings, we derive further research streams. Our results reveal a research gap for long-term studies on the use of CAs in education, and there is insufficient holistic design knowledge for pedagogical CAs. Moreover, target groups other than academic students are rarely considered. We condense our findings in a morphological box and conclude that pedagogical CAs have not yet reached their full potential of long-term practical application in education
Wide-Scale Automatic Analysis of 20 Years of ITS Research
The analysis of literature within a research domain can provide significant
value during preliminary research. While literature reviews may provide an
in-depth understanding of current studies within an area, they are limited by the
number of studies which they take into account. Importantly, whilst publications
in hot areas abound, it is not feasible for an individual or team to analyse a large
volume of publications within a reasonable amount of time. Additionally, major
publications which have gained a large number of citations are more likely to be
included in a review, with recent or fringe publications receiving less inclusion.
We provide thus an automatic methodology for the large-scale analysis of literature
within the Intelligent Tutoring Systems (ITS) domain, with the aim of identifying
trends and areas of research from a corpus of publications which is significantly
larger than is typically presented in conventional literature reviews. We
illustrate this by a novel analysis of 20 years of ITS research. The resulting analysis
indicates a significant shift of the status quo of research in recent years with
the advent of novel neural network architectures and the introduction of MOOCs
NLP-based personal learning assistant for school education
Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational systems and learning processes across the world are on the cusp of a major digital transformation. This paper seeks to explore the concept of an artificial intelligence and natural language processing (NLP) based intelligent tutoring system (ITS) in the context of computer education in primary and secondary schools. One of the components of an ITS is a learning assistant, which can enable students to seek assistance as and when they need, wherever they are. As part of this research, a pilot prototype chatbot was developed, to serve as a learning assistant for the subject Scratch (Scratch is a graphical utility used to teach school children the concepts of programming). By the use of an open source natural language understanding (NLU) or NLP library, and a slackbased UI, student queries were input to the chatbot, to get the sought explanation as the answer. Through a two-stage testing process, the chatbotâs NLP extraction and information retrieval performance were evaluated. The testing results showed that the ontology modelling for such a learning assistant was done relatively accurately, and shows its potential to be pursued as a cloud-based solution in future
Adapting Progress Feedback and Emotional Support to Learner Personality
Peer reviewedPostprin
The use of animated agents in eâlearning environments: an exploratory, interpretive case study
There is increasing interest in the use of animated agents in eâlearning environments. However, empirical investigations of their use in online education are limited. Our aim is to provide an empirically based framework for the development and evaluation of animated agents in eâlearning environments. Findings suggest a number of challenges, including the multiple dialogue models that animated agents will need to accommodate, the diverse range of roles that pedagogical animated agents can usefully support, the dichotomous relationship that emerges between these roles and that of the lecturer, and student perception of the degree of autonomy that can be afforded to animated agents
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