Intelligent Pedagogical Agents in Immersive Virtual Learning Environments: A Review

The concept of Intelligent Pedagogical Agents (IPA) has been an important research topic for a long time. IPA is supported by multi-agent systems research derived from AI. IPA provides personalized instruction, increase learner motivation, and act pedagogically on behalf or with the learner. On the other hand, virtual environments add value to the education process by giving new educational possibilities and computational-richness support. Combining both IPA and Virtual environments can make a promising approach for effective computer-aided learning. This paper provides a review on IPA and related topics focusing on a general overview of the topic, gives a detailed review in the application domain of virtual learning environments, and outlines a proposal for a flexible conceptual approach for the flexible application in different learning settings

DESIGNING CHATBOTS FOR HIGHER EDUCATION PRACTICE

In this research–in–progress paper, we employ design science research to articulate design knowledge for chatbots in higher education practice. We conducted a literature review to factor previous research into the design process. In addition, we performed a content analysis of student e-mails and forum posts from four instances of a basic Java programming course. Drawing from literature and data, we present a conceptual architecture for chatbots in higher education, discuss its rationale, and provide a proof-of-concept implementation. We conclude with a discussion including tentative design recommendations and a plan for continued research

Towards a Neural Era in Dialogue Management for Collaboration: A Literature Survey

Dialogue-based human-AI collaboration can revolutionize collaborative problem-solving, creative exploration, and social support. To realize this goal, the development of automated agents proficient in skills such as negotiating, following instructions, establishing common ground, and progressing shared tasks is essential. This survey begins by reviewing the evolution of dialogue management paradigms in collaborative dialogue systems, from traditional handcrafted and information-state based methods to AI planning-inspired approaches. It then shifts focus to contemporary data-driven dialogue management techniques, which seek to transfer deep learning successes from form-filling and open-domain settings to collaborative contexts. The paper proceeds to analyze a selected set of recent works that apply neural approaches to collaborative dialogue management, spotlighting prevailing trends in the field. This survey hopes to provide foundational background for future advancements in collaborative dialogue management, particularly as the dialogue systems community continues to embrace the potential of large language models

MVP: Multi-task Supervised Pre-training for Natural Language Generation

Pre-trained language models (PLMs) have achieved remarkable success in natural language generation (NLG) tasks. Up to now, most NLG-oriented PLMs are pre-trained in an unsupervised manner using the large-scale general corpus. In the meanwhile, an increasing number of models pre-trained with labeled data (i.e. "supervised pre-training") showcase superior performance compared to unsupervised pre-trained models. Motivated by the success of supervised pre-training, we propose Multi-task superVised Pre-training (MVP) for natural language generation. We collect a large-scale natural language generation corpus, MVPCorpus, from $77$ datasets over $11$ diverse NLG tasks. Then we unify these examples into a general text-to-text format to pre-train the text generation model MVP in a supervised manner. For each task, we further pre-train specific soft prompts to stimulate the model's capacity to perform a specific task. Our MVP model can be seen as a practice that utilizes recent instruction tuning on relatively small PLMs. Extensive experiments have demonstrated the effectiveness and generality of our MVP model in a number of NLG tasks, which achieves state-of-the-art performance on $13$ out of $17$ datasets, outperforming BART by $9.3\%$ and Flan-T5 by $5.8\%$.Comment: Accepted by ACL 202

Supportive technologies for group discussion in MOOCs

A key hurdle that prevents MOOCs from reaching their transformative potential in terms of making valuable learning experiences available to the masses is providing support for students to make use of the resources they can provide for each other. This paper lays the foundation for meeting this challenge by beginning with a case study and computational modeling of social interaction data. The analysis yields new knowledge that informs design and development of novel, real-time support for building healthy learning communities that foster a high level of engagement and learning. We conclude by suggesting specific areas for potential impact of new technology

A Computational Theory of the Use-Mention Distinction in Natural Language

To understand the language we use, we sometimes must turn language on itself, and we do this through an understanding of the use-mention distinction. In particular, we are able to recognize mentioned language: that is, tokens (e.g., words, phrases, sentences, letters, symbols, sounds) produced to draw attention to linguistic properties that they possess. Evidence suggests that humans frequently employ the use-mention distinction, and we would be severely handicapped without it; mentioned language frequently occurs for the introduction of new words, attribution of statements, explanation of meaning, and assignment of names. Moreover, just as we benefit from mutual recognition of the use-mention distinction, the potential exists for us to benefit from language technologies that recognize it as well. With a better understanding of the use-mention distinction, applications can be built to extract valuable information from mentioned language, leading to better language learning materials, precise dictionary building tools, and highly adaptive computer dialogue systems. This dissertation presents the first computational study of how the use-mention distinction occurs in natural language, with a focus on occurrences of mentioned language. Three specific contributions are made. The first is a framework for identifying and analyzing instances of mentioned language, in an effort to reconcile elements of previous theoretical work for practical use. Definitions for mentioned language, metalanguage, and quotation have been formulated, and a procedural rubric has been constructed for labeling instances of mentioned language. The second is a sequence of three labeled corpora of mentioned language, containing delineated instances of the phenomenon. The corpora illustrate the variety of mentioned language, and they enable analysis of how the phenomenon relates to sentence structure. Using these corpora, inter-annotator agreement studies have quantified the concurrence of human readers in labeling the phenomenon. The third contribution is a method for identifying common forms of mentioned language in text, using patterns in metalanguage and sentence structure. Although the full breadth of the phenomenon is likely to elude computational tools for the foreseeable future, some specific, common rules for detecting and delineating mentioned language have been shown to perform well

Implementing intelligent pedagogical agents in virtual worlds: Tutoring natural science experiments in OpenWonderland

Intelligent Pedagogical Agents (IPAs) can be thought of as embodied intelligent agents that are designed for pedagogical purposes to support learning. They can be designed in particular for virtual worlds. Virtual worlds are becoming an interesting medium for engineering education for the properties of visual collaboration abilities providing authentic learning experiences and for the opportunity of providing active learning. However, virtual worlds need more educational support to be more inhabited with increased learning services. Incorporating intelligent pedagogical agents into virtual worlds adds such learning support by adding intelligence, improving believability, and the opportunity to increase communication with an artificial educator. However the implementation of intelligent pedagogical agents and adopting them in a virtual world require several efforts with different aspects of implementation. This paper reports our first prototype implementation of an IPA interacting with a learner and a learning object in natural science experiment in a virtual world while providing supporting multi-modal communication abilities. The IPA has features of text chat based on the Artificial Intelligence Markup Language (AIML), a text-to-speech synthesis function, and non-verbal communication abilities through gesture animation. The implementation is presented through explained scenarios of the IPA tutoring an experiment or monitoring a learner avatar interaction with a learning object in a Virtual World. The IPA & the learning scenarios are implemented in the open source of Open Wonderland

The language of tourism on the Web: an analysis of Tripadvisor reviews

The web has transformed every aspect of our social, political and cultural life and it has also changed the tourism industry and its communication. This dissertation aims to analyse the evolution of tourism text genres, from the traditional guidebook to the travel digital text, with a focus on a particular area of the language of tourism, that of online travel communities. Through the analysis of online reviews on TripAdvisor this research poses a number of significant questions for linguistic research: - To what extent online travel reviews could be considered as a part of the tourism discourse? - What features to online travel reviews share with other genres of tourism discourse? - Could we consider this particular area of tourism as a specific language, which relies on a set of standard and conventions? - What are these? - Which lexical features do tourists use mist to demonstrate satisfaction in online context? - Which lexico-grammatical features do tourists use more to demonstrate satisfaction in online context? Using a corpus-assisted approach, this study attempts to investigate the most common lexical and lexico-grammatical features used by tourists in the English language to describe their experiences about cultural attractions in Italy and to express their positive impressions. The work is carried out through the analysis of some reviews extracted from the website TripAdvisor, related to the main cultural sites of the city of Padua in Italy

Lilly Endowment Annual Report 2015

During 2015, the Endowment paid grants totaling $435.5 million. Community development grants accounted for$200.4 million (46 percent), religion grants accounted for $124.1 million (29 percent) and education grants accounted for$111.0 million (25 percent). Most grants were paid to organizations in Indiana - a total of $257.8 million (59 percent). Of the payment total of$435.5 million, $107.9 million (25 percent) was paid to nonMarion County grantees in Indiana and$149.9 million (34 percent) to Marion County (Indianapolis) grantees. Organizations outside of Indiana received $177.7 million (41 percent). Most of these grants paid outside of Indiana were religion grants.The annual report includes a complete list of 2015 grants