Chatbot

About: Chatbot is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 24372 citations. The topic is also known as: IM bot & AI chatbot.

Interacting with a conversational agent system for educational purposes in online courses

Abstract: Since distance education creates new opportunities for learners, the enrollment in online courses has been sharply increasing in higher education. However, the higher attrition rate is one of the more significant concerns in this field. Educational researchers have found that meaningful interactions play a significant role in learner persistence in online courses. Still, it is challenging for an individual instructor to promote learners' positive interaction experiences. The expectation of improved learners' interaction with conversational agent systems has received attention in the distance education field. Few conversational agent systems have been developed for educational purposes, and few systems are used in real online learning settings. This study aims at designing and developing a conversational agent system to promote the learner's meaningful interaction in online courses, and also exploring the feasibility of human interaction with the conversational agent system, or chatbot, in online courses in higher education. The primary findings of this study show that instant, content-related, and quality interactions between the learner and the conversational agent system is applicable to graduate-level online courses. Implications and future research are discussed.

Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time

Abstract: Crowd-powered conversational assistants have been shown to be more robust than automated systems, but do so at the cost of higher response latency and monetary costs. A promising direction is to combine the two approaches for high quality, low latency, and low cost solutions. In this paper, we introduce Evorus, a crowd-powered conversational assistant built to automate itself over time by (i) allowing new chatbots to be easily integrated to automate more scenarios, (ii) reusing prior crowd answers, and (iii) learning to automatically approve response candidates. Our 5-month-long deployment with 80 participants and 281 conversations shows that Evorus can automate itself without compromising conversation quality. Crowd-AI architectures have long been proposed as a way to reduce cost and latency for crowd-powered systems; Evorus demonstrates how automation can be introduced successfully in a deployed system. Its architecture allows future researchers to make further innovation on the underlying automated components in the context of a deployed open domain dialog system.

Chatbot for e-learning: A case of study

Abstract: Nowadays the use of Chatbots is very popular in a large scale of applications especially in systems that provide an intelligence support to the user. In fact, to speed up the assistance, in many cases, these systems are equipped with Chatbots that can interpret the user questions and provide the right answers, in a fast and correct way. This paper presents the realization of a prototype of a Chatbot in educational domain: it has been developed a system to provide support to university students on some courses. The initial purpose has focused on the design of the specific architecture, model to manage communication and furnish the right answers to the student. For this aim, it has been realized a system that can detect the questions and thanks to the use of natural language processing techniques and the ontologies of domain, gives the answers to student. Finally, after the implementation of the designed model, experimental campaign was conducted in order to demonstrate its enforceability and efficiency.

The Rise of the Conversational Interface: A New Kid on the Block?

Abstract: The conversational interface has become a hot topic in the past year or so, providing the primary means of interaction with chatbots, messaging apps, and virtual personal assistants. Major tech companies have been making huge investments in the supporting technologies of artificial intelligence, such as deep learning and natural language processing, with the aim of creating systems that will enable users of smartphones and other devices to obtain information and access services in a natural, conversational way. Yet the vision of the conversational interface is not new, and indeed there is a history of research in dialogue systems, voice user interfaces, embodied conversational agents, and chatbots that goes back more than fifty years. This chapter explores what has changed to make the conversational interface particularly relevant today, examines some key issues from earlier work that could inform the next generation of conversational systems, and highlights some challenges for future work.

Convey: Exploring the Use of a Context View for Chatbots

Abstract: Text messaging-based conversational systems, popularly called chatbots, have seen massive growth lately. Recent work on evaluating chatbots has found that there exists a mismatch between the chatbot's state of understanding (also called context) and the user's perception of the chatbot's understanding. Users found it difficult to use chatbots for complex tasks as the users were uncertain of the chatbots' intelligence level and contextual state. In this work, we propose Convey (CONtext View), a window added to the chatbot interface, displaying the conversational context and providing interactions with the context values. We conducted a usability evaluation of Convey with 16 participants. Participants preferred using chatbot with Convey and found it to be easier to use, less mentally demanding, faster, and more intuitive compared to a default chatbot without Convey. The paper concludes with a discussion of the design implications offered by Convey.