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.

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

Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up conversational agent (chatbot) artificially. There are developed a lot of works to make conversational agent. But low cost, configuration and availability make possible to use it in various applications. In this paper, we give a brief review of some applications which are used AIML chatbot for their conversational service. These applications are related to cultural heritage, e-learning, e-government, web base model, dialog model, semantic analysis framework, interaction framework, humorist expert, network management, adaptive modular architecture as well. In this case, they are not only providing useful services but also interact with customers and give solution of their problems through AIML chatbot instead of human beings. So, this is popular day by day with entrepreneur and users to provide efficient service.

Review of integrated applications with AIML based chatbot

Recently, technology has become more attractive for industry by paving the way to new applications, which go well beyond traditional sensor applications. These applications can be classified in different categories: monitoring, alerting, healthcare assistance, and actuating, among others. A Wireless Sensor Network (WSN) is feasible for the heritage scenarios protection and for monitoring because its specificity, autonomy, self-configurability, lasting lifetime, and mobility. However, their services, protocols, and architectures have constraints to support new issues for monitoring cultural assets: geographical dispersion, insufficient resources, and not enough staff to protect all the monuments and to provide tourist information broadcasting. We propose a modular system. It consists of three elements: a WSN, a “Central System,” and a novel platform named “Local Node Gateway.” It allows the coexistence of different wireless technologies in order to provide actuation, processing and communication functionalities. This proposal takes a new approach to solve these heritage-monitoring problems.

Wireless Sensor Networks for Conservation and Monitoring Cultural Assets

In this paper, we focus on the personalized response generation for conversational systems. Based on the sequence to sequence learning, especially the encoder-decoder framework, we propose a two-phase approach, namely initialization then adaptation, to model the responding style of human and then generate personalized responses. For evaluation, we propose a novel human aided method to evaluate the performance of the personalized response generation models by online real-time conversation and offline human judgement. Moreover, the lexical divergence of the responses generated by the 5 personalized models indicates that the proposed two-phase approach achieves good results on modeling the responding style of human and generating personalized responses for the conversational systems.

Neural Personalized Response Generation as Domain Adaptation

In this work we propose an interpretation of the LSA framework which leads to a data-driven “conceptual” space creation suitable for an “intuitive” conversational agent.

The proposed approach allows overcoming the limitations of traditional, rule-based, chat-bots, leading to a more natural dialogue.

A conversational agent based on a conceptual interpretation of a data driven semantic space

A conversational agent, capable to have a ldquosense of humourrdquo is presented. The agent can both generate humorous sentences and recognize humoristic expressions introduced by the user during the dialogue. Humorist Bot makes use of well founded techniques of computational humor and it has been implemented using the ALICE framework embedded into an Yahoo! Messenger client. It includes also an avatar that changes the face expression according to humoristic content of the dialogue.

Humorist Bot: Bringing Computational Humour in a Chat-Bot System

The use of a PDA with ad-hoc built-in information retrieval and auto-localization functionalities can help people in visiting a museum in a natural manner instead of traditional audio/visual pre-recorded guides. The goal of this paper is to build an user-friendly virtual-guide system adaptable to the user needs of mobility and therefore usable on different mobile devices (e.g. PDAs, Smartphones). An information retrieval service is included which is easily accessible through a spoken language interaction or an auto-localization service. The system takes the advantages of Chatbot, speech recognition technologies and RFID detection, allowing a natural interaction with the user.

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MAGA: A Mobile Archaeological Guide at Agrigento

LSA for Intuitive Chat-Agents Tutoring System

The proposed work illustrates how "primitive concepts" can be automatically induced from a text corpus. The primitive concepts are identified by the orthonormal axis of a "conceptual" space induced by a methodology inspired tothe latent semantic analysis approach. The methodology represents a natural language sentence by means of a set of rotations of an orthonormal basis in the "conceptual"space. The rotations, triggered by the sequence of words composing the sentence and realized by means of geometric algebra rotors, allow to highlight "conceptual" relations that can arise among the primitive concepts.

Sentence Induced Transformations in "Conceptual" Spaces

The availability of versatile and interconnected embedded devices makes it possible to build low-cost networks with a large number of nodes running even complex applications and protocols in a distributed manner. Common tools used for modeling and verification, such as simulators, present some limitations as application correctness is checked off-board and only focuses on source code. Execution in the real network is thus excluded from the early stages of design and verification. In this paper, a system for modeling and verification of symbolic distributed protocols running on embedded devices is introduced. The underlying methodology is rooted in a symbolic programming paradigm that makes it possible to model protocols with a high level of abstraction still permitting their execution on resource-constrained devices. The preliminary experimental results shown in this paper concern verification of a distributed averaging protocol in a simulated network at increasing number of nodes. The results support the feasibility of the approach to test distributed applications running on large networks of resource- constrained nodes.

A. Augello

Papers

Humorist Bot: Bringing Computational Humour in a Chat-Bot System

MAGA: A Mobile Archaeological Guide at Agrigento

LSA for Intuitive Chat-Agents Tutoring System

Sentence Induced Transformations in "Conceptual" Spaces

Verification of Symbolic Distributed Protocols for Networked Embedded Devices