A Framework for Building Emotional-Motivational Agents as Intelligent Tutoring Entities

2008 ◽  
pp. 168-184
Author(s):  
Bogdan-Florin Marin ◽  
Axel Hunger

This chapter presents our efforts to integrate role theory and agent technology in order to support collaborative work/learning processes between users spatially distributed within a synchronous collaborative virtual environment. Our work aims to overcome a major inconvenience in distance education systems: tutors’ difficulties when following up a distance collaborative learning process and in particular those students who cannot keep up progress with their team-mates. Our approach embraces the learning paradigms mentioned above and the work on pedagogical and intelligent agents as a mechanism for modelling and analyzing student-tutor interactions.

Author(s):  
Adriana Peña Pérez Negrón ◽  

Current virtual environments are predominantly visual-spatial, which allows their ‘inhabitants’ the display, either in a conscious or unconscious way, of nonverbal cues during interaction, such as gaze direction, deictic gestures or location. This interchange of nonverbal messages enriches interaction while supports mutual comprehension, fundamental for collaborative work and therefore particularly important in a multiuser virtual environment, that is, a Collaborative Virtual Environment. Different techniques, the media involvement, and automatic detection related collaborative nonverbal interaction are here discussed.


Author(s):  
Thanh-Hai Trinh ◽  
Cédric Buche ◽  
Ronan Querrec ◽  
Jacques Tisseau

This study focuses on the notion of erroneous actions realized by human learners in Virtual Environments for Training. Our principal objective is to develop an Intelligent Tutoring System (ITS) suggesting pedagogical assistances to the human teacher. For that, the ITS must obviously detect and classify erroneous actions produced by learners during the realization of procedural and collaborative work. Further, in order to better support human teacher and facilitate his comprehension, it is necessary to show the teacher why learner made an error. Addressing this issue, we firstly modeling the Cognitive Reliability and Error Analysis Method (CREAM). Then, we integrate the retrospective analysis mechanism of CREAM into our existing ITS, thus enable the system to indicate the path of probable cause-effect explaining reasons why errors have occurred.


2021 ◽  
Vol 13 (9) ◽  
pp. 4892
Author(s):  
Sandra Stefanovic ◽  
Elena Klochkova

This manuscript aims to present possibilities for developing mobile and smart platforms and systems in teaching and learning the English language for engineering professionals in different engineering study programs. Foreign language teaching and learning processes are based on traditional methods, while in engineering and technical sciences, teaching and learning processes include different digital platforms. Therefore, the following hypotheses were stated. (H1) It is possible to develop a software solution for mobile platforms that can have a higher level of interactivity, and it may lead to better learning outcomes, especially in the field of adopting engineering vocabulary. (H2) Implementation of the developed solution increases motivation for learning and leads to a higher level of satisfaction with the learning process as a part of the quality of life. (H3) Students who have digital and mobile platforms in the learning process could have higher achievement values. This manuscript presents software application development and its implementation in teaching English as a foreign language for engineering and technical study programs on the bachelor level. Initial results in implementation and satisfaction of end users point to the justification of implementing such solutions.


Author(s):  
S. Sadasivan ◽  
R. Rele ◽  
J. S. Greenstein ◽  
A. K. Gramopadhye ◽  
J. Masters ◽  
...  

The human inspector performing visual inspection of an aircraft is the backbone of the aircraft inspection process, a vital element in assuring safety and reliability of an air transportation system. Training is an effective strategy for improving their inspection performance. A drawback of present-day on-the-job (OJT) training provided to aircraft inspectors is the limited exposure to different defect types. Previous studies have shown offline feedback training using virtual reality (VR) simulators to be effective in improving visual inspection performance. This research aims at combining the advantages of VR technology that includes exposure to a wide variety of defects and the one-on-one tutoring approach of OJT by implementing a collaborative virtual training environment. In an immersive collaborative virtual environment (CVE), avatars are used to represent the co-participants. In a CVE, information of where the trainer is pointing can be provided to a trainee as visual deictic reference (VDR). This study evaluates the effectiveness of simulating on-the-job training in a CVE for aircraft inspection training, providing VDR slaved to a 3D mouse used by the trainer for pointing. The results of this study show that the training was effective in improving inspection performance.


2019 ◽  
Vol 14 (1) ◽  
pp. 91-114 ◽  
Author(s):  
Ju Liu

Purpose The purpose of this paper is to contextually theorise the different patterns of emerging multinational companies’ (EMNCs’) learning processes for innovation and the different influences of their technology-driven FDIs (TFDIs) on the processes. Design/methodology/approach A comparative case study method and process tracing technique are employed to investigate how and why firms’ learning processes for innovation took place, how and why the TFDIs emerged and influenced the firms’ learning processes in different ways. Findings The paper identifies two different patterns of learning process for innovation (Glider model vs Helicopter model) and two different roles of the case firms’ TFDIs (accelerator vs starter) in the different contexts of their learning processes. It is found that the capability building of the domestic wind energy industry has an important influence on the case of EMNCs’ learning processes and thus on the roles of their TFDIs. Research limitations/implications The limitation of the paper lies in its small number of cases in a specific industry of a specific country. The two contextually identified learning models and roles of TFDIs may not be applied to other industries or other countries. Future research should investigate more cases in broader sectoral and geographic scope to test the models and also to identify new models. Practical implications For EMNCs, who wants to use the Helicopter model to rapidly gain production and innovation capability, cross-cultural management and integration management are crucial to practitioners. For emerging countries with ambitions to explore the global knowledge and technology pool, besides of the EMNC’s capability building, the capability building in the domestic industries should not be overlooked by policy makers. Originality/value The paper develops a dynamic and contextual analytical framework which helps to answer the important questions about how and under what context a TFDI emerges and influences firm’s learning process for innovation. It theorises the EMNCs’ learning process and TFDIs in the context of the development of the domestic industry. It strengthens the explanatory power of the learning-based view and adds new knowledge to the current FSA/CSA discourse in the international business literature.


2012 ◽  
Vol 241-244 ◽  
pp. 3116-3120
Author(s):  
Xiao Mei Hu ◽  
Biao Wang

Collaborative Virtual Environment (CVE) system supports a large number of users to explore a virtual world and interact with each other through networks, so one of the key issues in the design of scalable CVE systems is the partitioning problem. Existing partitioning algorithms in CVE systems based on multiple-server architecture, in our opinion, hardly consider the communication character of virtual environment. In this paper, we propose a new partitioning method based on area of interest (AOI) model matching to improve the quality of partitioning. The experimental results show preliminarily that our partitioning approach based on AOI model matching does decrease the traffic among the servers in the system and improve the partitioning performance.


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