Tutoria com agentes inteligentes na educação online

Revista Teias. Vol. 20 (Edição Especial - 2019): Educação ativista na cibercultura: experiências pluraisA evolução tecnológica, particularmente a Inteligência Artificial, tem contribuído significativamente para mudanças relevantes em quase todas as dimensões da nossa sociedade, nomeadamente na Educação e, consequentemente, no Ensino à Distância. Tais mudanças exigem transformações significativas, especialmente no processo de ensino e aprendizagem, de forma a minimizar a incapacidade dos docentes e tutores responderem na totalidade às solicitações de suporte por parte dos alunos e, por isso, a enorme necessidade de potenciar as tecnologias existentes, com o objetivo de minorar essa dificuldade. Este artigo tem como objetivo caracterizar os agentes inteligentes e a sua importância pedagógica para a tutoria na educação online. A metodologia utilizada baseou-se no método dedutivo, resultante do processo de pesquisa bibliográfica e documental, em consonância com a investigação de doutoramento em curso sobre a temática dos tutores inteligentes. Como resultados, a literatura especializada tem destacado a enorme vantagem da utilização dos agentes inteligentes no ensino superior online.Technological evolution, particularly Artificial Intelligence, has contributed to changes in almost all dimensions of our society, in education and in Distance Learning. Such changes require significant transformations in the teaching and learning process in order to minimize the inability of Virtual Tutors to respond to students' requests for support and, therefore, the need to improve existing technologies, with the aim of reducing this difficulty. This article aims to characterize intelligent agents and their pedagogical importance for tutoring in online education. The methodology used was based on the deductive method, resulting from the bibliographic and documentary research process, in consonance with the ongoing doctoral research on the subject of virtual tutors. As a result, the literature has highlighted the enormous advantage of using intelligent agents in online higher education.La evolución tecnológica, particularmente la Inteligencia Artificial, ha contribuido a los cambios en casi todas las dimensiones de nuestra sociedad, en la educación y en la Enseñanza a Distancia. Estos cambios requieren transformaciones significativas en el proceso de enseñanza y aprendizaje para minimizar la incapacidad de los Tutores Virtuales para responder a las solicitudes de apoyo por parte de los alumnos y por lo tanto la necesidad de mejorar las tecnologías existentes con el objetivo de aliviar esa dificultad. Este artículo tiene como objetivo caracterizar a los agentes inteligentes y su importancia pedagógica para la tutoría en la educación online. La metodología utilizada fue basada en el método deductivo, resultante del proceso de investigación bibliográfica y documental, en consonancia con la investigación de doctorado en curso sobre la temática de los tutores virtuales. Como resultados, la literatura especializada ha destacado la enorme ventaja del uso de los agentes inteligentes en la enseñanza superior en línea.info:eu-repo/semantics/publishedVersio

Identifying divergent design thinking through the observable behavior of service design novices

© 2018, Springer Nature B.V. Design thinking holds the key to innovation processes, but is often difficult to detect because of its implicit nature. We undertook a study of novice designers engaged in team-based design exercises in order to explore the correlation between design thinking and designers’ physical (observable) behavior and to identify new, objective, design thinking identification methods. Our study addresses the topic by using data collection method of “think aloud” and data analysis method of “protocol analysis” along with the unconstrained concept generation environment. Collected data from the participants without service design experience were analyzed by open and selective coding. Through the research, we found correlations between physical activity and divergent thinking, and also identified physical behaviors that predict a designer’s transition to divergent thinking. We conclude that there are significant relations between designers’ design thinking and the behavioral features of their body and face. This approach opens possible new ways to undertake design process research and also design capability evaluation

Exploring the use of hand-to-face input for interacting with head-worn displays

International audienceWe propose the use of Hand-to-Face input, a method to interact with head-worn displays (HWDs) that involves contact with the face. We explore Hand-to-Face interaction to find suitable techniques for common mobile tasks. We evaluate this form of interaction with document navigation tasks and examine its social acceptability. In a first study, users identify the cheek and forehead as predominant areas for interaction and agree on gestures for tasks involving continuous input, such as document navigation. These results guide the design of several Hand-to-Face navigation techniques and reveal that gestures performed on the cheek are more efficient and less tiring than interactions directly on the HWD. Initial results on the social acceptability of Hand-to-Face input allow us to further refine our design choices, and reveal unforeseen results: some gestures are considered culturally inappropriate and gender plays a role in selection of specific Hand-to-Face interactions. From our overall results, we provide a set of guidelines for developing effective Hand-to-Face interaction techniques

Towards Hand-over-Face Gesture Detection

Facial microexpressions are immediately appearing reactions on the face that indicate various details about people's mental and emotional states. Their most important property is that their interpretation is identical or very similar for people all over the world. At present, their identification requires a psychologist expert. Thus automating this task would enable a broader application. The goal of this research is the detection of microexpressions using hybrid expert algorithms. Our algorithms mainly rely on landmark point detectors. Based on their output, several expert algorithms are utilized to extract key features and changes appearing on the face of a subject. These algorithms usually include several steps of image processing and time series analysis algorithms. In this paper, a component responsible for detecting hand gestures and hand pose is introduced. This component helps other algorithms to eliminate false positive detections by detecting the hands over the face. In addition, the recognizability of hand-over-face gestures is investigated. Finally, the implemented face occlusion detector method is evaluated on videos

Associating Facial Expressions and Upper-Body Gestures with Learning Tasks for Enhancing Intelligent Tutoring Systems

Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of learner’s nonverbal behaviors involving hand-over-face gestures, head and eye movements and emotions via facial expressions during learning. The proposed computer vision-based behavior monitoring method uses a low-cost webcam and can easily be integrated with modern tutoring technologies. We investigate these behaviors in-depth over time in a classroom session of 40 minutes involving reading and problem-solving exercises. The exercises in the sessions are divided into three categories: an easy, medium and difficult topic within the context of undergraduate computer science. We found that there is a significant increase in head and eye movements as time progresses, as well as with the increase of difficulty level. We demonstrated that there is a considerable occurrence of hand-over-face gestures (on average 21.35%) during the 40 minutes session and is unexplored in the education domain. We propose a novel deep learning approach for automatic detection of hand-over-face gestures in images with a classification accuracy of 86.87%. There is a prominent increase in hand-over-face gestures when the difficulty level of the given exercise increases. The hand-over-face gestures occur more frequently during problem-solving (easy 23.79%, medium 19.84% and difficult 30.46%) exercises in comparison to reading (easy 16.20%, medium 20.06% and difficult 20.18%)

Identifying divergent design thinking through the observable behavior of service design novices

Design thinking holds the key to innovation processes, but is often difficult to detect because of its implicit nature. We undertook a study of novice designers engaged in team-based design exercises in order to explore the correlation between design thinking and designers’ physical (observable) behavior and to identify new, objective, design thinking identification methods. Our study addresses the topic by using data collection method of “think aloud” and data analysis method of “protocol analysis” along with the unconstrained concept generation environment. Collected data from the participants without service design experience were analyzed by open and selective coding. Through the research, we found correlations between physical activity and divergent thinking, and also identified physical behaviors that predict a designer’s transition to divergent thinking. We conclude that there are significant relations between designers’ design thinking and the behavioral features of their body and face. This approach opens possible new ways to undertake design process research and also design capability evaluation

Creating sparks: comparing search results using discriminatory search term word co-occurrence to facilitate serendipity in the enterprise.

Categories or tags that appear in faceted search interfaces which are representative of an information item, rarely convey unexpected or non-obvious associated concepts buried within search results. No prior research has been identified which assesses the usefulness of discriminative search term word co-occurrence to generate facets to act as catalysts to facilitate insightful and serendipitous encounters during exploratory search. In this study, 53 scientists from two organisations interacted with semi-interactive stimuli, 74% expressing a large/moderate desire to use such techniques within their workplace. Preferences were shown for certain algorithms and colour coding. Insightful and serendipitous encounters were identified. These techniques appear to offer a significant improvement over existing approaches used within the study organisations, providing further evidence that insightful and serendipitous encounters can be facilitated in the search user interface. This research has implications for organisational learning, knowledge discovery and exploratory search interface design

Interaction Methods for Smart Glasses : A Survey

Since the launch of Google Glass in 2014, smart glasses have mainly been designed to support micro-interactions. The ultimate goal for them to become an augmented reality interface has not yet been attained due to an encumbrance of controls. Augmented reality involves superimposing interactive computer graphics images onto physical objects in the real world. This survey reviews current research issues in the area of human-computer interaction for smart glasses. The survey first studies the smart glasses available in the market and afterwards investigates the interaction methods proposed in the wide body of literature. The interaction methods can be classified into hand-held, touch, and touchless input. This paper mainly focuses on the touch and touchless input. Touch input can be further divided into on-device and on-body, while touchless input can be classified into hands-free and freehand. Next, we summarize the existing research efforts and trends, in which touch and touchless input are evaluated by a total of eight interaction goals. Finally, we discuss several key design challenges and the possibility of multi-modal input for smart glasses.Peer reviewe