Multiple Viewpoints for Tutoring Systems.

This thesis investigates the issue of how a tutoring system, intelligent or otherwise, may be designed to utilise multiple viewpoints on the domain being tutored, and what benefits may accrue from this. The issue was relevant to earlier systems, such as WHY (Stevens et al. 1979) and STEAMER (Hollan et al. 1984). The relevant literature is reviewed, and criteria which must be met by our implementation of viewpoints are established. Viewpoints are conceptualised as pre-defined structures which can be represented in a tutoring system with the potential to increase its effectiveness and adaptability. A formalism is proposed where inferences are drawn from a model by a range of operators. The application of this combination to problems and goals is to be described heuristically. This formulation is then related to the educational philosophy of Cognitive Apprenticeship. The formalism is tested and refined in a protocol analysis study which leads to the definition of three classes of operators. The viewpoint structure is used to produce a detailed formulation of the domain of Prolog debugging for novices, with the goal that students should learn how different bugs may be localised using different viewpoints. Three models of execution are defined, based on those described by Bundy et al. (1985). These are mapped onto a restricted catalogue of bugs by specifying a number of conventions which produce a simplified and consistent domain suited to the needs of novices. VIPER, a tutoring system which can itself accomplish and explain the relevant domain tasks, is described. VIPER is based on a meta-interpreter which produces detailed execution histories which are then analysed. An evaluation of VIPER is reported, with generally favourable results. VIPER is discussed in relation to the research goals, the usefulness of Cognitive Apprenticeship in supporting such a design, and possible future work. This discussion exemplifies the use of established student modeling techniques, the implementation of other viewpoints on Prolog, and the application of the design strategy to other domains. Claims are made in relation to the formulation of viewpoints, the architecture of VIPER, and the relevance of Cognitive Apprenticeship to the use of multiple viewpoints

Fostering reflection in the training of speech-receptive action

Dieser Aufsatz erörtert Möglichkeiten und Probleme der Förderung kommunikativer Fertigkeiten durch die Unterstützung der Reflexion eigenen sprachrezeptiven Handelns und des Einsatzes von computerunterstützten Lernumgebungen für dessen Förderung. Kommunikationstrainings widmen sich meistens der Förderung des beobachtbaren sprachproduktiven Handelns (Sprechen). Die individuellen kognitiven Prozesse, die dem sprachrezeptiven Handeln (Hören und Verstehen) zugrunde liegen, werden häufig vernachlässigt. Dies wird dadurch begründet, dass sprachrezeptives Handeln in einer kommunikativen Situation nur schwer zugänglich und die Förderung der individuellen Prozesse sprachrezeptiven Handelns sehr zeitaufwändig ist. Das zentrale Lernprinzip - die Reflexion des eigenen sprachlich-kommunikativen Handelns - wird aus verschiedenen Perspektiven diskutiert. Vor dem Hintergrund der Reflexionsmodelle wird die computerunterstützte Lernumgebung CaiMan© vorgestellt und beschrieben. Daran anschließend werden sieben Erfolgsfaktoren aus der empirischen Forschung zur Lernumgebung CaiMan© abgeleitet. Der Artikel endet mit der Vorstellung von zwei empirischen Studien, die Möglichkeiten der Reflexionsunterstützung untersucheThis article discusses the training of communicative skills by fostering the reflection of speech-receptive action and the opportunities for using software for this purpose. Most frameworks for the training of communicative behavior focus on fostering the observable speech-productive action (i.e. speaking); the individual cognitive processes underlying speech-receptive action (hearing and understanding utterances) are often neglected. Computer-supported learning environments employed as cognitive tools can help to foster speech-receptive action. Seven success factors for the integration of software into the training of soft skills have been derived from empirical research. The computer-supported learning environment CaiMan© based on these ideas is presented. One central learning principle in this learning environment reflection of one's own action will be discussed from different perspectives. The article concludes with two empirical studies examining opportunities to foster reflecti

El uso del chatbot como elemento de acción tutorial en la enseñanza universitaria

Abstract: It is of great importance to help and pay attention to students through different educational activities to ensure their participation in class and thus reduce the dropout rate. Traditionally, tutoring activities have been limited to face-to-face sessions in which students pose questions to the teacher. However, in a connected world with many available information systems, innovative tools are needed to facilitate and speed up both the study and the resolution of doubts in a comfortable way. Methods: This paper proposes using a chatbot based tutoring system as a novel educational experience focused on motivating universities students. Results: Besides, we provide a proof-of-concept implementation of a chatbot that answers questions as quickly and accurately possible at any time, in a comfortable way for the students, and at the same time it gathers feedback from the students regarding those topics that need to be explained in class in more detail. Conclusions: This experience is intended to increase the engagement and collaboration of both students and instructors and has helped to decrease the dropout rate in recent years.Resumen: Es de vital importancia ayudar y guiar el aprendizaje de los estudiantes a través de diferentes herramientas y actividades educativas que faciliten su participación en clase y permitan reducir la tasa de abandono. Tradicionalmente, las actividades de tutorización para estudiantes universitarios, se limita a reuniones presenciales en las que los estudiantes plantean preguntas al docente. Sin embargo, dadas las circunstancias actuales y ante un mundo conectado con muchos sistemas de información disponibles, se necesitan herramientas docentes innovadoras que faciliten el aprendizaje y una ágil resolución de dudas. Método: en este trabajo se propone la utilización de un sistema de tutorías, basado en el uso de un chatbot como experiencia educativa novedosa y orientada a motivar y facilitar el aprendizaje en estudiantes universitarios. Resultados: estudio aporta la implementación de un chatbot que responde de forma rápida y precisa, disponible en cualquier momento para solucionar dudas y facilitar el estudio de las materias a los estudiantes. Este chatbot además permite recopilar comentarios de los propios estudiantes sobre los temas que requieren ser explicados en clase con un mayor detalle. Conclusiones: El uso del chatbot tutorial, ha permitido aumentar el compromiso y la colaboración tanto de los estudiantes como de los docentes, disminuyendo la tasa del número de estudiantes que abandonan la asignatura.Ministerio Español de Economía y Competitividad - project TIN2017-85727-C4-2-P -UGR-DeepBio

Personalising Learning with Dynamic Prediction and Adaptation to Learning Styles in a Conversational Intelligent Tutoring System

This thesis presents research that combines the benefits of intelligent tutoring systems (ITS), conversational agents (CA) and learning styles theory by constructing a novel conversational intelligent tutoring system (CITS) called Oscar. Oscar CITS aims to imitate a human tutor by implicitly predicting individuals’ learning style preferences and adapting its tutoring style to suit them during a tutoring conversation. ITS are computerised learning systems that intelligently personalise tutoring based on learner characteristics such as existing knowledge and learning style. ITS are traditionally student-led, hyperlink-based learning systems that adapt the presentation of learning resources by reordering or hiding links. Research suggests that students learn more effectively when instruction matches their learning style, which is typically modelled explicitly using questionnaires or implicitly based on behaviour. Learning is a social process and natural language interfaces to ITS, such as CAs, allow students to construct knowledge through discussion. Existing CITS adapt tutoring according to student knowledge, emotions and mood, however no CITS adapts to learning styles. Oscar CITS models a human tutor by directing a tutoring conversation and automatically detecting and adapting to an individual’s learning styles. Original methodologies and architectures were developed for constructing an Oscar Predictive CITS and an Oscar Adaptive CITS. Oscar Predictive CITS uses knowledge captured from a learning styles model to dynamically predict learning styles from an individual’s tutoring dialogue. Oscar Adaptive CITS applies a novel adaptation algorithm to select the best tutoring style for each tutorial question. The Oscar CITS methodologies and architectures are independent of the learning styles model and subject domain. Empirical studies involving real students have validated the prediction and adaptation of learning styles in a real-world teaching/learning environment. The results show that learning styles can be successfully predicted from a natural language tutoring dialogue, and that adapting the tutoring style significantly improves learning performance

The Beetle and BeeDiff Tutoring Systems

We describe two tutorial dialogue systems that adapt techniques from task-oriented dialogue systems to tutorial dialogue. Both systems employ the same reusable deep natural language understanding and generation components to interpret students ' written utterances and to automatically generate adaptive tutorial responses, with separate domain reasoners to provide the necessary knowledge about the correctness of student answers and hinting strategies. We focus on integrating the domain-independent language processing components with domain-specific reasoning and tutorial components in order to improve the dialogue interaction, and present a preliminary analysis of BeeDiff's evaluation

A review on massive e-learning (MOOC) design, delivery and assessment

MOOCs or Massive Online Open Courses based on Open Educational Resources (OER) might be one of the most versatile ways to offer access to quality education, especially for those residing in far or disadvantaged areas. This article analyzes the state of the art on MOOCs, exploring open research questions and setting interesting topics and goals for further research. Finally, it proposes a framework that includes the use of software agents with the aim to improve and personalize management, delivery, efficiency and evaluation of massive online courses on an individual level basis.Peer ReviewedPostprint (author's final draft