Fuzzy cognitive diagnosis for modelling examinee performance

© 2018 ACM. Recent decades have witnessed the rapid growth of educational data mining (EDM), which aims at automatically extracting valuable information from large repositories of data generated by or related to people's learning activities in educational settings. One of the key EDM tasks is cognitive modelling with examination data, and cognitive modelling tries to profile examinees by discovering their latent knowledge state and cognitive level (e.g. the proficiency of specific skills). However, to the best of our knowledge, the problem of extracting information from both objective and subjective examination problems to achieve more precise and interpretable cognitive analysis remains underexplored. To this end, we propose a fuzzy cognitive diagnosis framework (FuzzyCDF) for examinees' cognitive modelling with both objective and subjective problems. Specifically, to handle the partially correct responses on subjective problems, we first fuzzify the skill proficiency of examinees. Then we combine fuzzy set theory and educational hypotheses to model the examinees' mastery on the problems based on their skill proficiency. Finally, we simulate the generation of examination score on each problem by considering slip and guess factors. In this way, the whole diagnosis framework is built. For further comprehensive verification, we apply our FuzzyCDF to three classical cognitive assessment tasks, i.e., predicting examinee performance, slip and guess detection, and cognitive diagnosis visualization. Extensive experiments on three real-world datasets for these assessment tasks prove that FuzzyCDF can reveal the knowledge states and cognitive level of the examinees effectively and interpretatively

Visualising alignment to support students’ judgment of confidence in open learner models

Knowledge monitoring is a component of metacognition which can help students regulate their own learning. In adaptive learning software, the system’s model of the student can be presented as an open learner model (OLM) which is intended to enable monitoring processes. We explore how presenting alignment, between students’ self-assessed confidence and the system’s model of the student, supports knowledge monitoring. When students can see their confidence and their performance (either combined within one skill meter or expanded as two separate skill meters), their knowledge monitoring and performance improves, particularly for low-achieving students. These results indicate the importance of communicating the alignment between the system’s evaluation of student performance and student confidence in the correctness of their answers as a means to support metacognitive skills

Analysis and Comparison of Open Student Models

[EN] This article is focused on the study of Open Student Models, area that takes on the opening of Student Models¿ characteristics in Technology Based Learning Systems. In this work a review of the state of the art on Open Student Models is performed. Different approximations of the literature are compared against an opening guide that authors have defined. This guide is formulated on three main parts: learning domain, learning state and progress and student profile.Este trabajo está cofinanciado por la Universidad del País Vasco/Euskal Herriko Unibertsitatea (EHU09/09), el Ministerio de Ciencia y Tecnología a través del programa CICYT (TIN2009-14380) y el Gobierno Vasco (IT421-10).Rueda Molina, U.; Calvo Fabo, I.; Arruarte Lasa, A.; Elorriaga Arandia, JA. (2011). Análisis y Comparación de Modelos de Estudiante Abiertos. Rita -IEEE-. 6(1):19-27. http://hdl.handle.net/10251/30170S19276

Model-Based Methods for Assessment, Learning, and Instruction: Innovative Educational Technology at Florida State University

Abstract In this chapter, we describe our research and development efforts relating to eliciting, representing, and analyzing how individuals and small groups conceptualize complex problems. The methods described herein have all been devel-oped and are in various states of being validated. In addition, the methods we describe have been automated and most have been integrated in an online model-based set of tools called HIMATT (Highly Interactive Model-based Assessment Tools and Technologies; available for research purposes a

Investigating the Effectiveness of Problem Templates on Learning in Intelligent Tutoring Systems

Deliberate practice within a coached environment is required for skill acquisition and mastery. Intelligent Tutoring Systems (ITSs) provide such an environment. A goal in ITS development is to find means to maximise effective learning. This provides the motivation for the project presented. This paper proposes the notion of problem templates. These mental constructs extend the idea of memory templates, and allow experts in a domain to store vast amounts of domain-specific information that are easily accessible when faced with a problem. This research aims to examine the validity of such a construct and investigate its role in regards to effective learning within ITSs. After extensive background research, an evaluation study was performed at the University of Canterbury. Physical representations of problem templates were formed in Structured Query Language (SQL). These were used to model students, select problems, and provide customised feedback in the experimental version of SQLTutor, an Intelligent Tutoring System. The control group used the original version of SQL-Tutor where pedagogical (problem selection and feedback) and modelling decisions were based on constraints. Preliminary results show that such a construct could exist; furthermore, it could be used to help students attain high levels of expertise within a domain. Students using template based ITS showed high levels of learning within short periods of time. The author suggests further evaluation studies to investigate the extent and detail of its effect on learning

Supporting students’ confidence judgement through visualising alignment in open learner models

Supporting students’ knowledge monitoring skills, a component of metacognition, can help students regulate their own learning. This thesis investigates the alignment of learners’ confidence in their knowledge with a computer’s assessment of their knowledge, visualised using an Open Learner Model (OLM). The research explored students’ preferred method for visualising inconsistent data (e.g. misalignment) in an OLM, and the ways in which visualising alignment can influence student interaction with the computer. The thesis demonstrates that visualising alignment in Open Learner Models signifi-cantly increases students’ confidence compared to a control condition. In particular, visualising alignment benefited low-achieving students, in terms of knowledge monitoring and this was associated with improvements in their performance. Students showed a preference towards the visualisations that provides an overview of the in-formation (i.e. opacity) rather than ones, which provide detailed information. Graph-ical representation is shown to be more beneficial in motivating students to interact with the system than text-based representation of the same information in the con-text of representing the alignment within OLMs

Adaptação em um sistema educacional hipermídia baseada na classificação de perfis de usuários: Gisele Trentin da Silva ; orientadora, Marta Costa Rosatelli

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Ciência da ComputaçãoEsta dissertação apresenta a modelagem de um sistema hipermídia adaptativo para um curso à distância baseado na Web. O sistema classifica os estudantes em diferentes perfis através do método do Vizinho Mais Próximo (Nearest Neighbor) utilizando os dados do usuário e os dados de uso do sistema pelo estudante e adapta a navegação no conteúdo por meio da técnica de ocultação e anotação de links. A arquitetura do sistema hipermídia adaptativo baseia-se em três módulos principais: Módulo de Classificação, Módulo de Estudante e Módulo de Adaptação. Estes três módulos são responsáveis, respectivamente, pela classificação dos perfis de estudantes, pela atualização destes perfis no Módulo de Estudante e pela adaptação da navegação no conteúdo conforme os perfis contidos no Modelo de Estudante. Esse processo é realizado desde que o estudante interage pela primeira vez com o sistema

Uso da FAQ como base de casos em um sistema tutor inteligente: Demetrius Ribeiro Lima ; orientadora, Marta Costa Rosatelli

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Ciência da ComputaçãoEste trabalho apresenta um Sistema Tutor Inteligente integrado a um Ambiente Virtual de Aprendizagem, implementando a tutoria inteligente em um curso a distância. Neste contexto, a tutoria inteligente consiste no auxílio e suporte ao aluno durante um curso virtual de modo a orientá-lo no processo de aprendizado, realizando um trabalho de acompanhamento de forma constante. Considerando que a Educação a Distância pode ser definida como um processo de ensino-aprendizagem em que o professor e o aluno estão separados fisicamente, a utilização de recursos tecnológicos que possibilitem a supervisão contínua e imediata deste processo é de grande relevância. O Sistema Tutor Inteligente desenvolvido utiliza como técnica de Inteligência Artificial, o Raciocínio Baseado em Casos, fazendo da Frequently Asked Questions a base de conhecimento do modelo do domínio. Através dela, os casos são recuperados e apresentados ao aluno. O modelo do estudante adapta características do sistema ao perfil do aluno a cada interação deste com o ambiente. As intervenções do sistema, que são acionadas pelo modelo do tutor, são feitas de acordo com este perfil. This work presents an Intelligent Tutoring System that is integrated into a Learning Virtual Environment, implementing intelligent tutoring in a distance course. In this context, intelligent tutoring consists of assisting and supporting the student during a virtual course, aiming to guide the student in the learning process through a permanent accompaniment. Taking into account that Distance Education can be defined as a process of teaching and learning in which the teacher and the student are physically separated, using technological resources that allow immediate and continuous supervising the student is of great relevance. The Intelligent Tutoring System that was developed uses Case-Based Reasoning as an Artificial Intelligence technique to make the Frequently Asked Questions the knowledge base of the domain model. The student model adapts system characteristics to the student profile at each interaction between him or her and the system. The system interventions, which are initiated by the tutor model, are also generated according to the student profile

Designing Embodied Interactive Software Agents for E-Learning: Principles, Components, and Roles

Embodied interactive software agents are complex autonomous, adaptive, and social software systems with a digital embodiment that enables them to act on and react to other entities (users, objects, and other agents) in their environment through bodily actions, which include the use of verbal and non-verbal communicative behaviors in face-to-face interactions with the user. These agents have been developed for various roles in different application domains, in which they perform tasks that have been assigned to them by their developers or delegated to them by their users or by other agents. In computer-assisted learning, embodied interactive pedagogical software agents have the general task to promote human learning by working with students (and other agents) in computer-based learning environments, among them e-learning platforms based on Internet technologies, such as the Virtual Linguistics Campus (www.linguistics-online.com). In these environments, pedagogical agents provide contextualized, qualified, personalized, and timely assistance, cooperation, instruction, motivation, and services for both individual learners and groups of learners. This thesis develops a comprehensive, multidisciplinary, and user-oriented view of the design of embodied interactive pedagogical software agents, which integrates theoretical and practical insights from various academic and other fields. The research intends to contribute to the scientific understanding of issues, methods, theories, and technologies that are involved in the design, implementation, and evaluation of embodied interactive software agents for different roles in e-learning and other areas. For developers, the thesis provides sixteen basic principles (Added Value, Perceptible Qualities, Balanced Design, Coherence, Consistency, Completeness, Comprehensibility, Individuality, Variability, Communicative Ability, Modularity, Teamwork, Participatory Design, Role Awareness, Cultural Awareness, and Relationship Building) plus a large number of specific guidelines for the design of embodied interactive software agents and their components. Furthermore, it offers critical reviews of theories, concepts, approaches, and technologies from different areas and disciplines that are relevant to agent design. Finally, it discusses three pedagogical agent roles (virtual native speaker, coach, and peer) in the scenario of the linguistic fieldwork classes on the Virtual Linguistics Campus and presents detailed considerations for the design of an agent for one of these roles (the virtual native speaker)