Metareasoning suffers from the heterogeneity problem, in which different researchers build diverse metareasoning models for intelligent systems with comparable functionality but differing contexts, ...ambiguous terminology, and occasionally contradicting features and descriptions. This article presents an ontology-driven knowledge representation for metareasoning in intelligent systems. The proposed ontology, called IM-Onto, provides a visual means of sharing a common understanding of the structure and relationships between terms and concepts. A rigorous research method was followed to ensure that the two main requirements of the ontology (integrity based on relevant knowledge and acceptance by researchers and practitioners) were met. The high accuracy rate indicates that most of the knowledge elements in the ontology are useful information for the integration of multiple types of metareasoning problems in intelligent systems.
This paper presents a model of metacognitive expectations about the running time of cognitive functions in the metacognitive architecture CARINA. A formal and ontological representation is created ...that establishes the relationship between the process of observing a fact in the self-model and a belief stored in the semantic memory of the system. The cognitive ontology evidenced tracing and interchange information process among different kind of memories, such as: sensorial memory, semantic memory, procedural memory, prospective memory and working memory. The experiment carried out demonstrated the functionality of the model where expectations were generated for each observation and could be compared with the observed values in real time. Another type of result was the conceptual advance of an expectation, the formal mathematical representation, the design of the ontology and the model as a mechanism of implementation in CARINA architecture.
Pedagogic strategies are action plans designed to manage issues related to sequencing and content organization, specifying learning activities, and deciding how to deliver content and activities in ...teaching processes. In this paper, we present an approach to personalization of pedagogical strategies in Intelligent Tutoring Systems using pedagogical knowledge rules in a Web environment. The adaptation of pedagogical strategies is made based on a multilevel pedagogical model. An Intelligent Tutoring Systems called FUNPRO was developed to validate the multilevel pedagogical model. The results of empirical tests show that the multilevel pedagogical model enables FUNPRO to improve the process of personalization of pedagogical strategies, due to the reduction of inappropriate recommendations.
Trends of Educational Informatics in Latin America Gómez, Adán A; Caro, Manuel F; Solano, Angela M ...
International journal of software science and computational intelligence,
01/2018, Letnik:
10, Številka:
1
Journal Article
Recenzirano
Educational Informatics is a multidisciplinary research area that uses Information and Communication Technology (ICT) in education. This article reports a wide overview about the new perspective of ...educational informatics that has been implemented in Latin America. This general view is the result of the different talks presented during the XIII Conference of Educational Informatics, organized by the Ibero-American Network of Educational Informatics RIBIE (Red Iberoamericana de Informática Educativa) in Colombia. These talks were proposed by international panelists from various parts of Latin America in the lines of ICT for Education and Peace, Thinking and Artificial Intelligence, Emergent Scenarios in Education and Mobiles Technologies and Apps for Entrepreneurship and Learning.
This paper presents a formal model of metacognitive reasoning in intelligent systems (IS). The proposed model was named fM2 and uses predicate logic to represent a cycle of reasoning about failures ...generated in reasoning tasks in an IS. fM2 has mechanisms such as introspective monitoring and meta-level control to perform metacognitive reasoning. fM2 was implemented and validated on an intelligent tutoring system named FUNPRO. The performance metrics of FUNPRO indicate the capacity of fM2 to drastically decrease the reasoning failures produced in the recommendations of FUNPRO. Thus, this paper demonstrates the efficacy of fM2 as a valid tool to improve the performance of the reasoning processes of IS.
Computational metacognition is a technical area of artificial intelligence whose aim is to increase the degree of autonomy and awareness an intelligent system has about its own reasoning and ...learning. In the literature, different models of metacognition are applied to artificial intelligent systems. However many of these models have a narrow focus, because they do not address comprehensively the elements of metacognition. This paper presents an analysis of metacognitive models discussed in the literature in order to discover the common (invariants) and varying (variants) elements. The main contribution of this work is the development of a comprehensive and general purpose metamodel named MISM that covers and describes a broad range of commonly referenced concepts in metacognitive models in the area of artificial intelligence. A validation process was conducted to ensure the reliability of MISM in terms of generality, expressiveness and completeness. The validation was performed using three techniques for improvements and adjustments to the metamodel: (i) comparison with other models; (ii) frequency-based selection; and (iii) model tracing. The adjusted and improved version of the metamodel was named MISM 1.1.
Este artículo presenta un modelo de expectativas metacognitivas sobre el tiempo de funcionamiento de las funciones cognitivas en la arquitectura metacognitiva CARINA. Se crea una representación ...formal y ontológica que establece la relación entre el proceso de observar un hecho en el auto-modelo y una creencia almacenada en la memoria semántica del sistema. La ontología cognitiva evidenció el proceso de búsqueda e intercambio de información entre diferentes tipos de recuerdos, tales como: memoria sensorial, memoria semántica, memoria de procedimientos, memoria prospectiva y memoria de trabajo. El experimento realizado demostró la funcionalidad del modelo en donde se generó expectativas para cada observación y podía compararlas con los valores observados en tiempo real. Otro tipo de resultado fue avance conceptual de una expectativa, la representación matemática formal, el diseño de la ontología y el modelo como un mecanismo de implementación en la arquitectura CARINA.
Las estrategias pedagógicas son los planes de acción encaminados a gestionar los aspectos relacionados con la secuenciación y organización de los contenidos, especificación de las actividades de ...aprendizaje, y decidir cómo entregar el contenido y las actividades en los procesos de enseñanza. En este artículo se presenta un enfoque para la personalización de las estrategias pedagógicas en Sistemas Tutoriales Inteligentes utilizando reglas de conocimientos pedagógicos en un entorno Web. La adaptación de las estrategias pedagógicas que se hace con base en un modelo pedagógico multinivel. Un Sistemas Tutorial Inteligente llamado FUNPRO fue desarrollado para la validación del modelo pedagógico multinivel. Los resultados de las pruebas empíricas muestran que el modelo pedagógico multinivel permite a FUNPRO mejorar el proceso de personalización de estrategias pedagógicas debido a la reducción de las recomendaciones inapropiadas.
Metacognition has been used in artificial intelligence to increase the level of autonomy of intelligent systems. However the design of systems with metacognitive capabilities is a difficult task due ...to the number and complexity of processes involved. This paper presents a domain-specific visual language specifically developed for modeling metacognition in intelligent systems called M++. In M++ the specifications of the cognitive level (object-level) and metacognitive level (meta-level) are supported in a metamodel configured according to the standard Meta-Object Facility (MOF) of Model-Driven Architecture (MDA) methodology. M++ allows the generation of metacognitive diagrams in a visual editor named MetaThink. A validation process was conducted to ensure the reliability of M++ in terms of quality of the notation and consistency of generated models. The validation was performed using two techniques: (i) empirical study and (ii) model tracing. The results given in the experimental study demonstrate that M++ is a useful notation for the process of modeling metacognitive components in intelligent systems. Metacognitive models generated from the validation process using the Tracing technique were consistent with the MOF-based metamodel. M++ contribute to cognitive architecture research adding precision to metacognitive concepts and enabling cognitive architecture researchers to do fast and exploratory prototyping of metacognitive systems using MetaThink tool.
In the era of rapidly evolving technological advancements and the growing importance of 21st-century skills and environmental consciousness, education systems face the challenge of providing ...personalized learning experiences that cater to individual student needs while fostering critical thinking, problem-solving abilities, and environmental awareness. This paper presents a formal model for personalizing learning paths through the integration of artificial intelligence (AI) into in- structional planning. The proposed model accounts for varying difficulty levels in learning activities related to 21st-century skills and environmental care, creating a comprehensive framework for optimizing student learning paths.
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