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The Metacognitive Architecture CARINA is used to execute cognitive agents. CARINA is defined as a metacognitive architecture for artificially intelligent agents and is derived from the MISM Metacognitive Metamodel. A Factoid WH- question (FWhQ) is an interrogative statement that begins with a WH word (when, what, where, who, which) and gives a fact as answer reflected in the text. A Cognitive Agent is an entity of software that perceives stimulus from its external environment to achieve its goals selecting actions from its internal knowledge rationally. The problem which is tackled in this research is the need to offer and develop educational resources enabling foreign language learners to better cope with this type of questions, problem perceived as a priority in the Foreign Language Program at Universidad de Cordoba. This paper aims at reporting the design of a Cognitive Agent-based on Metacognitive architecture CARINA for the generation of Factoid WH- Questions. The methodology used in this study involved the cognitive modelling designed for this purpose, which consists of seven steps and the application of a test for validation based on 2 research questions focused on two specific dimensions: Readability and Potential Usefulness. Results showed that cognitive models based in M++ are easy to read and allows understanding the relations among different elements of a cognitive model. This allowed a cognitive agent to be developed to answer Factoid questions in English.

The Metacognitive Architecture CARINA is used to execute cognitive agents. CARINA is defined as a metacognitive architecture for artificially intelligent agents and is derived from the MISM Metacognitive Metamodel. A Factoid WH- question (FWhQ) is an interrogative statement that begins with a WH word (when, what, where, who, which) and gives a fact as answer reflected in the text. A Cognitive Agent is an entity of software that perceives stimulus from its external environment to achieve its goals selecting actions from its internal knowledge rationally. The problem which is tackled in this research is the need to offer and develop educational resources enabling foreign language learners to better cope with this type of questions, problem perceived as a priority in the Foreign Language Program at Universidad de Cordoba. This paper aims at reporting the design of a Cognitive Agent-based on Metacognitive architecture CARINA for the generation of Factoid WH- Questions. The methodology used in this study involved the cognitive modelling designed for this purpose, which consists of seven steps and the application of a test for validation based on 2 research questions focused on two specific dimensions: Readability and Potential Usefulness. Results showed that cognitive models based in M++ are easy to read and allows understanding the relations among different elements of a cognitive model. This allowed a cognitive agent to be developed to answer Factoid questions in English.

The Metacognitive Architecture CARINA is used to execute cognitive agents. CARINA is defined as a metacognitive architecture for artificially intelligent agents and is derived from the MISM Metacognitive Metamodel. A Factoid WH- question (FWhQ) is an interrogative statement that begins with a WH word (when, what, where, who, which) and gives a fact as answer reflected in the text. A Cognitive Agent is an entity of software that perceives stimulus from its external environment to achieve its goals selecting actions from its internal knowledge rationally. The problem which is tackled in this research is the need to offer and develop educational resources enabling foreign language learners to better cope with this type of questions, problem perceived as a priority in the Foreign Language Program at Universidad de Cordoba. This paper aims at reporting the design of a Cognitive Agent-based on Metacognitive architecture CARINA for the generation of Factoid WH- Questions. The methodology used in this study involved the cognitive modelling designed for this purpose, which consists of seven steps and the application of a test for validation based on 2 research questions focused on two specific dimensions: Readability and Potential Usefulness. Results showed that cognitive models based in M++ are easy to read and allows understanding the relations among different elements of a cognitive model. This allowed a cognitive agent to be developed to answer Factoid questions in English.