Designer - Supporting Teachers Experience in Learning Management Systems

Our paper entitled “Designer - Supporting Teachers Experience in Learning Management Systems” has been accepted for presentation at the International Conference on Web-based Learning in Sinaia, Romania. This conference is one of the top conferences in the area of technology enhanced learning and the acceptance of our paper at this conference provided us with the chance to present our work to leading researchers in our area. In our paper, we introduced Designer, an approach for teachers to help them in designing courses via a semi-automatic design process based on dynamic user modeling and adaptive learning design generation. In a virtual learning environment supporting the competence development process as well as providing students with personalized/adaptive courses ends up being an elusive and time-consuming task for teachers and/or instructional designers. Our proposed tool, Designer, aims at addressing this issue by supporting teachers to create adaptive courses based on students’ competencies and learning styles. A qualitative and quantitative evaluation demonstrated the effectiveness of Designer in supporting teachers to create such adaptive courses. The presentation of our paper was received very well and leaded to many questions after the presentation, further discussions during the conference, many ideas for future research, and a potential collaboration with an international research group.In the lifelong learning context, the efficiency of learning is measured according to the users’ achievement of the target competences. However, in a virtual learning environment supporting the competence development process ends up being an elusive and time-consuming task for teachers or instructional designers. Furthermore, tailoring courses to the individual learner’s needs and preferences has high potential to improve the learning process of learners. However, again, this is a time-consuming and complex task for teachers and instructional designers. In this paper, we introduce Designer, an approach for teachers to help them in designing courses via a semi-automatic design process based on dynamic user modeling and adaptive learning design generation. A qualitative and quantitative evaluation demonstrated the effectiveness of Designer in supporting teachers to create adaptive courses

Redes bayesianas para predecir el estilo de aprendizaje de estudiantes en entornos virtuales

Introdução: Descreve o uso de Redes Bayesianas - com base no modelo Felder-Silverman - para a implementação de um modelo de incerteza voltado à previsão do estilo de aprendizagem de alunos que interagem em um ambiente virtual de aprendizagem. Método: O modelo de incerteza,  projetado e desenvolvido para operar na LMS Moodle foi validado em um cenário educacional, consistindo em sua aplicação experimental em dois grupos de participantes oriundos da Universidade Nacional de Loja e da Universidade Internacional do Equador. Resultados: O bloco "Estilo de Aprendizagem" (EA) permitiu aos estudantes visualizar as probabilidades de cada dimensão de sua EA, notando que, de acordo com sua interação, essas probabilidades se modificavam. Da mesma forma, o professor pode visualizar as mudanças de probabilidade de EA obtidos pelos alunos quando estes interagiram em um curso virtual hospedadono Ambiente Virtual de Aprendizagem. Conclusão: A proposta pode servir de suporte para os professores que desejem identificar os estilos de aprendizagem predominantes dos estudantes e, com base nisso, elaborar atividades e recursos para suas disciplinas.Introducción: Describe la utilización de las Redes Bayesianas para implementar un modelo de incertidumbre que permita predecir el estilo de aprendizaje de los estudiantes mediante la interacción en un entorno virtual de aprendizaje basado en el modelo de Felder-Silverman. Método: El modelo de incertidumbre se lo diseño y desarrolló para el funcionamiento en el LMS Moodle. Para validar el modelo propuesto se planteó un escenario educativo real conformado por dos grupos experimentales pertenecientes a la Universidad Nacional de Loja y Universidad Internacional del Ecuador. Resultados: El bloque “Estilo de Aprendizaje” (EA) permitió a los estudiantes visualizar las probabilidades de cada dimensión de su EA observando que, de acuerdo a su interacción, cambiaban dichas probabilidades. De igual forma el docente pudo visualizar las probabilidades del EA que obtuvo cada estudiante al interactuar en un curso virtual alojado en el Entorno Virtual de Aprendizaje. Conclusión: La propuesta podrá servir como apoyo al docente que desee identificar los estilos de aprendizaje predominantes de los estudiantes y, en base a ello,  preparar actividades y recursos en su aula virtual.Introduction: It describes the use of Bayesian Networks to implement a model of uncertainty to predict the learning style of students through their interaction in a virtual learning environment based on the Felder-Silverman model. Method: The model uncertainty was designed and developed to be integrated in the LMS Moodle. In order to validate the proposed model, an actual educational scenario was built and two groups - one from the National University of Loja and other from the International University of Ecuador - were exposed to the experiment. Results: The block "Learning Style" (EA) allowed students to visualize the probabilities of each dimension of their EA by observing that, according to their interactions, these probabilities changed. Likewise, the teachers could visualize the probabilities of EA obtained by each student when these interactions were done in the hosted virtual course enclosed in the Virtual Learning Environment. Conclusion: The proposal may serve as support for teachers who want to identify predominant learning styles of their students and, based on that, prepare activities and resources in the courses under their responsibilities

Ajuste instructivo entre objetos de aprendizaje y estilos de aprendizaje

Creating learning objects is part of a learner centered culture of education that provides individual tailored training. Therefore, personal fitted instruction or the selection of suitable learning objects to meet student individual needs is conceived as a means to contribute to such training. The study, associated to the research project "Implementation of the use of learning objects and virtual classrooms in professional training", provides additional procedural clues for creating learning objects methodology supported by RHODA and eXeLearning tools, and identifying individual learning styles from a socio-affective perspective. The findings include the description of stages and steps for the methodology and stress the linking to Moodle virtual learning environment objects in the process of adjusting learning and assessing activities to individual learning styles.La creación de objetos de aprendizaje forma parte de una cultura formativa- educativa que coloca la centralidad del aprendizaje en el estudiante y constituye una práctica acorde a una formación personalizada y personalizable. Por ello, el ajuste instructivo o la adaptación de los objetos de aprendizaje a los estilos de aprendizaje de los estudiantes se presenta como una ví­a que contribuye a dicha formación. El estudio, asociado al proyecto “Implementación del uso de los objetos de aprendizaje y las aulas virtuales en la formación del profesional”, complementa mediante recomendaciones metodológicas, la dimensión práctica de una metodologí­a de creación de objetos de aprendizaje basada en la herramienta RHODA y apoyado con eXeLearning, teniendo en cuenta la identificación de los estilos de aprendizaje desde una dimensión socio- afectiva del proceso de aprendizaje. Las recomendaciones particularizan en etapas y pasos de dicha metodologí­a y enfatizan desde el uso de funcionalidades de las herramientas RHODA, eXe y la vinculación de los objetos al entorno virtual de aprendizaje MOODLE, en la adaptación de actividades de aprendizaje y actividades de evaluación a los estilos de aprendizaje de los estudiantes. Se aplica el Taller de Socialización para la validación de la propuesta