Context awareness for collaborative learning with uncertainty management

Postprint (published version

Context awareness and uncertainty in collocated collaborative systems

Context awareness is a necessary feature for mobile collocated collaborative learning. In this paper we describe how requirements for contextaware cooperative learning activities are derived from the jigsaw technique augmented with the use of mobile devices, applications to support the activities of groups, and tools to provide context-awareness to detect group formation. The emergence of groups is detected based on the location of the students within the classroom, but this information has to be careful filtered to evaluate the degree of uncertainty and protect from erroneous estimations. A three-phase strategy to manage uncertainty by identifying possible sources of uncertainty, representing uncertain information, and determining how to proceed under the presence of uncertainty is used for this propose. These requirements are validated and confirmed in experiments with students working together in the classroom, measuring neutral or positive effects on learning and the usefulness of introducing mobile devices, group support applications, and context awareness. The ratio of unwanted interruptions to users made by the system is used to evaluate the utility of the system. Results show that by managing uncertainty, location estimation becomes more reliable, thus increasing the usefulness of the learning application.Postprint (published version

Supporting context-aware collaborative learning through automatic group formation

Collaborative learning is based on groups of students working together with traditional and computer-based tools or applications. We have found that to make these supporting applications more effective we need to address the problem of automating group awareness in CSCL applications by estimating group arrangements from location sensors and the history of interaction. This contextual information can enable the construction of applications that facilitate communication among group members in synchronous and collocated collaborative learning activities. We used data traces collected from the study of students‟ behavior to train and test an intelligent system. Results show that context-information can be effectively used as a basis for a middleware for automating group management. Inferring group membership is technically feasible, can be integrated in group-support applications and can be used in real-world settings.Postprint (published version

Context awareness and uncertainty in collocated collaborative systems

Context awareness is a necessary feature for mobile collocated collaborative learning. In this paper we describe how requirements for contextaware cooperative learning activities are derived from the jigsaw technique augmented with the use of mobile devices, applications to support the activities of groups, and tools to provide context-awareness to detect group formation. The emergence of groups is detected based on the location of the students within the classroom, but this information has to be careful filtered to evaluate the degree of uncertainty and protect from erroneous estimations. A three-phase strategy to manage uncertainty by identifying possible sources of uncertainty, representing uncertain information, and determining how to proceed under the presence of uncertainty is used for this propose. These requirements are validated and confirmed in experiments with students working together in the classroom, measuring neutral or positive effects on learning and the usefulness of introducing mobile devices, group support applications, and context awareness. The ratio of unwanted interruptions to users made by the system is used to evaluate the utility of the system. Results show that by managing uncertainty, location estimation becomes more reliable, thus increasing the usefulness of the learning application

FACILITANDO EL ACCESO A LAS FUENTES DE INFORMACIÓN DE UN GRUPO DE MANTENIMIENTO DE SOFTWARE POR MEDIO DE UN MAPA DE CONOCIMIENTO

RESUMENEntre los problemas que enfrentan las organizaciones de desarrollo de software, y en particular los grupos encargados del mantenimiento de software, se encuentran la pérdida o desaprovechamiento del conocimiento que existe en las distintas fuentes disponibles dentro de estos grupos. Esto se produce debido a que con frecuencia esas fuentes son desconocidas o difíciles de localizar. Los Mapas de Conocimiento (MC) son una técnica que puede ser de utilidad para abordar este problema, dado que pueden ser usados para describir las fuentes de conocimiento disponibles, el conocimiento que puede ser obtenido de las mismas, y cómo éstas pueden ser localizadas. Un aspecto importante para la creación de un MC, es definir qué conocimiento y qué fuentes deberán ser tomadas en cuenta. Con este fin, la identificación del flujo del conocimiento dentro de una organización puede ayudar a identificar qué conocimiento es el requerido en las actividades que sus miembros deben llevar a cabo, así como las fuentes donde ese conocimiento puede ser obtenido, con el fin de centrar nuestro interés en aquellas que realmente puedan ser de ayuda para los usuarios del MC. En este trabajo describimos el proceso que se llevó a cabo para la creación de unMCen el ámbito del mantenimiento de software, por medio de una metodología para identificar flujos de conocimiento con base en técnicas de modelado de procesos. El objetivo es plantear nuestra experiencia en la realización de este esfuerzo, con la finalidad de que algunas de estas ideas puedan ayudar a otras organizaciones de desarrollo de software en trabajos similares. PALABRAS CLAVESMapa de conocimientoGestión de conocimientoIdentificación de flujos de conocimientoIngeniería de softwareMantenimiento de softwareMejoramiento de proceso software ABSTRACTSome of the problems in software development organizations, particularly in the groups in charge of software maintenance, are the scarce use of the knowledge that can be obtained from the sources available in the organization. This is because those sources are often unknown or difficult to locate. Knowledge maps can help to address this problem since these maps can be used to describe the knowledge sources available in the organization, the knowledge that can be obtained from them, and how or where those sources can be accessed. To create a knowledge map, an important factor is to define what knowledge and which sources should be considered. The identification of how knowledge flow through the organization can help to accomplish this, since it can help to identify the knowledge required by the members of the organization to carry on their activities, as well as the sources in which that knowledge can be obtained, in order to focus on those sources that may be really useful to the users of the knowledge map. This paper describes the process followed to create a knowledge map for a software maintenance group following a methodology to identify knowledge flows based on process modelling techniques. The main goal of this paper is to present our experience in the development of the map, expecting that some of these ideas could be useful to other software organizations that could engage similar works in the future. KEYWORDSKnowledge mapKnowledge managementKnowledge flows identificationSoftware engineeringSoftware maintenanceSoftware process improvement

Study on Mobile Augmented Reality Adoption for Mayo Language Learning

This paper presents the results of a study applied to undergraduates in order to know how the cultural dimensions affect their perceptions of the acceptance and use of new technologies in a student-centered learning environment. A total of 85 undergraduate students from the Autonomous Indigenous University of Mexico (UAIM) participated in the study. Each student was asked to use a mobile augmented reality (MAR) application designed to learn Mayo language (language spoken in Northwestern Mexico). Afterwards, the students responded to a survey with items concerning the use and technology acceptance and about cultural dimensions of individualism and uncertainty avoidance. Structural equation modeling (SEM) was used to analyze the data collected from students. Results provide evidence that the individualism contributes positively to perceived ease of use of the MAR app, and uncertainty avoidance has no impact. The findings showed that the MAR system could be easily used if it includes a natural way to promote collaborative work. In addition, to gain the trust of students, the uncertainty avoidance needs to be reduced by enriching the help information offered for app use

Supporting context-aware collaborative learning through automatic group formation

Collaborative learning is based on groups of students working together with traditional and computer-based tools or applications. We have found that to make these supporting applications more effective we need to address the problem of automating group awareness in CSCL applications by estimating group arrangements from location sensors and the history of interaction. This contextual information can enable the construction of applications that facilitate communication among group members in synchronous and collocated collaborative learning activities. We used data traces collected from the study of students‟ behavior to train and test an intelligent system. Results show that context-information can be effectively used as a basis for a middleware for automating group management. Inferring group membership is technically feasible, can be integrated in group-support applications and can be used in real-world settings