Adaptive group formation to promote desired behaviours

BACKGROUND There is substantial literature that shows the benefits of collaborative work, though these benefits vary enormously with circumstances. Irrespective of their structure and composition, groups usually exist for a particular reason and implicitly or explicitly target one or more outcomes. The achievements of group outcomes depend on many factors, including the individual behaviour of each group member. These behaviours are, in turn, affected by the individual characteristics, the context and the group composition. Constructing groups in a way that maximises the achievement of a specific outcome is complex with the optimal group composition depending on the attributes of the group members. Previous work has in most cases considered group formation based on one particular attribute, such as learning style, gender, personality, etc. Less common are instances of group formation rules being adjusted systematically to accommodate changes in an individualâs attributes or disposition. PURPOSE This paper considers how the multi-factorial nature of group performance and the variations in desired behaviour across different circumstances can be addressed within a consistent framework. DESIGN/METHOD The methodology consisted of two main stages. In the first stage, a simulation was encoded in MatLab to assess the conceptual approach of progressively updating rules for group formation. The method uses an unsupervised learning algorithm and correlation factors between quantifiable group characteristics (average age, degree of motivation, etc.) and resultant behaviours of the groups that are actually formed (level of dialogue, interface interactions, etc.) to update the rules used for group formation, and hence progressively construct groups that are more likely to behave in desired ways. The second stage involved an evaluation of this approach in a real world scenario using remotely accessible laboratories where engineering students voluntarily participated in a study in April 2012. RESULTS The simulation results show that under certain conditions the desired behaviour chosen with the intention of improving specific learning outcomes can be optimized and that groups can be constructed that are more likely to exhibit desired behaviour. The paper also reports preliminary evidence that shows the feasibility of this approach in selecting group participants in an engineering class to promote a desired outcome in this case independent learning. CONCLUSIONS This study demonstrates the feasibility of using a set of individual characteristics of group members to form groups that are more likely to have desired group behaviours and that these characteristics can be monitored and updated to dynamically alter group formation to account for changes in any individualâs characteristics. This has potential to allow groups formation decisions to be made dynamically to achieve a desired outcome, for example promote collaborative learning

Group formation for collaboration in exploratory learning using group technology techniques

Exploratory Learning Environments (ELEs) allow learners to approach a problem in different ways; they are particularly suitable for ill-defined problems where knowledge is less structured and open-ended exploration is allowed. Moreover, multiple solutions which are equally valid are possible and a common and efficient way to convey this is by promoting and supporting students’ collaboration. Successful collaboration, however, depends on forming groups in which the activity is relevant for all members of the group. In this paper we present a computational model for group formation for open-ended exploration in ELEs by modelling the various strategies that learners adopt to solve the same task. This is underpinned by Group Technology techniques that use as criteria the learners’ strategies and the similarity among them to form groups that match pedagogy considerations. The proposed mechanism is tested in an exploratory learning environment for mathematical generalisation

Marco conceptual para la gestión de grupos colaborativos en cursos de escala masiva y variable

Los MOOC (Massive Open Online Courses, Cursos Abiertos Masivos en Línea), etiquetados como nuevo paradigma disruptivo en el entorno educativo, son ampliamente criticados debido a sus altas tasas de abandono y a su baja calidad instruccional. La inclusión de pedagogías colaborativas en este tipo de cursos podría mejorar su calidad instruccional, además de aumentar la motivación e implicación de los alumnos. La escala masiva y variable dificulta la introducción de dichas pedagogías y en especial la formación y mantenimiento de grupos de trabajo de alumnos. El apoyo a los profesores en las tareas de gestión de los grupos, podría facilitar la adopción de diseños pedagógicos colaborativos. Para abordar esta meta y poder llevar a cabo el desarrollo de herramientas de apoyo a los profesores, es conveniente un conocimiento profundo del contexto y del problema a acometer, así como una visión holística del mismo. Por este motivo, este TFM pretende realizar una primera iteración exploratoria sobre el problema y desarrollar un marco conceptual que describa el contexto e identifique y clasifique los factores a considerar en el diseño de herramientas que apoyen a los profesores en la gestión de agrupaciones en cursos de escala masiva y variable. Para ello se realiza una revisión de literatura y se obtiene la opinión de expertos mediante entrevistas semiestructuras. La información obtenida por estos métodos se analiza, se sintetiza y se comunica en forma de artefactos gráficos que se usan posteriormente en tres escenarios ilustrativos que tratan de facilitar la comprensión de los artefactos en un contexto ficticio pero realista.Máster en Investigación en Tecnologías de la Información y las Comunicacione

Faculty Perspectives And Practices Of Social Presence In Online Post-Secondary Learning Environments

University of Minnesota D.Ed. dissertation. April 2018. Major: Education, Curriculum and Instruction. Advisor: Joyce Strand. 1 computer file (PDF); xii, 226 pages.This study explored the almost 20-year-old Community of Inquiry (CoI) social presence construct through faculty’s perspectives and practices of their online teaching. Social presence has many CoI-identified characteristics, but overall it is the ability of a student to project their persona into the classroom. The preponderance of investigation has been on the other two CoI constructs, teaching and cognitive presences. Questions have arisen whether social presence is even necessary or achievable in online learning. This research was to provide more insight on the importance of online social presence and its characteristics in the online learning environment. The investigation invited faculty of a Midwestern university who teach solely online courses to share their perspectives on and practices supporting social presence. Methodology employed was inquiry-based, qualitative research utilizing survey and interview questionnaires. The sample consisted of 62 survey respondents and six interviewees. Data and information gathered were survey respondents’ demographics, type and sizes of courses they taught, and responses to qualitative and Likert-scaled questions, as well as interviewees’ qualitative responses. These findings were analyzed using descriptive statistics, Pearson correlations, and qualitative information review to find patterns to help answer the research questions. From the survey data, significant Pearson Correlations were present related to very small (less than 21 students) and very large classes (over 80 students). Most social presence CoI characteristics were rated at least important to extremely important by over 50% of the faculty responses. Only two characteristics rated mostly somewhat important or not important. From the survey and interview responses, patterns arose that social presence is contextually important and can be impacted by class size, instructor course design, the course level (undergraduate versus graduate), subject matter, student’s self-regulate learning, and the amount of time and resources allotted to the instructor. A few survey responses stated that social presence is not at all important. Interviewees relayed that online social presence can be just as important as it is in face-to-face courses for learning outcomes. This investigation warrants more social presence research regarding class size and level, subject matter, institutional supports, instructor course design, student self-learning abilities, and CoI construct-to-construct impacts