A Social Learning Space Grid for MOOCs: Exploring a FutureLearn Case

Collaborative and social engagement promote active learning through knowledge intensive interactions. Massive Open Online Courses (MOOCs) are dynamic and diversified learning spaces with varying factors like flexible time frames, student count, demographics requiring higher engagement and motivation to continue learning and for designers to implement novel pedagogies including collaborative learning activities. This paper looks into available and potential collaborative and social learning spaces within MOOCs and proposes a social learning space grid that can aid MOOC designers to implement such spaces, considering the related requirements. Furthermore, it describes a MOOC case study incorporating three collaborative and social learning spaces and discusses challenges faced. Interesting lessons learned from the case give an insight on which spaces to be implemented and the scenarios and factors to be considered

Technology support for scalable and dynamic collaborative learning: a pyramid flow pattern approach

Collaborative Learning is the pedagogical approach that considers social interactions as key means to trigger rich learning processes. Collaborative Learning Flow Patterns define best practices to orchestrate collaborative learning activity flow mechanisms (i.e., group formation, roles or resources allocation, phase change). Flow patterns have been experimented and evaluated as effective in small scale settings for decades. Directly applying these pedagogical methods to large learning scenarios is challenging due to the burden that scale represents in the orchestration load or the difficulty of keeping a dynamic meaningful progression when flexible changes are required in a large classroom or in a MOOC. Some attempts have shown positive results, but research around scalable collaborative learning approaches, models and technologies for large classes is scattered. This dissertation conducts a systematic literature review of collaborative learning applications on large classes and analyses the social learning potential of diverse technology-supported spaces in massive courses. Then the dissertation focuses the study on how collaborative learning could address key challenges (i.e., scalability and dynamism) identified in large collaborative learning contexts. Consequently, the thesis proposes a Pyramid flow pattern instantiation, composed of a model with a set of algorithmic rules for flow creation, flow control and flow awareness as well as a PyramidApp authoring and enactment system implementing the model. Experimentation across diverse learning contexts shows that, on one hand, the contributions support meaningful scalable and dynamic collaborative learning and on the other hand, learners and educators perceive the experiences as engaging, with learning values and effective from the perspective of orchestration.El aprendizaje colaborativo es el enfoque pedagógico que considera las interacciones sociales como un medio clave para desencadenar procesos de aprendizaje ricos. Los patrones de flujo de aprendizaje colaborativo definen buenas prácticas para orquestar mecanismos de flujo en actividades de aprendizaje colaborativo (es decir, la formación de grupos, la asignación de roles o recursos, los cambios de fase). Los patrones de flujo han sido probados y evaluados como efectivos en entornos de pequeña escala durante décadas. La aplicación de estos métodos pedagógicos en grandes escenarios de aprendizaje supone un reto debido a la carga que representa la escala en la orquestación, así como a la dificultad de mantener una progresión dinámica con sentido pedagógico cuando se requieren cambios flexibles en un aula grande o en un MOOC. Existen algunos intentos interesantes, pero la investigación en torno a enfoques de aprendizaje colaborativo escalables, y modelos y tecnologías para entornos educativos con muchos estudiantes está dispersa. Esta tesis lleva a cabo una revisión sistemática de la literatura sobre aplicaciones de aprendizaje colaborativo con muchos estudiantes y analiza el potencial de aprendizaje social de diversos espacios apoyados por la tecnología en este tipo de contextos. A continuación, la tesis se centra en el estudio de cómo el aprendizaje colaborativo podría abordar desafíos clave identificados en contextos de aprendizaje colaborativo con un gran número de estudiantes (es decir, la escalabilidad y el dinamismo). En consecuencia, la tesis propone una instanciación del patrón de flujo Pirámide, compuesto de un modelo con un conjunto de reglas algorítmicas para la creación, el control y la conciencia del flujo de aprendizaje, así como un sistema de creación e implementación del modelo. La experimentación realizada en distintos contextos de aprendizaje demuestra que, por un lado, las contribuciones apoyan un aprendizaje colaborativo escalable y dinámico, y que, por otro lado, los estudiantes y los educadores perciben las experiencias como amenas, con valor para el aprendizaje y efectivas desde la perspectiva de la orquestación

Has research on collaborative learning technologies addressed massiveness?

There is a growing interest in understanding to what extent innovative educational technologies can be used to/nsupport massive courses. Collaboration is one of the main desired elements in massive learning actions/ninvolving large communities of participants. Accumulated research in collaborative learning technologies has/nproposed and evaluated multiple models and implementation tools that engage learners in knowledge-intensive/nsocial interactions fostering fruitful learning. However, it is unclear to what extent these technologies have been/ndesigned to support large-scale learning scenarios involving arguably massive participation. This paper/ncontributes with a literature review that aims at providing an answer to this question as well as offering insights/nabout the context of use, characteristics of the technologies, and the types of activities and collaboration/nmechanisms supported. The main results point out that till 2013 the level of massiveness considered in top/nscientific journal papers on collaborative learning technologies was low, the scenarios studied were/npredominantly contextualized in co-located higher education settings using Learning Management Systems, the/nmost common activities considered were open and structured discussion, followed by peer assessment and/ncollaborative writing, and the most broadly used mechanism to foster fruitful collaboration was group formation/nfollowing diverse policies.This research has been partially funded by the Spanish Ministry of Economy and Competitiveness in the EEE Project (TIN2011-28308-C03-03

Towards scalable collaborative learning flow pattern orchestratrion technologies

Comunicació presentada a: EDULEARN17 9th International Conference on Education and New Learning Technologies, celebrat del 3 al 4 de juliolt de 2017 a Barcelona.Collaborative Learning Flow Patterns (CLFPs) structure learning flows to shape desired social interactions among learners leading to fruitful learning gains. It is worthwhile to study the possibilities of CLFP extensions to be applicable in large class contexts and also in Massive Open Online Courses (MOOCs) considering their dynamic, unpredictable nature. This study considers most commonly used patterns for the adaptability in such contexts from different dimensions like pedagogical interest, scalability and other related perspectives. As a result derived from the analysis, a collection of use cases is elaborated illustrating potential collaborative learning opportunities, design requirements, initial screen designs of such activities and expected functionality descriptions for novel CSCL orchestration technologies. One of these use cases is implemented in the PyramidApp tool.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness under RESET (TIN2014-53199-C3-3-R), the Maria de Maeztu Units of Excellence Programme (MDM-2015- 0502) and RecerCaixa (CoT project)

PyramidApp: scalable method enabling collaboration in the classroom

Computer Supported Collaborative Learning methods support fruitful social interactions using technological mediation and orchestration. However, studies indicate that most existing CSCL methods have not been applied to large classes, means that they may not scale well or that it’s unclear to what extent or with which technological mechanisms scalability could be feasible. This paper introduces and evaluates PyramidApp, implementing a scalable pedagogical method refining Pyramid (aka Snowball) collaborative learning flow pattern. Refinements include rating and discussing to reach upon global consensus. Three different face-to-face classroom situations were used to evaluate different tasks of pyramid interactions. Experiments led to conclude that pyramids can be meaningful with around 20 participants per pyramid of 3–4 levels, with several pyramids running in parallel depending on the classroom size. An underpinning algorithm enabling elastic creation of multiple pyramids, using control timers and triggering flow awareness facilitated scalability, dynamism and overall user satisfaction in the experience.Paper presented at 11th European Conference on Technology Enhanced Learning, EC-TEL 2016, Lyon, France, September 13-16, 2016.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness (TIN2014-53199-C3-3-R; MDM-2015-0502)

Flexible CSCL orchestration technology: mechanisms for elasticity and dynamism in pyramid script flows

Comunicació presentada a: the 13th International Conference on Computer Supported Collaborative Learning (CSCL), celebrada del 17 al 21 de juny de 2019 a Lió, França.Flow patterns (e.g., Pyramid or Snowball) formulate good practices to script collaborative learning scenarios, which have been experimented in small-scale settings widely. Applying flow patterns on large-scale contexts present challenges to educators in terms of orchestration load. Orchestration technology can support educators to manage collaborative activities; yet existing technology do not address flexibility challenges like accommodating growing numbers of students or tolerating dynamic conditions in learning settings. We define elasticity and dynamism as two key elements in the flexibility of a script. Elasticity is related to the capacity of an orchestration technology to incorporate varying participant counts. Dynamism is the capacity to maintain a pedagogically meaningful script progression in presence of different individual behaviors. In this paper we propose flow creation and flow control mechanisms to address elasticity and dynamism in orchestration technology for Pyramid flows. These mechanisms, implemented in the PyramidApp tool, have been evaluated across four scenarios varying from small to large settings. The results show that rules enabling pyramid creation on-demand and the use of timers are useful to achieve elasticity and dynamism in the pyramid formation and progression in an automatic manner.DHL is a Serra Húnter fellow. This work has been partially funded by “la Caixa Foundation” (CoT project, 100010434) and the National Research Agency of the Spanish Ministry of Science, Innovations and Universities MDM-2015-0502, TIN2014-53199-C3-3-R, TIN2017-85179-C3-3-R

A multiple constraints framework for collaborative learning flow orchestration

Paper presented at ICWL 2016, 15th International Conference, Rome, Italy, October 26–29, 2016.Collaborative Learning Flow Patterns (e.g., Jigsaw) offer sound pedagogical strategies to foster fruitful social interactions among learners. The pedagogy behind the patterns involves a set of intrinsic constraints that need to/nbe considered when orchestrating the learning flow. These constraints relate to the organization of the flow (e.g., Jigsaw pattern - a global problem is divided into sub-problems and a constraint is that there need to be at least one expert group working on each sub-problem) and group formation policies (e.g., groups solving the global problem need to have at least one member coming from a different previous expert group). Besides, characteristics of specific learning situations such as learners’ profile and technological tools used provide additional parameters that can be considered as context-related extrinsic constraints relevant to the orchestration (e.g., heterogeneous groups depending on experience or interests). This paper proposes a constraint framework that considers different constraints for orchestration services enabling adaptive computation of orchestration aspects. Substantiation of the framework with a case study demonstrated the feasibility, usefulness and the expressiveness of the framework.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness/n(TIN2014-53199-C3-3-R; MDM-2015-0502)

Flexible CSCL orchestration technology: mechanisms for elasticity and dynamism in pyramid script flows

Comunicació presentada a: the 13th International Conference on Computer Supported Collaborative Learning (CSCL), celebrada del 17 al 21 de juny de 2019 a Lió, França.Flow patterns (e.g., Pyramid or Snowball) formulate good practices to script collaborative learning scenarios, which have been experimented in small-scale settings widely. Applying flow patterns on large-scale contexts present challenges to educators in terms of orchestration load. Orchestration technology can support educators to manage collaborative activities; yet existing technology do not address flexibility challenges like accommodating growing numbers of students or tolerating dynamic conditions in learning settings. We define elasticity and dynamism as two key elements in the flexibility of a script. Elasticity is related to the capacity of an orchestration technology to incorporate varying participant counts. Dynamism is the capacity to maintain a pedagogically meaningful script progression in presence of different individual behaviors. In this paper we propose flow creation and flow control mechanisms to address elasticity and dynamism in orchestration technology for Pyramid flows. These mechanisms, implemented in the PyramidApp tool, have been evaluated across four scenarios varying from small to large settings. The results show that rules enabling pyramid creation on-demand and the use of timers are useful to achieve elasticity and dynamism in the pyramid formation and progression in an automatic manner.DHL is a Serra Húnter fellow. This work has been partially funded by “la Caixa Foundation” (CoT project, 100010434) and the National Research Agency of the Spanish Ministry of Science, Innovations and Universities MDM-2015-0502, TIN2014-53199-C3-3-R, TIN2017-85179-C3-3-R

Has research on collaborative learning technologies addressed massiveness?

There is a growing interest in understanding to what extent innovative educational technologies can be used to/nsupport massive courses. Collaboration is one of the main desired elements in massive learning actions/ninvolving large communities of participants. Accumulated research in collaborative learning technologies has/nproposed and evaluated multiple models and implementation tools that engage learners in knowledge-intensive/nsocial interactions fostering fruitful learning. However, it is unclear to what extent these technologies have been/ndesigned to support large-scale learning scenarios involving arguably massive participation. This paper/ncontributes with a literature review that aims at providing an answer to this question as well as offering insights/nabout the context of use, characteristics of the technologies, and the types of activities and collaboration/nmechanisms supported. The main results point out that till 2013 the level of massiveness considered in top/nscientific journal papers on collaborative learning technologies was low, the scenarios studied were/npredominantly contextualized in co-located higher education settings using Learning Management Systems, the/nmost common activities considered were open and structured discussion, followed by peer assessment and/ncollaborative writing, and the most broadly used mechanism to foster fruitful collaboration was group formation/nfollowing diverse policies.This research has been partially funded by the Spanish Ministry of Economy and Competitiveness in the EEE Project (TIN2011-28308-C03-03