Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

D3.1 – First Bundle of Core Social Agency Assets

This deliverable presents and describes the first delivery of assets that are part of the core social agency bundle. In total, the bundle includes 16 assets, divided into 4 main categories. Each category is related to a type of challenge that developers of applied games are typically faced with and the aim of the included assets is to provide solutions to those challenges. The main goal of this document is to provide the reader with a description for each included asset, accompanied by links to their source code, distributable versions, demonstrations and documentation. A short discussion of what are the future steps for each asset is also given. The primary audience for the contents of this deliverable are the game developers, both inside and outside of the project, which can use this document as an official list of the current social agency assets and their associated resources. Note that the information about which RAGE use cases are using which of these assets is described in Deliverable 4.2.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains

Assessment of Knowledge and Competencies in 3D Virtual Worlds: A Proposal

Proceedings of: Key Competencies in the Knowledge Society World Computer Congress (KCKS 2010). Brisbane, Australia, September 20-23, 2010.Digital natives demand a more active approach to learning. Moreover, the acquisition and assessment of competencies, rather than the mere transmission of information, is becoming more relevant in the Knowledge Society. 3D virtual worlds are a promising environment to meet both of these requirements. In a 3D virtual world, learners are immersed in a rich environment that allows them to have an active experience through their avatars and interaction devices. The learning process in traditional learning management systems has been widely studied, but there is relatively little literature about the use of 3D virtual worlds for learning, although the expectations are high and the possibilities opened immense. This paper focuses on an important part of the teaching and learning process: the assessment. Our aim is to present a set of techniques adapted to this novel 3D medium that allows assessing knowledge, skills, and competencies by using the elements inherent to 3D virtual worlds (avatars, synthetic characters, smart objects) and take advantage of the new dimension introduced.This research is supported by the following projects: The Spanish project “Learn3: Towards Learning of the Third Kind” (TIN2008-05163/TSI) within the Spanish “Plan Nacional de I+D+I”, the Madrid regional project “eMadrid: Investigación y Desarrollo de tecnologías para el e-learning en la Comunidad de Madrid” (S2009/TIC-1650), the European eContentPlus Project “iCoper: Interoperable Content for Performance in a Competency-driven Society” (PPI-2008-A-12).Publicad

Designing Adaptive Instruction for Teams: a Meta-Analysis

The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or educational experience tailored by artificially-intelligent, computer-based tutors with the goal of optimizing learner outcomes (e.g., knowledge and skill acquisition, performance, enhanced retention, accelerated learning, or transfer of skills from instructional environments to work environments). The core contribution of this research was the identification of behavioral markers associated with the antecedents of team performance and learning thus enabling the development and refinement of teamwork models in ITS architectures. Teamwork focuses on the coordination, cooperation, and communication among individuals to achieve a shared goal. For ITSs to optimally tailor team instruction, tutors must have key insights about both the team and the learners on that team. To aid the modeling of teams, we examined the literature to evaluate the relationship of teamwork behaviors (e.g., communication, cooperation, coordination, cognition, leadership/coaching, and conflict) with team outcomes (learning, performance, satisfaction, and viability) as part of a large-scale meta-analysis of the ITS, team training, and team performance literature. While ITSs have been used infrequently to instruct teams, the goal of this meta-analysis make team tutoring more ubiquitous by: identifying significant relationships between team behaviors and effective performance and learning outcomes; developing instructional guidelines for team tutoring based on these relationships; and applying these team tutoring guidelines to the Generalized Intelligent Framework for Tutoring (GIFT), an open source architecture for authoring, delivering, managing, and evaluating adaptive instructional tools and methods. In doing this, we have designed a domain-independent framework for the adaptive instruction of teams

Best practices in developing global collaborations in education

This purpose of this study was to examine the best practices used by facilitators of global collaborations in education. Four research questions were examined to address this purpose, which included: (a) challenges faced by facilitators in developing online international collaborations in education (b) current strategies used by facilitators in developing online international collaborations in education (c) how success is measured and tracked (d) recommendations for future online international collaborations in education. This qualitative, phenomenological study utilized a purposive sample of 14 participants who were ISTE (International Society for Technology in Education) award recipients or conference presenters between 2014 - 2017 affiliated with global collaboration. Data collection was done through a semi-structured interview protocol comprised of six questions. The recorded interviews were transcribed, coded and analyzed to determine 27 total themes that emerged from the data. With some themes reinforced by literature and some unique to the study, results led to establishing “dimensions of leading global collaboration.” This includes two primary dimensions: (a) the responsibilities dimension, which entails the tasks and logistical aspects needed in global collaboration efforts, such as planning, practices during the collaboration, and logistical considerations (b) the characteristics dimension, which refers to the qualities that characterize a good global collaboration leader and partner, such as empathy, accountability, and willingness to take risks. Additionally, this study highlights the importance of people and developing a peer to peer network in the dynamic among facilitators (who should be seen as leaders) of global collaboration