6 resultados para communities of learning
em Open University Netherlands
Resumo:
Full paper presented at EC-TEL 2016
Resumo:
Demo paper presented at EC-TEL 2016
Resumo:
This article introduces the Evaluation Framework EFI for the Impact Measurement of learning, education and training: The Evaluation Framework for Impact Measurement was developed for specifying the evaluation phase and its objectives and tasks within the IDEAL Reference Model for the introduction and optimization of quality development within learning, education and training. First, a description of the Evaluation Framework for Impact Measurement will be provided, followed by a brief overview of the IDEAL Reference Model. Finally, an example for the implementation of the Evaluation Framework for Impact Measurement within the ARISTOTELE project is presented.
Resumo:
The last couple of years there has been a lot of attention for MOOCs. More and more universities start offering MOOCs. Although the open dimension of MOOC indicates that it is open in every aspect, in most cases it is a course with a structure and a timeline within which learning activities are positioned. There is a contradiction there. The open aspect puts MOOCs more in the non-formal professional learning domain, while the course structure takes it into the formal, traditional education domain. Accordingly, there is no consensus yet on solid pedagogical approaches for MOOCs. Something similar can be said for learning analytics, another upcoming concept that is receiving a lot of attention. Given its nature, learning analytics offers a large potential to support learners in particular in MOOCs. Learning analytics should then be applied to assist the learners and teachers in understanding the learning process and could predict learning, provide opportunities for pro-active feedback, but should also results in interventions aimed at improving progress. This paper illustrates pedagogical and learning analytics approaches based on practices developed in formal online and distance teaching university education that have been fine-tuned for MOOCs and have been piloted in the context of the EU-funded MOOC projects ECO (Elearning, Communication, Open-Data: http://ecolearning.eu) and EMMA (European Multiple MOOC Aggregator: http://platform.europeanmoocs.eu).
Resumo:
Gifted pupils differ from their age-mates with respect to development potential, actual competencies, self-regulatory capabilities, and learning styles in one or more domains of competence. The question is how to design and develop education that fits and further supports such characteristics and competencies of gifted pupils. Analysis of various types of educational interventions for gifted pupils reflects positive cognitive or intellectual effects and differentiated social comparison or group-related effects on these pupils. Systemic preventive combination of such interventions could make these more effective and sustainable. The systemic design is characterised by three conditional dimensions: differentiation of learning materials and procedures, integration by and use of ICT support, and strategies to improve development and learning. The relationships to diagnostic, instructional, managerial, and systemic learning aspects are expressed in guidelines to develop or transform education. The guidelines imply the facilitation of learning arrangements that provide flexible self-regulation for gifted pupils. A three-year pilot in Dutch nursery and primary school is conducted to develop and implement the design in collaboration with teachers. The results constitute prototypes of structured competence domains and supportive software. These support the screening of entry characteristics of all four-year old pupils and assignment of adequate play and learning processes and activities throughout the school career. Gifted and other pupils are supported to work at their actual achievement or competency levels since their start in nursery school, in self-regulated learning arrangements either in or out of class. Each pupil can choose other pupils to collaborate with in small groups, at self-chosen tasks or activities, while being coached by the teacher. Formative evaluation of the school development process shows that the systemic prevention guidelines seem to improve learning and social progress of gifted pupils, including their self-regulation. Further development and implementation steps are discussed.
Resumo:
Learning Analytics is an emerging field focused on analyzing learners’ interactions with educational content. One of the key open issues in learning analytics is the standardization of the data collected. This is a particularly challenging issue in serious games, which generate a diverse range of data. This paper reviews the current state of learning analytics, data standards and serious games, studying how serious games are tracking the interactions from their players and the metrics that can be distilled from them. Based on this review, we propose an interaction model that establishes a basis for applying Learning Analytics into serious games. This paper then analyzes the current standards and specifications used in the field. Finally, it presents an implementation of the model with one of the most promising specifications: Experience API (xAPI). The Experience API relies on Communities of Practice developing profiles that cover different use cases in specific domains. This paper presents the Serious Games xAPI Profile: a profile developed to align with the most common use cases in the serious games domain. The profile is applied to a case study (a demo game), which explores the technical practicalities of standardizing data acquisition in serious games. In summary, the paper presents a new interaction model to track serious games and their implementation with the xAPI specification.