Why not empower knowledge workers and lifelong learners to develop their own environments?

In industrial and educational practice, learning environments are designed and implemented by experts from many different fields, reaching from traditional software development and product management to pedagogy and didactics. Workplace and lifelong learning, however, implicate that learners are more self-motivated, capable, and self-confident in achieving their goals and, consequently, tempt to consider that certain development tasks can be shifted to end-users in order to facilitate a more flexible, open, and responsive learning environment. With respect to streams like end-user development and opportunistic design, this paper elaborates a methodology for user-driven environment design for action-based activities. Based on a former research approach named 'Mash-Up Personal Learning Environments'(MUPPLE) we demonstrate how workplace and lifelong learners can be empowered to develop their own environment for collaborating in learner networks and which prerequisites and support facilities are necessary for this methodology

The afterlife of 'living deliverables': angels or zombies?

Within the STELLAR project, we provide the possibility to use living documents for the collaborative writing work on deliverables. Compared to 'normal' deliverables, 'living' deliverables come into existence much earlier than their delivery deadline and are expected to 'live on' after their official delivery to the European Commission. They are expected to foster collaboration. Within this contribution we investigate, how these deliverables have been used over the first 16 months of the project. We therefore propose a set of new analysis methods facilitating social network analysis on publicly available revision history data. With this instrumentarium, we critically look at whether the living deliverables have been successfully used for collaboration and whether their 'afterlife' beyond the contractual deadline had turned them into 'zombies' (still visible, but no or little live editing activities). The results show that the observed deliverables show signs of life, but often in connection with a topical change and in conjunction with changes in the pattern of collaboration

Shortcomings of learning design approaches and a possible way out

Shifting away from traditional instructional design to younger research streams like personalized, workflow-based or collaborative e-learning, learning design (LD) has become an important issue in the field of technology-enhanced learning. Nevertheless, current LD approaches turn out to be rather unhandy or costly in teaching and research practice. In this paper, we discuss these shortcomings and propose an alternative solution approach which is based on a web application mashup, learner interactions, and a semantic layer for tool recommendations. As the evaluation of our first prototype is in progress, we can not highlight first experiences, but outline benefits and possible application scenarios in this position paper

El futuro de la tecnología educativa

Aprendizaje es cambio, y, de forma natural, el campo de la educación siempre ha estado abierto a innovaciones tecnológicas. El campo interdisciplinar emergente del "technology-enhanced learning" o TEL (que podríamos traducir como "aprendizaje potenciado por la tecnología") se puede decir que hoy en día avanza a gran velocidad. Especialmente en los últimos años, en los que ha habido un apoyo significativo de financiación de la Unión Europea, de grandes iniciativas nacionales y de la dedicación entusiasta de organizaciones e individuos, se han logrado avances considerables

Positioning for conceptual development using latent semantic analysis

With increasing opportunities to learn online, the problem of positioning learners in an educational network of content offers new possibilities for the utilisation of geometry-based natural language processing techniques. In this article, the adoption of latent semantic analysis (LSA) for guiding learners in their conceptual development is investigated. We propose five new algorithmic derivations of LSA and test their validity for positioning in an experiment in order to draw back conclusions on the suitability of machine learning from previously accredited evidence. Special attention is thereby directed towards the role of distractors and the calculation of thresholds when using similarities as a proxy for assessing conceptual closeness. Results indicate that learning improves positioning. Distractors are of low value and seem to be replaceable by generic noise to improve threshold calculation. Furthermore, new ways to flexibly calculate thresholds could be identified

Monitoring conceptual development with text mining technologies: CONSPECT

This paper evaluates CONSPECT, a service that analyses states in a learner’s conceptual development. It combines two technologies – Latent Semantic Analysis to analyse text and Network Analysis (NA) to provide visualisations – into a technique called Meaningful Interaction Analysis (MIA). CONSPECT was designed to help both online learners and their tutors monitor their conceptual development. This paper reports on the validation experiments undertaken to determine how well LSA matches first year medical students in clustering concepts and in annotating text. The validation used several techniques, including card sorting and Likert scales. CONSPECT produces almost ‘peer’ quality results and what remains to be tested is whether it improves with more advanced learners. One of the experiments showed an average 0.7 correlation between humans and CONSPECT

Designing for change: mash-up personal learning environments

Institutions for formal education and most work places are equipped today with at least some kind of tools that bring together people and content artefacts in learning activities to support them in constructing and processing information and knowledge. For almost half a century, science and practice have been discussing models on how to bring personalisation through digital means to these environments. Learning environments and their construction as well as maintenance makes up the most crucial part of the learning process and the desired learning outcomes and theories should take this into account. Instruction itself as the predominant paradigm has to step down. The learning environment is an (if not 'the�) important outcome of a learning process, not just a stage to perform a 'learning play'. For these good reasons, we therefore consider instructional design theories to be flawed. In this article we first clarify key concepts and assumptions for personalised learning environments. Afterwards, we summarise our critique on the contemporary models for personalised adaptive learning. Subsequently, we propose our alternative, i.e. the concept of a mash-up personal learning environment that provides adaptation mechanisms for learning environment construction and maintenance. The web application mash-up solution allows learners to reuse existing (web-based) tools plus services. Our alternative, LISL is a design language model for creating, managing, maintaining, and learning about learning environment design; it is complemented by a proof of concept, the MUPPLE platform. We demonstrate this approach with a prototypical implementation and a – we think – comprehensible example. Finally, we round up the article with a discussion on possible extensions of this new model and open problems

Using latent-semantic analysis and network analysis for monitoring conceptual development

This paper describes and evaluates CONSPECT (from concept inspection), an application that analyses states in a learner’s conceptual development. It was designed to help online learners and their tutors monitor conceptual development and also to help reduce the workload of tutors monitoring a learner’s conceptual development. CONSPECT combines two technologies - Latent Semantic Analysis (LSA) and Network Analysis (NA) into a technique called Meaningful Interaction Analysis (MIA). LSA analyses the meaning in the textual digital traces left behind by learners in their learning journey; NA provides the analytic instrument to investigate (visually) the semantic structures identified by LSA. This paper describes the validation activities undertaken to show how well LSA matches first year medical students in 1) grouping similar concepts and 2) annotating text

Language design for a personal learning environment design language

Approaching technology-enhanced learning from the perspective of a learner, we foster the idea of learning environment design, learner interactions, and tool interoperability. In this paper, we shortly summarize the motivation for our personal learning environment approach and describe the development of a domain-specific language for this purpose as well as its realization in practice. Consequently, we examine our learning environment design language according to its lexis and syntax, the semantics behind it, and pragmatical aspects within a first prototypic implementation. Finally, we discuss strengths, problematic aspects, and open issues of our approach

The MUPPLE competence continuum

The idea of Personal Learning Environments (PLEs) seems to polarise the educational sphere into supporters and opponents. Both groups relate their enthusiasm or criticism to underlying competences motivated by or needed for building up, running, and maintaining a PLE. Within the following article, results of a qualitative study with multiple cases will be presented to shed light onto which competence and which of its building blocks are involved in running a (mash-up) PLE. Data about the involved skills, abilities, habits, attitudes and knowledge will be presented in a raster of the five dimensions 'plan', 'reflect', 'monitor', 'act', and 'interact' against the three stages 'start', 'trigger', and 'outcome'. The findings indicate that there is a continuum ranging from the ones needed right ahead to the ones ultimately sought