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

Learning to diagnose collaboratively – Effects of adaptive collaboration scripts in agent-based medical simulations

We investigated how medical students' collaborative diagnostic reasoning, particularly evidence elicitation and sharing, can be facilitated effectively using agent-based simulations. Providing adaptive collaboration scripts has been suggested to increase effectiveness, but existing evidence is diverse and could be affected by unsystematic group constellations. Collaboration scripts have been criticized for undermining learners' agency. We investigate the effect of adaptive and static scripts on collaborative diagnostic reasoning and basic psychological needs. We randomly allocated 160 medical students to one of three groups: adaptive, static, or no collaboration script. We found that learning with adaptive collaboration scripts enhanced evidence sharing performance and transfer performance. Scripting did not affect learners’ perceived autonomy and social relatedness. Yet, compared to static scripts, adaptive scripts had positive effects on perceived competence. We conclude that for complex skills complementing agent-based simulations with adaptive scripts seems beneficial to help learners internalize collaboration scripts without negatively affecting basic psychological needs

Learning 21st century science in context with mobile technologies

The paper describes a project to support personal inquiry learning with handheld and desktop technology between formal and informal settings. It presents a trial of the technology and learning across a school classroom, sports hall, and library. The main aim of the study was to incorporate inquiry learning activities within an extended school science environment in order to investigate opportunities for technological mediations and to extract initial recommendations for the design of mobile technology to link inquiry learning across different contexts. A critical incident analysis was carried out to identify learning breakdowns and breakthroughs that led to design implications. The main findings are the opportunities that a combination of mobile and fixed technology bring to: manage the formation of groups, display live visualisations of student and teacher data on a shared screen to facilitate motivation and personal relevance, incorporate broader technical support, provide context-specific guidance on the sequence, reasons and aims of learning activities, offer opportunities to micro-sites for reflection and learning in the field, to explicitly support appropriation of data within inquiry and show the relation between specific activities and the general inquiry process

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

Collaboration scripts - a conceptual analysis

This article presents a conceptual analysis of collaboration scripts used in face-to-face and computer-mediated collaborative learning. Collaboration scripts are scaffolds that aim to improve collaboration through structuring the interactive processes between two or more learning partners. Collaboration scripts consist of at least five components: (a) learning objectives, (b) type of activities, (c) sequencing, (d) role distribution, and (e) type of representation. These components serve as a basis for comparing prototypical collaboration script approaches for face-to-face vs. computer-mediated learning. As our analysis reveals, collaboration scripts for face-to-face learning often focus on supporting collaborators in engaging in activities that are specifically related to individual knowledge acquisition. Scripts for computer-mediated collaboration are typically concerned with facilitating communicative-coordinative processes that occur among group members. The two lines of research can be consolidated to facilitate the design of collaboration scripts, which both support participation and coordination, as well as induce learning activities closely related to individual knowledge acquisition and metacognition. In addition, research on collaboration scripts needs to consider the learners’ internal collaboration scripts as a further determinant of collaboration behavior. The article closes with the presentation of a conceptual framework incorporating both external and internal collaboration scripts

Adaptive Educational Hypermedia based on Multiple Student Characteristics

The learning process in Adaptive Educational Hypermedia (AEH) environments is complex and may be influenced by aspects of the student, including prior knowledge, learning styles, experience and preferences. Current AEH environments, however, are limited to processing only a small number of student characteristics. This paper discusses the development of an AEH system which includes a student model that can simultaneously take into account multiple student characteristics. The student model will be developed to use stereotypes, overlays and perturbation techniques. Keywords: adaptive educational hypermedia, multiple characteristics, student model

ARGUMENTATION-BASED COMPUTER SUPPORTED COLLABORATIVE LEARNING (ABCSCL): THE ROLE OF INSTRUCTIONAL SUPPORTS

This paper investigates the role of instructional supports for argumentation-based computer supported collaborative learning (ABCSCL), a teaching approach that improves the quality of learning processes and outcomes. Relevant literature has been reviewed to identify the instructional supports in ABCSCL environments. A range of instructional supports in ABCSCL is proposed including scaffolding, scripting, and representational tools. Each of these instructional supports are discussed in detail. Furthermore, the extent to which and the way in which such instructional supports can be applied in ABCSCL environments are discussed. Finally, suggestions for future work and implications for the design of ABCSCL environments are provided.  Article visualizations

Technology to enable new paradigms of teaching/learning in mathematics: the digital interactive storytelling case

This paper concerns the design and implementation of a particular methodology for mathematics teaching/learning which exploits an interactive and immersive metaphor of storytelling. This research aims to promote processes such as inquiring, conjecturing, formalizing, proving in mathematics, and to investigate which is the best way to organize ICT tools to achieve that purpose. We also report the findings of an ongoing experimentation at the K12 school level

Exploring the Experiences of Call Center Employees Regarding Business Scripting

Scripting, defined as the mechanization of business processes through automated tools or orchestrated responses, has played a significant role in shaping call center activities and the resultant customer relationship. However, findings of industry research have shown that the use of scripting to maximize operational efficiency has had a disempowering effect on call center employees by lowering their job-skill and knowledge requirements. Grounded in the concepts of knowledge management and knowledge transfer, this study explored the experiences of frontline call center employees on the effects of scripting on customer problem solving. A single-case study design with semistructured interviews was used with a population of 20 frontline employees in a North American call center to gather insights. Thematic analysis was applied to the interview data using nodes to identify emerging themes and insights. Three major themes emerged: First, although scripting had contributed to improved service quality and operational efficiency, scripted practices undermined the use of team knowledge and limited the amount of shared information. Second, the employees requested that call center scripted solutions be more intuitive and better aligned to knowledge requirements. Third, the employees suggested that an object-oriented approach to solution management be used, one that could better leverage communities of practices and collective team knowledge sharing within the organization. This object-oriented approach to solution management may promote virtual knowledge flow and the building of subject matter expertise that could elicit higher agent engagement and problem ownership. The proposed object-oriented approach to knowledge sharing is important to management, as it could help facilitate knowledge reuse and improved organizational performance