This article reports what information members of a virtual project team specifically find important for the formation of an initial impression of the trustworthiness of their colleagues.Collaboration in virtual project teams heavily relies on interpersonal trust, for which perceived trustworthiness is an important determinant.We reviewed different trust-requiring and collaborative online environments to determine what information people have available through profiles.Taking this analysis as a starting point, a group of 226 students with experience in virtual project teams was questioned on signals they preferred to use to form an impression of trustworthiness.On the basis of the results obtained we have formulated several recommendations for the design of groupware environments.They pertain in particular to personal identity profiles.

Learning design models provide guidelines and guidance for educators and course designers in the production and delivery of educational products. It is seen as beneficial to base learning designs on general learning theories, but these must be operationalised into concrete learning design solutions. We therefore present one such educational design model: the Design Cycle for Education (DC4E). The model has primarily been created to support the shift from traditional face-to-face education to blended learning scenarios. The cycle describes eight steps that can be used iteratively in the (re)design of educational products and provides educators and course designers with a flexible but clearly structured design model that enables them to reinvent traditional course content for blended learning with appropriate learning design tools.

Teaching English pronunciation is being neglected in English lessons in the Netherlands. Most teachers do not have a specific pedagogy for teaching English pronunciation or do not consider it to be important. Students with a desire for more native-like English pronunciation, be it to enhance their intelligibility, confidence or credibility, are faced with a lack of skilled professionals who are able to provide them with the necessary feedback for improvement. Research shows that a student- oriented computer-assisted pronunciation teaching tool can significantly improve students’ pronunciation skills, even without initial teacher input.

The design of learning opportunities is an integral part of the work of all educators. However, educators often lack the design skills and knowledge that professional designers have. One of these basic skills is related to the evaluation of produced artefacts, an essential step in all design frameworks. As a result, evaluation of learning activities falters due to this lack of knowledge and mindset. The present study analyses how in-service educators perceived and accomplished an evaluation activity aimed at promoting assessment prior to enactment. Heuristic evaluation is an inspection method considered to be one of the easiest to learn and yet is efficient, time and cost effective. These characteristics make it suitable for the design work of educators; which is, above all, practice-driven and practice-oriented. Results show that educators grasped the value of such an activity (solving possible second-order barriers) but struggled to understand how to do the specifics of the task (first-order barrier), which was to define their own set of educational heuristics. Based on the lessons learned, the paper finalises with a proposal for a design task to include evaluation to support learning design; empowering educators to assess both existing learning activities and ICT-tools as well as their own designs.

Many current authors point toward the heightening of networked individualism and how this affects community creation and engagement. This trend poses strong challenges to the potential beneficial effects of collective intelligence. Education is one of the realms that can strongly suffer from this globalized individualism. Learning is deeply enhanced by social interactions and losing this social dimension will have long-lasting effects in future generations. Networked learning is also a by-product of our societal context, but not per se individual. Our paper presents a case—the HANDSON massive open online course (MOOC)—in which a purposely designed learning environment fosters the emergence of a kind of collective intelligence which, by the learners own accord, brings about a heightened sense of community. The MOOC's design managed to enable individual learning paces without killing the social dimension. Thus, we argue that when learning together intentionally and informally in networked online environments, small and temporary communities (pop-up communities we call them) will form. This nascent sense of community is a first step that will ultimately contribute to the common good.

Educators of all sectors are learning designers, often unwittingly. To succeed as designers, they need to adopt a design mindset and acquire the skills needed to address the design challenges they encounter in their everyday practice. Human-centred design (HCD) provides professional designers with the methods needed to address complex problems. It emphasizes the human perspective throughout the design lifecycle and provides a practice-oriented approach, which naturally fits educators' realities. This research reports the experiences of educators who used HCD to design ICT-based learning activities. A mixed-methods approach was used to gauge how participating educators experienced the design tasks. The perceived level of difficulty and value of the various methods varied, revealing significant differences between educators according to their level of knowledge of pedagogy frameworks. We discuss our findings from the vantage point of educators' pedagogical beliefs and how experience shapes these. The results support the idea that HCD is a valuable framework for educators, one that may inform ongoing international efforts to shape a science and practice of learning design for teaching.

Educational institutions are designing, creating and evaluating courses to optimize learning outcomes for highly diverse student populations. Yet, most of the delivery is still monitored retrospectively with summative evaluation forms. Therefore, improvements to the course design are only implemented at the very end of a course, thus missing to benefit the current cohort. Teachers find it difficult to interpret and plan interventions just-in-time. In this context, Learning Analytics (LA) data streams gathered from ‘authentic’ student learning activities, may provide new opportunities to receive valuable information on the students’ learning behaviors and could be utilized to adjust the learning design already “on the fly” during runtime. We presume that Learning Analytics applied within Learning Design (LD) and presented in a learning dashboard provide opportunities that can lead to more personalized learning experiences, if implemented thoughtfully. In this paper, we describe opportunities and challenges for using LA in LD. We identify three key opportunities for using LA in LD: (O1) using on demand indicators for evidence based decisions on learning design; (O2) intervening during the run-time of a course; and, (O3) increasing student learning outcomes and satisfaction. In order to benefit from these opportunities, several challenges have to be overcome. Following a thorough literature review, we mapped the identified opportunities and challenges in a conceptual model that considers the interaction of LA in LD.

Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction. Therefore, evaluations that measure user satisfaction should also be performed before deploying a recommender system in a real target environment. Such evaluations are laborious and complicated compared to the traditional, data-centric evaluations, though. In this study, we carried out a user-centric evaluation of state-of-the-art recommender systems as well as a graph-based approach in the ecologically valid setting of an authentic social learning platform. We also conducted a data-centric evaluation on the same data to investigate the added value of user-centric evaluations and how user satisfaction of a recommender system is related to its performance in terms of accuracy metrics. Our findings suggest that user-centric evaluation results are not necessarily in line with data-centric evaluation results. We conclude that the traditional evaluation of recommender systems in terms of prediction accuracy only does not suffice to judge performance of recommender systems on the user side. Moreover, the user-centric evaluation provides valuable insights in how candidate algorithms perform on each of the five quality metrics for recommendations: usefulness, accuracy, novelty, diversity, and serendipity.

Even though they may never describe themselves in such terms, teachers have always been designers of learning experiences, whether 'performing' in the lecture theatre and classroom or writing handouts, syllabi or textbooks.Acting in the rather stable learning ecosystem of the classrooms and lecture halls of the past, there was no need to reflect upon their role as designers, indeed teachers saw themselves predominantly as bearers and transmitters of the values and knowledge that our cultures are made of.However, things have changed.Knowledge and values still matter, there can be no doubt about that.But one has come to conclude that a lot of learning takes place outside the classroom and lecture theatre.Also, the pace of societal change is ever increasing, making it a necessity to keep learning after formal schooling, informally at home or at the workplace.And perhaps most importantly, technology has entered our daily lives to an unprecedented degree.So we need to learn about technology as a subject, but also and in the present context more relevant, we need to figure out how technology can allow us to learn more effectively, more efficiently and, if at all possible, more agreeably.These changes pose many challenges, particularly for those who have made fostering the learning of others their call teachers, that is.The present-day consensus seems to be that teachers can only address these challenges if they adopt a designer's mindset, if they start seeing themselves as designers of learning experiences for others.Transforming oneself from an information (and values) conduit into a learning designer (perhaps even co-designer) is a tall order.Teachers are in the midst of going through that transition, be they in-service teachers who need to change their prevailing practices or pre-service teachers who need to learn the tricks of the new trade.To this special issue a total of 11 papers was submitted.Five of them were deemed unsuitable in regards the topic, 2 of them were rejected after peer review; consequently, the issue counts four articles that all in their own way discuss aspects of the transformation of 'traditional' teachers to 'modern' learning designers.The paper by Gachago, Morkel, Hitge, van Zyl, and Ivala (Developing eLearning champions: a design thinking approach (https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239

People recommenders are a widespread feature of social networking sites and educational social learning platforms alike. However, when these systems are used to extend learners' Personal Learning Networks, they often fall short of providing recommendations of learning value to their users. This paper proposes a design of a people recommender based on content-based user profiles, and a matching method based on dissimilarity therein. It presents the results of an experiment conducted with curators of the content curation site Scoop.it!, where curators rated personalized recommendations for contacts. The study showed that matching dissimilarity of interpretations of shared interests is more successful in providing positive experiences of breakdown for the curator than is matching on similarity. The main conclusion of this paper is that people recommenders should aim to trigger constructive experiences of breakdown for their users, as the prospect and potential of such experiences encourage learners to connect to their recommended peers.

In this study we focus on the effects of an intervention aiming to improve the English pronunciation skills of secondary school students in the Netherlands. In order to implement a new pedagogy successfully it is of the essence to take into account how teachers learn and what motivates them to adapt and change their way of teaching. Teachers need time to test and adapt a teaching design to fit the needs of their classroom practice and the students' needs. In this paper the main focus is on finding evidence of teacher professional development in teaching English pronunciation. Results show that teachers are extrinsically motivated to change their teaching behaviour and classroom practice after using a computer assisted teaching tool to teach English pronunciation.

chapter followed a standard methodology for evaluating recommender systems in learning.to provide educational stakeholders in Europe with a social learning platform in a social sharing.In this chapter, we describe a full recommender system data study in a stepwise process.Furthermore, we outline shortcomings for data-driven studies in the domain of by the SoLAR society.

In a non-formal learning network, knowledge sharing is often desirable when working on complex tasks. However, without support, learners need to first find a tutor and then maintain social interaction, which, according to cognitive load theory, may hamper learning. After all, the extraneous load imposed by these two activities and the intrinsic load imposed by the task itself might easily overload learners' cognitive capacity. We compared the effects of using a peer support system with an automatic tutor assignment and an interaction tool (wiki) to a forum and control group (without any support) on learners' cognitive load and learning efficiency for simple and complex tasks. The results did not significantly show that this peer support system was instrumental in reducing cognitive load and improving learning efficiency. However, the study did shed an illuminating light on how to apply instructional guidelines of cognitive load theory to non-formal learning networks.

Almost all studies on course recommenders in online platforms target closed online platforms that belong to a University or other provider. Recently, a demand has developed that targets open platforms. Such platforms lack rich user profiles with content metadata. Instead they log user interactions. We report on how user interactions and activities tracked in open online learning platforms may generate recommendations. We use data from the OpenU open online learning platform in use by the Open University of the Netherlands to investigate the application of several state-of-the-art recommender algorithms, including a graph-based recommender approach. It appears that user-based and memory-based methods perform better than model-based and factorization methods. Particularly, the graph-based recommender system outperforms the classical approaches on prediction accuracy of recommendations in terms of recall.

This chapter discusses guidelines for networked learning. First, a few definitions are analyzed and it is concluded that networks are essentially different than communities, although the former will contain the latter. Then, the notion of learning design is examined, resulting in the conclusion that the distinction of Carvalho and Goodyear between epistemic, social, and set design should guide the design of networked learning. Each of these design aspects is then scrutinized. After analysis of pertinent metaphors of learning, epistemic design turns out to be subject to the maxim that learning networks cannot be designed, only designed for. With this as a limiting perspective, guidelines for the social design of learning networks are derived, in which the notion of an ad hoc transient communities plays a key role. In the context of the set design, examples of tools for social interaction support, navigation support, and (formative) assessment support are inventoried. Together, the results of the analysis of epistemic design, the guidelines for social design, and the inventory of tools for set design provide a valuable if still growing toolkit to the designer of learning networks.

A new approach for overcoming the language and culture barriers to participation in Massive Open Online Courses (MOOCs) is reported. It is hypothesised that the juxtaposition of English as the language of instruction, used for interacting with course materials, and one’s preferred language as the language of participation, used for interaction with peers and facilitators, is preferable to “English only” for participation in a MOOC. The Hands-On ICT (HANDSON) MOOC included seven teams of facilitators, each catering for a different language community. Facilitators were responsible for promoting active participation and peer tutoring. Comparing language groups revealed a series of predictors of intention to learn, some of which became apparent in the first days of the MOOC already. The comparison also uncovered four critical factors that influence participation: facilitation, language of participation, group size, and a pre-existing sense of community. Especially crucial was reaching a sufficient number of active participants during the first week. We conclude that multilingual facilitation activates participation in MOOCs in various ways, and that synergy between the four aforementioned factors is critical for the formation of the learning network that supports a social dynamic of active participation. Our approach suggests future targets for the development of the multilingual and community potential of MOOCs.

Verslag van een symposium over docentprofessionalisering gehouden aan de Open Universiteit, Heerlen op 20 mei 2016 naar aanleiding van de oratie van Marjan Vermeulen en de afscheidsrede van Peter Sloep

Open learning environments, such as Massive Open Online Courses (MOOCs), often lack adequate learner collaboration opportunities; they are also plagued by high levels of drop-out. Introducing project-based learning (PBL) can enhance learner collaboration and motivation, but PBL does not easily scale up into MOOCS. To support definition and staffing of projects, team formation principles and algorithms are introduced to form productive, creative, or learning teams. These use data on the project and on learner knowledge, personality and preferences. A study was carried out to validate the principles and the algorithms. Students (n = 168) and educational practitioners (n = 56) provided the data. The principles for learning teams and productive teams were accepted, while the principle for creative teams could not. The algorithms were validated using team classifying tasks and team ranking tasks. The practitioners classify and rank small productive, creative and learning teams in accordance with the algorithms, thereby validating the algorithms outcomes. When team size grows, for practitioners, forming teams quickly becomes complex, as demonstrated by the increased divergence in ranking and classifying accuracy. Discussion of the results, conclusions, and directions for future research are provided.