This paper presents doctoral research work on supporting social work professionals in learning through their personal professional networks and online Personal Learning Networks. In particular, it proposes an empirical investigation into current practice in order to develop appropriate technological support for the networking activities of building, maintaining and activating personal professional networks. It proposes a rethinking of functionality and usability of domain and network analysis technology to put these more in line with the actual needs and requirements of networked learners. The research methodology is presented as well as the current stage of the project.
Social work professionals deal with issues of health care, poverty, homelessness,
migration and integration in (inter)national environments supported by
governmental and non-governmental organisations (NGO). They carry out small-,
medium- and large-scale projects to achieve better social conditions for a speci c
target group, depending highly on their advanced knowledge and competencies.
As they work individually or in small teams in well-de ned unique environments,
they often cannot depend on traditional standardized organisational support
structures for professional learning (such as in standard business processes and
solutions, courses, etc.). Therefore, they need to develop non-conventional
learning strategies to succeed in their goals. Learning in this context is aimed at
developing the individuals'skills and abilities to deal with complex problems [
As a consequence, these professionals are independently responsible to
continuously plan their learning in order to acquire and create new skills and knowledge
to ful l the jobs demands successfully. They develop their individual expertise
through the experiences they gain along the way in di erent projects and through
their own re ection, thereby building up a high level of tacit knowledge [1{3].
They also greatly emphasise the importance of sharing their experiences and
re ections with each other [
Therefore, learning through experience and learning through social
interaction in particular seem to play a prominent role in the social work
professional context [
Such dialogues and discussions have the potential to in uence the learning of a social work professional, provided the professional is su ciently sensitive to this type of learning. Especially the learning theories of socio-constructivism and Connectivism support this, where a learner learns by internalising collaboratively created and constructed knowledge and builds on her personal ability to make connections in a meaningful way [12{14]. In this way, each dialogue partner brings their own unique input to an interaction and takes away whatever has been created in that unique interaction with others that is relevant for their own personal learning. As a consequence, the speci c expertise and experience of dialogue partners in these dialogues and discussions have an e ect on the quality of these interactive activities.
To create an environment in which e ective personal learning can occur,
social work professionals need to nd the right and most relevant dialogue
partner for a given problem, i.e. with the expertise and experience that that
learner considers most appropriate. The rst point of call to nd these dialogue
partners are their personal professional network, i.e. the network of people set up
by an individual speci cally in the context of her professional activities.
Professionals who consider their personal professional networks as a learning resource
may employ particular strategies in building, maintaining and activating that
network [
However, little research has been conducted on this aspect of personal
professional networks till date, as well as on the network of people an individual
creates on and through online platforms speci cally in the context of her
professional activities to support her professional non-formal learning needs, what
we call a `Personal Learning Network'. Studying the used strategies on the
content of the relation and on the process of nding and interacting with
potential dialogue partners will help in understanding better how professionals create
and use their personal professional networks for learning. More empirical data
from practice is needed to de ne and develop the concept of Personal Learning
Network against the background of the literature on Learning Networks [
It can be expected that professionals make considerable investments to conduct these strategies. This investment can be speci ed and studied with di erent perspectives, such as a social capital perspective, game-theoretical perspective (return on investment made), cost perspective (time and e ort needed to identify and contact relevant others), etc. Naturally, the more e ectively and e ciently professionals can build, maintain and activate their Personal Learning Network, the easier it will be to nd relevant dialogue partners within this network to support their learning. Professionals use various technologies to support these activities. Particularly, domain and network analysis technology o ers various solutions to increase the e ectiveness and e ciency in gaining insight into the experience and expertise present in existing networks (recommender systems and social matching systems [20{22], expert systems [23{25], network visualisations [26{29]). However, it is unclear if the extracted information is relevant to professionals and if this information is presented in a suitable way; in other words, does the functionality and usability of this technology e ectively match the professionals needs? 2
The focus of this research project will be on investigating how social work professionals create and use their Personal Learning Networks and how the technology they use for supporting these networks can be optimized to help them in doing this more e ectively and e ciently. The research question is `what is the relationship between the functionality and usability of network analysis technology and its e ectiveness and e ciency in optimizing the investment needed (among others costs such as time, e ort, etc.) in building, maintaining and activating a Personal Learning Network to nd relevant dialogue partners?'The sub-questions are: { What are the guiding principles in building, maintaining and activating a Personal Learning Network that maximize the quality of such a network as a source for relevant dialogue partners? { To what extent does existing network analysis technology e ectively reduce the investment required (such as transaction costs incurred) for building, maintaining and activating a Personal Learning Network? { How can the e ectiveness and e ciency of existing network analysis technology in reducing the required investment be improved with regards to the relevance of the information provided and the method in which it is provided (functionality and usability of the technology)? As the quality of dialogues and discussions with dialogue partners is in uenced by their speci c expertise and experience, a better view on their expertise and experience might enable better and more e ective personal learning networks. The hypothesis is that a di erent approach to functionality and usability in network analysis technology, which o ers more relevant information in line with the needs of professionals and presents this information in a more suitable way, will increase the e ectiveness and e ciency of this technology by reducing the investment costs incurred in designing and using Personal Learning Networks. In turn, this will enable professionals to create and use Personal Learning Networks of higher quality in less time. 3
This research project has a conceptual and a technological aim. Conceptually, it aims to de ne the concept of a Personal Learning Network more closely in relation to the concepts of Learning Networks and Personal Learning Environments, by basing it on data on how these networks are built, maintained and activated in practice. Technologically, it aims to gauge the usability and usefulness of domain and network visualisations of a personal learning network in order to improve the e ciency and e ectiveness of these technologies for individual users through the addition of value-adding personalising features. The project consists of three phases: 1. Exploring Phase: in this phase, more insight will be gained into the practice of learning in personal professional networks. The notion of `quality of personal networks 'and criteria to assess this will be de ned in this phase on the basis of exploratory open-ended interviews. Through a structured survey and possibly some selected in-depth interviews, a working framework on Personal Learning Networks will be created and user requirements for technology will be de ned. 2. Design and Development Phase: in this phase, the de ned user requirements will be translated into the design and implementation of a technical artefact. 3. Experimental Phase: in this phase, experiments will be conducted with the developed artefact to investigate the in uence of functionality and usability on learning in professional networks. 4
At the time of writing, the doctoral research is in the rst phase. A literature study was taken as a starting point to identify the factors in uencing the building, maintaining and activating of personal professional networks. However, as the projected outcome of this literature study is low, 6 exploratory, semi-structured and open-ended interviews with selected interviewees will also be conducted. These interviewees are people in the development sector who have set up concrete projects from scratch: they have gone through the process of identifying and understanding a complex problem and of devising a solution for this problem. As learning through networks seems to be a skill to be learnt, there will be 3 novices (under 5 years experience in the sector) and 3 experts (more than 5 years experience) in these interviews. A survey will be developed and conducted on 100 participants, who will be a representative sample of professionals working in social work. The criteria to select these participants are to be de ned, but will include the extent of their experience in the sector and the level of their pro ciency in using their personal networks for learning.
Acknowledgements. This paper presents a doctoral study conducted within the LTfLL project. The LTfLL project is partially supported/co-funded by the European Union under the Information and Communication Technologies (ICT) theme of the 7th Framework Programme for R&D. This document does not represent the opinion of the European Union, and the European Union is not responsible for any use that might be made of its content.