The document is an abstract for a PhD student conference that describes Thomas Daniel Ullmann's proposed PhD thesis. The thesis aims to develop a framework for mash-up learning environments that allows users to reflect on resources to make informed decisions. Mash-ups combine separate data sources and APIs to create new applications. The goal is to provide reflection functionality in a mash-up environment by including manually and automatically added indicators to foster reflection on resources and topics.

1. 2010 CRC PhD Student Conference
Supporting Reflection about Web Resources within Mash-
Up Learning Environments
Thomas Daniel Ullmann
t.ullmann@open.ac.uk
Supervisors Peter Scott
Fridolin Wild
Department/Institute Knowledge Media Institute – The Open University
Status Fulltime
Probation viva Before
Starting date October 2010
The proposed PhD thesis addresses the problem of how to empower users to reflect
about resources, helping them to make informed decisions. The goal of the PhD is to
develop a framework of a mash-up learning environment that takes into account the
reflection of users about resources.
Mashups are usually seen as software applications that merge separate APIs or data
sources (Zang, Rosson, and Nasser 2008). They compose new applications based on
existing data services and user interfaces. Mashups are “a combination of pre-existing,
integrated units of technology, glued together to achieve new functionality, as
opposed to creating that functionality from scratch” (Hartmann, Doorley, and
Klemmer 2006). They are the manifestation of the programmable web (Maximilien,
Ranabahu, and Gomadam 2008).
Learners looking at the wealth of available learning resources need strategies to deal
with its complexity. The abilities to reflect about information, to rate, and to review it,
seem to be important skills to cope with this. Many tools are available on the web
addressing these challenges. For example, search engines, one of the major backbones
of the web, deliver a ranked result set of more or less relevant information.
Recommendation services aggregate opinions of users to top lists of items or use
collaborative filtering mechanisms to make predictions about future interests of users.
While these services lack connectivity and do not explicitly address reflective practice,
Mashup Personal Learning Environments (MUPPLEs) (Wild, Mödritscher, and
Sigurdarson 2008) enable learners to construct their own learning space through
facilities to mash up services and tools from different sources to support collaborative
and individual learning activities.
Research carried out in the context of reflection (e.g. (Dewey 1933); (Boud, Keogh,
and Walker 1985); (Schön 1983); (Moon 1999)(Moon 2004)) finds its application in
mash-up personal learning environments in form of indicators (Glahn 2009).
Indicators are usually small widgets embedded in a learning system, which represents
information for the learners for example about their activity level or performance
measure. While indicators focus on the visualization of interaction footprints, methods
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2. 2010 CRC PhD Student Conference
coming from evaluation research (Thierau and Wottawa 1990), especially of
qualitative (Stake, Denzin, and Lincoln 2005) and quantitative (Neuman 2005)
research are considered as possible reflection points about (web) resources.
The goal is to provide users these functionalities in a mash-up environment. In order
to reflect about a topic the proposed system takes into account manually added
indicators as well as automatically added criteria fostering reflection. The later are
partly derived from the data services and tools of the Science 2.0 infrastructure ((Wild
and Ullmann 2010) and (Wild and Ullmann 2009)) for researchers in technology-
enhanced learning.
References:
Boud, David, Rosemary Keogh, and David Walker. 1985. Reflection: Turning
Experience into Learning. Routledge, April 1.
Dewey, J. 1933. How we think: A restatement of the relation of reflective thinking to
the educative process. DC Heath Boston.
Glahn, Christian. 2009. Contextual support of social engagement and reflection on the
Web. http://dspace.ou.nl/handle/1820/2062.
Hartmann, Björn, Scott Doorley, and Scott R Klemmer. 2006. Hacking, Mashing,
Gluing: A Study of Opportunistic Design and Development.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.66.1603.
Maximilien, E.M., A. Ranabahu, and K. Gomadam. 2008. An Online Platform for
Web APIs and Service Mashups. Internet Computing, IEEE 12, no. 5: 32-43.
doi:10.1109/MIC.2008.92.
Moon, Jennifer A. 1999. Reflection in learning & professional development.
Routledge.
———. 2004. A handbook of reflective and experiential learning. Routledge, June 15.
Neuman, W. L. 2005. Social research methods: Quantitative and qualitative
approaches. Allyn and Bacon.
Schön, D. A. 1983. The reflective practitioner. Basic Books New York.
Stake, R. E, N. K. Denzin, and Y. S. Lincoln. 2005. The Sage handbook of qualitative
research. Sage Thousand Oaks, CA.
Thierau, H., and H. Wottawa. 1990. Lehrbuch Evaluation. Bern, Stuttgart, Toronto:
Huber.
Wild, Fridolin, Felix Mödritscher, and Steinn Sigurdarson. 2008. Designing for
Change: Mash-Up Personal Learning Environments. eLearning Papers 9.
http://www.elearningeuropa.info/files/media/media15972.pdf.
Wild, Fridolin, and T. D. Ullmann. 2009. Science 2.0 Mash-Ups. STELLAR
Deliverable 6.3.
http://www.stellarnet.eu/kmi/deliverables/20100120_stellar___d6-3.pdf.
———. 2010. The STELLAR Science 2.0 Mash-Up Infrastructure. In Accepted paper
for the 10th IEEE International Conference on Advanced Learning
Technologies. Sousse, Tunisia.
Zang, Nan, Mary Beth Rosson, and Vincent Nasser. 2008. Mashups: who? what?
why? In CHI '08 extended abstracts on Human factors in computing systems,
3171-3176. Florence, Italy: ACM. doi:10.1145/1358628.1358826.
http://portal.acm.org/citation.cfm?id=1358826.
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