Services, Semantics, and Standards: Elements of a Learning Grid Infrastructure

Allison, Colin; Cerri, Stefano A.; Ritrovato, Pierluigi; Gaeta, Angelo; Gaeta, Matteo

doi:10.1080/08839510500234271

Cited by 26 publications

(18 citation statements)

References 5 publications

(5 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The results bear out our choice of a synthetic variable measuring quality, implicitly gathering together information, system, and service qualities. The statistically significant hypotheses of our confirmation model involving ERS Quality substantiate the relevance of retaining a service orientation for measuring such solutions (Allison et al, 2005). Our analysis also validates the choice of the individual and organizational levels at which to measure the net benefits of ERS, since the hypotheses are statistically confirmed with high regression weights.…”

Section: Ers Success For Customerssupporting

confidence: 59%

“…Fourthly and finally, our focus on the 'service' delivered is deemed appropriate, as the knowledge seeker may only partially be able to formulate or express what knowledge they hope to gain from the expert, so the precise identification of the specific knowledge and of the expert required may depend on interaction between the expert seeker and the expert recommender (Allison et al, 2005;Spohrer & Riecken, 2006): such interaction is a typical service component (Chesbrough & Spohrer, 2006). Furthermore, looking at ERS as a service allows us to focus on customer activities and concerns, and on how the seeker, recommender and expert co-produce value (Alter, 2008).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The success of Expert Recommending Services and the part played by organizational context

Vitari

2011

Knowledge Management Research & Practice

View full text Add to dashboard Cite

Knowledge Management (KM) practice includes services designed to reduce the difficulty of sourcing knowledge, that is, getting the right knowledge to the right people at the right time. The phenomenon addressed in the study reported in this paper is a specific type of KM service -the Expert Recommending Service (ERS) -which contributes to achieving the difficult objective of getting the right expert to the right people at the right time. The findings of the study identify the dimensions of ERS success in different organizational contexts and the organizational characteristics that influence ERS success. Research contributions of the study are therefore two-fold. On the one hand, our results show that, among all the organizational characteristics, being aware of others, and specifically of others' knowledge domains, influences ERS success. On the other hand, our results suggest that ERS success can be significantly measured by employing the following dimensions: Quality, Use, Satisfaction, Individual Net Benefit, and Organizational Net Benefit. We also propose a set of recommendations for practitioners to help improve the success of their ERS, taking into account the informal expert recommending processes, improving the accessibility of all personnel to knowledge about their colleagues and considering the organizational characteristics, in particular awareness, before launching new ERS.

show abstract

Section: Ers Success For Customerssupporting

confidence: 59%

Section: Introductionmentioning

confidence: 99%

The success of Expert Recommending Services and the part played by organizational context

Vitari

2011

Knowledge Management Research & Practice

View full text Add to dashboard Cite

show abstract

“…This paradigm promotes the focus on stateful services and on flexibility in the way they are combined [3]. Unlike stateless services, stateful ones keep a record of the previous transactions; the interested reader can find more details on stateful services in [37].…”

Section: Introductionmentioning

confidence: 99%

Participatory Learner Modelling Design: A methodology for iterative learner models development

Cocea

Magoulas

2015

Information Sciences

View full text Add to dashboard Cite

Learner models are built to offer personalised solutions related to learning. They are often developed in parallel to the development of adaptive learning systems and thus, linked to the system's development.The adaptive learning systems literature reports numerous accounts of learner model development, but there are no reports on the methodological aspects of developing learner models and the relation between the development of the learner model component and the rest of the system. This paper presents the Participatory Learner Modelling Design methodology, which outlines the steps for learner model development and their relation to the development of the system. The methodology is illustrated with a case study of an adaptive educational system.

show abstract

“…The context-aware feature of the u-computing environments allows better understanding of both the user and the specific situation "around" him or her [7]. The term "ubiquitous" does not refer here simply to anytime/anywhere, but more specifically to the ability to support multiple diverse learning contexts and automatically adapt to them [3]. Currently, ubiquitous learning takes place in various education environments, in contrast with early applications of ubiquitous learning (tourist and museum guides), which offered the possibility of getting information based on visitor's current position, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…More often, the communities will establish their own goals in terms of knowledge and skills to be acquired, instead of using a predefined curriculum. The goals themselves will fully correspond to learners' needs, and will be highly dependent on the local culture and its priorities [3].…”

Section: Introductionmentioning

confidence: 99%