IDR : a participatory methodology for interdisciplinary design in technology enhanced learning

One of the important themes that emerged from the CAL’07 conference was the failure of technology to bring about the expected disruptive effect to learning and teaching. We identify one of the causes as an inherent weakness in prevalent development methodologies. While the problem of designing technology for learning is irreducibly multi-dimensional, design processes often lack true interdisciplinarity. To address this problem we present IDR, a participatory methodology for interdisciplinary techno-pedagogical design, drawing on the design patterns tradition (Alexander, Silverstein & Ishikawa, 1977) and the design research paradigm (DiSessa & Cobb, 2004). We discuss the iterative development and use of our methodology by a pan-European project team of educational researchers, software developers and teachers. We reflect on our experiences of the participatory nature of pattern design and discuss how, as a distributed team, we developed a set of over 120 design patterns, created using our freely available open source web toolkit. Furthermore, we detail how our methodology is applicable to the wider community through a workshop model, which has been run and iteratively refined at five major international conferences, involving over 200 participants

Refining Implicit Argument Annotation for UCCA

Predicate-argument structure analysis is a central component in meaning representations of text. The fact that some arguments are not explicitly mentioned in a sentence gives rise to ambiguity in language understanding, and renders it difficult for machines to interpret text correctly. However, only few resources represent implicit roles for NLU, and existing studies in NLP only make coarse distinctions between categories of arguments omitted from linguistic form. This paper proposes a typology for fine-grained implicit argument annotation on top of Universal Conceptual Cognitive Annotation's foundational layer. The proposed implicit argument categorisation is driven by theories of implicit role interpretation and consists of six types: Deictic, Generic, Genre-based, Type-identifiable, Non-specific, and Iterated-set. We exemplify our design by revisiting part of the UCCA EWT corpus, providing a new dataset annotated with the refinement layer, and making a comparative analysis with other schemes.Comment: DMR 202

Induction of root and pattern lexicon for unsupervised morphological analysis of Arabic

We propose an unsupervised approach to learning non-concatenative morphology, which we apply to induce a lexicon of Arabic roots and pattern templates. The approach is based on the idea that roots and patterns may be revealed through mutually recursive scoring based on hypothesized pattern and root frequencies. After a further iterative refinement stage, morphological analysis with the induced lexicon achieves a root identification accuracy of over 94%. Our approach differs from previous work on unsupervised learning of Arabic morphology in that it is applicable to naturally-written, unvowelled text