9,984 research outputs found
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Innovating Pedagogy 2015: Open University Innovation Report 4
This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This fourth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Center for Technology in Learning at SRI International. We proposed a long list of new educational terms, theories, and practices. We then pared these down to ten that have the potential to provoke major shifts in educational practice, particularly in post-school education. Lastly, we drew on published and unpublished writings to compile the ten sketches of new pedagogies that might transform education. These are summarised below in an approximate order of immediacy and timescale to widespread implementation
Argumentation Mining in User-Generated Web Discourse
The goal of argumentation mining, an evolving research field in computational
linguistics, is to design methods capable of analyzing people's argumentation.
In this article, we go beyond the state of the art in several ways. (i) We deal
with actual Web data and take up the challenges given by the variety of
registers, multiple domains, and unrestricted noisy user-generated Web
discourse. (ii) We bridge the gap between normative argumentation theories and
argumentation phenomena encountered in actual data by adapting an argumentation
model tested in an extensive annotation study. (iii) We create a new gold
standard corpus (90k tokens in 340 documents) and experiment with several
machine learning methods to identify argument components. We offer the data,
source codes, and annotation guidelines to the community under free licenses.
Our findings show that argumentation mining in user-generated Web discourse is
a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in
User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17
S-COL: A Copernican turn for the development of flexibly reusable collaboration scripts
Collaboration scripts are usually implemented as parts of a particular collaborative-learning platform. Therefore, scripts of demonstrated effectiveness are hardly used with learning platforms at other sites, and replication studies are rare. The approach of a platform-independent description language for scripts that allows for easy implementation of the same script on different platforms has not succeeded yet in making the transfer of scripts feasible. We present an alternative solution that treats the problem as a special case of providing support on top of diverse Web pages: In this case, the challenge is to trigger support based on the recognition of a Web page as belonging to a specific type of functionally equivalent pages such as the search query form or the results page of a search engine. The solution suggested has been implemented by means of a tool called S-COL (Scripting for Collaborative Online Learning) and allows for the sustainable development of scripts and scaffolds that can be used with a broad variety of content and platforms. The tool’s functions are described. In order to demonstrate the feasibility and ease of script reuse with S-COL, we describe the flexible re-implementation of a collaboration script for argumentation in S-COL and its adaptation to different learning platforms. To demonstrate that a collaboration script implemented in S-COL can actually foster learning, an empirical study about the effects of a specific script for collaborative online search on learning activities is presented. The further potentials and the limitations of the S-COL approach are discussed
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Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL
Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N
Persuasion Monologue
The emphasis in most process-oriented models of argumentation is placed heavily upon analysis of dialogue. The current work puts forward an account which examines the argumentation involved in persuasive monologue, drawing upon commitment-based theories of dialogue. The various differences between monologue and dialogue are discussed, with particular reference to the possibility of designing a monologue game in which commitments are dynamically incurred and updated as the monologue is created. Finally, the computational advantages of adopting such an approach are explored in the context of an existing architecture for the generation of natural language arguments
GHOST: experimenting countermeasures for conflicts in the pilot's activity
An approach for designing countermeasures to cure
conflict in aircraft pilots’ activities is presented,
both based on Artificial Intelligence and Human
Factors concepts.
The first step is to track the pilot’s activity, i.e. to
reconstruct what he has actually done thanks to the
flight parameters and reference models describing
the mission and procedures. The second step is
to detect conflict in the pilot’s activity, and this is
linked to what really matters to the achievement
of the mission. The third step is to design accu-
rate countermeasures which are likely to do bet-
ter than the existing onboard devices. The three
steps are presented and supported by experimental
results obtained from private and professional pi-
lots
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