60,007 research outputs found
Ripple: Concept-Based Interpretation for Raw Time Series Models in Education
Time series is the most prevalent form of input data for educational
prediction tasks. The vast majority of research using time series data focuses
on hand-crafted features, designed by experts for predictive performance and
interpretability. However, extracting these features is labor-intensive for
humans and computers. In this paper, we propose an approach that utilizes
irregular multivariate time series modeling with graph neural networks to
achieve comparable or better accuracy with raw time series clickstreams in
comparison to hand-crafted features. Furthermore, we extend concept activation
vectors for interpretability in raw time series models. We analyze these
advances in the education domain, addressing the task of early student
performance prediction for downstream targeted interventions and instructional
support. Our experimental analysis on 23 MOOCs with millions of combined
interactions over six behavioral dimensions show that models designed with our
approach can (i) beat state-of-the-art educational time series baselines with
no feature extraction and (ii) provide interpretable insights for personalized
interventions. Source code: https://github.com/epfl-ml4ed/ripple/.Comment: Accepted as a full paper at AAAI 2023: 37th AAAI Conference on
Artificial Intelligence (EAAI: AI for Education Special Track), 7-14 of
February 2023, Washington DC, US
Using motivation derived from computer gaming in the context of computer based instruction
This paper was originally presented at the IEEE Technically Sponsored SAI Computing Conference 2016, London, 13-15 July 2016. Abstract— this paper explores how to exploit game based motivation as a way to promote engagement in computer-based instruction, and in particular in online learning interaction. The paper explores the human psychology of gaming and how this can be applied to learning, the computer mechanics of media presentation, affordances and possibilities, and the emerging interaction of playing games and how this itself can provide a pedagogical scaffolding to learning. In doing so the paper focuses on four aspects of Game Based Motivation and how it may be used; (i) the game player’s perception; (ii) the game designers’ model of how to motivate; (iii) team aspects and social interaction as a motivating factor; (iv) psychological models of motivation. This includes the increasing social nature of computer interaction. The paper concludes with a manifesto for exploiting game based motivation in learning
Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph
Police SWAT teams and Military Special Forces face mounting pressure and
challenges from adversaries that can only be resolved by way of ever more
sophisticated inputs into tactical operations. Lethal Autonomy provides
constrained military/security forces with a viable option, but only if
implementation has got proper empirically supported foundations. Autonomous
weapon systems can be designed and developed to conduct ground, air and naval
operations. This monograph offers some insights into the challenges of
developing legal, reliable and ethical forms of autonomous weapons, that
address the gap between Police or Law Enforcement and Military operations that
is growing exponentially small. National adversaries are today in many
instances hybrid threats, that manifest criminal and military traits, these
often require deployment of hybrid-capability autonomous weapons imbued with
the capability to taken on both Military and/or Security objectives. The
Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of
Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that
required military response and police investigations against a fighting cell of
the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade
The Faculty Notebook, September 2019
The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost
Technology-enhanced Personalised Learning: Untangling the Evidence
Technology-enhanced personalised learning is not yet common in Germany, which is why we have tasked scientists with summarising the current status of international research on the matter. This study demonstrates the great potential of technology in implementing effective personalised learning. Nevertheless, it has not been assessed yet whether the practical implementation actually works: Even in countries such as the U.S., which lead the way in using techology in classroom settings, hardly any evaluation studies have been done to prove the effectiveness of technology-enhanced personalised learning. In the light of the above, the authors make recommendations for actions to be taken in Germany to make best use of the potential of technology in providing individual support and guidance to students
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