Results 51 to 60 of about 12,004,986 (327)
Practices, policies, and problems in the management of learning data: A survey of libraries’ use of digital learning objects and the data they create [PDF]
, 2019 This study analyzed libraries’ management of the data generated by library digital learning objects (DLO’s) such as forms, surveys, quizzes, and tutorials.
Atwood, Gary +2 more
core +2 more sources
, 2020 This is the author accepted manuscript. The final version is available from SAGE Publications via the ISBN in this record ; Learning is a fascinating topic for political science. Whether we look at comparative politics, public policy, or governance, we find that all these three main fields of political science are concerned with learning – but in ...
Dunlop, CA, Radaelli, CM
openaire +2 more sources
Learning Replanning Policies With Direct Policy Search [PDF]
IEEE Robotics and Automation Letters, 2019 Direct policy search has been successful in learning challenging real-world robotic motor skills by learning open-loop movement primitives with high sample efficiency. These primitives can be generalized to different contexts with varying initial configurations and goals.
Florian Brandherm +3 more
openaire +3 more sources
Policy sciences, 2021 Policy learning can alter the perceptions of both the seriousness and the causes of a policy problem, thus also altering the perceived need to do something about the problem. This then allows for the informed weighing of different policy options.
A. Gronow +4 more
semanticscholar +1 more source
Campbell Systematic Reviews, 2007 There is a lack of evidence about the efficacy of behavioural or cognitive‐behavioural training interventions for foster carers. The programmes are intended to assist foster carers in the management of the difficult behaviour of looked‐after children and
William Turner +2 more
doaj +1 more source
Policy learning and policy evaluation
, 2023 Published online: 19 October 2023 The theory and practice of evaluation have often been inspired by the motivation to learn. We explain the conceptual and causal connections between evaluation and learning, addressing three questions: what is the content of learning that is expected from evaluations? How is learning created? And what is learning useful
Claire A. Dunlop, Claudio M. Radaelli
openaire +3 more sources
Learning modular policies for robotics [PDF]
Frontiers in Computational Neuroscience, 2014 A promising idea for scaling robot learning to more complex tasks is to use elemental behaviors as building blocks to compose more complex behavior. Ideally, such building blocks are used in combination with a learning algorithm that is able to learn to select, adapt, sequence and co-activate the building blocks.
Neumann, G. +4 more
openaire +6 more sources
Anticipated Fiscal Policy and Adaptive Learning [PDF]
, 2007 We consider the impact of anticipated policy changes when agents form expectations using adaptive learning rather than rational expectations. To model this we assume that agents combine limited structural knowledge with a standard adaptive learning rule.
Evans, George W. +2 more
core +2 more sources
Learning Optimal Fair Policies
Proceedings of machine learning research, 2018 Systematic discriminatory biases present in our society influence the way data is collected and stored, the way variables are defined, and the way scientific findings are put into practice as policy. Automated decision procedures and learning algorithms applied to such data may serve to perpetuate existing injustice or unfairness in our society.
Nabi, Razieh +2 more
openaire +3 more sources
Policy learning and policy change: exploring possibilities on the Advocacy Coalition Framework
Revista de Administração Pública, 2020 This article aims to advance the discussion about the influence of knowledge and policy learning on policy change, taking the Advocacy Coalition Framework as reference. We propose unlinking the comprehension of learning through change in two perspectives.
Janaina Ma, Diego Mota Vieira
doaj +2 more sources