The educational value of student generated podcasts

Podcasting is becoming a well established technology in Higher Education (HE). However, most applications tend to use staff-developed content to provide material to supplement lectures. The use of learner-generated podcasts and its impact on the learning of both student producers and listeners are under researched. This paper reports on a pilot study of student-created podcasts. The podcasts were developed by a group of medical students at the University of Leicester who chose to study a genetic module in their second year. The content of the podcasts was entirely generated by students. Their topics covered a range of ethical issues surrounding genetics. Five student-developed podcasts were made available in early 2007 for other medical students to access through the Medical School Virtual Learning Environment (VLE). The study focused on the impact of these student-developed podcasts on student producers’ learning. It demonstrated how podcasting can empower learners and help them become more active and independent learners, and how student developed podcasts can promote engagement and motivation for learning, improve cognitive learning and develop transferable team-working skills among student producers. This paper offers an example of student-generated podcasts from practice and insights on how this practice might be expanded and transferred to other learning contexts with HE sectors

Simpler Analyses of Union-Find

We analyze union-find using potential functions motivated by continuous algorithms, and give alternate proofs of the $O(\log\log{n})$, $O(\log^{*}n)$, $O(\log^{**}n)$, and $O(\alpha(n))$ amortized cost upper bounds. The proof of the $O(\log\log{n})$ amortized bound goes as follows. Let each node's potential be the square root of its size, i.e., the size of the subtree rooted from it. The overall potential increase is $O(n)$ because the node sizes increase geometrically along any tree path. When compressing a path, each node on the path satisfies that either its potential decreases by $\Omega(1)$, or its child's size along the path is less than the square root of its size: this can happen at most $O(\log\log{n})$ times along any tree path.Comment: 13 pages, 1 figur

A Neural Network Approach to Context-Sensitive Generation of Conversational Responses

We present a novel response generation system that can be trained end to end on large quantities of unstructured Twitter conversations. A neural network architecture is used to address sparsity issues that arise when integrating contextual information into classic statistical models, allowing the system to take into account previous dialog utterances. Our dynamic-context generative models show consistent gains over both context-sensitive and non-context-sensitive Machine Translation and Information Retrieval baselines.Comment: A. Sordoni, M. Galley, M. Auli, C. Brockett, Y. Ji, M. Mitchell, J.-Y. Nie, J. Gao, B. Dolan. 2015. A Neural Network Approach to Context-Sensitive Generation of Conversational Responses. In Proc. of NAACL-HLT. Pages 196-20

Origin and evolution of the RIG-I like RNA helicase gene family

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MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks

Human commonsense understanding of the physical and social world is organized around intuitive theories. These theories support making causal and moral judgments. When something bad happens, we naturally ask: who did what, and why? A rich literature in cognitive science has studied people's causal and moral intuitions. This work has revealed a number of factors that systematically influence people's judgments, such as the violation of norms and whether the harm is avoidable or inevitable. We collected a dataset of stories from 24 cognitive science papers and developed a system to annotate each story with the factors they investigated. Using this dataset, we test whether large language models (LLMs) make causal and moral judgments about text-based scenarios that align with those of human participants. On the aggregate level, alignment has improved with more recent LLMs. However, using statistical analyses, we find that LLMs weigh the different factors quite differently from human participants. These results show how curated, challenge datasets combined with insights from cognitive science can help us go beyond comparisons based merely on aggregate metrics: we uncover LLMs implicit tendencies and show to what extent these align with human intuitions.Comment: 34 pages, 7 figures. NeurIPS 202

Sequence and Expression Analysis of Interferon Regulatory Factor 10 (IRF10) in Three Diverse Teleost Fish Reveals Its Role in Antiviral Defense

Acknowledgments This research was supported financially by the National Natural Science Foundation of China (31101928), the National Science and Technology Support Program of China (2013BAD20B06), the State Key Laboratory of Freshwater Ecology and Biotechnology (2010FB02) and the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) funded by the Scottish Funding Council (grant reference HR09011). Q.X. and Y.J. were supported financially by the National Scholarship Council of China. Funding: This research was supported financially by the National Natural Science Foundation of China (31101928), the National Science and Technology Support Program of China (2013BAD20B06), the State Key Laboratory of Freshwater Ecology and Biotechnology (2010FB02) and the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) funded by the Scottish Funding Council (grant reference HR09011). Q.X. and Y.J. were supported financially by the National Scholarship Council of China. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Sequence and expression analysis of rainbow trout CXCR2, CXCR3a and CXCR3b aids interpretation of lineage-specific conversion, loss and expansion of these receptors during vertebrate evolution

Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved. Open Access funded by Biotechnology and Biological Sciences Research Council This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. Q.X. and Y.J. were supported financially by the National Scholarship Council of China, J.W.H by the Biotechnology and Biological Sciences Research Council (BB/K009125/1), and M.M.M. by European Commision LIFECYCLE project (222919).Peer reviewedPublisher PD

Intracellular interferons in fish : a unique means to combat viral infection

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