by J. Biggs and C. Tang, Maidenhead, England,
Open University Press, 2007, 360 pp., £29.99, ISBN-13: 978-0-335-22126-4

Teaching for quality learning at university

How to ... be a reflective practitioner.

Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent’s PGM, Pacific Biosciences’ RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. Sequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform. All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.

/pdf/a-tale-of-three-next-generation-sequencing-platforms-kwlq74rwzb.pdf

A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers.

Thank you very much for downloading flow the psychology of optimal experience. As you may know, people have search numerous times for their chosen readings like this flow the psychology of optimal experience, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their desktop computer. flow the psychology of optimal experience is available in our digital library an online access to it is set as public so you can get it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the flow the psychology of optimal experience is universally compatible with any devices to read.

Flow The Psychology Of Optimal Experience

Learning analytics is a significant area of technology-enhanced learning that has emerged during the last decade. This review of the field begins with an examination of the technological, educational and political factors that have driven the development of analytics in educational settings. It goes on to chart the emergence of learning analytics, including their origins in the 20th century, the development of data-driven analytics, the rise of learning-focused perspectives and the influence of national economic concerns. It next focuses on the relationships between learning analytics, educational data mining and academic analytics. Finally, it examines developing areas of learning analytics research, and identifies a series of future challenges.

/pdf/learning-analytics-drivers-developments-and-challenges-217xn78a36.pdf

Learning analytics: drivers, developments and challenges

This paper questions an exclusively state-centred framing of global health justice and proposes a multilateral alternative. Using the distribution of COVID-19 vaccines to illustrate, we bring to light a broad range of global actors up and down the chain of vaccine development who contribute to global vaccine inequities. Section 1 (Background) presents an overview of moments in which diverse global actors, each with their own priorities and aims, shaped subsequent vaccine distribution. Section 2 (Collective action failures) characterises collective action failures at each phase of vaccine development that contributed to global vaccine disparities. It identifies as critical the task of establishing upstream strategies to coordinate collective action at multiple stages across a range of actors. Section 3 (A Multilateral model of global health governance) takes up this task, identifying a convergence of interests among a range of stakeholders and proposing ways to realise them. Appealing to a responsibility to protect (R2P), a doctrine developed in response to human rights atrocities during the 1990s, we show how to operationalise R2P through a principle of subsidiarity and present ethical arguments in support of this approach.

/pdf/towards-a-new-model-of-global-health-justice-the-case-of-25558cun.pdf

Towards a new model of global health justice: the case of COVID-19 vaccines

This paper considers the issue of 'noticing' in second language acquisition, and argues for the potential of handheld devices to: (i) support language learners in noticing and recording noticed features 'on the spot', to help them develop their second language system; (ii) help language teachers better understand the specific difficulties of individuals or those from a particular language background; and (iii) facilitate data collection by applied linguistics researchers, which can be fed back into educational applications for language learning. We consider: theoretical perspectives drawn from the second language acquisition literature, relating these to the practice of writing language learning diaries; and the potential for learner modelling to facilitate recording and prompting noticing in mobile assisted language learning contexts. We then offer guidelines for developers of mobile language learning solutions to support the development of language awareness in learners.

Theoretical perspectives on mobile language learning diaries and noticing for learners,teachers and researchers

This paper investigates the potential for simple open learner models for highly motivated, independent learners, using the example of trainee pilots. In particular we consider whether such users access their learner model to help them identify their current knowledge level, areas of difficulty and specific misconceptions, to help them plan their immediate learning activities; and whether they find a longer-term planning aid useful. The Flight Club open learner model was deployed in a UK flight school over four weeks. Results suggest that motivated users such as trainee pilots will use a system with a simple open learner model, and are interested in consulting their learner model information both to facilitate planning over time, and to understand their current knowledge state. We discuss the extent to which our findings may be relevant to learners in other contexts. Keywords: Intelligent Tutoring Systems; learner model; open learner model; trainee pilots DOI: 10.1080/09687760802318436

https://files.eric.ed.gov/fulltext/EJ809751.pdf

An open learner model for trainee pilots

Many factors affect the learning of a foreign language. When designing computer assisted language learning software it is usually not sufficient to think only about creating an exercise in the language, but students should be modelled in order to allow the program to take account of individuals' beliefs and learning. However, student models are criticised for various reasons, the most common of which include: 1. Modelling the learner places a great burden on the system, as it has sole responsibility for the creation of an accurate student model. 2. Student models are inadequate because it is not possible to model all aspects of a student's knowledge and learning. This paper describes the student model of an intelligent computer assisted language learning (ICALL) system which strives to overcome problems of traditional student models by taking into account issues important in the field of second language acquisition, and research in collaborative approaches to learning.

Learning languages: Implications for student modelling in ICALL

Adpating to user context versus adapting to individual user features or behaviour patterns has been a topic of recent discussion. We believe both types of adaptation are valuable and the decision of which to apply, or how to combine the two, is domain or application specific. As an illustration, this paper presents two approaches to adapting the interface according to the type of user and the extent to which the user’s task and location is predetermined.

/pdf/location-aware-adaptive-interfaces-for-information-access-5d1clhrnc0.pdf

Location-aware adaptive interfaces for information access with handheld computers

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Susan Bull

Author Tools

Chat about Author