EMA

EMA

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1 Introduction

The EMA accounts for 50% of your final mark. It also gives you an opportunity to extend your understanding of data management beyond what’s provided elsewhere in the module, by developing a more detailed knowledge of a topic that is of particular relevance to your own interests or career aspirations. The EMA will require you to take a coherent academic approach to discussing how recent research innovations could affect the practice of data management.
In terms of skills, the EMA builds on the research skills you’ve acquired through your practical and continuous assessment work.
The EMA topic will be one that interests you and for which there is a significant amount of prior academic and/or professional research that provides the detailed information you’ll need. The topic of the EMA can be drawn from any area of data management that is covered by or relevant to the module, and that you feel is relevant to you or your organisation.
2 Learning outcomes
The EMA will validate your ability to:
· select a relevant topic related to data management
· select and critically appraise appropriate resources on your chosen topic.
3 What to submit

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The EMA has a 2500 word limit and consists of just one question, in the form of the following brief.
Using the knowledge, understanding and skills you’ve gained on M816, write a critical review of a data management topic that you’ve chosen. The topic should be of relevance to the data management community, to you and possibly your organisation, and should relate to the content of M816. You should base your critical review on three recent peer-reviewed articles that you’ve read.
Your critical review must include the following elements.
1. A description of the topic common to the articles along with an explanation of why this topic is of relevance to the data management community and (if applicable) to your organisation.
2. A summary of each article.
3. A comparison, contrastive analysis and evaluation of each article’s contribution to the topic you’ve identified.
4. A discussion of the extent to which the ideas set out in the articles might or might not be used to change policy and/or practice in data management, along with suggestions as to how any change might be incorporated.

EMA

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4 What’s expected of your answer
Your chosen topic may relate to a theme, issue, technique, approach, theory, or whatever, which relates to data management and the content of M816. However, if you choose a topic which is completely out of scope you’ll gain no marks.
You’re free to expand on topics you’ve already read about as part of your TMA work, or topics you’ve encountered while tracking the leading edge. In such cases you’re allowed to reuse at most one article out of those you’ve used previously as part of your TMA work.
You should pay particular attention to the quality of the articles you choose. All your articles must be peer-reviewed – that is, they should come from journals, conference proceedings, magazines or other periodicals which publish materials only after it has been independently assessed. In particular, leading scholarly journals and conference proceedings will contain articles which have been rigorously reviewed and which usually cover research topics at the leading edge of the subject. Scholarly articles are often authoritative surveys or reviews of a topic of interest, undertaken by experienced researchers. For the highest grades you should include at least two scholarly articles in your review. High-quality professional periodicals are also valuable; indeed, these are often a good place to start a search as they’ll usually point you to the original research on which a particular article is based.
We urge you to use the electronic resources available via the Open University Library to identify and select appropriate articles, but you’re welcome to use additional sources – for example, any university or major public library. However, all your articles must be accessible online by the marker, being either free or accessible through the OU Library. If you access an article via an OU Library subscription you should inlcude the DOI (Digital Object Identifier), otherwise include the URL.
We actively caution you against using the internet in an indiscriminate fashion. In many cases, journal articles you find available at a price on the internet will be available free of charge via the OU Library. Your tutor will be able to offer general advice on whatever reading you propose to undertake, and feedback on whether what you’ve identified will support your work towards the grade you aspire to. However, this advice will relate mainly to the nature of the proposed source – tutors aren’t expected to engage with you in an extended discussion about the subject matter or content of your reading.
We don’t want to be dogmatic about interpreting ‘recent’ with regard to your choice of resources. As a guide, we would consider anything published within the last five years as very recent and within five to ten years as recent – but anything more than ten years old we would consider potentially dated. However, an item ten or more years old can still be a valid resource if it is authoritative, seminal, or offers a worthwhile viewpoint in light of recent developments affecting a given topic.
You should provide a full bibliographical reference for each of the three articles you’ve chosen, at the start of your critical review. You should use the OU Harvard style of referencing. See also the advice on the use of citations and references in the Assessment guide. If you’re reusing any article from M816, you should indicate this clearly in the references list.
Failure to provide references will result in an automatic Fail. If you do NOT cite your references in the text, then you are unlikely to score better than a Pass.
You should include an accurate word count on the front of your EMA (most word processors incorporate a tool that can count the words in a document or block of selected text). The word count should include any tables in the body of your EMA, but should not include figures, your list of references and covering pages. You should not have appendices in your EMA.
There is a tolerance of up to 10% over the limit, for which you will not be penalised, although markers are not obliged to mark any text above the total word limit for the EMA. Moreover, they are instructed to deduct up to five marks from the total awarded for the EMA for any additional material beyond the 10% excess.
Whenever appropriate, you should cite your chosen articles, relevant module materials, your experience of TMA activities and professional practice, and any additional reading you’ve undertaken throughout M816 that support your critical review. All articles, module texts and additional reading should be properly referenced and cited.

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Avoid all forms of plagiarism. Your EMA will be checked using plagiarism-detection software tools: if any issues are reported, your work will be carefully scrutinised by Award Board members. Evidence of plagiarism will result in an automatic Fail and possible disciplinary action.
In your critical review, the marker will look for evidence of good coverage of what is required in the brief, including good understanding of knowledge and principles, ability to critically evaluate the knowledge contained in the articles, ability to relate such knowledge to module materials and professional practice, capacity to form judgements properly informed by evidence, and ability to communicate clearly and effectively to a knowledgeable and specialist audience. For the highest marks, good evidence of synthesis is essential.
Finally, presentation is also important – so please make sure your essay is properly structured and that you’ve checked that any typographic and/or grammatical errors have been removed.
The tables below outline the criteria that will be used to assess your EMA.
Content

Grades (marks)/
Content Distinction (85%+) Merit (70 to 84%) Pass (40 to 69%) Fail with resubmission (15 to 39%) Fail (0 to 14%)
1. A description of the topic common to the articles along with an explanation of why this topic is of relevance to the data management community and (if applicable) to your organisation. Excellent description of the topic and explanation of its relevance. Good depth and breadth of topic coverage. Good description of the topic and explanation of its relevance. Good topic coverage but imbalance in respect of breadth vs. depth. Limited description of the topic and explanation of its relevance. Good topic coverage but mainly in respect of breadth. Poor understanding of the topic with emphasis on description of the reading. Limited or no understanding of the topic; mainly a descriptive account of the reading.
2. A summary of each article. An excellent objective outline of each article, describing the main ideas and the evidence supporting those ideas. A good objective outline of each article, describing the main ideas and the evidence supporting those ideas. A good objective outline of each article, describing the main ideas but with little evidence presented supporting those ideas. Limited description of the main ideas with little evidence presented supporting those ideas. Limited description of the main ideas with no evidence presented supporting those ideas.
3. A comparison, contrastive analysis and evaluation of each article’s contribution to the topic they’ve identified. An excellent evaluation of each article’s contribution to the topic. A good evaluation of each article’s contribution to the topic. A limited evaluation of each article’s contribution to the topic. Each article’s contribution to the topic is unclear or evaluation is incomplete. No evaluation of each article’s contribution to the topic.
4. A discussion of the extent to which the ideas set out in the articles might or might not be used to change policy and/or practice in data management, along with suggestions as to how any change might be incorporated. A thorough discussion of how the ideas set out in the articles will contribute to data management. A good discussion of how the ideas set out in the articles will contribute to data management. An incomplete discussion of how the ideas set out in the articles will contribute to data management. Not all ideas are discussed and/or their impact on data management described. An incomplete discussion of how the ideas set out in the articles will contribute to data management. Only a few ideas are discussed or their impact on data management is not described. No discussion of how the ideas set out in the articles will contribute to data management.
Skills demonstrated

Grades (marks)/
Skills demonstrated Distinction (85%+) Merit (70 to 84%) Pass (40 to 69%) Fail with resubmission (15 to 39%) Fail (0 to 14%)
Knowledge and understanding of data management principles, practices and technologies. Authoritative interpretation of data management principles, practices and technologies; relates research to module where appropriate; wider reading. Sound in respect of data management principles, practices and technologies; relates research to module where appropriate; wider reading. Legitimate interpretation of most important data management principles, practices and technologies; relates research to module occasionally. ‘Literal’ or ‘rote-learnt’, occasionally incorrect, understanding of important data management principles, practices and technologies; largely descriptive account of research. Essential data management principles, practices and technologies not understood clearly; largely descriptive account of research which is related to module in a forced or contrived way.
Ability to evaluate new data management principles, practices and technologies proposed in recent professional, scholarly and research literature. Comprehends and evaluates new data management principles, practices and technologies from demanding sources of research and scholarship against clear and relevant criteria. Comprehends and evaluates new data management principles, practices and technologies from a variety of sources of research and scholarship against stated criteria. Comprehends and describes relevant new data management principles, practices and technologies from a variety of sources of research and scholarship. Descriptive rather than evaluative account of new data management principles, practices and technologies from relatively undemanding sources of research and scholarship. Descriptive account of principles, practices and technologies from ‘magazine’ style articles relating to data management
Ability to deploy a full range of analytic skills in relation to module materials, research and scholarly sources, and personal experience. Full range of skills evident; includes synthesis; shows clear insight. Comprehensive range of skills; excludes/weak on synthesis; some evidence of insight. Varied analytic skills. Mainly descriptive but some evidence of other skills. Entirely descriptive.
Ability to communicate clearly and effectively to examiners who constitute a knowledgeable and specialist audience. Clear, concise, structured communication using illustration where appropriate. Aimed at a knowledgeable and specialist audience. Statements supported by relevant citations. Clear, concise, structured communication, using illustration as appropriate. Broadly successful in writing for audience. Statements usually supported by relevant citations. Accessible communication style, perhaps lacking in structure. Statements not always supported by relevant citations. Ineffective communication, indiscriminate inclusion (exclusion) of material. Statements NOT supported by relevant citations. Style obscures what is being conveyed, difficult to comprehend, requires second or third reading. Statements NOT supported by relevant citations.

EMA

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By admin in Essays on March 23, 2017