英语论文网

that might be done or even that they have any understanding at all as to what it means.
The second error is in some way more worrying because it points to a serious lack of awareness on the part of the student. In almost all MSc projects there is no time to implement the outcome and get feedback or metrics relating to its use but it is unfortunately all too common for students to write material that can only happen after the project has ended.
Evaluating & Testing Practice
Testing what you plan as tasks, methods and approach is hard work because often we don’t like critically reflecting on the way we work but in a project you must do it and do it honestly - there is no room for arrogance. But again recall that in the proposal you are writing just a plan of what you will do. The actual evaluation obviously can only take place after the project outcome has been generated. There are two elements:
Basic Reflection - run through a series of general questions, writing down your thoughts some of which will be positive and some negative but all designed to show that learning has taken place: how well did I do it; was it successful? Could or should I have done it another way in parts or as a whole? Did I make any mistakes and were there any surprises? Did I learn anything about research? Did I properly identify constraints involved, including time management? Did I get the scale or scope wrong?
Focused Reflection - In this section you plan how you will evaluate the main elements of your project work and again it must be done with commitment and honesty so that you can show you have learned from the experience. Here are several things you might consider.
Outcome Process Evaluation – look at your research design and the defined model or process used to take the primary data and transform it into the outcome and reflect on how well it worked. This is generally in two parts:
Pre-Processing – was this easy, were your processing and data organisational ideas right or wrong, did you have to go back to get more data, did you have all the tools you needed and were they adequate, was the data consistent and matched to the criteria you set and so on.
Outcome Processing – how easy was it to generate your intended Outcome using the models you defined or perhaps the secondary data you needed at this stage was hard to obtain. Did you follow your design here or did it prove impossible, did you have to get further help, did you misjudge what was needed and so on.
Literature Preparation – were there omissions, looking back were there things you misunderstood, were the sources you used reliable and were they current.

Primary Data Definition – how well did you define the data, did you get good coverage of the problem area, was your definition inaccurate or vague, did you consider confidentiality?
Choices Made – Epistemological Outlook, Research Method, Research Approach and Style, data collection protocol, sample size, population, etc

Data Collection Protocol – how well did this go in practice, where your selection criteria accurate, did you get the calculated sample size, did it prove hard to use, any ethical or confidentiality issues that proved difficult and so on.
Common Errors – this is similar to what was written above in that many students will just copy these headings into their answers without a shred of understanding, contextualization or selectivity. Other will ignore this section altogether