[Grad2022] [Turnbull Zemi] Tomorrow's Zemi

[Stephen J. Turnbull]

Hi everyone,

I'm sorry for writing only in English, but I'm very tired and left
this until late.

We are now preparing the M2 students for their midterm presentations.
Those students are 王　曉飛, 張　子雲, 蒋　穎, 鈴木　康介 in an order
to be announced tomorrow.  Discussants will also be assigned
tomorrow.  Discussants have no preparation to do, and do not need to
receive presentation materials.  See "Discussants" below.

Presenters
----------

The presenters should present as much of their research as possible.
Do not worry about a time constraint, you may use up to 30 minutes,
but you shouldn't *try* to use that much time: between 12 and 20
minutes is best.  The following areas should be covered:

- These slides are the basis for your midterm presentation.  Make
  every revision as perfect as possible in form, because you may not
  have time to change it later.

- Title and self-introduction

- Background and motivation of the research.
  Why did you become interested in this theme, and any interesting
  aspects for science, society, or policy (*except* previous
  research).

- Literature survey.
  This includes previous scientific papers in your field.  Usually
  there is a seminal ("seed") work which is famous, and one or more
  paths made of several papers each leading directly to your thesis.
  How you describe these paths is up to you, but usually it's
  "depth-first", that is, you start at the beginning and cover each
  paper in one thread until you reach your paper's original idea, then
  return to a branch point and cover another thread.

- Model.
  This describes the variables and relationships among those variables
  that you are studying.  Usually it is a modification of a model
  presented in an earlier paper.

- Data.  [skip if theory paper]
  This describes the source and method of measurement of each
  variable.  If you are using data published by someone else, source
  is easy but you must be able to describe the method for gathering
  data as if it were your own.

- Statistical methodology.  [skip if theory paper]
  This describes the statistical methods you are using, including
  parameter estimation and hypothesis tests.  If you are using a
  questionnaire survey you should be doing reliability tests, factor
  analysis.  Hypothesis tests should include power (probability of
  Type II error, accepting the null hypothesis when it is false).  The
  computer programs you use are *not* methodology.  You *should* cite
  them, however.

- Estimation and test results.  [skip if theory paper]
  Describes the results you achieve with your statistics.

- Calculations and proofs.  [skip if empirical paper]
  Describes your analytical methods for calculations and proofs and
  any theorems or results.

- Implications of your results for scientific progress or policy.

- Suggestions for further research.

- Reference list.

- Appendices.
  These include any instruments (eg, questionnaires) you have
  constructed yourself, full data sets if practical else reference to
  online sources, detailed proofs or calculations, additional graphs
  and tables, and any other materials that don't belong in a
  presentation but might be useful in answering questions.

These areas do not correspond to chapters in your thesis, and not
always in exactly this order.  However, this is a fairly conventional
order.

Discussants
-----------

Discussants should focus on the presentation materials, not on the
content.  If you notice anything in the research itself you want to
ask about, that's fine, but your main job is to check format.

- Are page numbers visible on every slide?

- Are titles informative?  For example, better than "Implications" is
  something like "Effects on the Trade Balance".  Also, in a full
  presentation some sections will require several slides.  Each slide
  should have a unique title.

- Are fonts readable?  Many faculty members are older and don't have
  great eyesight.  If they can't read it from the back of our lab, it
  *does not belong on a slide*.  Exceptions include the reference list
  (which nobody except me reads until your final version) and large
  tables.

- Does every table and graph have a caption?

- Is all text on graphs readable?  Do the colors help you to
  understand?  Are all needed labels present (variables on axes, tic
  marks and values for graphs of data, functions that are visualized
  as curves, any curves or lines that divide a graph into regions,
  etc?

- Can you understand what the graph means without the presentation?
  Check this before the speaker explains!

- Citations should be in the form "Author last name[s] (year)".  Do
  not include titles and publication data other than the publication
  year (that's what the reference list is for).  When you cite a
  paper, explain why you need to cite it.  For example, "Nick and
  Percy (2019) first applied the Furgleblatz everted regression method
  to triply-redundant Poirotian data.  Their methodology is therefore
  most appropriate for this research based on triply-redundant
  Poirotian data."  *Never* use numerical references such as "[1]" or
  "Percy [1]" in a presentation.  *Do not* make the audience flip back
  and forth between the content and the references.

- Does the time used for each slide seem way too little, or way too
  much?  If it's too little, should the slide be deleted, or does it
  need more discussion?  If it's too much, should the slide be split
  into more than one, or should the discussion be trimmed?


-- 
Associate Professor              Division of Policy and Planning Science
http://turnbull.sk.tsukuba.ac.jp/     Faculty of Systems and Information
Email: turnbull at sk.tsukuba.ac.jp                   University of Tsukuba
Tel: 029-853-5175                 Tennodai 1-1-1, Tsukuba 305-8573 JAPAN