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Kevin Waugh, Neil Smith, Pete Thomas

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Title: Kevin Waugh, Neil Smith, Pete Thomas


1
DEAP Diagrammatic Electronic Assessment Project
  • Kevin Waugh, Neil Smith, Pete Thomas
  • Department of Computing
  • The Open University

2
Toward the automated assessment of ERDs
3
The investigators
  • Diagram Understanding
  • Neil Smith
  • Natural Language Processing
  • Kevin Waugh
  • Assessment, Teaching and Learning
  • Pete Thomas

4
What is a diagram?
  • A picture isn't

5
What is a diagram?
  • Free and structured text aren't

"It _is_ a long tail, certainly," said Alice,
looking down with wonder at the Mouse's
tail "but why do you call it sad?" And
she kept on puzzling about it while the
Mouse was speaking, so that her idea of the tale
was something like this----"Fury said to
a mouse, That
he met in the
house, Let us
both go to
law _I_ will
prose- cute
_you_.--
Come, I'll
take no de- nial
We must have
the trial
For really this morn-
ing I've nothing
to do.' Said
the mouse to
the cur,
Graham Joyce was sitting in one of the
sunloungers. He leaned forward and gave Tim a
firm handshake. 'Tim, greetings and salutations.'
For a man in his eighties he retained a
remarkably vigorous air, possessing a gaunt face
that genoprotein treatments had never quite
managed to soften and a shock of unruly
snow-white hair. His voice was like a forceful
foghorn.
6
These are diagrams.
7
and these are diagrams.
8
Traditional take on diagrams
  • Treated as formal "visual" languages
  • so, they're expected to be parsable
  • grammatical, correct and complete
  • But real diagrams aren't formal
  • they're not always grammatical
  • they're often incomplete, often incorrect
  • (we use the term imprecise)
  • they are not always parsable
  • (especially when drawn by students!)

9
Interesting question What if we treat
diagrams in the same way that we treat text?
10
Text and diagram - a simple correspondence
  • Characters/punctuation - segments
  • Words features
  • Phrases - "minimal meaningful units
  • Sentences mmu aggregations

11
Natural language
  • A grammar is an approximation to actual language
    use do we even need a grammar?
  • Pragmatic - rather than correct/complete
  • Sub-languages
  • specific grammars for specific domains
  • stylistic conventions
  • novels
  • instruction manual
  • interpretation is domain specific
  • no "universal" solution

12
Research question
  • If we attempt to process diagrams in ways
    comparable to the ways we process formal, natural
    and sub-language texts.
  • (bag of words, syntactic ,semantic,
    statistical analysis)
  • can we do useful things with diagrams?
  • Things such as automated assessment?

13
Automated assessment
14
Automated assessment
  • Coursework and Examinations
  • Self-assessment and revision support
  • Grade automated feedback
  • grading alone is not sufficient
  • directed, appropriate, focused feedback is a
    requirement
  • (multiple choice - not our concern)

15
Successful automated assessment
  • Textual assessment (essay and short texts)
  • bag-of-words
  • bag-of-phrases
  • sequences (ordered-bag-of-words/phrases)
  • syntactic structure
  • abstracting and comparison (semantic-syntactic)
  • semantic analysis
  • Diagram assessment
  • restricted choice and "slot filling"
  • multiple choice
  • "Free" diagram assessment has not been
    successfully achieved

16
What if we assess diagrams the same way that we
assess text?
  • What are the diagram assessment equivalents to
  • bag-of-words
  • bag-of-phrases
  • sequences
  • abstracting and comparison
  • syntactic structure
  • semantic analysis
  • Can we achieve automated assessment of diagrams
    comparable to that achieved by a human marker?
  • Can we provide focused feedback comparable to a
    human tutor?

17
Our initial experiment with ERDs
18
Feasibility experiment pipelines
  • Approach comparable to bag-of-words
  • Results (13 answers)
  • Human Mean 2.78/5 StdDev 1.05
  • Tool Mean 2.73/5 StdDev 1.09
  • Pearson correlation coefficient 0.75,
    (significant at the 0.01 level, two
    tailed), N13

19
Why entity relationship diagrams?
  • Scope right/wrong interpretable
  • Range small large
  • Range simple complex
  • Correctness notation meaning
  • Format of question, sample solution, marking
    guide (and
    familiarity)
  • Interesting aggregations mn
    decomposition, relationship signatures,
    sub-typing ...

20
The question
  • Give an E-R diagram that corresponds to the
    relational model given. 25
  • model BookGroup
  • relation MemberNumber MemberNumbersName
    PeopleNamesAddress AddressesIntroducedBy
    MemberNumbersBorrowedBook ISBNsBorrowedCopy
    CopyNumbersprimary key Numberalternate key
    (BorrowedBook, BorrowedCopy) allowed
    nullrelationship Introducesforeign key
    IntroducedBy references Member not allowed
    nullrelationship Borrowsforeign key
    (BorrowedBook, BorrowedCopy) references Copy
  • . ltseveral relations omittedgt

21
Solution and marking scheme
Marking scheme 1 mark for all three entities. (
zero if any more or less than three are shown) 6
marks for each relationship (64 24 marks)
broken down as 1 mark for naming used in the
relational model comments 1 mark for the
relationship being between the right entity
types 2 marks for the degree (11 or 1m as per
above figure zero marks if incorrect) 1 mark
for each participation condition correctly shown
22
On the risks of using a drawing tool
  • Slot filling?
  • Prompting?
  • No segmentation or feature extraction?
  • Drawing "correct" diagrams because tool enforces
    correctness?

23
First results
  • 21 human marked answers (max. mark 25)
  • Human Mean 21.29 StdDev 3.757
  • Tool Mean 22.24 StdDev 2.508
  • Spearman rho correlation coefficient 0.95
    (significant at the 0.01 level, two-tailed), N21
  • Pearson correlation coefficient 0.92
    (significant at the 0.01 level, two-tailed), N21

24
Simplistic? Yes - but ....
  • First step in our assessment of diagrams as text
  • comparable to bag-of-phrases processing
  • the pipeline experiment was bag-of-words
  • Essentially uses same algorithm as the marking of
    short answer texts
  • Gives us a baseline when investigating the
    addition of aggregation etc.
  • We are also aware of ...
  • need to investigate how to express complex
    marking schemes (if we need them)
  • the above assessment is not dependent on
    aggregation nor interpretation

25
Where next
  • Take what we have, add feedback and we have a
    revision support tool
  • More complex marking schemes inc. alternative
    solutions
  • Include aggregation and abstraction
  • ERD questions with scope for interpretation
    scenario-based rather than translation based

26
DEAP Diagrammatic Electronic Assessment Project
  • Thank you
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