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Neural Network Based Intelligent Analysis of
Learners' Response for an e-Learning Environment
201O 2nd International Conference on Education Technology and
Computer (ICETC)
姓名：謝宏偉
學號：M99G0219
班級：碩研資工一甲
Outline
 1. INTRODUCTION
 2. LEARNERS RESPONSE IN AN E-LEARNING
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ENVIRONMENT
3. INTELLIGENT RESPONSE ANALYSIS
4. PROPOSED SCHEME
5. EXPERIMENTAL RESULTS
6. CONCLUSIONS
1. INTRODUCTION
 The scheme applies to typed-in single-word
textual response from the learners' end.
 The proposed system is intelligently adaptive to
inadvertent mistakes committed by the learner
while responding to the system's queries.
2. LEARNERS RESPONSE IN AN ELEARNING ENVIRONMENT
 Typed interactions may take place in an e-
Learning system under two circumstances, viz.,
dialog between the learner and the system, to
simulate the real-life learning experience and
assessment of learning achievement.
 While objective type interaction is close ended
and guided, based on the options available in the
test item itself, dialog based test items need
embedded intelligence to assess.
2. LEARNERS RESPONSE IN AN ELEARNING ENVIRONMENT
 To provide a more meaningful learning experience,
or assessment of learning achievement, under an
E-learning environment, a learner must be offered
the scope of interacting with the system through
typed-in texts.
3. INTELLIGENT RESPONSE ANALYSIS
 The limitations of MCQ's are covered to some
extent by close ended questions having text
based answers with single words or a few
sentences in which case we get the best of both
worlds.
3. INTELLIGENT RESPONSE ANALYSIS
3. INTELLIGENT RESPONSE ANALYSIS
3. INTELLIGENT RESPONSE ANALYSIS
4. PROPOSED SCHEME
 Neural Networks have been trained and used as
effective classification tools where the values in
the output neurons are indicative of the class to
which the input patterns culminate.
 Viable and successful applications of ANN's as
language classifiers are available both for text
and phonetics based approaches .
4. PROPOSED SCHEME
4. PROPOSED SCHEME
5. EXPERIMENTAL RESULTS
5. EXPERIMENTAL RESULTS
5. EXPERIMENTAL RESULTS
5. EXPERIMENTAL RESULTS
6. CONCLUSIONS
 The proposed scheme successfully simulates a
human instructor communicating with the learner
through single-word typed in text.
 Experimental results show that the system is
intelligent enough to simulate the interaction
between a human instructor and a learner when
the learner's response is restricted to single word.