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Intelligent Tutoring Systems and Affective Computing

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... that 'computers have feelings' ... What computer-detectible behaviors correspond to ... 'Gaming the system' an attempt to advance through the ... – PowerPoint PPT presentation

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Title: Intelligent Tutoring Systems and Affective Computing


1
Intelligent Tutoring Systems and Affective
Computing
2
What makes a good teacher?
3
What makes a good teacher?
  • Mastery of the subject matter
  • Good communication skills
  • An understanding of what students get and dont
    get
  • Genuine care and concern for the students

4
Intelligent Tutoring
  • Mastery of the subject matter
  • Good communication skills
  • An understanding of what students get and dont
    get
  • Genuine care and concern for the students

5
A Problem
  • How can we more effectively help novices learn to
    program?
  • What errors do they most commonly make?
  • How can we intervene?

6
A Possible Approach
  • Educational framework
  • Examine the programming syllabus
  • Make a set of exercises
  • Make a set of all possible solutions to the
    exercises
  • Programming
  • Create a middle layer that will capture all
    compilation errors and their corresponding source
    files
  • Analysis
  • Compute for distances between the wrong solutions
    and the set of solutions

7
What makes a good teacher?
  • Mastery of the subject matter
  • Good communication skills
  • An understanding of what students get and dont
    get
  • Genuine care and concern for the students

8
Affective Computing
  • Mastery of the subject matter
  • Good communication skills
  • An understanding of what students get and dont
    get
  • Genuine care and concern for the students

9
Affective Computing
  • Concerned with the development of systems that
    can detect, respond to, or exhibit human emotions
  • Does not assert that computers have feelings
  • Built on models of emotions that are
    computationally tractable

10
Current Research
  • Studies the relationships between affect and user
    behaviors while using games, simulation
    environments, and intelligent tutors

11
A Problem
  • What computer-detectible behaviors correspond to
    what emotions?
  • What behaviors indicate boredom, frustration,
    delight, surprise, engagement, etc.

12
A Possible Approach
  • Human observation to judge emotions
  • Automated interaction and/or biometric sensor
    logging to record behaviors
  • Statistics and data mining to find patterns and
    correlations

13
Related tools
  • Synchronization tools of logs
  • Video
  • Human observations
  • Biometric sensors
  • Automatic interaction logging
  • Validation tools
  • Playback and labeling tools

14
Related work
  • Gaming the system an attempt to advance
    through the curriculum without actually doing the
    work
  • Intelligent agents now that you have the model,
    how do you fold it into the application?

15
More info?
  • mrodrigo_at_ateneo.edu

16
For Networks
  • Research Websitehttp//cng.ateneo.edu/cng/wyu/cl
    asses/cs197/Presentation Materialshttp//cng.a
    teneo.edu/cng/wyu/classes/cs197/presentation/discs
    -fmc-20070117.pdf
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