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Help seeking model

Help seeking model. By: Geraldine Clarebout (Univ of Leuven, Belgium) Nik Nailah Binti Abdullah (National Institute of Informatics, Japan) Track : DataMining. Help Seeking Model. What is it? Describes student’s ideal help seeking behavior. It determines

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Help seeking model

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  1. Help seeking model By: Geraldine Clarebout (Univ of Leuven, Belgium) Nik Nailah Binti Abdullah (National Institute of Informatics, Japan) Track: DataMining

  2. Help Seeking Model • What is it? • Describes student’s ideal help seeking behavior. It determines • what type of action the students should ideally perform • The number of steps of actions so far on the step • The number of time students spends answering

  3. Help Seeking Model We are here!

  4. Research question • Do different patterns in “help seeking” correlate with student’s attitudes about the cognitive tutor? • We think so, what do you think?

  5. Method • Data from Ryan S. Baker PhD. • Environment • Geometry scatter plot.

  6. The Analysis • Learning to work with Excel, Pivot Table. • Building rules. • Try step abuse 1) Too fast (VARTF) If “not first attempt” = 1, AND time <.10, AND if answer = 0; then too fast If “not first attempt” = 0; And if time <.7, And if answer = 0; then too fast 2)Guess quickly If probability >.80, and if time <.7, and if answer =1, (then guessing)) => VARguess If errors >2 then help is need, if help requested = 0, ; and if answer=1) then guessing =>VARguess2 (answer can be right or wrong when guessing; but we only see it as a problem for guessing when the answer is correct, because then a student can think he actually knows the problem; but he doesn’t necessarily)

  7. Results • Correlations

  8. Results • Descriptives

  9. Results • For each of the variables (i.e.,VARTF) • We divided student into two groups: high or low scores on VARTF,VARguess,VARguess2 median split. • We defined 9 groups based on this 3 variables. • E.g., high on the 3 variables or high on 1 variable and low on 1 variable.

  10. Results Fig 2. Histogram showing the patterns of the VAR with the count of hi/low.

  11. Results • Correlation with the attitude data? • Remains mystery….

  12. Conclusion and perspectives • 18% try step abuse. • 17.5% for high on guessing and low on the other ones. • 17.5% high for too fast and high on guess2 and low on guess. • 14.4% low on all of the variables.

  13. Conclusion and perspectives • The % does not explain why students has the tendency to try step abuse. • What is the relationship of try step abuse with the other help seeking factors? • What is the relationship with student’s attitude?

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