Difference between revisions of "Blending layers of CUMULATE's user model"

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This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily [[CUMULATE]]'s considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of [http://www.officeport.com/edu/blooms.htm| Bloom's taxonomy] of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).
 
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This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily [[CUMULATE]]'s considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of [http://www.officeport.com/edu/blooms.htm| Bloom's taxonomy] of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).
 
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This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily [[CUMULATE]]'s considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of [http://www.officeport.com/edu/blooms.htm| Bloom's taxonomy] of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).
 
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This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily [[CUMULATE]]'s considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of [http://www.officeport.com/edu/blooms.htm| Bloom's taxonomy] of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).
 
  
 
This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily [[CUMULATE]]'s considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of [http://www.officeport.com/edu/blooms.htm| Bloom's taxonomy] of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).
 
This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily [[CUMULATE]]'s considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of [http://www.officeport.com/edu/blooms.htm| Bloom's taxonomy] of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).
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=== Data ===
 
=== Data ===
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We were using previously collected student [[CUMULATE_Usage_Logs#Database_Management_6_Course_Dataset|usage logs]] collected from 4 Database Management courses offered during Fall 2007 and Spring 2008 semesters at the [http://www.pitt.edu University of Pittsburgh]. Each course had roughly the same structure, an identical set of 48 problems served by [[SQLKnoT]] system, and an identical set of 64 examples served by [[WebEx]] system.
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We were using previously collected student [[CUMULATE_Usage_Logs#Database_Management_6_Course_Dataset|usage logs]] collected from 4 Database Management courses offered during Fall 2007 and Spring 2008 semesters at the [http://www.pitt.edu University of Pittsburgh] and [http://www.dcu.ie Dublin City University]. Each course had roughly the same structure, an identical set of 48 problems served by [[SQLKnoT]] system, and an identical set of 64 examples served by [[WebEx]] system. Basic usage statistics are given in the table below.
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{|  border=0 cellspacing=0 cellpadding=0
 +
| School
 +
| Semester
 +
| Level
 +
| No. of users
 +
| Avg. problem attempts
 +
| Avg. example views
 +
|  valign=top | Avg. distinct problems
 +
|  valign=top | Avg. distinct examples
 +
|-
 +
|  valign=top | U. of Pitt
 +
|  valign=top | Fall 2007
 +
|  valign=top | U*
 +
|  valign=top | 27
 +
|  valign=top | 156.40
 +
|  valign=top | 189.00
 +
|  valign=top | 29.96
 +
|  valign=top | 32.07
 +
|-
 +
|  valign=top | U. of Pitt
 +
|  valign=top | Fall 2007
 +
|  valign=top | G
 +
|  valign=top | 20
 +
|  valign=top | 61.70
 +
|  valign=top | 104.70
 +
|  valign=top | 29.95
 +
|  valign=top | 29.10
 +
|-
 +
|  valign=top | U. of Pitt
 +
|  valign=top | Spring 2008
 +
|  valign=top | U
 +
|  valign=top | 15
 +
|  valign=top | 26.94
 +
|  valign=top | 46.65
 +
|  valign=top | 16.35
 +
|  valign=top | 10.29
 +
|-
 +
|  valign=top | DCU
 +
|  valign=top | Spring 2008
 +
|  valign=top | U
 +
|  valign=top | 52
 +
|  valign=top | 81.68
 +
|  valign=top | 257.25
 +
|  valign=top | 22.82
 +
|  valign=top | 38.63
 +
|}
 +
 
 +
=== Procedures ===

Revision as of 14:06, 28 June 2009

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This work is focused on mutual influence of heterogeneous user activity types (reading texts, viewing examples, and solving problems) on user's knowledge of some educational domain. Ordinarily CUMULATE's considers them separately by classifying them to modeling tiers or levels, each corresponding to a level of Bloom's taxonomy of intellectual behavior. Great part of this work is devoted on cross-tier user modeling. Namely, how user activity can (positively) influence on another/other layer(s).

Study 1

In this study we have inspected the influence of the comprehension layer of CUMULATE's user model (viewing examples) on the application layer (solving problems). Our approach was to create "blends" of problem-solving tier of the user model and weighted (from 0 to 1, with .1 step) example viewing tier Our hypotheses were that:

  • Using example browsing activity when modeling problem solving improves model accuracy
  • Different users benefit from different “blends” of user model levels

In addition we wanted to se if

  • There is a single optimal blend for all users, and. or
  • Classes of users benefitting from different model blends can be determined

Data

We were using previously collected student usage logs collected from 4 Database Management courses offered during Fall 2007 and Spring 2008 semesters at the University of Pittsburgh and Dublin City University. Each course had roughly the same structure, an identical set of 48 problems served by SQLKnoT system, and an identical set of 64 examples served by WebEx system. Basic usage statistics are given in the table below.

School Semester Level No. of users Avg. problem attempts Avg. example views Avg. distinct problems Avg. distinct examples
U. of Pitt Fall 2007 U* 27 156.40 189.00 29.96 32.07
U. of Pitt Fall 2007 G 20 61.70 104.70 29.95 29.10
U. of Pitt Spring 2008 U 15 26.94 46.65 16.35 10.29
DCU Spring 2008 U 52 81.68 257.25 22.82 38.63

Procedures

Retrieved from "http://adapt2.sis.pitt.edu/w/index.php?title=Blending_layers_of_CUMULATE%27s_user_model&oldid=1210"