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Goal:	
  Guide	
  students	
  to	
  right	
  content	
  in	
  
intelligent	
  educa1onal	
  systems	
  
Idea:	
  Social	
 ...
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AIED 2015 Poster- Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface

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This poster is presented at 17th International Conference on Artificial Intelligence in Education (AIED 2015) in Madrid, Spain.

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AIED 2015 Poster- Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface

  1. 1. Goal:  Guide  students  to  right  content  in   intelligent  educa1onal  systems   Idea:  Social  guidance  based  on  open  social   student  modeling   § Allows  students  to  explore  each  others   model  or  cumula1ve  model  of  the  class   § Increases  student  engagement   § Provides  effec1ve  naviga1on  support   Mo+va+on   Challenges  in  Social  Guidance   Adap+ve  Sequencing   Impact  of  GS  on  Learning  Gain,  Learning  Speed,  System/Class  Performance       Greedy  sequencing  (GS):  Aims  at  maximizing   student  level  of  knowledge  in  domain  concepts   Off  the  Beaten  Path:  The  Impact  of  Adap+ve  Content  Sequencing    on  Student  Naviga+on  in  an  Open  Social  Student  Modeling  Interface     Classroom  Study   R.  Hosseini,  I.H.  Hsiao,  J.  Guerra,  P.  Brusilovsky   Naviga+onal  PaIerns   Problem:   How  to  avoid  students  becoming  more   conserva1ve  with  their  work  with  content?   Solu+on:  Increasing  the  personaliza1on  power  of   social  guidance   § Combine  social  guidance  with  adap1ve   sequencing  of  contents   Open  Social  Student  Modeling   Students  in  the  class  (you  are  4th  out  of  7)   4.  Me  -­‐>   User   Modeling   database   Greedy   Sequencing   Knowledge   Report  Service   Rank  C1   Prerequisites   Outcomes   Content  C1:  Concepts   P:  ra1o  of  known  prerequisites   O:  ra1o  of  unknown  outcomes   np:  number  of  prerequisites   no:  number  of  outcomes   Greedy  Sequencing  Rank   Rank = npP + noO np + no GS  and  Social  Guidance   § Star  size  is  rela1ve  to  the  rank  of  content   § A  bigger  star  means  content  has  higher  priority   § 143  undergraduates  in  ASU  (Fall  2014),  in  Java   Programming  and  Data  Structure  course     § 111  problems  —  103  examples  —  19  topics   Part:  (1)  No  Sequencing  (Aug.  21  –  Sep.  25)                      (2)  Introduced  Sequencing  (Sep.  26  –  Oct.  21)   Logs:  86  subjects  —  53  of  them  had  at  least  30                          problem  aaempts   Rela1ve  Frequencies  of  topic-­‐based  paaerns   § GS  promotes  non-­‐sequen1al  paaerns     0   0.1   0.2   0.3   0.4   0.5   0.6   0.7   0.8   0.9   Weak  students   Strong  students   Normalized  learning  gain   Non-­‐followers   Followers   0.00   0.20   0.40   0.60   0.80   1.00   1.20   1.40   1.60   1.80   2.00   Weak  students   Strong  students   %  Learning  speed     Non-­‐followers   Followers   § No  significant  differences  in  the  learning  gain   § Followers  with  high  prior  knowledge  learn  faster  (p=.039)   § Correctness  is  more  frequent  in  recommended   problems  (p<.001)   § Aaemp1ng  a  recommended  content  is  associated   with  0.56  increase  in  final  grade  (SE=0.24,  p=.017)     ~  9  1mes  greater  than  a  not  recommended  content   Within-­‐Topic   Next-­‐Topic   Jump-­‐Forward   Jump-­‐Backward   Part  1   Part  2-­‐N   Part  2-­‐R   0.08 0.08 0.16 0.68 0.06 0.05 0.12 0.78 0.17 0.17 0.2 0.47 Jump−Backward Jump−Forward Next−Topic Within−Topic Part 1 Part 2−N Part 2−R

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