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Adaptive Sequencing and Course
          Generation

        Speaker: Wenkai Dai
       Tutor: George Goguadze

                                 1
Motivation




             2
Motivation




             3
Outline
• Motivation
• Introduction
• Concepts
• Pedagogical Objectives
• Operator & Method
• Dynamic Task
• Converting a Plan into a Course
• Performance & Discussion          4
Introduction
• Middle way between above studying ways
• Course generator
• Content organized by pedagogical principles
• Problems of existing course generators




                                                5
Introduction
• PAIGOS, web-based course generator on math study
• Using novel techniques from
  • Semantic web
  • Artificial intelligence
  • Technology-enhanced learning




                                                     6
Introduction




Pedagogical knowledge       Learning goal         Learner’s competencies




                        Personally structured courses                      7
Screenshot of LeActiveMath




                             8
Screenshot of LeActiveMath




                             9
Course Generation




                    10
Concepts
• Hierarchical Task Network Planning
• An HTN planning problem consists of
  • An initial state
  • Logical atoms
  • The initial task network
  • A domain description

– Planning operators: (:operator h P D A)
– Methods: (:method h L1 T1 L2 T2 . . .Ln Tn)
                                                11
Pedagogical Objectives




• t = (discover, (def_slope, def_diff))
                                          12
General Form of Planning Problem




                                   13
Operators and Methods
• An assignment expression (assign ?var t) binds ?var to
  the term t.
• Basic operator (:operator (!insertResource ?r) () ()
  ((inserted ?r))). no precondition and delete list. It adds
  a logical atom to the world state that describes that a
  resource ?r was inserted into the course
• Insert method




                                                         14
Dynamic Tasks
• Dilemma: The sequence of contents leading to his goal
  has been structured in advance but the assumptions
  about the learner become invalid in real time




                                                   15
Dynamic Tasks
• Extended the planner in such a way that planning may
  stop at the level of specially marked tasks (dynamic
  tasks)
• These tasks are inserted into the course like any other
  reference to a learning object
• When the learner first visits a page that contains a
  dynamic task, this task is passed on to the course
  generator
• Dynamic subtask is not natively supported
• Solution: Dynamic Items
                                                         16
Dynamic Items
• Dynamic tasks are simulated by (:operator
  (!dynamicTask ?ped Obj ?refs) ()()())
• No precondition for the Operator to perform this task
• Operator creates a special element called dynamic
  item when applied
• Latter when course is presented, dynamic item on the
  page will pass the associated dynamic task to the
  course generator
• By this way, some contents of the next page to be
  viewed are inserted dynamically                     17
Converting a Plan into a Course
• After plan found, generate a course, a table of
  contents
• PAIGOS represents courses using the element
  omgroup from OMDoc Standard, a semantic
  knowledge representation for math documents
• But omgroup is independent of math domain, which
  can be easily map to other data structures
• Omgroup consist of metadata information like author
  and title of the element, references to other OMDoc
  elements, omgroup elements and dynamic items.
                                                    18
Selecting Exercises & Examples




                                 19
Scenario of LearnNew




                       20
Generated Course of LearnNew




                               21
Performance




Required time of course generation vs. increasing
amount of concepts


                                                    22
Performance




A plot of the number of concepts vs. time required for
course generation in milliseconds                        23
Discussion
• Including more factors like motivation, meta cognitive
  adaptation




                                                     24
Question, Thanks

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E learning

  • 1. Adaptive Sequencing and Course Generation Speaker: Wenkai Dai Tutor: George Goguadze 1
  • 4. Outline • Motivation • Introduction • Concepts • Pedagogical Objectives • Operator & Method • Dynamic Task • Converting a Plan into a Course • Performance & Discussion 4
  • 5. Introduction • Middle way between above studying ways • Course generator • Content organized by pedagogical principles • Problems of existing course generators 5
  • 6. Introduction • PAIGOS, web-based course generator on math study • Using novel techniques from • Semantic web • Artificial intelligence • Technology-enhanced learning 6
  • 7. Introduction Pedagogical knowledge Learning goal Learner’s competencies Personally structured courses 7
  • 11. Concepts • Hierarchical Task Network Planning • An HTN planning problem consists of • An initial state • Logical atoms • The initial task network • A domain description – Planning operators: (:operator h P D A) – Methods: (:method h L1 T1 L2 T2 . . .Ln Tn) 11
  • 12. Pedagogical Objectives • t = (discover, (def_slope, def_diff)) 12
  • 13. General Form of Planning Problem 13
  • 14. Operators and Methods • An assignment expression (assign ?var t) binds ?var to the term t. • Basic operator (:operator (!insertResource ?r) () () ((inserted ?r))). no precondition and delete list. It adds a logical atom to the world state that describes that a resource ?r was inserted into the course • Insert method 14
  • 15. Dynamic Tasks • Dilemma: The sequence of contents leading to his goal has been structured in advance but the assumptions about the learner become invalid in real time 15
  • 16. Dynamic Tasks • Extended the planner in such a way that planning may stop at the level of specially marked tasks (dynamic tasks) • These tasks are inserted into the course like any other reference to a learning object • When the learner first visits a page that contains a dynamic task, this task is passed on to the course generator • Dynamic subtask is not natively supported • Solution: Dynamic Items 16
  • 17. Dynamic Items • Dynamic tasks are simulated by (:operator (!dynamicTask ?ped Obj ?refs) ()()()) • No precondition for the Operator to perform this task • Operator creates a special element called dynamic item when applied • Latter when course is presented, dynamic item on the page will pass the associated dynamic task to the course generator • By this way, some contents of the next page to be viewed are inserted dynamically 17
  • 18. Converting a Plan into a Course • After plan found, generate a course, a table of contents • PAIGOS represents courses using the element omgroup from OMDoc Standard, a semantic knowledge representation for math documents • But omgroup is independent of math domain, which can be easily map to other data structures • Omgroup consist of metadata information like author and title of the element, references to other OMDoc elements, omgroup elements and dynamic items. 18
  • 19. Selecting Exercises & Examples 19
  • 21. Generated Course of LearnNew 21
  • 22. Performance Required time of course generation vs. increasing amount of concepts 22
  • 23. Performance A plot of the number of concepts vs. time required for course generation in milliseconds 23
  • 24. Discussion • Including more factors like motivation, meta cognitive adaptation 24