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Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest,

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Presentation on theme: "Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest,"— Presentation transcript:

1 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 1 Adaptive knowledge maps M árta Turcsányi-Szabó assosiate professor Péter Kaszás PhD student Eötvös Loránd University Informatics Methodology Group

2 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 2 Internet-based materials Difficult of navigate in the topic structure Lack of personalized guidance No information about the usability and Special needs are rarely satisfied

3 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 3 New requirements Tracing students’ personal workflow Giving feedback to the students Offering suggestion to the most effective route in the material Pick and change the less effective items in the materials Suit the material to the changing needs

4 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 4 An example: English grammar course Analysis of atomic links of free Internet- based materials in quality educational sites 2 main types of materials: grammar explanations and exercises Materials in 3 levels Synthesis of selected atomic links into hierarchical course structure using Coraler maps 

5 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 5 Coraler maps English grammar course represented by Coraler map (deepest level of the map)

6 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 6 Criteria-oriented learning Level test New coloured map Practice Small tests New coloured map Default map

7 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 7 Default map Submap of the topic Tenses

8 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 8 Criteria-oriented learning Level test New coloured map Practice Small tests New coloured map

9 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 9 Level test More than 50 questions in a test (database of over 800 questions) Questions in each topic Typical exercises of the particular topic Several kinds of questions (gap filling, sentence constructing, multiple choice, etc.)

10 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 10 Criteria-oriented learning Level test New coloured map Practice Small tests New coloured map

11 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 11 New coloured map Personalized submap of the topic Tenses

12 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 12 Criteria-oriented learning Level test New coloured map Practice Small tests New coloured map

13 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 13 Practice Over 500 links to free materials Exercises with self-checking Practicing the particular topic Applied sites: ESL Lounge: ESL Lesson Plans, ESL Materials for Teaching English EnglishClub English Grammar ELC Study Zone EduFind About ESL sites

14 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 14 Criteria-oriented learning Level test New coloured map Practice Small tests New coloured map

15 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 15 Small tests 3 questions in a test All questions in the specific topic Its style is like the level test

16 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 16 Criteria-oriented learning Level test New coloured map Practice Small tests New coloured map

17 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 17 New coloured map Personalized submap of the topic Tenses

18 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 18 Action research process Pilot system between Feb – April 2003 Data were collected about students’ activity The material and the test database were also examined

19 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 19 Evaluation of the learners Workflows of over 50 students were analyzed Average efficiency: 64.0% Average improvement: 5.4%

20 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 20 Evaluation of the material The most improvements: Conditionals The most mistakes: General adverbs, Adjectives The most certain knowledge: Possessive pronouns, Adverbs of place

21 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 21 Evaluation of the question-types The most successful: multiple choice (75.0%) The least successful: Sentence rewriting (23.3%) Significant difference between the questions needed active knowledge and the ones needed just passive knowledge.

22 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 22 After the evaluation Create student clusters to suggest personal route in the material Change improper test questions Replace the items of the materials that are not effective enough Extend the variety of the material

23 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 23 Adaption within the Colabs project Complex site with many activities Which route is the best?

24 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 24 Adaption within the Colabs project Coraler map shows the structure of the portal

25 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 25 Adaption within the Colabs project Coraler map is used to trace students’ activities Borders show the visited tasks of the student

26 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 26 Adaption within the Colabs project Individual knowledge maps contain: Accessed trajectories Time spent on a particular task Test results Uploaded portfolio Points of collaboration Using the knowledge maps we wish to investigate: What the favourite activities are Which nodes invoke collaboration The validity of the knowledge map The clustering of students routes

27 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 27 Adaption within the Colabs project Aims: Help novice students in a highly visual form Personal knowledge maps for students to review their activities and results Personal knowledge maps for teachers to review the students’ activities and results Provide on-going advice for students

28 Adaptive knowledge maps by Márta Turcsányi-Szabó & Péter Kaszás Eötvös Loránd University, Faculty of Science, Informatics Methodology Group, Budapest, HUNGARY 28 Information TeaM Lab Coraler Corporation Péter Kaszás


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