An insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey

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An insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey

  1. 1. Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Educational Data Mining An insight into EDM at Muğla Sıtkı Koçman University Presentation by Steven Strehl, HTW Berlin E-Mail: steven.strehl@htw-berlin.de June 30th, 2014
  2. 2. Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Gürüler, Hüseyin and Istanbullu, Ayhan (2014): Modeling Student Performance in Higher Education Using Data Mining. In: Educational Data Mining, Alejandro Peña-Ayala (Ed.). Gürüler, Hüseyin (2005): Veritabanları Üzerinde Veri Madenciliği Uygulaması. Muğla Sıtkı Koçman Üniversitesi. Teşekkür ederim to Hüseyin Gürüler for providing support and additional information by mail and Sema Karakurt for helping me translate important aspects of Hüseyin’s Master’s thesis from Turkish to English. Primary sources
  3. 3. Vision and Goals Student Knowledge Discovery Software Improve efficiency, quality, “experience” of studies Predict failure or success of students Eliminate factors that lead to failure Figure 1: SKDS user interface Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
  4. 4. Context Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Student profiling Figure 2: Female student Gender Military service Grade Point Average Name Secondary school Scholarship Age Final mark Secondary school Nationality Study programme Family income Marital status Focus subject Parents’ professions Religion Hometown …
  5. 5. Context Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Figure 3: Individual students Figure 4: Anonymous students
  6. 6. Basics Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Knowledge Discovery in Databases Data MiningAvailable Data Selected Data Pre-processed Data Transformed Data Interpretation and Evaluation Figure 5: Stages of the KDD process
  7. 7. Basics Data Mining Cross Industry Standard Process for Data Mining (CRISP-DM) Verification-driven DM Aims at verifying assumptions by data queries Discovery-driven DM Aims at gaining new insights by unveiling patterns Figure 6: CRISP-DM Process Diagram Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
  8. 8. Approach Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Data curation Figure 7: Male student Gender Military service Grade Point Average Name Secondary school Scholarship Age Final mark Secondary school Nationality Study programme Family income Marital status Focus subject Parents’ professions Religion Hometown …
  9. 9. Approach Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Data volume and provenience Data Mining Microsoft Decision Tree Algorithm Available Data University departments, faculties, central registration system and archives Selected Data 13 tables related to the scope of SKDS Pre-processed Data 6 tables Transformed Data View consisting of 111 columns and 6,470 records Interpretation and Evaluation Figure 8: Stages of the KDD process
  10. 10. Approach Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Models and results Model 1: GPA >= 3.0 - Language prep. (English) - Registration preference Model 2: GPA >= 2.0 - Family income Figure 9: Decision Tree for Model 1 Figure 10: Decision Tree for Model 2
  11. 11. Issues and Outlook Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Issues Data availability, variety, format Usability not yet suitable for everyday use Transfer impact of findings Outlook Data Mining new algorithms available MÜKÜP/SKDS was an early WEKA Improvement new GUI, easier to use
  12. 12. Discussion Except where otherwise noted, content of this work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Topics Social background Family income has been discovered as an important factor for success. Does the data scientist’s work end here? Study conditions How to measure and find aspects that counterbalance negative preconditions of the social background? Health How does the mental and physical state influence success and failure? Open Data What if Student Life Cycle Data were open?
  13. 13. List of Figures [1] Gürüler, Hüseyin and Istanbullu, Ayhan (2014): Modeling Student Performance in Higher Education Using Data Mining. No CC license. [2] http://openclipart.org/user-detail/ryanlerch Public domain. [3] http://openclipart.org/user-detail/ryanlerch Public domain. [4] http://openclipart.org/user-detail/thekua Public domain. [5] Composed graphic from http://openclipart.org/user-detail/jean_victor_balin, http://openclipart.org/user-detail/buggi, http://openclipart.org/user-detail/gsagri04 Public Domain. [6] Kenneth Jensen, https://en.wikipedia.org/wiki/Cross_Industry_Standard_Process_for_Data_Mining#mediaviewer/File:CRISP-DM_Process_Diagram.png [7] http://openclipart.org/user-detail/ryanlerch Public domain. [8] Composed graphic from http://openclipart.org/user-detail/jean_victor_balin, http://openclipart.org/user-detail/buggi, http://openclipart.org/user-detail/gsagri04 Public Domain. [9] Gürüler, Hüseyin and Istanbullu, Ayhan (2014): Modeling Student Performance in Higher Education Using Data Mining. No CC license. [10] Gürüler, Hüseyin and Istanbullu, Ayhan (2014): Modeling Student Performance in Higher Education Using Data Mining. No CC license.

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