Observation of Success Status of Employees in E-Learning Courses in Organizations with Data Mining

Kocoglu F. Ö., Emre I. E., Erol Ç.

INTERNATIONAL JOURNAL OF E-ADOPTION, cilt.9, sa.1, ss.38-49, 2017 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 9 Sayı: 1
  • Basım Tarihi: 2017
  • Doi Numarası: 10.4018/ijea.2017010104
  • Dergi Adı: INTERNATIONAL JOURNAL OF E-ADOPTION
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), INSPEC, Library and Information Science Abstracts
  • Sayfa Sayıları: ss.38-49
  • Anahtar Kelimeler: C5.0 Algorithm, Data Analysis, Data Mining, Decision Tree, E-Learning, Educational Data Mining, KNOWLEDGE
  • İstanbul Üniversitesi Adresli: Evet

Özet

The aim of this study is to analyze success in e-learning with data mining methods and find out potential patterns. In this context, 374.073 data of 2013-14 period taken from an institution serving in e-learning field in Turkey are used. Data set, which is collected from information technology, banking and pharmaceutical industries, includes success and industry of employees', trainings which they complete, whether the trainings are completed, first login and last logout dates, training completion date and duration of experience in training. Using this data set, success status of participants is observed by using data mining methods (C5.0, Random Forest and Gini). By observing using accuracy, error rate, specificity and f- score from performance evaluation criteria, C5.0 has chosen the algorithm which gives the best performance results. According to the results of the study, it has been determined that the sectors of the employees are not important, on the contrary the ones that are important are the completion status, the duration of experience and training.