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

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

Fatma Önay Koçoğlu (Informatics Department, İstanbul University, İstanbul, Turkey), İlkim Ecem Emre (Informatics Department, İstanbul University, İstanbul, Turkey) and Çiğdem Selçukcan Erol (Informatics Department, İstanbul University, İstanbul, Turkey)
Copyright: © 2017 |Pages: 12
DOI: 10.4018/IJEA.2017010104
OnDemand PDF Download:
List Price: $37.50
10% Discount:-$3.75


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.
Article Preview


With emerging technologies of today, e-learning and data mining concepts are becoming more popular and widespread. E-learning is getting attention and gaining in importance in both academia and industry. As technologies change, changes in the concepts are becoming inevitable like in education field. Education today cannot be thought apart from information technologies. Technology has modified the style of education and learning processes. It can be clearly seen from the perspective of education institutions as well as various industries.

For data analyzes statistics is being used ever since. Statistical data analyzes techniques are being used widespread almost in every field where data exists. Today another concept is being discussed among statistics which is the concept of data mining. What data mining techniques offer to the researchers today, is to be able to analyze very large volumes data sets where statistical approaches could be inadequate. Nonetheless, data mining techniques are mainly based on statistics. Since data mining offers analyzes for both structured and unstructured data sets, these are gaining more and more in importance in various research fields where data volumes are growing day by day. Fundamental information about data mining concept and techniques are revealed by Fayyad, Piatetsky-Shapiro, & Smyth (1996a), Fayyad, Piatetsky-Shapiro, & Smyth (1996b), and Han & Kamber (2011) in their studies. There have been various researches, books and papers in different fields including data mining applications (Gezer, Erol, & Gülseçen, 2007; Özkan, 2008; Koçoğlu, 2012; Atasoy, 2015; Balaban & Kartal, 2015a, 2015b; Erol & Özkan, 2015; Gülseçen & Özen, 2016; Balaban & Kartal, 2016; Kartal, 2016; Koçoğlu & Özcan, 2016). The results gained from data mining analyzes could be used in decision making processes which play significant roles in institutions including schools, universities, private institution etc. Education field is one of the fields where data mining techniques could be used in order to determine most important objectives in learning processes, to predicts students’ performances, to evaluate the patterns of the students’ and to improve quality of the processes etc.

In this study, it is tried to obtain results about e-learning platform users by using data mining techniques. So, that a popular concept for data analyses and a wide spread concept of e-learning have been brought together.


With technological advances of today education field has been changed a lot. Not only the usage of technological instruments in learning processes but also the expectation of students/employees have been changed. Traditional classrooms and learning styles are still remaining but however these have inevitably fallen under the influence of information technologies.

Yılmaz (2012) has defined e-learning as below:

E-learning is the use of Internet technologies in order to create a rich learning environment which includes a large variety of instruction and information resources and solutions, and also to deliver this environment. And the goal of e-learning is to improve individual and organizational performance.

Various definitions made by different researchers are similar. E-learning is the usage of IT technologies or Internet to provide information or trainings to the students or employees. Learning materials can be brought into use over Internet or other web technologies by companies or instructors. E-learning platforms brings web technologies and learning concept together so that time and place dependency for learning disappears in contrast to traditional classroom which requires physical participation in a specific time period. These platforms provides employees or students to learn from distance, enable them to work independently from a physical classroom and to self-organize the time schedule for learning of course if it is possible (Henderson, 2003).

The benefits of e-learning for the companies have been itemized by Henderson (2003) as follow:

  • Cost savings

  • Learning quality

  • Rapid training rollout

  • Coping with shortened knowledge lifecycles

Complete Article List

Search this Journal:
Volume 15: 1 Issue (2023): Forthcoming, Available for Pre-Order
Volume 14: 3 Issues (2022): 2 Released, 1 Forthcoming
Volume 13: 2 Issues (2021)
Volume 12: 2 Issues (2020)
Volume 11: 2 Issues (2019)
Volume 10: 2 Issues (2018)
Volume 9: 2 Issues (2017)
Volume 8: 2 Issues (2016)
Volume 7: 2 Issues (2015)
Volume 6: 2 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing