Investigating teacher's integrity through association rule mining

• Main Authors: Din, Roshidi, Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza
• Format: Monograph
• Language: English
• Published: Universiti Utara Malaysia 2012
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/14369/1/2012.pdf; http://repo.uum.edu.my/14369/

The selection of teachers to attend trainings is currently done randomly, by rotation and not based on their work performance.This poses a problem in selecting the right teacher to attend the right course.Up until now, there is no intelligent model to assist the school management to determine the integrity level of teacher and assign them to the right training program.Thus, this study investigates the integrity traits of teacher using association rule technique with an aim, which can assist the school management to organize a training related to teachers’ integrity performance and to avoid sending the wrong teacher for the training.A dataset of Trainees Integrity Dataset representing 1500 secondary school teachers in Langkawi Island, Malaysia in the year 2009 were pre-processed and mined using apriori. Mining knowledge was analyzed based on demographic and integrity trait of teacher.The finding indicates that adaptability and stability are the weakest integrity trait among teachers.Teachers from the age group of 26 - 30 years are found to have lower integrity performance.However, other demographic factor such as gender, race, and grade position of teachers were not able to reflect their low integrity level in this study.Finally, this study produces a component of trainee selection module which can be used as guideline for school management to propose suitable training programs for teacher to improve their integrity mainly on adaptability and stability traits.