E-Assessment Application using A Decision-Tree in Predicting Teachers’ Information and Communication Technology (ICT) Competency Level
Reymon M. Santiañez1, Maria Visitacion Nepomuceno Gumabay2, Jesus Bartolome Pizarro3
1Reymon M. Santiañez, MIT Graduate School, DIT Student, Paul University Philippines, Cagayan, Philippines, Southeast Asia.
2Maria Visitacion Nepomuceno Gumabay, DIT Program Coordinator, Information Technology, Paul University Philippines, Cagayan, Philippines, Southeast Asia.
3Jesus Bartolome Pizarro, Associate Dean, Graduate School, Paul University Philippines, Cagayan, Philippines, Southeast Asia.
Manuscript received on 05 April 2019 | Revised Manuscript received on 14 April 2019 | Manuscript Published on 24 May 2019 | PP: 61-67 | Volume-8 Issue-6S3 April 2019 | Retrieval Number: F10110486S319/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The study focused on the development of the application on predicting ICT Competency of teachers based from the model created from the different decision tree algorithms. The proponent decided to create a model and develop a system on predicting ICT competency using a decision tree to assess the level of ICT knowledge and by using the standardized questionnaires. This innovation can lead to a newer paradigm using artificial intelligence. Through developing such innovation, the teachers can easily identify the level of ICT knowledge using the framework from National ICT Competency Standards (NICS) by assessing the developed applications. The algorithm used on the prediction of Teachers ICT Competency are J48 and Best First Decision Tree (BFTree) with the highest accuracy value after being test using cross-validation and classification in Weka. The summary of the evaluation showed that the e-Assessment Application got an overall average weighted mean of 4.63, which described as a very high extent. Based on the response of the respondents, the strongest point of the system was its portability and performance efficiency, which earned the highest average mean among other major categories in the system evaluation. The e-Assessment Application in Predicting Teachers’ ICT Competency Level is very useful in terms of predicting the ICT knowledge and skills through the self-evaluation of teachers. The result of the self-assessment and validation of the School Head or Department Head is a big help on identifying different intervention to improve the ICT skills of the teachers used in the teaching instruction and apply the trends in Information Technology.
Keywords: Machine Learning, Algorithm, Prediction, Weka, Data Mining, Decision Tree, ICT Competency, E-Assessment.
Scope of the Article: Machine Learning