University Licensure Examination Reviewer for Teacher: A Framework for Developing Gamified Examination
Mervin Jommel T. De Jesus () and
Francis F. Balahadia ()
Additional contact information
Mervin Jommel T. De Jesus: Laguna State Polytechnic Universtiy
Francis F. Balahadia: Laguna State Polytechnic Universtiy
International Journal of Computing Sciences Research, 2020, vol. 4, issue 1, 1-16
Abstract:
Purpose – The study aims to develop a framework that can be used in gamifying the LET reviewer and determine the necessary gamification elements to be used and identify the area of improvement of the students based on their assessment in the system. Method – The researchers will use the descriptive research in order to accomplish the study and as for the development of the system, the researchers will apply the Iterative and Incremental Model Methodology. Results – Based on the literature, gamification is an effective technique in which necessary game elements should be implemented, namely: points, levels, leaderboards, points, and feedback with the game design. Through gamification, the framework was developed to apply in the creation of a gamified examination for teachers. Conclusion – As the results of different studies, gamification is a good approach to make a positive change in students’ behavior and attitude towards learning that helps improves students’ motivation and engagement. Recommendations – Develop a gamified application that can cater to the needs of the students, must be used by the College of Teacher Education every Pre-LET examination in all campuses of the university to assess the student performance to determine possible intervention to assist the student’s need. Research Implications – The integration of new educational technique helps to progress the learners, so it is upright to introduce the developed framework and system that might help to increase positive impact on the passing rate of the university.
Keywords: gamification; licensure examination; reviewer; descriptive analytics; predictive analytics; prescriptive analytics (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.stepacademic.net/ijcsr/article/view/124/64 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jcs:journl:v:4:y:2020:i:1:p:1-16
DOI: 10.25147/ijcsr.2017.001.1.40
Access Statistics for this article
More articles in International Journal of Computing Sciences Research from Step Academic
Bibliographic data for series maintained by Liam Demafelix ().