Pregledni rad
https://doi.org/10.32985/ijeces.12.si.6
Deep Learning Approach for cognitive competency assessment in Computer Programming subject
Shahidatul Arfah Baharudin
; Malaysian Institute of Information Technology, Universiti Kuala Lumpur
Adidah Lajis
Sažetak
This research examines the competencies that are essential for an lecturer or instructor to evaluate the student based on automated assessments. The competencies are the skills, knowledge, abilities and behavior that are required to perform the task given, whether in a learning or a working environment. The significance of this research is that it will assist students who are having difficulty learning a Computer Programming Language course to identify their flaws using a Deep Learning Approach. As a result, higher education institutions have a problem with assessing students based on their competency level because; they still use manual assessment to mark the assessment. In order to measure intelligence, it is necessary to identify the cluster of abilities or skills of the type in which intelligence expresses itself. This grouping of skills and abilities referred to as "competency". Then, an automated assessment is a problem-solving activity in which the student and the computer interact with no other human intervention. This review focuses on collecting different techniques that have been used. In addition, the review finding shows the main gap that exists within the context of the studied areas, which contributes to our key research topic of interest.
Ključne riječi
Cognitive competency; deep learning; automated assessment; Bloom's taxonomy; computer programming
Hrčak ID:
266730
URI
Datum izdavanja:
2.11.2021.
Posjeta: 600 *