Universiti Teknologi Malaysia Institutional Repository

Student approach to learning in programming courses among industrial mechatronics engineering technology students

Shahri, Norsyarizan and Abdul Rahman, Roselainy and Hussain, Noor Hamizah (2014) Student approach to learning in programming courses among industrial mechatronics engineering technology students. International Conference on Teaching and Learning in Computing and Engineering . pp. 100-105. ISSN 2377-0309

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Official URL: https://dx.doi.org/10.1109/LaTiCE.2014.26


Experience has shown that students face some difficulties in the learning of Programmable Logic Controller (PLC), Programming Technique and Micro controller courses which are the core technical courses taught in MARA High Skill College Penang (KKTM), Malaysia. As a preliminary study, it was considered pertinent to identify the learning approaches that students use and which characteristics will contribute to learning success and the achievement of learning outcomes. Thus, this study will first focus on Student Approach to Learning (SAL). SAL can be described as how students approach their learning tasks during the process of study while considering their own actual motivation, how they learn the topics and how they engage in the learning process in real college context. Two learning approaches will be examined, i.e., either surface or deep learning approaches. The samples will be taken from first and second year students in Industrial Mechatronics Engineering Technology Program. Questionnaire is the main instrument used that will focus on students' learning approaches. Interviews were conducted to gather more qualitative data which will support the results from the survey. The results from this study will inform and uncover the relationship among students' approaches to learning and study success. This finding will be useful to determine students' engagement in learning, and thus will help to inform on how to support and foster students use of deep learning approach and improve their self-regulation in learning.

Item Type:Article
Uncontrolled Keywords:deep learning approach, self-regulation in learning
Subjects:T Technology
Divisions:Razak School of Engineering and Advanced Technology
ID Code:62699
Deposited By: Fazli Masari
Deposited On:05 Jun 2017 02:02
Last Modified:05 Jun 2017 02:02

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