AbstractsComputer Science

Pedagogical-based learning object system to support self-regulated learning of computer science

by Ali Alharbi




Institution: University of Newcastle
Department:
Degree: PhD
Year: 2013
Keywords: computer science education; learning objects; self regulated learning; learning styles
Record ID: 1070646
Full text PDF: http://hdl.handle.net/1959.13/1039667


Abstract

Research Doctorate - Doctor of Philosophy (PhD) Educators strive to design high-quality learning materials to help students gain an understanding of the subjects under study. Today, in many disciplines, learning is self-regulated by students rather than enforced by teachers. Students are expected to seek knowledge through active participation in the learning process, and teachers serve as facilitators. In areas such as computer science, a dynamically changing field that is affected by new technologies, there is a lack of application of learning theories to the design and delivery of learning materials. In the last few years, there has been increased attention to the concept of learning objects as a future generation in designing and delivering learning materials. Learning objects can provide a standard approach to design of flexible, adaptable, reusable, and easy to find learning materials. However, research indicated a lack of consideration of learning theories in the current approach to the design and delivery of learning objects. This thesis investigates the educational effectiveness of the design and delivery of learning objects based on contemporary theories of self-regulated learning by taking into consideration students’ learning styles. The study proposes a pedagogical self-regulated learning framework that considers the theory of learning styles as one of its central components. The framework was then applied to the design of a learning object system to demonstrate how learning theories can be embodied in the design and delivery of computer science learning materials. A number of learning objects were designed to support students’ different learning styles. The system also implemented a learning style awareness module, which is responsible for identifying students’ learning styles and providing guides to learning strategies to help students utilise the strengths and overcome the weaknesses of their learning styles. Moreover, the system focuses on improving students’ metacognitive strategies, such as self-assessment and self-reflection, to help them become more self-regulated learners. An empirical study was conducted to educationally evaluate the system in a core course on programming languages. The study used a quasi-experiment to compare the academic achievement of a group of students who used the system for their self- regulated learning with a group that was taught using the traditional instructional approach. The results of the study support the educational effect of the system, as indicated by the students’ achievement and high level of satisfaction.