Towards understanding and improving the process of small group collaborative learning in software engineering education

Oriogun, Peter (2006) Towards understanding and improving the process of small group collaborative learning in software engineering education. Doctoral thesis, London Metropolitan University.

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Abstract / Description

The research aim of this submission for PhD by Prior Output is to understand and improve the process of small group collaborative learning in software engineering education. The research portfolio supporting the submission specifically deals with a number of background studies (the establishment of an optimal software life cycle process model for teaching software engineering in the small group collaborative setting) leading to the development of an appropriate pedagogical approach for underpinning small group learning, understanding the type of learning interaction that was taking place within such small group learning, and finally, the development of appropriate methods for analysing collaborative small group learning in software engineering education. In the portfolio of work submitted for the PhD, I have systematically investigated my research aim and problem in studies involving 241 different students over a period of 8 years. I contend in my submission that I have made a significant contribution to knowledge in my quest to understand and improve the process of small group collaborative learning in software engineering education within higher education, in order to prepare students for employment in software engineering by (i) developing and testing a documentation toolkit for collaborative problem-based learning (ii) a methodological tool for analysing and understanding inter-rater reliability (iii) a framework for the development of teamwork and cognitive reasoning when learning in small groups.

Item Type:	Thesis (Doctoral)
Additional Information:	uk.bl.ethos.529790
Uncontrolled Keywords:	collaborative learning; learning interaction; teamwork; problem-based learning; cognitive reasoning; software engineering education; higher education; employment
Subjects:	000 Computer science, information & general works
Department:	School of Computing and Digital Media
Depositing User:	Chiara Repetto
Date Deposited:	17 May 2022 08:21
Last Modified:	17 May 2022 08:21
URI:	https://repository.londonmet.ac.uk/id/eprint/7647

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