Martina A. Doolan

DEVELOPING A PEDAGOGY: THE ROLE OF THE TUTOR IN ENABLING STUDENT LEARNING THROUGH THE USE OF A WIKI

This chapter clarifies the role of the tutor in enabling collaborative learning through assessment using technology as part of a blended learning framework. This is achieved through a practical example of using Wikipedia and the Collaborative Learning through Assessment and Technology (CLAT) pedagogical model.

A Pedagogical Framework For Collaborative Learning in a Social Blended E-Learning Context

The aim of this chapter is to introduce a pedagogical framework, the dialogic shamrock, for collaborative learning through technology, which is not a replacement for other learning theories rather it is a synthesis of the literature which draws upon learner centric, constructivist, and sociocultural perspectives and is related to the concepts of online learning and collaborative technology including Web 2.0 in higher education. The examples of use focus on the learner as participator in curriculum design. The dialogic shamrock and examples of use presented test the framework and are intended to help educators across the educational sector to understand the key concepts to encourage learners to work collaboratively supported by technology within a socially blended learning framework in a social learning context.The framework is not intended to be prescriptive rather to act as a guide for educators who seek to use a blend of technology and class-based activities to engage learners in collaborative social learning contexts.

Student Choice: Blends of Technology Beyond the University to Support Social Interaction and Social Participation in Learning

This paper presents an overview of a blended collaborative learning design driven by assessment and feedback. To extend class based activities students were provided with a private group space on the university managed learning environment. They chose to supplement this using technologies beyond those provided by the University to support their social interactions and participate in their learning. Qualitative data analysis of student’s reflections provides insights into the students own blends of technology including Skype, What’s App, Facebook amongst others and accessed via their hand held mobile devices such as Smartphones and laptops. These were used by the students to connect and collaborate with their peer group to complete the set tasks throughout the module and the final group based assessment.

Developing an agent-based simulation model of software evolution

Abstract Context In attempt to simulate the factors that affect the software evolution behaviour and possibly predict it, several simulation models have been developed recently. The current system dynamic (SD) simulation model of software evolution process was built based on actor-network theory (ANT) of software evolution by using system dynamic environment, which is not a suitable environment to reflect the complexity of ANT theory. In addition the SD model has not been investigated for its ability to represent the real-world process of software evolution. Objectives This paper aims to re-implements the current SD model to an agent-based simulation environment ‘Repast’ and checks the behaviour of the new model compared to the existing SD model. It also aims to investigate the ability of the new Repast model to represent the real-world process of software evolution. Methods a new agent-based simulation model is developed based on the current SD models specifications and then tests similar to the previous model tests are conducted in order to perform a comparative evaluation between of these two results. In addition an investigation is carried out through an interview with an expert in software development area to investigate the models ability to represent real-world process of software evolution. Results The Repast model shows more stable behaviour compared with the SD model. Results also found that the evolution health of the software can be calibrated quantitatively and that the new Repast model does have the ability to represent real-world processes of software evolution. Conclusion It is concluded that by applying a more suitable simulation environment (agent-based) to represent ANT theory of software evolution, that this new simulation model will show more stable bahaviour compared with the previous SD model; And it will also shows the ability to represent (at least quantatively) the real-world aspect of software evolution.