How Simulation can Illuminate Pedagogical and System Design Issues in Dynamic Open Ended Learning Environments

A Dynamic Open-Ended Learning Environment (DOELE) is a collection of learners and learning objects (LOs) that could be constantly changing. In DOELEs, learners need the support of Advanced Learning Technology (ALT), but most ALT is not designed to run in such environments. An architecture for designing advanced learning technology that is compatible with DOELEs is the ecological approach (EA). This thesis looks at how to test and develop ALT based on the EA, and argues that this process would benefit from the use of simulation. The essential components of an EA-based simulation are: simulated learners, simulated LOs, and their simulated interactions. In this thesis the value of simulation is demonstrated with two experiments. The first experiment focuses on the pedagogical issue of peer impact, how learning is impacted by the performance of peers. By systematically varying the number and type of learners and LOs in a DOELE, the simulation uncovers behaviours that would otherwise go unseen. The second experiment shows how to validate and tune a new instructional planner built on the EA, the Collaborative Filtering based on Learning Sequences planner (CFLS). When the CFLS planner is configured appropriately, simulated learners achieve higher performance measurements that those learners using the baseline planners. Simulation results lead to predictions that ultimately need to be proven in the real world, but even without real world validation such predictions can be useful to researchers to inform the ALT system design process. This thesis work shows that it is not necessary to model all the details of the real world to come to a better understanding of a pedagogical issue such as peer impact. And, simulation allowed for the design of the first known instructional planner to be based on usage data, the CFLS planner. The use of simulation for the design of EA-based systems opens new possibilities for instructional planning without knowledge engineering. Such systems can find niche learning paths that may have never been thought of by a human designer. By exploring pedagogical and ALT system design issues for DOELEs, this thesis shows that simulation is a valuable addition to the toolkit for ALT researchers

Search and restore: a study of cooperative multi-robot systems

Swarm intelligence is the study of natural biological systems with the ability to transform simple local interactions into complex global behaviours. Swarm robotics takes these principles and applies them to multi-robot systems with the aim of achieving the same level of complex behaviour which can result in more robust, scalable and flexible robotic solutions than singular robot systems. This research concerns how cooperative multi-robot systems can be utilised to solve real world challenges and outperform existing techniques. The majority of this research is focused around an emergency ship hull repair scenario where a ship has taken damage and sea water is flowing into the hull, decreasing the stability of the ship. A bespoke team of simulated robots using novel algorithms enable the robots to perform a coordinated ship hull inspection, allowing the robots to locate the damage faster than a similarly sized uncoordinated team of robots. Following this investigation, a method is presented by which the same team of robots can use self-assembly to form a structure, using their own bodies as material, to cover and repair the hole in the ship hull, halting the ingress of sea water. The results from a collaborative nature-inspired scenario are also presented in which a swarm of simple robots are tasked with foraging within an initially unexplored bounded arena. Many of the behaviours implemented in swarm robotics are inspired by biological swarms including their goals such as optimal distribution within environments. In this scenario, there are multiple items of varying quality which can be collected from different sources in the area to be returned to a central depot. The aim of this study is to imbue the robot swarm with a behaviour that will allow them to achieve the most optimal foraging strategy similar to those observed in more complex biological systems such as ants. The author’s main contribution to this study is the implementation of an obstacle avoidance behaviour which allows the swarm of robots to behave more similarly to systems of higher complexity