Designing Effective Simulation Games for Active Learning in Systems Engineering

Simulation games have been an effective method of teaching, especially for Systems Engineering concepts. The hands-on activities facilitate active, experiential, and collaborative learning with fun elements. Many simulation games have been developed in the past, but not all are equally effective. How to design a simulation game that is effective and easy to implement? This paper attempts to identify the key design factors that affect the performance of simulation games for teaching systems engineering concepts. By reviewing designs of several existing simulation games, important design factors were identified and verified. With these factors, a more effective way to design new simulation games has been suggested.Cockrell School of Engineerin

A Four Dimensional Model of Formal and Informal Learning

Learning systems focused on collaborative learning are often described in terms of formal and informal learning, however definitions of formal and informal learning vary, which makes it difficult to compare systems that may have been described using different perspectives. In this paper we present a framework for describing formality in e-learning systems, which can account for the most common perspectives: formality focused on Learning Objective, Learning Environment, Learning Activity and/or Learning Tool. Our framework can be used to compare different e-learning systems, and can also describe collaborative systems where different students can take very different roles in the activity, and the degree of formality can vary according to the role

Learning participation as systems practice

We describe an evolving praxeology for Systems Practice for managing complexity built on 30 years of developing supported open learning opportunities in the area of Systems within the curriculum of The Open University (UK). We ground this description in two specific examples of how notions of participation are incorporated conceptually and practically into a learners programme of study by considering: (i) the postgraduate course 'Environmental Decision Making. A Systems Approach' (T860) and (ii) the undergraduate course 'Managing complexity. A systems approach' (T306)

Holistic Learning: A workforce development paradigm

The development of workforce knowledge, skills and attitudes are widely acknowledged in extant literature as being pivotal levers to deliver process improvement and efficiency. The success of an organisation depends as much on its technical system as on the social system that supports it. Strategies for improving organisational performance need to incorporate arrangements for developing the workforce competences required to implement strategy. Lean construction by definition involves continuous small-step improvements (Kaizen), problem solving and employee involvement at all levels. The argument for providing workplace systems that support life-long learning within construction businesses therefore takes on greater significance. This paper reports on the pilot for a wider research aimed at firmly linking construction businesses to the learning domain. The pilot involved a survey of domain experts (276) which sought to characterise the Nigerian construction industry in terms of its knowledge and learning requirements, the supply systems for construction skills, the individual attributes required for optimal performance, and the appropriate pedagogical approaches for learning construction skills. Findings to date suggest that the Nigerian construction industry exhibits many characteristics of Taylor-Fordist systems but with tendencies towards knowledge-based systems suggesting the need for improved systems of learning. The training systems of construction firms were found to supply a small percentage of skilled workers to the industry pool, but the few were perceived to be the most competent. Construction skilled workers were perceived to require not only cognitive but also emotional and social competencies for optimal performance. This paper posits that the construction industry needs to align its skill provision systems with modern learning theory to create effective learners and learning environments within organisations to drive the learning needed for performance and innovation. The paper proposes the development of a conceptual model which captures the key elements of an effective skills learning solution for construction

Navigation in hypermedia learning systems: Experts vs. novices

With the advancement of Web technology, hypermedia learning systems are becoming more widespread in educational settings. Hypermedia learning systems present course content with non-sequential formats, so students are required to develop learning paths by themselves. Yet, empirical evidence indicates that not all students can benefit from hypermedia learning. Research into individual differences suggests that prior knowledge has significant effects on student learning in hypermedia systems, with experts and novices showing different preferences to the use of hypermedia learning systems and requiring different levels of navigation support. It is therefore essential to develop a mechanism to help designers understand the needs of experts and novices. To address this issue, this paper presents a framework to illustrate the needs of students with different levels of prior knowledge by analyzing the findings of previous research. The overall aim of this framework is to integrate students’ prior knowledge into the design of hypermedia learning systems. Finally, implications for the design of hypermedia learning systems are discussed

Inverse Reinforcement Learning in Swarm Systems

Inverse reinforcement learning (IRL) has become a useful tool for learning behavioral models from demonstration data. However, IRL remains mostly unexplored for multi-agent systems. In this paper, we show how the principle of IRL can be extended to homogeneous large-scale problems, inspired by the collective swarming behavior of natural systems. In particular, we make the following contributions to the field: 1) We introduce the swarMDP framework, a sub-class of decentralized partially observable Markov decision processes endowed with a swarm characterization. 2) Exploiting the inherent homogeneity of this framework, we reduce the resulting multi-agent IRL problem to a single-agent one by proving that the agent-specific value functions in this model coincide. 3) To solve the corresponding control problem, we propose a novel heterogeneous learning scheme that is particularly tailored to the swarm setting. Results on two example systems demonstrate that our framework is able to produce meaningful local reward models from which we can replicate the observed global system dynamics.Comment: 9 pages, 8 figures; ### Version 2 ### version accepted at AAMAS 201