Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Bongo--a kids' programming environment for creating video games on the Web

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (leaves 86-87).by Andrew B. Bengel.M.Eng

Computers for learning : an empirical modelling perspective

In this thesis, we explore the extent to which computers can provide support for domain learning. Computer support for domain learning is prominent in two main areas: in education, through model building and the use of educational software; and in the workplace, where models such as spreadsheets and prototypes are constructed. We shall argue that computerbased learning has only realised a fraction of its full potential due to the limited scope for combining domain learning with conventional computer programming. In this thesis, we identify some of the limitations in the current support that computers offer for learning, and propose Empirical Modelling (EM) as a way of overcoming them. We shall argue that, if computers are to be successfully used for learning, they must support the widest possible range of learning activities. We introduce an Experiential Framework for Learning (EFL) within which to characterise learning activities that range from the private to the public, from the empirical to the theoretical, and from the concrete to the abstract. The term ‘experiential’ reflects a view of knowledge as rooted in personal experience. We discuss the merits of computer-based modelling methods with reference to a broad constructionist perspective on learning that encompasses bricolage and situated learning. We conclude that traditional programming practice is not well-suited to supporting bricolage and situated learning since the principles of program development inhibit the essential cognitive model building activity that informs domain learning. In contrast, the EM approach to model construction directly targets the semantic relation between the computer model and its domain referent and exploits principles that are closely related to the modeller’s emerging understanding or construal. In this way, EM serves as a uniform modelling approach to support and integrate learning activities across the entire spectrum of the EFL. This quality makes EM a particularly suitable approach for computer-based model construction to support domain learning. In the concluding chapters of the thesis, we demonstrate the qualities of EM for educational technology with reference to practical case studies. These include: a range of EM models that have advantages over conventional educational software due to their particularly open-ended and adaptable nature and that serve to illustrate a variety of ways in which learning activities across the EFL can be supported and scaffolded

Computers for learning : an empirical modelling perspective

In this thesis, we explore the extent to which computers can provide support for domain learning. Computer support for domain learning is prominent in two main areas: in education, through model building and the use of educational software; and in the workplace, where models such as spreadsheets and prototypes are constructed. We shall argue that computerbased learning has only realised a fraction of its full potential due to the limited scope for combining domain learning with conventional computer programming. In this thesis, we identify some of the limitations in the current support that computers offer for learning, and propose Empirical Modelling (EM) as a way of overcoming them. We shall argue that, if computers are to be successfully used for learning, they must support the widest possible range of learning activities. We introduce an Experiential Framework for Learning (EFL) within which to characterise learning activities that range from the private to the public, from the empirical to the theoretical, and from the concrete to the abstract. The term ‘experiential’ reflects a view of knowledge as rooted in personal experience. We discuss the merits of computer-based modelling methods with reference to a broad constructionist perspective on learning that encompasses bricolage and situated learning. We conclude that traditional programming practice is not well-suited to supporting bricolage and situated learning since the principles of program development inhibit the essential cognitive model building activity that informs domain learning. In contrast, the EM approach to model construction directly targets the semantic relation between the computer model and its domain referent and exploits principles that are closely related to the modeller’s emerging understanding or construal. In this way, EM serves as a uniform modelling approach to support and integrate learning activities across the entire spectrum of the EFL. This quality makes EM a particularly suitable approach for computer-based model construction to support domain learning. In the concluding chapters of the thesis, we demonstrate the qualities of EM for educational technology with reference to practical case studies. These include: a range of EM models that have advantages over conventional educational software due to their particularly open-ended and adaptable nature and that serve to illustrate a variety of ways in which learning activities across the EFL can be supported and scaffolded.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Programming with agents new metaphors for thinking about computation

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1996.Includes bibliographical references (p. [197]-206).by Michael David Travers.M.S

Skill progression demonstrated by users in the Scratch animation environment

The Scratch environment exemplifies a tool+community approach to teaching elementary programming skills, as it includes a website where users can publish, discuss, and organize animations that are programs. To explore this environment’s effectiveness for helping people to develop programming skills, we performed a quantitative analysis of 250 randomly-selected users’ data, including over 1000 of their animations. We measured skill based on four models that had proven useful in prior empirical studies. Overall, we found mixed results about the environment’s effectiveness. Among users who do not drop out, we found an increasing progression in social skills. However, we also observed an extremely high drop-out rate. Moreover, we observed a flat or decreasing level of demonstrated skill on virtually every measure. These results call into question whether simply combining an animation tool and an online community is sufficient for keeping people engaged long enough to learn elementary programming skills.This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Taylor & Francis and can be found at: http://www.tandfonline.com/toc/hihc20/current.Keywords: Empirical studies, Novice animation programmer

Music Learning with Massive Open Online Courses

Steels, Luc et al.-- Editors: Luc SteelsMassive Open Online Courses, known as MOOCs, have arisen as the logical consequence of marrying long-distance education with the web and social media. MOOCs were confidently predicted by advanced thinkers decades ago. They are undoubtedly here to stay, and provide a valuable resource for learners and teachers alike. This book focuses on music as a domain of knowledge, and has three objectives: to introduce the phenomenon of MOOCs; to present ongoing research into making MOOCs more effective and better adapted to the needs of teachers and learners; and finally to present the first steps towards 'social MOOCs’, which support the creation of learning communities in which interactions between learners go beyond correcting each other's assignments. Social MOOCs try to mimic settings for humanistic learning, such as workshops, small choirs, or groups participating in a Hackathon, in which students aided by somebody acting as a tutor learn by solving problems and helping each other. The papers in this book all discuss steps towards social MOOCs; their foundational pedagogy, platforms to create learning communities, methods for assessment and social feedback and concrete experiments. These papers are organized into five sections: background; the role of feedback; platforms for learning communities; experiences with social MOOCs; and looking backwards and looking forward. Technology is not a panacea for the enormous challenges facing today's educators and learners, but this book will be of interest to all those striving to find more effective and humane learning opportunities for a larger group of students.Funded by the European Commission's OpenAIRE2020 project.Peer reviewe

Empirical modelling as a new paradigm for educational technology

Educational technology has yet to deliver the benefits or successes that were expected in educational practice, especially in relation to issues other than the communication and delivery of teaching materials. Evidence suggests that these difficulties stem from the mismatch between formalised virtual learning environments and everyday sensemaking and between the rich potential for enhanced learning afforded by new technology and the constraints of old-style educational practice. In addressing this mismatch, some commentators suggest that the primary need is for a new culture of educational practice-and even that such a culture is already emerging, and others identify the need for a new paradigm for educational technology. The aim of this thesis is to explore the potential for a new paradigm for educational technology based on the principles and tools of Empirical Modelling (see http://dcs.warwick.ac.uk/modelling). The thesis builds upon previous research on Empirical Modelling as a constructionist approach to learning, and in particular Roe's doctoral thesis 'Computers for learning: an Empirical Modelling perspective'. Roe's treatment of Empirical Modelling can be viewed as generalising the use of spreadsheets for learning through applying 'programming by dependency' within the framework of existing educational practice. In contrast, this thesis is concerned at a more fundamental level with the contribution that Empirical Modelling can make to technology enhanced learning that may lead to new educational practices. In particular, it identifies eight significant characteristics of learning that are well-matched to Empirical Modelling activity, and associates these with experimental, flexible and meaningful strands in learning. The credentials of Empirical Modelling as a potential new foundation for educational technology are enhanced by demonstrating that Empirical Modelling is radically different from traditional software development and use. It provides a methodology for modelling with dependency that is more closely related to the use of spreadsheets for learning. The thesis elaborates on the relationship between Empirical Modelling and learning in a variety of different contexts, ways and applications. Three examples drawn from computer science higher education are explored to emphasise the experimental, flexible and meaningful characteristics of Empirical Modelling. This discussion of Empirical Modelling in a specific educational context is complemented by an investigation of its relevance to learning in a wider context, with reference to a broad range of subjects, to specific issues in language learning, and to the topics of lifelong learning and collaborative learning. Although the application of Empirical Modelling for learning is as yet too immature for large scale empirical studies, its potential is evaluated using informal empirical evidence arising from Empirical Modelling practice at Warwick. The sources for this evaluation are well-established teaching activities relating to Empirical Modelling in Computer Science at the University of 'Warwick, comprising an introductory module and a number of final year undergraduate projects. The thesis concludes by considering the extent to which Empirical Modelling can go beyond the support for constructionism envisaged by Roe, to address the broader agenda of supporting constructivist learning using computers. To this end, a close relationship between Empirical Modelling and a vision of constructivism recently set out by Bruno Latour in his paper 'The Promises of Constructivism' is demonstrated

public class Graphic_Design implements Code { // Yes, but how? }: An investigation towards bespoke Creative Coding programming courses in graphic design education

Situated in the intersection of graphic design, computer science, and pedagogy, this dissertation investigates how programming is taught within graphic design education. The research adds to the understanding of the process, practice, and challenges associated with introducing an audience of visually inclined practitioners—who are often guided by instinct—to the formal and unforgiving world of syntax, algorithms, and logic. Motivating the research is a personal desire to contribute towards the development of bespoke contextualized syllabi specifically designed to accommodate how graphic designers learn, understand, and use programming as an integral skill in their vocational practice.The initial literature review identifies a gap needing to be filled to increase both practical and theoretical knowledge within the interdisciplinary field of computational graphic design. This gap concerns a lack of solid, empirically based epistemological frameworks for teaching programming to non-programmers in a visual context, partly caused by a dichotomy in traditional pedagogical practices associated with teaching programming and graphic design, respectively. Based on this gap, the overarching research question posed in this dissertation is: “How should programming ideally be taught to graphic designers to account for how they learn and how they intend to integrate programming into their vocational practice?”A mixed methods approach using both quantitative and qualitative analyses is taken to answer the research questions. The three papers comprising the dissertation are all built on individual hypotheses that are subsequently used to define three specific research questions.Paper 1 performs a quantitative mapping of contemporary, introductory programming courses taught in design schools to establish a broader understanding of their structure and content. The paper concludes that most courses are planned to favor programming concepts rather than graphic design concepts. The paper’s finding can serve as a point of departure for a critical discussion among researchers and educators regarding the integration of programming in graphic design education.Paper 2 quantitatively assesses how the learning style profile of graphic design students compares with that of students in technical disciplines. The paper identifies a number of significant differences that call for a variety of pedagogic and didactic strategies to be employed by educators to effectively teach programming to graphic designers. Based on the results, specific recommendations are given.Paper 3 proposes a hands-on, experiential pedagogic method specifically designed to introduce graphic design students to programming. The method relies on pre-existing commercial graphic design specimens to contextualize programming into a domain familiar to graphic designers. The method was tested on the target audience and observations on its use are reported. Qualitative evaluation of student feedback suggests the method is effective and well-received. Additionally, twenty-four heuristics that elaborate and extend the paper’s findings by interweaving other relevant and influential sources encountered during the research project are provided. Together, the literature review, the three papers, and the heuristics provide comprehensive and valuable theoretical and practical insights to both researchers and educators, regarding key aspects related to introducing programming as a creative practice in graphic design education

Empirical modelling as a new paradigm for educational technology

Educational technology has yet to deliver the benefits or successes that were expected in educational practice, especially in relation to issues other than the communication and delivery of teaching materials. Evidence suggests that these difficulties stem from the mismatch between formalised virtual learning environments and everyday sensemaking and between the rich potential for enhanced learning afforded by new technology and the constraints of old-style educational practice. In addressing this mismatch, some commentators suggest that the primary need is for a new culture of educational practice-and even that such a culture is already emerging, and others identify the need for a new paradigm for educational technology. The aim of this thesis is to explore the potential for a new paradigm for educational technology based on the principles and tools of Empirical Modelling (see http://dcs.warwick.ac.uk/modelling). The thesis builds upon previous research on Empirical Modelling as a constructionist approach to learning, and in particular Roe's doctoral thesis 'Computers for learning: an Empirical Modelling perspective'. Roe's treatment of Empirical Modelling can be viewed as generalising the use of spreadsheets for learning through applying 'programming by dependency' within the framework of existing educational practice. In contrast, this thesis is concerned at a more fundamental level with the contribution that Empirical Modelling can make to technology enhanced learning that may lead to new educational practices. In particular, it identifies eight significant characteristics of learning that are well-matched to Empirical Modelling activity, and associates these with experimental, flexible and meaningful strands in learning. The credentials of Empirical Modelling as a potential new foundation for educational technology are enhanced by demonstrating that Empirical Modelling is radically different from traditional software development and use. It provides a methodology for modelling with dependency that is more closely related to the use of spreadsheets for learning. The thesis elaborates on the relationship between Empirical Modelling and learning in a variety of different contexts, ways and applications. Three examples drawn from computer science higher education are explored to emphasise the experimental, flexible and meaningful characteristics of Empirical Modelling. This discussion of Empirical Modelling in a specific educational context is complemented by an investigation of its relevance to learning in a wider context, with reference to a broad range of subjects, to specific issues in language learning, and to the topics of lifelong learning and collaborative learning. Although the application of Empirical Modelling for learning is as yet too immature for large scale empirical studies, its potential is evaluated using informal empirical evidence arising from Empirical Modelling practice at Warwick. The sources for this evaluation are well-established teaching activities relating to Empirical Modelling in Computer Science at the University of 'Warwick, comprising an introductory module and a number of final year undergraduate projects. The thesis concludes by considering the extent to which Empirical Modelling can go beyond the support for constructionism envisaged by Roe, to address the broader agenda of supporting constructivist learning using computers. To this end, a close relationship between Empirical Modelling and a vision of constructivism recently set out by Bruno Latour in his paper 'The Promises of Constructivism' is demonstrated.EThOS - Electronic Theses Online ServiceGBUnited Kingdo