Working Together: Integrating Computational Modeling Approaches to Investigate Complex Phenomena

Complex systems are made up of many entities, whose interactions emerge into distinct collective patterns. Computational modeling platforms can provide a powerful means to investigate emergent phenomena in complex systems. Some research has been carried out in recent years about promoting students' modeling practices, specifically using technologically advanced tools and approaches that allow students to create, manipulate, and test computational models. However, not much research had been carried out on the integration of several modeling approaches when investigating complex phenomena. In this paper, we describe the design principles used to develop a middle school unit about ants' collective behavior that integrates three modeling approaches: conceptual drawn models, agent-based models, and system dynamics models. We provide results from an initial implementation of an 8th grade curricular unit, indicating that students engaged with several aspects of the modeling practice. Students' conceptual knowledge about ant pheromone communication increased following learning the unit. We also found gains in students' metamodeling knowledge about models as tools for investigating phenomena. We discuss the affordances and challenges of engaging students with several modeling approaches in science classroom

Security in online learning assessment towards an effective trustworthiness approach to support e-learning teams

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This paper proposes a trustworthiness model for the design of secure learning assessment in on-line collaborative learning groups. Although computer supported collaborative learning has been widely adopted in many educational institutions over the last decade, there exist still drawbacks which limit their potential in collaborative learning activities. Among these limitations, we investigate information security requirements in on-line assessment, (e-assessment), which can be developed in collaborative learning contexts. Despite information security enhancements have been developed in recent years, to the best of our knowledge, integrated and holistic security models have not been completely carried out yet. Even when security advanced methodologies and technologies are deployed in Learning Management Systems, too many types of vulnerabilities still remain opened and unsolved. Therefore, new models such as trustworthiness approaches can overcome these lacks and support e-assessment requirements for e-Learning. To this end, a trustworthiness model is designed in order to conduct the guidelines of a holistic security model for on-line collaborative learning through effective trustworthiness approaches. In addition, since users' trustworthiness analysis involves large amounts of ill-structured data, a parallel processing paradigm is proposed to build relevant information modeling trustworthiness levels for e-Learning.Peer ReviewedPostprint (author's final draft

Observation as a method to enhance collective efficacy: An integrative review

Objectives This review provides an integrative argument for the use of observation as an intervention to manipulate individual collective efficacy beliefs in sports teams. Design An exploration of the conceptual and empirical evidence underpinning observation-based interventions for increasing collective efficacy. Method A presentation of reflections on the following. First, we reflect on existing techniques used to increase self- and collective efficacy beliefs. Second, we consider collective efficacy in the context of observational learning and the various modeling techniques employed in the sports and motor performance literature. Third, we highlight relevant literature from neuroscience, outlining the analogous neural pathways evident for social cognition (i.e., collective efficacy) and observation. Results This review presents a case for the use of observation interventions to manipulate collective efficacy, drawing upon social psychological frameworks of human behavior, the observation-based literature, and contemporary understanding of brain and behavior. Conclusions Observation-based interventions are suited for collective efficacy manipulation in sport. There is a need to advance understanding of this relationship in order to maximize improvements in collective efficacy across group contexts

DESIGN, MODELING, AND CONTROL OF SOFT DYNAMIC SYSTEMS

Soft physical systems, be they elastic bodies, fluids, and compliant-bodied creatures, are ubiquitous in nature. Modeling and simulation of these systems with computer algorithms enable the creation of visually appealing animations, automated fabrication paradigms, and novel user interfaces and control mechanics to assist designers and engineers to develop new soft machines. This thesis develops computational methods to address the challenges emerged during the automation of the design, modeling, and control workflow supporting various soft dynamic systems. On the design/control side, we present a sketch-based design interface to enable non-expert users to design soft multicopters. Our system is endorsed by a data-driven algorithm to generate system identification and control policies given a novel shape prototype and rotor configurations. We show that our interactive system can automate the workflow of different soft multicopters\u27 design, simulation, and control with human designers involved in the loop. On the modeling side, we study the physical behaviors of fluidic systems from a local, collective perspective. We develop a prior-embedded graph network to uncover the local constraint relations underpinning a collective dynamic system such as particle fluid. We also proposed a simulation algorithm to model vortex dynamics with locally interacting Lagrangian elements. We demonstrate the efficacy of the two systems by learning, simulating and visualizing complicated dynamics of incompressible fluid

Collaborative design methodologies for clothing flat modeling

This article reflects on the importance of collaborative design methodologies in the construction of new configurations for teaching flat clothing modeling. Within the field of teaching fashion and clothing, but specifically in the disciplines of flat modeling, several problems can be identified regarding teaching-learning. Silva and França (2018) state that there is little perceived ability to understand the execution of the molds on the part of the students, which cause the discipline to be seen with a high degree of complexity, causing dissatisfaction, both on the part of the students and by part of the teachers who teach it. This article is based on data, four surveys carried out in fashion and clothing courses in Brazil regarding teaching-learning of the flat modeling technique and from the gaps identified in its results, we will substantiate the paths taken by this research.Based on the assumption that the understanding of the reasons and the difficulties present in the contexts of the researches carried out on teaching and learning of flat modeling in recent years, are not due to individual and solitary actions, but to collective constructions of all the authors involved. In this work, concepts of collaborative design methodologies are explored, as innovative and effective methods of this construction. Understanding that, through collaborative means, it is possible to contribute with activities and solutions from different fields, starting from a new perspective when conceiving formal concepts and solutions.Thus, the question that guides this study and which will be answered is: how can collaborative design methodologies contribute to the flat modeling of clothing? The article is structured in four topics, which aims to clarify points and difficulties raised in research that were carried out in recent years on teaching and learning of flat modeling through a systematic literature review that points out data on the state of the art of flat modeling and its relationship with collaborative methodologies

Lessons From the Assessment for Learning Project: Strategies for Building an Authentic Learning Community

This article explores findings from an evaluation of the Assessment for Learning Project, a grantee engagement strategy led by the Center for Innovation in Education focused on creating a learning community founded in continuous reflection and safety for risk-taking. The article shares the project’s model and approach, grounded in the core design elements of a field-facing learning agenda, grantmaking that leads with learning, and collective leadership. This article highlights the Assessment for Learning Project’s practices, such as a Request for Learning rather than traditional Request for Proposals; a requirement that grantees provide formative feedback to each other; and public demonstrations of learning in lieu of traditional reporting. And it explores how the project’s design helps flip the script on expertise by encouraging grantees to draw on one another for support and how it promotes a culture of experimentation that deepens learning relationships. Finally, this article points to the role of the project’s leadership team in modeling reflection and vulnerability, co-designing with grantees to bolster their leadership, and expanding its network by strategically connecting grantees to the broader field via a common learning agenda

Modelling collective learning in design

In this paper, a model of collective learning in design is developed in the context of team design. It explains that a team design activity uses input knowledge, environmental information, and design goals to produce output knowledge. A collective learning activity uses input knowledge from different agents and produces learned knowledge with the process of knowledge acquisition and transformation between different agents, which may be triggered by learning goals and rationale triggers. Different forms of collective learning were observed with respect to agent interactions, goal(s) of learning, and involvement of an agent. Three types of links between team design and collective learning were identified, namely teleological, rationale, and epistemic. Hypotheses of collective learning are made based upon existing theories and models in design and learning, which were tested using a protocol analysis approach. The model of collective learning in design is derived from the test results. The proposed model can be used as a basis to develop agent-based learning systems in design. In the future, collective learning between design teams, the links between collective learning and creativity, and computational support for collective learning can be investigated