Serious gaming for participatory planning of multi-hazard mitigation

Carson, Andrea; Windsor, Mary; Hill, Harvey; Haigh, Tonya; Wall, Nicole; Smith, Jason; Olsen, Rolf Erik; Bathke, Deborah J.; Demir, İbrahim; Muste, Marian

doi:10.1080/15715124.2018.1481079

Cited by 47 publications

(46 citation statements)

References 70 publications

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“…In a narrative review of literature in natural resource and environmental governance, we identified eight studies reporting on games used as learning-based interventions seeking to promote social learning and so contributing at changing in how things are done [32][33][34][35][36]44,45]. These studies differ in the way social learning is defined and operationalized, but share assumptions about game-play offering opportunities for (i) debate and interaction with other players/participants, (ii) critical reflection, either alone or collectively, (iii) development of a shared perception on the problem domain, (iv) development of a shared stock of knowledge, and (v) seeing the issue from a different perspective.…”

Section: Development and Evaluation Framework For Games As Learning-bmentioning

confidence: 99%

Conceptualizing Serious Games as a Learning-Based Intervention in the Context of Natural Resources and Environmental Governance

Rodela

Ligtenberg

Bosma

2019

Water

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The use of serious games in the governance of natural resources and the environment is progressively increasing and includes games used for research and data collection, teaching and training, and fostering a change of practices. However, this diversity remains underexplored and underreported. In view of a growing interest in the use of serious games in natural resource and environmental governance, the absence of discussions about how differences in intended use and delivery influence the performance, assessment, and outcomes of games is problematic. Here we present an inventory, and a description, of such different uses then, by focusing on serious games used as interventions, we discuss when, and how, games could be used to generate learning and social learning. To that end we use a narrative review of selected literature, and insight from research on social learning, to develop an inventory of game use, and within that inventory we conceptualize the use of serious games as a social learning intervention. Also, by means of an illustrative case of a serious game (developed as part of the Assessing the Learning Effects of Games on Attitude of Stakeholders toward Sustainable Shrimp Farming – ALEGAMS research project) we reflect on a few key aspects of game use. We suggest that developing a serious game needs several iterations and, although the learning outcomes can be assessed, the impact of games aiming at changes in current practice and policy will likely fall beyond the timespan of usual project periods. This is something future research should consider as it has implications for the research design and methodology.

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Section: Development and Evaluation Framework For Games As Learning-bmentioning

confidence: 99%

Conceptualizing Serious Games as a Learning-Based Intervention in the Context of Natural Resources and Environmental Governance

Rodela

Ligtenberg

Bosma

2019

Water

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“…Firstly, 21 publications describe an approach where participants were asked self-reflective questions in questionnaires, interviews or debriefings after game sessions, sometimes in combination with other methods [49,50,52,55,57,58,[62][63][64]67,68,[72][73][74][76][77][78]80,82,86,89]. For example, Dionnet et al [77] assessed their TADLA approach, which aims to facilitate farmers in the collective modernization of their irrigation system, by combining a questionnaire after game sessions with follow-up interviews.…”

Section: Cognitive Learningmentioning

confidence: 99%

“…Secondly, 12 publications analysed self-reported learning through pre-post measurements of participants' knowledge on the issues addressed in the game [58][59][60]65,70,76,78,[80][81][82]87,88]. Questionnaires were the common method in this approach, complemented with other methods, although Salvini et al [81] and Haug et al [82] instead used interviews and concept maps respectively.…”

Section: Cognitive Learningmentioning

confidence: 99%

“…The first category, reported by 13 publications, relates to participants acquiring an increased understanding on other participants' roles, mind-sets, and points of view [48,49,56,58,63,64,66,70,74,78,80,82,89]. The second category, reported by seven publications, instead relates to enhancing participants' ability to collaborate by building relationships and enhancing trust [48,49,52,55,69,80,81]. Both learning outcomes were assessed mostly qualitatively, based on self-reflective questions in questionnaires, interviews and debriefings conducted after game sessions or well after game sessions (post-post).…”

Section: Relational Learningmentioning

confidence: 99%

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On Evaluating Social Learning Outcomes of Serious Games to Collaboratively Address Sustainability Problems: A Literature Review

Haan

Voort

2018

Sustainability

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Serious games are increasingly explored as collaborative tools to enhance social learning on sustainable management of land and natural resources. A systematic literature review was conducted to examine the current state of the art of the different methods and procedures used to assess social learning outcomes of collaborative serious games. Forty-two publications were identified and included in the review following study selection and quality assessment steps. Extracted data from the publications were categorized in relation to five research questions. Approaches that were used to assess cognitive, normative, and relational learning outcomes of collaborative serious games were subsequently identified based on the categorizations. As a result, these approaches distinguished between the nature of learning in the assessment of collaborative serious games. Combined, these approaches provide an overview of how to assess social learning outcomes of collaborative serious games, including the methods and procedures that can be used, and may serve as a reference for scholars designing and evaluating collaborative serious games.

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“…The effective utilization of vast water data holds the key for long-term sustainability and resilience and presents opportunities to transform water governance for the upcoming decades (Grossman et al, 2015). In the hydrological domain, multivariate analysis relying on extensive and semantically-connected data resources is required to generate actionable knowledge and produce realistic and beneficial solutions to water challenges facing communities (Jadidoleslam et al, 2019;Carson et al, 2018). However, the inaccessible, unstructured, nonstandardized, and incompatible nature of the data makes optimized data models (Demir and Szczepanek, 2017) and smarter analytics approaches a necessity (Sermet and Demir, 2018a).…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources

Sit¹,

Demiray²,

Xiang³

et al. 2020

Preprint

Self Cite

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The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety, and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water resources management, and climate change. Combined with the growing availability of computational resources and popularity of deep learning, these data are transformed into actionable and practical knowledge, revolutionizing the water industry. In this article, a systematic review of literature is conducted to identify existing research which incorporates deep learning methods in the water sector, with regard to monitoring, management, governance and communication of water resources. The study provides a comprehensive review of state-of-the-art deep learning approaches used in the water industry for generation, prediction, enhancement, and classification tasks, and serves as a guide for how to utilize available deep learning methods for future water resources challenges. Key issues and challenges in the application of these techniques in the water domain are discussed, including the ethics of these technologies for decision-making in water resources management and governance. Finally, we provide recommendations and future directions for the application of deep learning models in hydrology and water resources.

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Serious gaming for participatory planning of multi-hazard mitigation

Cited by 47 publications

References 70 publications

Conceptualizing Serious Games as a Learning-Based Intervention in the Context of Natural Resources and Environmental Governance

Conceptualizing Serious Games as a Learning-Based Intervention in the Context of Natural Resources and Environmental Governance

On Evaluating Social Learning Outcomes of Serious Games to Collaboratively Address Sustainability Problems: A Literature Review

A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources

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