The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber‐infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell‐type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user‐friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community‐supported data evaluation metrics, accelerating plant research necessary for human and environmental health.
- NSF-PAR ID:
- 10329792
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Date Published:
- Journal Name:
- eLife
- Volume:
- 10
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract This exploratory paper highlights how problem‐based learning (PBL) provided the pedagogical framework used to design and interpret learning analytics from C
rystal Island: EcoJourneys , a collaborative game‐based learning environment centred on supporting science inquiry. In Crystal Island: EcoJourneys , students work in teams of four, investigate the problem individually and then utilize a brainstorming board, an in‐game PBL whiteboard that structured the collaborative inquiry process. The paper addresses a central question: how can PBL support the interpretation of the observed patterns in individual actions and collaborative interactions in the collaborative game‐based learning environment? Drawing on a mixed method approach, we first analyzed students' pre‐ and post‐test results to determine if there were learning gains. We then used principal component analysis (PCA) to describe the patterns in game interaction data and clustered students based on the PCA. Based on the pre‐ and post‐test results and PCA clusters, we used interaction analysis to understand how collaborative interactions unfolded across selected groups. Results showed that students learned the targeted content after engaging with the game‐based learning environment. Clusters based on the PCA revealed four main ways of engaging in the game‐based learning environment: students engaged in low to moderate self‐directed actions with (1) high and (2) moderate collaborative sense‐making actions, (3) low self‐directed with low collaborative sense‐making actions and (4) high self‐directed actions with low collaborative sense‐making actions. Qualitative interaction analysis revealed that a key difference among four groups in each cluster was the nature of verbal student discourse: students in the low to moderate self‐directed and high collaborative sense‐making cluster actively initiated discussions and integrated information they learned to the problem, whereas students in the other clusters required more support. These findings have implications for designing adaptive support that responds to students' interactions with in‐game activities.Practitioner notes What is already known about this topic
Learning analytic methods have been effective for understanding student learning interactions for the purposes of assessment, profiling student behaviour and the effectiveness of interventions.
However, the interpretation of analytics from these diverse data sets are not always grounded in theory and challenges of interpreting student data are further compounded in collaborative inquiry settings, where students work in groups to solve a problem.
What this paper adds
Problem‐based learning as a pedagogical framework allowed for the design to focus on individual and collaborative actions in a game‐based learning environment and, in turn, informed the interpretation of game‐based analytics as it relates to student's self‐directed learning in their individual investigations and collaborative inquiry discussions.
The combination of principal component analysis and qualitative interaction analysis was critical in understanding the nuances of student collaborative inquiry.
Implications for practice and/or policy
Self‐directed actions in individual investigations are critical steps to collaborative inquiry. However, students may need to be encouraged to engage in these actions.
Clustering student data can inform which scaffolds can be delivered to support both self‐directed learning and collaborative inquiry interactions.
All students can engage in knowledge‐integration discourse, but some students may need more direct support from teachers to achieve this.
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Sustainability, including environmental and social sustainability, has been identified across all sectors, from government to industry to academia, as a critical area for action. Sustainability goals and actions, by necessity, require input from many fields, but engineers play a potentially outsized role due to the structures and products they build, and the associated choices they make. The Engineering for One Planet (EOP) initiative aims to address this challenge by ensuring all future engineers, no matter their discipline, are equipped with the skills, knowledge, understanding, and mindsets to design, build, and create in sustainable ways. Much has been achieved to date by the EOP initiative, through a process of multi-stakeholder engagement, in both understanding and piloting solutions to realize the EOP vision. However, in order to achieve the far reaching systemic changes desired, a roadmap for a Collective Impact-informed, cross-sector, collaborative initiative was developed. This roadmap leverages the approaches yielded from the recent National Science Foundation (NSF)-funded EOP Scaling for Impact Workshop, the lessons learned and results achieved from the initiative to date, and key considerations drawn from a Collective Impact approach that centers equity. This roadmap calls for stakeholders—including academia, industry, accrediting and professional organizations, community organizations, non-profits, funders, and those communities most impacted by the negative impacts of environmental and social sustainability challenges— to move beyond singular programmatic interventions, and instead work to collaboratively understand and construct coordinated solutions, to integrating sustainability into engineering education and the engineering profession. The roadmap’s call to action invites collaborators to join this initiative and engage with the roadmap as a starting point for their work together; the roadmap provides immediate action steps, and invites collaborators to further shape the roadmap into a collective, achievable plan for systems change, that they, their institutions/organizations, and other cross-sector collaborators can embrace. For systems change is never complete and the solutions not finite; it is only through ongoing, collective action that we can fully understand, and learn how to address the lack of sustainability in engineering as the complex, social problem it is.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.66877
