Browsing by Subject "networks"

Now showing 1 - 3 of 3
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    Creating Boundary Infrastructures in Networks of Collaboration for Educational Change
    (2023) Price, Jeremy F.; Waechter-Versaw, Amy; Moreland, Brooke; Knoors, A.J.
    This research utilizes Actor Network Theory (Fenwick & Edwards, 2011; Latour, 1987; Nespor, 2002) to document, analyze, and interrogate an educational change effort to promote educational equity and inclusion with technology across a dispersed and heterogenous network (Kezar et al., 2019; Lieberman & McLaughlin, 1992; Penuel et al., 2016) of teachers and other educators, families, and community members in response to the COVID-19 Pandemic. This research maps a statewide project supporting educators, families, and communities to develop resources and practices rooted in equitable and inclusive education distributed on a publicly-available website. All resources were rooted in the Culturally Relevant Pedagogy (Howard, 2003; Joseph, 2009; Ladson-Billings, 1995) and Universal Design for Learning (Fritzgerald, 2020; Meyer et al., 2013; Rose & Meyer, 2002) frameworks.
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    Networks identify productive forum discussions
    (APS, 2018-07) Traxler, Adrienne; Gavrin, A.; Lindell, Rebecca; Physics, School of Science
    Discussion forums provide a channel for students to engage with peers and course material outside of class, accessible even to commuter and nontraditional populations. Forums can build classroom community and aid learning, but students do not always take up these tools. We use network analysis to compare three semesters of forum logs from an introductory calculus-based physics course. The networks show dense structures of collaboration that differ significantly between semesters, even though aggregate participation statistics remain steady. After characterizing network structure for each semester, we correlate students’ centrality—a numeric measure of network position—with final course grade. Finally, we use a backbone extraction procedure to clean up “noise” in the network and clarify centrality-grade correlations. We find that more central network positions are positively linked with course success in the two semesters with denser forum networks. Centrality is a more reliable indicator of grade than non-network measures such as postcount. Backbone extraction destroys these correlations, suggesting that the noise is in fact signal and further analysis of the discussion transcripts is required.
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    Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity
    (APS, 2017-01) Bertolotti, Elena; Burioni, Raffaella; di Volo, Matteo; Vezzani, Alessandro; Department of Mathematical Sciences, School of Science
    We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons f I and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on f I , highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.