Browsing by Subject "reciprocity"

Now showing 1 - 3 of 3
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    Forming a Mutually Respectful University-Community Partnership through a “Family as Faculty” Project
    (Engage!: Urban University Community Journal, 2019-05) Santamaría Graff, Cristina; Boehner, Joel
    In this paper, we, a university special education professor and an executive director of a parent-to- parent non-profit organization, describe our collaborative partnership built on a common understanding that parents of children with disabilities are educational leaders. We address how we work collaboratively to locate and establish families as co- educators in an undergraduate special education course on families for pre-service special education teachers by using a Family as Faculty (FAF) approach.
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    Predicting interval time for reciprocal link creation using survival analysis
    (Springer, 2018-12) Dave, Vachik S.; Al Hasan, Mohammad; Zhang, Baichuan; Reddy, Chandan K.; Computer and Information Science, School of Science
    The majority of directed social networks, such as Twitter, Flickr and Google+, exhibit reciprocal altruism, a social psychology phenomenon, which drives a vertex to create a reciprocal link with another vertex which has created a directed link toward the former. In existing works, scientists have already predicted the possibility of the creation of reciprocal link—a task known as “reciprocal link prediction”. However, an equally important problem is determining the interval time between the creation of the first link (also called parasocial link) and its corresponding reciprocal link. No existing works have considered solving this problem, which is the focus of this paper. Predicting the reciprocal link interval time is a challenging problem for two reasons: First, there is a lack of effective features, since well-known link prediction features are designed for undirected networks and for the binary classification task; hence, they do not work well for the interval time prediction; Second, the presence of ever-waiting links (i.e., parasocial links for which a reciprocal link is not formed within the observation period) makes the traditional supervised regression methods unsuitable for such data. In this paper, we propose a solution for the reciprocal link interval time prediction task. We map this problem to a survival analysis task and show through extensive experiments on real-world datasets that survival analysis methods perform better than traditional regression, neural network-based models and support vector regression for solving reciprocal interval time prediction.
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    The Transformational Relationship Evaluation Scale II (TRES II) Reflection Framework: Version 2
    (2022-04) Clayton, Patti H.; Camo-Biogradlija, Jasmina; Kniffin, Lori E.; Price, Mary F.; Bringle, Robert G.; Pier, Alyssa A.
    The Transformational Relationship Evaluation Scale Reflection Framework (TRES II Reflection Framework, Version 2) is a critical reflection tool designed for all participants in community-campus relationships to generate actionable learning regarding their collective work and to serve as an intervention to deepen those relationships. This tool was designed to accompany the Transformational Relationship Evaluation Scale II (TRES II), which on its own has documented utility to enhance partnership inquiry and practice (Kniffin et. al., 2020). The TRES II Reflection Framework broadens and deepens the scale with intentionally-designed prompts structured using the DEAL Model of Critical Reflection (Ash & Clayton, 2009). Authors’ Note: This version of the TRES II Reflection Framework was last updated in April, 2022, and a PDF file can be accessed at the link provided in the recommended reference. Contact Patti Clayton, patti.clayton@curricularengagement.com, for an editable Word file and/or future versions.