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Articles 1 - 7 of 7
Full-Text Articles in Psychology
Parametrically Constrained Lightness Model Incorporating Edge Classification And Increment-Decrement Neural Response Asymmetries, Michael E. Rudd
Parametrically Constrained Lightness Model Incorporating Edge Classification And Increment-Decrement Neural Response Asymmetries, Michael E. Rudd
MODVIS Workshop
Lightness matching data from disk-annulus experiments has the form of a parabolic (2nd-order polynomial) function when matches are plotted against annulus luminance on log-log axes. Rudd (2010) has proposed a computational cortical model to account for this fact and has subsequently (Rudd, 2013, 2014, 2015) extended the model to explain data from other lightness paradigms, including staircase-Gelb and luminance gradient illusions (Galmonte, Soranzo, Rudd, & Agostini, 2015). Here, I re-analyze parametric lightness matching data from disk-annulus experiments by Rudd and Zemach (2007) and Rudd (2010) for the purpose of further testing the model and to try to constrain …
An Image-Based Model For Early Visual Processing, Heiko H. Schütt, Felix A. Wichmann
An Image-Based Model For Early Visual Processing, Heiko H. Schütt, Felix A. Wichmann
MODVIS Workshop
No abstract provided.
A Learning Model For L/M Specificity In Ganglion Cells, Albert Ahumada
A Learning Model For L/M Specificity In Ganglion Cells, Albert Ahumada
MODVIS Workshop
An unsupervised learning model for developing L/M specific wiring at the ganglion cell level would support the research indicating L/M specific wiring at the ganglion cell level (Reid and Shapley, 2002). Removing the contributions to the surround from cells of the same cone type improves the signal-to-noise ratio of the chromatic signals. The unsupervised learning model used is Hebbian associative learning, which strengthens the surround input connections according to the correlation of the output with the input. Since the surround units of the same cone type as the center are redundant with the center, their weights end up disappearing. This …
The Effects Of Styles Of Dress On First Impressions, Ashley Dibert, Ashley Laird, Di Wu
The Effects Of Styles Of Dress On First Impressions, Ashley Dibert, Ashley Laird, Di Wu
The Research and Scholarship Symposium (2013-2019)
Many factors influence our first impression. Previous research found that clothes may affect people’s perceptions and attitudes toward others. Even subtle changes in the style of dress would affect others’ perceptions on multiple characters such as success, trustworthiness and reliability (Howlett, Pine, & Orakcioglu, 2013). It has also been found that the amount of similarities between raters and the individuals rated were positively correlated with the rating scores of favorable characteristics (Michinov & Michinov, 2011).The current research aimed to investigate how a person’s own style of dress would influence their perception on attraction based on those individuals’ style of dress. …
Birds Of A Feather Learn Together: Learning Community Outcomes Assessment Using Propensity Score Matching, Elisabeth M. Pyburn, Heather Dawn Harris
Birds Of A Feather Learn Together: Learning Community Outcomes Assessment Using Propensity Score Matching, Elisabeth M. Pyburn, Heather Dawn Harris
Showcase of Graduate Student Scholarship and Creative Activities
The goal of the study was to provide an example of propensity score matching techniques within the context of higher education assessment. At our institution, a select number of incoming first-year students participate in major-specific learning communities. Because the decision to join the communities is purely voluntary, one might expect that students who elect to join the program may differ from those who do not. Thus, important covariates related to self-selection into the learning community were identified. Two years of Arts learning community data were analyzed to compare the academic performance and civic-mindedness of learning community students to an arts …
Team Interaction Dynamics During Collaborative Problem Solving, Travis J. Wiltshire, Stephen M. Fiore Ph.D.
Team Interaction Dynamics During Collaborative Problem Solving, Travis J. Wiltshire, Stephen M. Fiore Ph.D.
Human Factors and Applied Psychology Student Conference
The need for better understanding collaborative problem solving (CPS) is rising in prominence as many organizations are increasingly addressing complex problems requiring the combination of diverse sets of individual expertise to address novel situations. This research draws from theoretical and empirical work that describes the knowledge coordination arising from team communications during CPS and builds from this by incorporating methods to study interaction dynamics. Interaction between team members in such contexts is inherently dynamic and exhibits nonlinear patterns not accounted for by extant research methods. To redress this gap, the present study draws from methods designed to study social and …
The Reliability Of Crowdsourcing: Latent Trait Modeling With Mechanical Turk, Matt Baucum, Steven Rouse Dr., Cindy Miller-Perrin, Elizabeth Mancuso Dr.
The Reliability Of Crowdsourcing: Latent Trait Modeling With Mechanical Turk, Matt Baucum, Steven Rouse Dr., Cindy Miller-Perrin, Elizabeth Mancuso Dr.
Seaver College Research And Scholarly Achievement Symposium
Mechanical Turk, an online crowdsourcing platform, has recently received increased attention in the social sciences as studies continue to suggest its viability as a source for reliable experimental data. Given the ease with which large samples can be quickly and inexpensively gathered, it is worth examining whether Mechanical Turk can provide accurate experimental data for methodologies requiring such large samples. One such methodology is Item Response Theory, a psychometric paradigm that defines test items by a mathematical relationship between a respondent’s ability and the probability of item endorsement. To test whether Mechanical Turk can serve as a reliable source of …