Black Male Collegiate Athletes’ Perceptions of Their Career and Academic Preparation: A Mixed Methods Study

We employed a mixed methods approach with sequential explanatory design (Creswell & Plano Clark, 2017) and a Social Capital Theory framework (Bourdieu, 1977) to investigate three research questions: (1) In what ways were participants’ career and college readiness capital developed during high school? (2) How do participants view their academic and career growth and development prior to and after coming to college? (3) Who provided career and college development to participants in this study prior to their college entrance? Results revealed potential reasons why disparities existed between Black and White participants beginning in K-12 and continuing through college. Implications for anti-racist school counseling are given

Using the DELPHI Method to Collect Feedback on Student\u27s Perceptions of Teaching Quality

In educational institutions, teaching effectiveness is a highly valued asset among administrators, professors, and students alike. Information gathered from students is often used as a basis for promotion and tenure decisions (Abrami & d’Apollonia, 1999; Waters, Kemp, & Pucci, 1988), and, ideally, formative purposes. However, students do not always believe that their evaluations carry much weight (Chen & Hoshower, 2003; Spencer & Schmelkin, 2002). This is likely due to the fact that summarized results from student evaluations often do not get in the hands of professors until after that particular course has concluded and, therefore, the feedback does not directly benefit the students who provided it. The goal of the current paper is to introduce a method that can be used by instructors to evaluate the effectiveness of their teaching in a particular course in such a way as to implement change in the course if necessary for those very same students. First, we will discuss teaching effectiveness in general; second we will introduce the DELPHI method and its usefulness in evaluating effective teaching; and third we will report on the results of using this method in our courses with the goal of improving the learning experience for the students providing the feedback

Using informative behavior to increase engagement while learning from human reward

In this work, we address a relatively unexplored aspect of designing agents that learn from human reward. We investigate how an agent’s non-task behavior can affect a human trainer’s training and agent learning. We use the TAMER framework, which facilitates the training of agents by human-generated reward signals, i.e., judgements of the quality of the agent’s actions, as the foundation for our investigation. Then, starting from the premise that the interaction between the agent and the trainer should be bi-directional, we propose two new training interfaces to increase a human trainer’s active involvement in the training process and thereby improve the agent’s task performance. One provides information on the agent’s uncertainty which is a metric calculated as data coverage, the other on its performance. Our results from a 51-subject user study show that these interfaces can induce the trainers to train longer and give more feedback. The agent’s performance, however, increases only in response to the addition of performance-oriented information, not by sharing uncertainty levels. These results suggest that the organizational maxim about human behavior, “you get what you measure”—i.e., sharing metrics with people causes them to focus on optimizing those metrics while de-emphasizing other objectives—also applies to the training of agents. Using principle component analysis, we show how trainers in the two conditions train agents differently. In addition, by simulating the influence of the agent’s uncertainty–informative behavior on a human’s training behavior, we show that trainers could be distracted by the agent sharing its uncertainty levels about its actions, giving poor feedback for the sake of reducing the agent’s uncertainty without improving the agent’s performance

Dynamics of Alpha Control: Preparatory Suppression of Posterior Alpha Oscillations by Frontal Modulators Revealed with Combined EEG and Event-related Optical Signal

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously, we proposed that alpha (8–12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top–down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently recorded EEG, while participants performed a visual target detection task. The pretarget alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha\u27s inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across participants. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks before posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top–down control from attention networks modulates both posterior alpha and awareness of visual stimuli

Prototype effect and the persuasiveness of generalizations

An argument that makes use of a generalization activates the prototype for the category used in the generalization. We conducted two experiments that investigated how the activation of the prototype affects the persuasiveness of the argument. The results of the experiments suggest that the features of the prototype overshadow and partly overwrite the actual facts of the case. The case is, to some extent, judged as if it had the features of the prototype instead of the features it actually has. This prototype effect increases the persuasiveness of the argument in situations where the audience finds the judgment more warranted for the prototype than for the actual case (positive prototype effect), but decreases persuasiveness in situations where the audience finds the judgment less warranted for the prototype than for the actual case (negative prototype effect)

Noninvasive studies of human visual cortex using neuromagnetic techniques

The major goals of noninvasive studies of the human visual cortex are: to increase knowledge of the functional organization of cortical visual pathways; and to develop noninvasive clinical tests for the assessment of cortical function. Noninvasive techniques suitable for studies of the structure and function of human visual cortex include magnetic resonance imaging (MRI), positron emission tomography (PET), single photon emission tomography (SPECT), scalp recorded event-related potentials (ERPs), and event-related magnetic fields (ERFs). The primary challenge faced by noninvasive functional measures is to optimize the spatial and temporal resolution of the measurement and analytic techniques in order to effectively characterize the spatial and temporal variations in patterns of neuronal activity. In this paper we review the use of neuromagnetic techniques for this purpose. 8 refs., 3 figs

On the Perception of Religious Group Membership from Faces

BACKGROUND: The study of social categorization has largely been confined to examining groups distinguished by perceptually obvious cues. Yet many ecologically important group distinctions are less clear, permitting insights into the general processes involved in person perception. Although religious group membership is thought to be perceptually ambiguous, folk beliefs suggest that Mormons and non-Mormons can be categorized from their appearance. We tested whether Mormons could be distinguished from non-Mormons and investigated the basis for this effect to gain insight to how subtle perceptual cues can support complex social categorizations. METHODOLOGY/PRINCIPAL FINDINGS: Participants categorized Mormons' and non-Mormons' faces or facial features according to their group membership. Individuals could distinguish between the two groups significantly better than chance guessing from their full faces and faces without hair, with eyes and mouth covered, without outer face shape, and inverted 180°; but not from isolated features (i.e., eyes, nose, or mouth). Perceivers' estimations of their accuracy did not match their actual accuracy. Exploration of the remaining features showed that Mormons and non-Mormons significantly differed in perceived health and that these perceptions were related to perceptions of skin quality, as demonstrated in a structural equation model representing the contributions of skin color and skin texture. Other judgments related to health (facial attractiveness, facial symmetry, and structural aspects related to body weight) did not differ between the two groups. Perceptions of health were also responsible for differences in perceived spirituality, explaining folk hypotheses that Mormons are distinct because they appear more spiritual than non-Mormons. CONCLUSIONS/SIGNIFICANCE: Subtle markers of group membership can influence how others are perceived and categorized. Perceptions of health from non-obvious and minimal cues distinguished individuals according to their religious group membership. These data illustrate how the non-conscious detection of very subtle differences in others' appearances supports cognitively complex judgments such as social categorization

Ensemble of a subset of kNN classifiers

Combining multiple classifiers, known as ensemble methods, can give substantial improvement in prediction performance of learning algorithms especially in the presence of non-informative features in the data sets. We propose an ensemble of subset of kNN classifiers, ESkNN, for classification task in two steps. Firstly, we choose classifiers based upon their individual performance using the out-of-sample accuracy. The selected classifiers are then combined sequentially starting from the best model and assessed for collective performance on a validation data set. We use bench mark data sets with their original and some added non-informative features for the evaluation of our method. The results are compared with usual kNN, bagged kNN, random kNN, multiple feature subset method, random forest and support vector machines. Our experimental comparisons on benchmark classification problems and simulated data sets reveal that the proposed ensemble gives better classification performance than the usual kNN and its ensembles, and performs comparable to random forest and support vector machines