Comprendiendo el potencial y los desafíos del Big Data en las escuelas y la educación

In recent years, the world has experienced a huge revolution centered around the gathering and application of big data in various fields. This has affected many aspects of our daily life, including government, manufacturing, commerce, health, communication, entertainment, and many more. So far, education has benefited only a little from the big data revolution. In this article, we review the potential of big data in the context of education systems. Such data may include log files drawn from online learning environments, messages on online discussion forums, answers to open-ended questions, grades on various tasks, demographic and administrative information, speech, handwritten notes, illustrations, gestures and movements, neurophysiologic signals, eye movements, and many more. Analyzing this data, it is possible to calculate a wide range of measurements of the learning process and to support various educational stakeholders with informed decision-making. We offer a framework for better understanding of how big data can be used in education. The framework comprises several elements that need to be addressed in this context: defining the data; formulating data-collecting and storage apparatuses; data analysis and the application of analysis products. We further review some key opportunities and some important challenges of using big data in educationEn los últimos años, el mundo ha experimentado una gran revolución centrada en la recopilación y aplicación de big data en varios campos. Esto ha afectado muchos aspectos de nuestra vida diaria, incluidos el gobierno, la manufactura, el comercio, la salud, la comunicación, el entretenimiento y muchos más. Hasta ahora, la educación se ha beneficiado muy poco de la revolución del big data. En este artículo revisamos el potencial de los macrodatos en el contexto de los sistemas educativos. Dichos datos pueden incluir archivos de registro extraídos de entornos de aprendizaje en línea, mensajes en foros de discusión en línea, respuestas a preguntas abiertas, calificaciones en diversas tareas, información demográfica y administrativa, discurso, notas escritas a mano, ilustraciones, gestos y movimientos, señales neurofisiológicas, movimientos oculares y muchos más. Analizando estos datos es posible calcular una amplia gama de mediciones del proceso de aprendizaje y apoyar a diversos interesados educativos con una toma de decisiones informada. Ofrecemos un marco para una mejor comprensión de cómo se puede utilizar el big data en la educación. El marco comprende varios elementos que deben abordarse en este contexto: definición de los datos; formulación de aparatos de recolección y almacenamiento de datos; análisis de datos y aplicación de productos de análisis. Además, revisamos algunas oportunidades clave y algunos desafíos importantes del uso de big data en la educació

Role of the neurologist in hazard identification and risk assessment.

This review describes strategies used by a clinical neurologist in the investigation of neurotoxic disease. It emphasizes the need for a high level of suspicion that environmental substances are capable of producing impairments in neurologic and neurobehavioral functions. Because of the difficulties in differentiating neurotoxic from nonneurotoxic disease when presented with common neurological symptoms, it is necessary to rely upon corroborative evidence from past medical records, work and environmental histories, and exposure data, as well as detailed neurological examinations, to reach a conclusion about causation. Sensitive electrophysiologic and neuropsychologic test batteries are useful in identifying subclinical impairments and in providing objective confirmation of abnormalities in the central and peripheral nervous systems. Combining scientific and epidemiologic information with experience and clinical judgment, these sources of information are used in the formulation of a clinical diagnosis. When many patients among a group of people are exposed to neurotoxicants, the effects of the exposure may vary from one to another because of differences in susceptibility, duration of exposure and dosage of neurotoxicant, and other possible risk factors. Group statistics may obscure a significant effect for the larger group, despite clinically obvious effects in an individual. The neurologist applies clinical skills and refers to the accumulated neurotoxicologic literature as a frame of reference to make a diagnosis about an individual patient or a group of patients who have been exposed to particular neurotoxicants. The Boston University Environmental Neurology Assessment (BUENA) is a scheme that attempts to combine epidemiologic methodology and clinical approaches to detect effects of neurotoxic exposure. The advantages and limitations of such a strategy are discussed

Aerospace Medicine and Biology: a Continuing Bibliography with Indexes (Supplement 328)

This bibliography lists 104 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

EEG-based cognitive control behaviour assessment: an ecological study with professional air traffic controllers

Several models defining different types of cognitive human behaviour are available. For this work, we have selected the Skill, Rule and Knowledge (SRK) model proposed by Rasmussen in 1983. This model is currently broadly used in safety critical domains, such as the aviation. Nowadays, there are no tools able to assess at which level of cognitive control the operator is dealing with the considered task, that is if he/she is performing the task as an automated routine (skill level), as procedures-based activity (rule level), or as a problem-solving process (knowledge level). Several studies tried to model the SRK behaviours from a Human Factor perspective. Despite such studies, there are no evidences in which such behaviours have been evaluated from a neurophysiological point of view, for example, by considering brain activity variations across the different SRK levels. Therefore, the proposed study aimed to investigate the use of neurophysiological signals to assess the cognitive control behaviours accordingly to the SRK taxonomy. The results of the study, performed on 37 professional Air Traffic Controllers, demonstrated that specific brain features could characterize and discriminate the different SRK levels, therefore enabling an objective assessment of the degree of cognitive control behaviours in realistic setting

The Court’s Brain: Neuroscience and Judicial Decision Making in Criminal Sentencing

Cutting-edge neuroscientific studies provide new insights into the inner workings of the human brain. At the same time, innovations in justice-system data collection have allowed researchers to gather and analyze vast quantities of statistical data in criminal-sentencing patterns. The combination of the two genres of study provides us with the first scientifically based demonstration that well-meaning egalitarian judges may have strong neurophysiologic reactions to defendants, victims, experts, and attorneys. These reactions help us explore whether or not race affects judicial decision making. The Model Code of Judicial Conduct, caselaw, the Fourteenth Amendment, and the constitutions of every state prohibit judges from using race as a factor in sentencing.1 However, traditional notions of race bias are based on the idea that disparate outcomes are a simpleminded application of racial bias perpetrated by a select few judges who are not aligned with the values of the justice system.2 The overwhelming majority of judges are committed to fairness and impartiality. The overwhelming majority of judges would also agree that racial bias is abhorrent and that it has no place in our justice system. However, the emerging neuroscience compels the thoughtful analyst to inquire about the role of the brain’s automatic reactions in decision making. Neuroscientists explore the brain’s processes, but the justice system must be provided with an analysis of how the law shapes the ways that a judge’s brain may react. The rigorous analysis required in the application of the four principles of criminal sentencing (i.e., retribution, rehabilitation, deterrence, and incapacitation)3 may allow or even facilitate problematic neurophysiologic reactions in a judge’s brain and may result in disparate sentencing patterns. Yet the sentencing disparities are not explored, and the proof that racial bias is the cause is not fully accepted.4 This is partially because the ways in which racial bias may manifest in a judge’s brain are not easily understood.

Resting-State Quantitative Electroencephalography Reveals Increased Neurophysiologic Connectivity in Depression

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–20 Hz) frequency bands. The frontopolar region contained the greatest number of “hub nodes” (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD

Evidence of Neurotoxicity of Ecstasy: Sustained Effects on Electroencephalographic Activity in Polydrug Users

According to previous EEG reports of indicative disturbances in Alpha and Beta activities, a systematic search for distinct EEG abnormalities in a broader population of Ecstasy users may especially corroborate the presumed specific neurotoxicity of Ecstasy in humans.105 poly-drug consumers with former Ecstasy use and 41 persons with comparable drug history without Ecstasy use, and 11 drug naives were investigated for EEG features. Conventional EEG derivations of 19 electrodes according to the 10-20-system were conducted. Besides standard EEG bands, quantitative EEG analyses of 1-Hz-subdivided power ranges of Alpha, Theta and Beta bands have been considered.Ecstasy users with medium and high cumulative Ecstasy doses revealed an increase in Theta and lower Alpha activities, significant increases in Beta activities, and a reduction of background activity. Ecstasy users with low cumulative Ecstasy doses showed a significant Alpha activity at 11 Hz. Interestingly, the spectral power of low frequencies in medium and high Ecstasy users was already significantly increased in the early phase of EEG recording. Statistical analyses suggested the main effect of Ecstasy to EEG results.Our data from a major sample of Ecstasy users support previous data revealing alterations of EEG frequency spectrum due rather to neurotoxic effects of Ecstasy on serotonergic systems in more detail. Accordingly, our data may be in line with the observation of attentional and memory impairments in Ecstasy users with moderate to high misuse. Despite the methodological problem of polydrug use also in our approach, our EEG results may be indicative of the neuropathophysiological background of the reported memory and attentional deficits in Ecstasy abusers. Overall, our findings may suggest the usefulness of EEG in diagnostic approaches in assessing neurotoxic sequela of this common drug abuse

Moving psychopathology forward: combining a transdiagnostic and dimensional approach to clinical anxiety, depressive, and substance use constructs

The National Institute of Mental Health Research Domain Criteria (RDoC) initiative calls for systemic efforts to integrate neurobehavioral traits into dimensional models of psychopathology (Nelson et al., 2016). Examples are needed of how RDoC constructs can be linked to clinical symptoms. Thus, researchers evaluate two domains proposed by the RDoC model, Positive and Negative Valence System. Relevant MMPI-2-RF subscales, RC2 (Low Positive Emotion), RC7 (Negative Emotionality), and DISC-r (Disconstraint) are used to examined the extent to which depressive, anxiety, and substance use disorders share underlying neurobehavioral constructs in 2,873 inpatients and outpatients from the Minneapolis Veterans Affairs (VA) Medical Center and the Hennepin County Medical Center. Predictions were partially supported, clinical symptoms of depression and substance use overlap on neurobehavioral domains of positive valance, anxiety and substance use overlap on neurobehavioral domains of anxiety and substance use, however depression and anxiety did not overlap with cognitive systems. Results partially provide support for building a bridge between neurobehavioral constructs derived from neurophysiologic research (i.e., RDoC model) with core features of co-occurring psychopathology using a dimensional approach (MMPI-2-RF). With regards to inhibitory control (Cognitive Systems Domain), more research is needed to conceptualize INH as transdiagnostic

Covert Reorganization of Implicit Task Representations by Slow Wave Sleep

There is evidence that slow wave sleep (SWS) promotes the consolidation of memories that are subserved by mediotemporal- and hippocampo-cortical neural networks. In contrast to implicit memories, explicit memories are accompanied by conscious (attentive and controlled) processing. Awareness at pre-sleep encoding has been recognized as critical for the off-line memory consolidation. The present study elucidated the role of task-dependent cortical activation guided by attentional control at pre-sleep encoding for the consolidation of hippocampus-dependent memories during sleep.A task with a hidden regularity was used (Number Reduction Task, NRT), in which the responses that can be implicitly predicted by the hidden regularity activate hippocampo-cortical networks more strongly than responses that cannot be predicted. Task performance was evaluated before and after early-night sleep, rich in SWS, and late-night sleep, rich in rapid eye movement (REM) sleep. In implicit conditions, slow cortical potentials (SPs) were analyzed to reflect the amount of controlled processing and the localization of activated neural task representations.During implicit learning before sleep, the amount of controlled processing did not differ between unpredictable and predictable responses, nor between early- and late-night sleep groups. A topographic re-distribution of SPs indicating a spatial reorganization occurred only after early, not after late sleep, and only for predictable responses. These SP changes correlated with the amount of SWS and were covert because off-line RT decrease did not differentiate response types or sleep groups.It is concluded that SWS promotes the neural reorganization of task representations that rely on the hippocampal system despite absence of conscious access to these representations.Original neurophysiologic evidence is provided for the role of SWS in the consolidation of memories encoded with hippocampo-cortical interaction before sleep. It is demonstrated that this SWS-mediated mechanism does not depend critically on explicitness at learning nor on the amount of controlled executive processing during pre-sleep encoding

Essays in Behavioral Economics and Neuroeconomics

This dissertation is composed of three unrelated chapters on Behavioral Economics and Neuroeconomics, all of which are on different topics. Chapter 1: Willingness to Get Vaccinated Against COVID-19 and Reasons for Hesitancy Among U.S Residents. Chapter 2: Testosterone Administration Induces A Red Shift in Democrats. Chapter 3: Neurophysiologic Predictors of Mood in the Elderly