To understand instruction during the spring 2020 transition to emergency distance learning (EDL), we surveyed a sample of instructors teaching undergraduate EDL courses at a large university in the southwest. We asked them how frequently they used and how confident they were in their ability to implement each of nine promising practices, both for their spring 2020 EDL course and a time when they previously taught the same course face-to-face (F2F). Using latent class analysis, we examined how behavioral frequencies and confidence clustered to form meaningful groups of instructors, how these groups differed across F2F and EDL contexts, and what predicted membership in EDL groupings. Results suggest that in the EDL context, instructors fell into one of three profiles in terms of how often they used promising practices: Highly Supportive, Instructor Centered, and More Detached. When moving from the F2F to EDL context, instructors tended to shift down in terms of their profile-for example, among F2F Highly Supportive instructors, 34% shifted to the EDL Instructor Centered profile and 30% shifted to the EDL More Detached Profile. Instructors who reported lower self-efficacy for EDL practices were also more likely to end up in the EDL More Detached profile. These results can assist universities in understanding instructors' needs in EDL, and what resources, professional development, and institutional practices may best support instructor and student experiences.

Researchers have held differing views on the effects of feedback timing for decades. A closer reading of the timing of feedback literature that favored delayed feedback revealed that this conclusion may have been reached prematurely, because the results might have been confounded by the time interval between feedback and a posttest. This study differs from previous feedback timing studies in three distinct ways: First, this study addressed the limitations of previous studies by holding time interval between the feedback (either immediate or delayed) and the posttest constant. Second, this study included various types of knowledge and investigated the interaction between feedback timing and different knowledge types. Third, most studies that investigate the comparative effectiveness of immediate and delayed feedback on written assignments were conducted in the STEM fields, whereas few studies can be found in the second language learning field. Results revealed that the immediate feedback condition significantly outperformed the delayed feedback condition on conceptual knowledge learning, however, no difference between the two conditions was found on situational knowledge learning. © 2021, North American Business Press. All rights reserved.

The ability to produce novel ideas is central to societal progress and innovation; however, little is known about the biological basis of creativity. Here, we investigate the organization of brain networks that support creativity by combining functional neuroimaging data with gene expression information. Given the multifaceted nature of creative thinking, we hypothesized that distributed connectivity would not only be related to individual differences in creative ability, but also delineate the cortical distributions of genes involved in synaptic plasticity. We defined neuroimaging phenotypes using a graph theory approach that detects local and distributed network circuits, then characterized the spatial associations between functional connectivity and cortical gene expression distributions. Our findings reveal strong spatial correlations between connectivity maps and sets of genes devoted to synaptic assembly and signaling. This connectomic-transcriptome approach thus identifies gene expression profiles associated with high creative ability, linking cognitive flexibility to neural plasticity in the human brain.

Introduction: Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed.Methods: Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on target statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR).Results: Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 min on a 12 min scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters.Conclusion: A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.

A key area of research in epilepsy neurological disorder is the characterization of epileptic networks as they form and evolve during seizure events. In this paper, we describe the development and application of an integrative workflow to analyze functional and structural connectivity measures during seizure events using stereotactic electroencephalogram (SEEG) and diffusion weighted imaging data (DWI). We computed structural connectivity measures using electrode locations involved in recording SEEG signal data as reference points to filter fiber tracts. We used a new workflow-based tool to compute functional connectivity measures based on non-linear correlation coefficient, which allows the derivation of directed graph structures to represent coupling between signal data. We applied a hierarchical clustering based network analysis method over the functional connectivity data to characterize the organization of brain network into modules using data from 27 events across 8 seizures in a patient with refractory left insula epilepsy. The visualization of hierarchical clustering values as dendrograms shows the formation of connected clusters first within each insulae followed by merging of clusters across the two insula; however, there are clear differences between the network structures and clusters formed across the 8 seizures of the patient. The analysis of structural connectivity measures showed strong connections between contacts of certain electrodes within the same brain hemisphere with higher prevalence in the perisylvian/opercular areas. The combination of imaging and signal modalities for connectivity analysis provides information about a patient-specific dynamical functional network and examines the underlying structural connections that potentially influences the properties of the epileptic network. We also performed statistical analysis of the absolute changes in correlation values across all 8 seizures during a baseline normative time period and different seizure events, which showed decreased correlation values during seizure onset; however, the changes during ictal phases were varied.

Developing research self-efficacy is an important part of doctoral student preparation. Despite the documented importance of research self-efficacy, little is known about the progression of doctoral students' research self-efficacy over time in general and for students from minoritized groups. This study examined both within- and between-person stability of research self-efficacy from semester to semester over 4 years, focusing on doctoral students in biological sciences (N = 336). Using random intercept autoregressive analyses, we evaluated differences in stability across gender, racially minoritized student status, and first-generation student status. Results showed similar mean levels of self-efficacy across demographic groups and across time. However, there were notable differences in between-person and within-person stability over time, specifically showing higher between-person and lower within-person stability for racially minoritized and first-generation students. These findings indicate that racially minoritized and first-generation students' research self-efficacy reports were less consistent from semester to semester. Such results may indicate that non-minoritized and continuing-generation students' experiences from semester to semester typically reinforce their beliefs about their own abilities related to conducting research, while such is not the case for racially minoritized nor first-generation students. Future research should examine what types of experiences impact self-efficacy development across doctoral study to offer more precise insights about factors that influence these differences in within-person stability.

In museum settings, caregivers support children's learning as they explore and interact with exhibits. Museums have developed exhibit design and facilitation strategies for promoting families' exploration and inquiry, but these strategies have rarely been contrasted. The goal of the current study was to investigate how prompts offered through staff facilitation vs. labels printed on exhibit components affected how family groups explored a circuit blocks exhibit, particularly whether children set and worked toward their own goals, and how caregivers were involved in children's play. We compared whether children, their caregivers, or both set goals as they played together, and the actions they each took to connect the circuits. We found little difference in how families set goals between the two conditions, but did find significant differences in caregivers' actions, with caregivers in the facilitation condition making fewer actions to connect circuits while using the exhibit, compared to caregivers in the exhibit labels condition. The findings suggest that facilitated and written prompts shape the quality of caregiver-child interactions in distinct ways.

Relational reasoning is a complex form of human cognition involving the evaluation of relations between mental representations of information. Prior studies have modified stimulus properties of relational reasoning problems and examined differences in difficulty between different problem types. While subsets of these stimulus properties have been addressed in separate studies, there has not been a comprehensive study, to our knowledge, which investigates all of these properties in the same set of stimuli. This investigative gap has resulted in different findings across studies which vary in task design, making it challenging to determine what stimulus properties make relational reasoning-and the putative formation of mental models underlying reasoning-difficult. In this article, we present the Multidimensional Relational Reasoning Task (MRRT), a task which systematically varied an array of stimulus properties within a single set of relational reasoning problems. Using a mixed-effects framework, we demonstrate that reasoning problems containing a greater number of the premises as well as multidimensional relations led to greater task difficulty. The MRRT has been made publicly available for use in future research, along with normative data regarding the relative difficulty of each problem.

Recent evidence suggests that infants and toddlers may recognize counting as numerically relevant long before they are able to count or understand the cardinal meaning of number words. The Give-N task, which asks children to produce sets of objects in different quantities, is commonly used to test children’s cardinal number knowledge and understanding of exact number words but does not capture children’s preliminary understanding of number words and is difficult to administer remotely. Here, we asked whether toddlers correctly map number words to the referred quantities in a two-alternative forced choice Point-to-X task (e.g., “Which has three?”). Two- to three-year-old toddlers ( N = 100) completed a Give-N task and a Point-to-X task through in-person testing or online via videoconferencing software. Across number-word trials in Point-to-X, toddlers pointed to the correct image more often than predicted by chance, indicating that they had some understanding of the prompted number word that allowed them to rule out incorrect responses, despite limited understanding of exact cardinal values. No differences in Point-to-X performance were seen for children tested in-person versus remotely. Children with better understanding of exact number words as indicated on the Give-N task also answered more trials correctly in Point-to-X. Critically, in-depth analyses of Point-to-X performance for children who were identified as 1- or 2-knowers on Give-N showed that 1-knowers do not show a preliminary understanding of numbers above their knower-level, whereas 2-knowers do. As researchers move to administering assessments remotely, the Point-to-X task promises to be an easy-to-administer alternative to Give-N for measuring children’s emerging number knowledge and capturing nuances in children’s number-word knowledge that Give-N may miss.

Professional engineering organizations (PEOs) have the potential to provide women and underrepresented and minoritized (URM) students with social capital (i.e., resources gained from relationships) that aids their persistence in their engineering undergraduate programs and into the workforce. We hypothesize that women and URM students engineering students who participate in PEOs are more likely to persist in their engineering major and that PEOs contribute to their persistence by providing them access to insider information that supports their persistence. Each year for five years we administered surveys with closed- and open-ended items to examine the association between participating in PEOs and the persistence of a cohort of engineering majors from 11 diverse universities. We used logistic regression and thematic analysis to analyze the data. URM students who participated in PEOs and other engineering related activities were more likely to persist to the second year than URM students who did not (adjusted odds ratio = 2.18, CI: 1.09, 4.37). Students reported that PEOs contributed to their persistence by enabling them to network, reduce gender and race/ethnic isolation, and access professional resources. URM students should be encouraged to participate in PEOs beginning in their first year to increase their integration in their major, which we have found to increase their persistence.