Procedure automation can relieve users of the burden of repetitive, time-consuming, or complex procedures and enable them to focus on more cognitively demanding tasks. Procedural learning is a method by which procedure automation can be achieved by intelligent computational assistants. This paper explores the use of filtering heuristics based on action models for automated planning to augment sequence mining techniques. Sequential pattern mining algorithms rely primarily on frequency of occurrence to identify patterns, leaving them susceptible to discovering patterns that make little sense from a cognitive perspective. In contrast, humans are able to form models of procedures from small numbers of observations, even without explicit instruction. We posit that humans are able to do so because of background knowledge about actions and procedures, which lets them effectively filter out meaningless sequential patterns. The action models foundational to artificial intelligence (AI) planning is one way to provide semantics to actions, supporting the design of heuristics for eliminating spurious patterns discovered from event logs. We present experiments with various filters derived from these action models, the results of which show the value of the filters in greatly reducing the number of sequential patterns discovered without sacrificing the number of correct patterns found, even with small, noisy event logs.
We explore sequence determinants of enzyme activity and specificity in a major enzyme family of terpene synthases. Most enzymes in this family catalyze reactions that produce cyclic terpenes—complex hydrocarbons widely used by plants and insects in diverse biological processes such as defense, communication, and symbiosis. To analyze the molecular mechanisms of emergence of terpene cyclization, we have carried out in-depth examination of mutational space around (E)-β-farnesene synthase, an Artemisia annua enzyme which catalyzes production of a linear hydrocarbon chain. Each mutant enzyme in our synthetic libraries was characterized biochemically, and the resulting reaction rate data were used as input to the Michaelis–Menten model of enzyme kinetics, in which free energies were represented as sums of one-amino-acid contributions and two-amino-acid couplings. Our model predicts measured reaction rates with high accuracy and yields free energy landscapes characterized by relatively few coupling terms. As a result, the Michaelis–Menten free energy landscapes have simple, interpretable structure and exhibit little epistasis. We have also developed biophysical fitness models based on the assumption that highly fit enzymes have evolved to maximize the output of correct products, such as cyclic products or a specific product of interest, while minimizing the output of byproducts. This approach results in nonlinear fitness landscapes that are considerably more epistatic. Overall, our experimental and computational framework provides focused characterization of evolutionary emergence of novel enzymatic functions in the context of microevolutionary exploration of sequence space around naturally occurring enzymes.
Advancing Local Early Childhood Systems in Virginia: Next Steps for Local, Regional, and State Stakeholders
Strong local early childhood systems are key to ensuring the healthy development of young children. Over the last decade, Virginia communities have leveraged public and private sector efforts to make substantial progress in coordinating and strengthening local early childhood systems. The Virginia Early Childhood Foundation (VECF) partnered with researchers from SRI Education (SRI) to examine the progress and challenges of early childhood systems building in Virginia with a focus on communities that are part of VECF’s Smart Beginnings network. This document summarizes the findings from that examination and provides recommendations for how VECF, state government, and local leaders can more equitably and effectively serve children and families.
We describe a principled approach to designing STEM curricular activities that puts equity and inclusion (EI) at the forefront of the design process from its instantiation to its development. We illustrate this process using insights from designing a curriculum unit aligned with the US Next Generation Science Standards (NGSS) and an EI framework focused on supporting student engagement and use of language. The process identifies helpful ways to articulate design guidance for instructional designers.
The 21st century skills and STEM learning standards include collaboration as a necessary learning skill in K-12 science education. To support the development of collaboration skills among students, it is important to assess and support students’ proficiency in collaboration. We present the process of developing a tool that assesses collaboration quality based on behavioral communication at individual and group levels. The assessment tool uses behavior analytics comprised of multistage machine learning models built on an intricate collaboration conceptual model and coding scheme. Our collaboration conceptual model shows how layers of behavioral cues contribute to collaboration and serves as the foundation of an automated assessment tool for collaboration. We present initial findings that show reliability between our assessment of behavioral interactions with and without speech. An automated collaboration assessment tool will give teachers information about student collaboration and help inform instruction that will guide and support students’ collaboration skill development.
With schools across the United States turning to distance learning during the COVID-19 pandemic, concerns are being raised about the quality of instruction that English learners—students whose English proficiency affects their ability to meaningfully participate in school—are receiving. English learners make up nearly 10 percent of all public school students in the United States and, even during normal times, face significant barriers to academic success. Those challenges are multiplied when instruction goes online.
For many students, the COVID-19 pandemic is compounding traumatic experiences for diverse reasons, such as potential increased incidents of neglect, abuse, and isolation. At the same time, educators are limited in how they can support their students while school are closed. In the Appalachia region, this new wave of stressors comes on top of the traumatic experiences students are experiencing related to the opioid epidemic. Family and community opioid use has devastating impacts on children and families, especially in this region, with about 170,000 children experiencing a range of stressors and trauma related to parental opioid use, such as losing a parent to an opioid-related death, having an incarcerated parent due to opioid use, or being removed from their home due to an opioid-related issue. 1 REL Appalachia (REL AP) has been working with key stakeholders from the region in state and local education agencies, departments of health, community-based organizations, and universities to identify best practices for addressing student- and educator-related trauma through the Cross-State Collaborative to Support Schools in the Opioid Crisis (CCSSOC). Through this work, the collaborative developed and curated tools and strategies all educators may find useful when supporting students during this time.
Everyday strategies for educators to support students experiencing trauma
In response to education stakeholders’ high-priority needs, the REL AP team and CCSSOC members co-developed the “Common trauma symptoms in students and helpful strategies for educators“ handout.
The handout provides information about the common symptoms of trauma, grouped into five main categories, 2 as well as everyday strategies 3 that educators can implement in the classroom to support students exhibiting symptoms of trauma.
Everyday strategies in virtual settings
In the context of the COVID-19 pandemic, we adapted strategies from the handout to help educators address student’s social-emotional and mental health needs associated with trauma in virtual settings:
Provide structure and routine: Educators can work with parents to ensure that students have proper structure and routine—a critical need for students who experience trauma. One strategy is to work with families to build daily schedules that combine academic enrichment (e.g., reading, practicing math), physical exercise, and entertainment. Educators can also promote structure on a macro-level by organizing remote learning opportunities that follow a consistent and familiar structure for students, such as an abbreviated daily school schedule.
Promote a sense of control: Students’ resiliency increases when we help them increase their locus of control—the extent to which they feel in control of their own lives. To do so, educators can work with students to identify ways they can control their own lives —staying healthy (e.g., maintaining social distance), managing emotions (e.g., practicing mindfulness), and staying connected to others (e.g., connect with friends and relatives by phone).
Be present: In this period of time, perhaps more so than ever before, students who have experienced trauma need to feel the support of trusted adults in their lives—including their educators. Educators can maintain ongoing (e.g., weekly) communication with students through various means: small group video calls, one-on-one phone calls, sending postcards, etc. The primary purpose of these interactions is to convey to each child that they can continue to emotionally lean on their educators even when school buildings are closed. For more information on relationship building, see Virtual Relationship Mapping (source: Harvard Graduate School of Education) which provides strategies and lesson plans for school administrators and staff to make sure that every student has a supportive adult mentor at the school.
Provide emotional check-ins: During virtual interactions, educators should provide students with emotional check-in opportunities (e.g., using the mood meter; source: National Association for the Education of Young Children, NAEYC) and validate students’ feelings. Educators should praise students for using relaxation or coping strategies. In addition, educators can follow up with students who endorse negative emotions, especially if they are noticing that this is becoming a pattern, and discuss appropriate coping responses and strategies to use in such situations.
Strengthen self-regulation skills: Students (and adults) can develop skills to regulate their own emotions. As with any type of skill, self-regulation skills need to be learned, practiced, and then practiced some more to achieve mastery. These skills include mindfulness, breathing exercises, physical exercises, active journaling, and yoga. Educators can guide and practice these skills with students using various games and activities ( source: Stop, Breathe, & Think) during remote learning meetings. Educators can also refer students and families to various apps and games; for example, see this collection from Common Sense. Educators can also help parents and caregivers make an at-home schedule with various activities to practice these skills with their children; see this blog post from the Children’s Hospital of Orange County on how parents can schedule and spend one week focusing on building these skills with their children.
These strategies, as shown in the Virtual Preventative Strategies infographic below, can be appended to and used together with the “Common trauma symptoms in students and helpful strategies for educators” handout. Download the Virtual Preventative Strategies infographic here.
School-based programs to support students experiencing trauma
District and school administrators may consider implementing school-based programs to address student trauma once students return to school in the fall. The REL AP team and CCSSOC members co-developed two relevant resources to help school and district leaders address the likely overwhelming need for evidence-based or promising interventions that align with their specific needs and contexts:
Selecting the right interventions to support students’ mental health needs: This infographic provides key questions to ask when considering and selecting programs with specific decision-support tools and can be used with the Menu of trauma-informed programs for schools (below) to consider and choose from various programs.
Menu of trauma-informed programs for schools: This handout provides descriptions of trauma-informed programs and available information about their implementation and evaluation/evidence.
These materials provide preventative and intervention strategies for supporting students affected by trauma. For suggestions on how to use the materials, refer to the relevant sections of this blog post.
Common Trauma Symptoms in Students and Helpful Strategies for Educators
Virtual Preventative Strategies to Support Students’ Social-Emotional and Mental Health Needs Associated With Trauma
Selecting the Right Interventions to Support Students’ Mental Health Needs
Menu of Trauma-Informed Programs for Schools
Additional resources to support students
How can educators and families support students’ mental health and social emotional needs?: The REL Northeast and Islands (REL NEI) put together FAQs to assist schools and districts in supporting students’ mental health and social-emotional needs, sharing ideas from districts across the country, and resources from local and state education agencies.
Distance learning resources for education stakeholders in the northwest: This REL Northwest (REL NW) page compiles a list of distance learning resources for education stakeholders.
Supporting children during Coronavirus (COVID-19): This resource from The National Child Traumatic Stress Network (NCTSN) describes how adults can provide support, help, and guidance to children and youth during the COVID-19 outbreak.
Staying resilient during COVID-19: This page from the Compassion Resilience Toolkit provides various resources on how to stay resilient during COVID-19.
Student Behavior Blog’s COVID-19 resources: This page shares resources to help families and teachers support children and themselves during the COVID-19 crisis.
Study objectives: To investigate the pre-sleep psychophysiological state and the arousal deactivation process across the sleep onset (SO) transition in adolescents.
Methods: Data were collected from a laboratory overnight recording in 102 healthy adolescents (48 girls, 12-20 years old). Measures included pre-sleep self-reported cognitive/somatic arousal, and cortical electroencephalographic (EEG) and electrocardiographic activity across the SO transition.
Results: Adolescent girls, compared with boys, reported higher pre-sleep cognitive activation (p = 0.025) and took longer to fall asleep (p < 0.05), as defined with polysomnography. Girls also showed a less smooth progression from wake-to-sleep compared with boys (p = 0.022). In both sexes, heart rate (HR) dropped at a rate of ~0.52 beats per minute in the 5 minutes preceding SO, and continued to drop, at a slower rate, during the 5 minutes following SO (p < 0.05). Older girls had a higher HR overall in the pre-sleep period and across SO, compared to younger girls and boys (p < 0.05). The EEG showed a progressive cortical synchronization, with increases in Delta relative power and reductions in Alpha, Sigma, Beta1, and Beta2 relative powers (p < 0.05) in the approach to sleep, in both sexes. Delta relative power was lower and Theta, Alpha, and Sigma relative powers were higher in older compared to younger adolescents at bedtime and across SO (p < 0.05). Conclusions: Our findings show the dynamics of the cortical-cardiac de-arousing process across the SO transition in a non-clinical sample of healthy adolescents. Findings suggest a female-specific vulnerability to inefficient sleep initiation, which may contribute to their greater risk for developing insomnia.
Particle radiation-induced dysregulation of protein homeostasis in primary human and mouse neuronal cells
Space particle radiations may cause significant damage to proteins and oxidative stress in the cells within the central nervous system and pose a potential health hazard to humans in long-term manned space explorations.
A process for maximizing the titer of lentivirus particles, deemed to be a necessity for transducing primary cells, is developed. Lentivirus particles, with a set of transgenes encoding an artificial cell‐signaling pathway, are used to transform primary T cells as vectors for calibrated synthesis of desired proteins in situ, that is, T‐cell biofactory cells. The process is also used to generate primary T cells expressing antigen‐specific chimeric antigen receptors, that is, CAR T cells. The two differently engineered primary T cells are expanded and validated for their respective functions, that is, calibrated synthesis of desired proteins upon engaging the target cells, which is specific for the T‐cell biofactory cells, and cytolysis of the target cells common to both types of cells. The process is compliant with current Good Manufacturing Practices and can be used to support the scale‐up for clinical translation.
Sleep Disturbance Predicts Depression Symptoms in Early Adolescence: Initial Findings From the Adolescent Brain Cognitive Development Study
Purpose: The aim of the study was to investigate associations between sleep disturbances and mental health in adolescents.
Methods: Data are from a national sample of 11,670 U.S. participants (5,594 females, aged 9-10 years, 63.5% white) in the Adolescent Brain Cognitive Development study. Initial longitudinal analyses were conducted for a subset of the sample (n = 4,951). Measures of youth sleep disturbance (disorders of initiating and maintaining sleep, sleep-wake transition disorders, and disorders of excessive somnolence) and “typical” total sleep time (number of hours slept on most nights in the past 6 months) were obtained from the parent-report Sleep Disturbance Scale (Data Release 2.0). Parent-report measures of youth mental health (depression, internalizing, and externalizing behaviors) from the Child Behavior Checklist and typical screen time were included.
Results: At baseline, greater sleep disturbance and shorter total sleep time were associated with greater internalizing, externalizing, and depression scores. After controlling for baseline mental health symptoms, baseline sleep disturbance significantly predicted depression and internalizing and externalizing scores at 1-year follow-up. A significant interaction with sex indicated that the association between disorders of excessive somnolence and depression 1 year later was steeper for girls, compared with boys (p < .001; 95% confidence interval 1.04-3.45). Conclusions: Sleep disturbances predicted future mental health, particularly depression in this young sample, highlighting the potential to harness sleep as a tool to mitigate the persistence of depression across early adolescence and potentially prevent an adolescent onset of major depressive disorder.
The Pathway to Academic Success: Scaling Up a Text-Based Analytical Writing Intervention for Latinos and English Learners in Secondary School
This study reports findings from a multisite cluster randomized controlled trial designed to validate and scale up an existing successful professional development program that uses a cognitive strategies approach to text-based analytical writing. The Pathway to Academic Success Project worked with partner districts affiliated with 4 National Writing Project (NWP) sites in southern California. Informed by a wide body of research on the efficacy of strategy instruction to enhance students’ academic literacy, the intervention aimed to help secondary school students, particularly Latinos and mainstreamed English learners, to develop the academic writing skills called for in the rigorous Common Core State Standards for English Language Arts. Two hundred thirty teachers from partner districts affiliated with the NWP sites were stratified by school and grade and then randomly assigned to the treatment or control group. Treatment teachers participated in 46 hrs of training and learned how to apply cognitive strategies by using an on-demand writing assessment to help students understand, interpret, and write analytical essays about nonfiction texts. Multilevel models revealed significant effects on a holistic measure of an on-demand writing assessment ( d = .32) as well as on 4 analytic attributes: content ( d = .31), structure ( d = .29), fluency ( d = .27), and conventions ( d = .32). Four dimensions of scaling up—spread, reform ownership, depth, and sustainability—are also discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved)
Orexin/hypocretin-producing and melanin-concentrating hormone-producing (MCH) neurons are co-extensive in the hypothalamus and project throughout the brain to regulate sleep/wakefulness.
Background: The diagnosis of posttraumatic stress disorder (PTSD) is usually based on clinical interviews or self‐report measures. Both approaches are subject to underand over‐reporting of symptoms. An objective test is lacking. We have developed a classifier of PTSD based on objective speech‐marker features that discriminate PTSD cases from controls.
Methods: Speech samples were obtained from warzone‐exposed veterans, 52 cases with PTSD and 77 controls, assessed with the Clinician‐Administered PTSD Scale. Individuals with major depressive disorder (MDD) were excluded. Audio recordings of clinical interviews were used to obtain 40,526 speech features which were input to a random forest (RF) algorithm.
Results: The selected RF used 18 speech features and the receiver operating characteristic curve had an area under the curve (AUC) of 0.954. At a probability of PTSD cut point of 0.423, Youden’s index was 0.787, and overall correct classification rate was 89.1%. The probability of PTSD was higher for markers that indicated slower, more monotonous speech, less change in tonality, and less activation. Depression symptoms, alcohol use disorder, and TBI did not meet statistical tests to be considered confounders.
Conclusions: This study demonstrates that a speech‐based algorithm can objectively differentiate PTSD cases from controls. The RF classifier had a high AUC. Further validation in an independent sample and appraisal of the classifier to identify those with MDD only compared with those with PTSD comorbid with MDD is required.
Combining strategic instruction model routines with technology to improve academic outcomes for students with disabilities
All students, including those with disabilities, are faced with a challenging standards environment. Through funding from the U.S. Department of Education’s Investing in Innovation fund, researchers and teachers worked together using a Design Based Implementation Research approach to create tools to help students face these challenging standards, particularly to support attainment of higher order thinking skills. This team integrated research-based Strategic Instruction Model’s Content Enhancement Routines with technology to create Enhanced Units (EUs). The technology developed to deliver the EUs is CORGI: Co-Organize Your Learning. Two randomized controlled trials (RCTs) of the EUs and the CORGI technology were conducted. In this presentation, the researchers will discuss the EUs, CORGI, the findings from the RCTs, and ongoing research and development activities.