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Strategies for Early Learners
Get PDFNEWER EDITION AVAILABLE: https://scholar.utc.edu/open-textbooks/6 Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp
Junior year GPA - understanding its predictive relationship to high school ranking, ACT score, and the shift to online learning
Get PDFConsiderable amounts of resources are allocated to assist and retain students during their first and second years in college, and many universities provide extra support to students as they prepare to graduate and start their professional careers; however, resources are not often specially aimed at third year students (i.e., students in their junior year). The primary goals of this study were to contribute to the body of literature and gain a better understanding of the relationships between students’ ACT scores, their Tennessee High School Quality ranking scores, and their cumulative GPA at the end of their junior year. This research project also considered the possible impact that the transition to online learning designs may have had on junior-level students’ GPAs during the COVID-19 pandemic by comparing students who did not experience the COVID-19 pandemic during or prior to the junior-year (2015-2019 cohorts) and students who did experience the COVID-19 pandemic and the transition to online learning (2021 cohort). An understanding of these relationships and differences is important because students are usually beginning their upper-level courses for their designated majors during their third year of college; therefore, their GPAs are beginning to reflect, not only the students’ abilities to understand basic knowledge in a subject area, but also their abilities to understand complex, content-specific material. This information could be useful to university educators and administrators as they work toward making data-driven decisions about the programs and resources that are allocated to assist their students during all years of their postsecondary education career. There were three quantitative research questions: 1) Is there a significant, predictive relationship between high school quality, ACT scores, and end-of-junior-year of college GPA? 2) Is there a significant difference between the GPAs of college juniors in 2021 versus those from 2015, 2016, 2017, 2018, and 2019? 3) Is there a significant difference between the GPAs of college juniors in 2021 versus those from 2015, 2016, 2017, 2018, and 2019 in STEM and non-STEM fields? Statistical analyses involving multiple regression and analysis of variance were used to answer these questions. It was determined that ACT score is a statistically significant predictor of students’ GPAs at the end of their junior year in college, and the GPAs of 2021 juniors were significantly different to the GPAs of juniors from previous years
Are We Giving Them a Fair Chance? Racial Stereotypes and the Juvenile Justice System
Get PDFPrior research indicates that there are racial disparities throughout the criminal justice system and that decision-makers may use stereotypes when determining guilt and deciding on sentences for juveniles. This study looked at sentence disparities between White and Latinx juveniles, as well as potential stereotypes that could be used in decision-making. There were no differences in sentence length and severity between the White and Latinx offender. Additionally, the likelihood of the offender receiving a lesser or greater sentence as an adult did not differ among conditions. Our results also showed that participants with prior juror experience used less stereotypical language in their sentence explanations. This research highlights the presence of sentence disparities in prior studies and generates avenues for future research
Teaching cybersecurity: a project-based learning and guided inquiry collaborative learning approach
Get PDFCybersecurity is integral to modern life but it is often overlooked and taken for granted, creating an ever-increasing problem for governments, businesses, and consumers alike and costing billions of dollars in investments losses, disaster recovery expenses, and regulatory fines. Compounding this problem is the alarming shortage of cybersecurity professionals worldwide that has continued to worsen. In 2015, industry experts estimated a shortfall of 1.5 million cybersecurity professionals by 2019. The revised estimate in 2019 was 3 million and growing. For these reasons, educating and training cybersecurity professionals has become a top priority for governments and companies around the world. This research study investigates the performance of established student-centered active learning models. It combines Project-Based Learning (PBL) and Guided Inquiry Collaborative Learning (GICL) learning models to teach cybersecurity. Following Bloom’s Taxonomy pedagogical practices, a PBL-GICL framework and activities were developed for teaching a Cybersecurity Biometrics class. Scaffolding activities included items like lab assignments, guided inquiry questions, and a semester long project where students, through experimentation, designed and developed an optical fingerprint reader using a Raspberry Pi, a camera, a prism, and a 3D printed case. Embedded assessments consisting of a survey, peer reviews, exam questions, and research data from a published study that uses Process Oriented Guided Inquiry Learning (POGIL) to teach cybersecurity modules, are used to evaluate the following research questions: 1. How does PBL-GICL approach compare to POGIL as a learning model for teaching cybersecurity? 2. How effective is the PBL-GICL approach for teaching cybersecurity concepts? 3. What are the challenges and opportunities in implementing PBL-GICL to teach cybersecurity? Quantitative analysis of the survey data suggests that PBL-GICL performance is comparable to POGIL and exceeds it in categories like teamwork experience, motivation, and engagement. The data also suggests that the PBL-GICL approach is an effective student-centered learning model for teaching cybersecurity concepts. Lastly, several challenges concerning online teaching and opportunities for process improvements to implement PBL-GICL are discussed. These findings are important to mitigate the shortfall of qualified cybersecurity professionals by identifying effective student-centered active learning models that motivate and engage students
Addressing the challenges facing deep learning based Specific Emitter Identification via preamble based waveforms
Get PDFThe purpose of this study is to conduct in-depth experiments that analyze the effects on Deep Learning (DL) based Specific Emitter Identification (SEI) and address three issues facing the field. SEI is targeted as a physical-layer security measure that can identify radios within an Internet of Things (IoT) deployment without the need of digital credentials. In the current space, DL SEI is still in its infancy, and has not had the incubation time for a tailor-suited approach to solve issues facing SEI. This thesis introduces methods of improving DL SEI using transforms to allow the networks to learn features that reduce computational cost and improve security. Overall, this thesis highlights the introduction of (i) the natural logarithm as a computationally inexpensive transform of preamble-based waveforms, (ii) assessment of the impacts signal energy has on DL SEI, and (iii) an approach to improving the multi-day classification performance of IEEE 802.11a OFDM emitters
Predicting enrollment in a metropolitan university in southeast Tennessee
Get PDFInstitutions of higher education are tasked with making decisions that will impact their students, faculty, staff, and other stakeholders. Many of these decisions are focused on varying aspects of budgeting, and an institution’s sustainability and reputation could be impacted by misallocations of resources. Some of this risk could potentially be eliminated if there was a strategic way to predict which data points have meaningful impact on student enrollment. This study used data collected at a metropolitan university in Southeast Tennessee for six fall semesters to develop enrollment prediction models for the institution. The focus of the study was to determine whether one or more variables could be used to predict undergraduate student headcount at a 4-year university based on one or more student demographic and attribute variables. Using Markov Chain Monte Carlo (MCMC) simulation allowed for a more instinctive way to derive statistical methods by enabling probability estimation for hypotheses. The first step, linear regression, demonstrated there were specific sets of predictor variables for institutional enrollment and for four academic programs’ enrollment; no two models included the same variables. Subsequently, it was determined that the MCMC simulation models were able to accurately predict institutional and program enrollment for specific fall semesters, but not for all fall semesters, perhaps due to limitations related to COVID-19. While the enrollment prediction models developed were not accurate for each fall semester, it is important to note that having some type of estimation and a place to start with potential enrollment provide a huge benefit to individual academic programs as well as to the institution. Previously, there has not been a consistent or comparable way to make estimates of enrollment; however, using data that are readily available and considering variables that are not typically utilized provides a way to develop robust models for use at the institution. This model can be adapted for individual programs, and it is likely that each academic program would include different predictor variables. Those in leadership positions can benefit from better estimating the number of students to be enrolled in order to allocate resources appropriately, which helps facilitate student success
Lay Perceptions of Treating Mental Illness with Psychedelic Assisted Therapy
Get PDFWith roughly 44.7 million individuals struggling with mental health problems, it is important that new methods of treatment are explored. Currently, the primary method of treatment is Selective Serotonin Reuptake Inhibitors (SSRIs) for disorders such as: anxiety, depression, and post-traumatic stress disorder (PTSD), but they also provide many detrimental side effects and only decrease symptomology for a short period of time. However, the interest and enthusiasm of many researchers has led to uncovering the true benefits of utilizing psychedelic drugs as a leading treatment for mental health problems. Participants (N = 474) were given a questionnaire regarding their knowledge of mental illnesses (anxiety, depression, and PTSD), traditional treatment (SSRIs), perception, potential usage, and recommendations towards psychedelic drugs being used as treatment for mental illnesses. A correlation analysis revealed that participants were not being open to their personal usage of psychedelics, but being more open to recommend to their loved ones. Thus, these results suggest that while society may be open to others engaging in psychedelic-assisted therapy, there is still some hesitation for self-use
Through the Looking Glass: Investigating Incivility and Depletion through a Cognitive Process Lens
Get PDFBackground Experiencing incivility at work is a common phenomenon that has increased in recent years (Porath & Pearson, 2014). In addition, the effects of experiencing incivility are not bound to the workplace and can continue to negatively impact individuals after they leave work (e.g., Fritz et al., 2019). However, little is known about the mechanisms which transmit the experience of incivility at work to one’s non-work domain. One such mechanism that may be associated with detrimental outcomes of incivility at work in the non-work domain is depletion (Christian & Ellis, 2011), which represents a reduced state of cognitive capacity. However, the use of activing coping mechanisms may buffer the effects of experienced incivility on depletion. Specifically, we will examine how an individual’s cognitive appraisal of experienced incivility influences coping mechanisms, which in turn may buffer (through active coping) or exacerbate (through maladaptive coping) the relationship between workplace incivility and depletion. Please see Figure 1 for the proposed theoretical model. Method Participants will include approximately 100 working adults recruited via Prolific. Participants will be prescreened to ensure they are full-time working adults who are not self-employed and interact with coworkers/supervisors on a regular basis. Participants will complete a baseline survey and daily-diary surveys for 10 working-days. Adapted measures will include incivility (6 items, Cortina et al., 2001), cognitive appraisal (5 items, Cortina & Mangley, 2009), self-report depletion (6 items, Christian & Ellis, 2011), and coping (6 items, Fitzgerald, 1990), as well as job and personal demographic items. Proposed Analyses We will conduct multilevel analyses via path modeling, with hypothesized relationships modeled at the within-level (level 1); we will examine the use of statistical control at the between- and within- levels. Preliminary Discussion We expect to see a strong association between experienced workplace incivility and depletion. Cognitive appraisal should be associated with the use of coping mechanisms, such that positive cognitive appraisal will be associated with more adaptive coping following experienced incivility. Our study will contribute to research determining the relationship between individual’s experiences of workplace incivility and spillover effects via depletion
Validating a picture-based values measure across three studies
Get PDFWhile the importance of congruence between personal and organizational values to employees and organizations has been well established in the academic literature, existing values measures have shortcomings in applied settings. We have developed the Picture-Based Values Measure (PBVM) to measure Schwartz’s 19 refined basic individual values, resist faking, avoid construct contamination, and show cross-cultural relevance. In this research proposal, we intend to establish the psychometric properties of the PBVM across three studies. In Study 1, to examine convergent validity, 300 working adults will take both the PBVM and Revised Portrait Value Questionnaire (PVQ-RR) via Prolific. To examine discriminant validity, participants will take measures of cognitive ability and social skills. Established correlates to values like personality, age, education, gender, race, religiosity, and political orientation will be assessed for nomological validity. Finally, to examine test-retest reliability, we will randomly assign 100 participants to retake the PBVM. In Study 2, values congruence will be assessed by administering the PBVM and measures of job satisfaction, organizational commitment and leader-member exchange to 150 Study 1 participants and their supervisors, who will also complete measures regarding employee in-role performance, organizational citizenship behaviors (OCBs), and counterproductive work behaviors (CWBs). In Study 3, we will examine applicants to nursing positions in a collaborating hospital. Applicants will take the PBVM and the PVQ-RR, and those hired will retake the values measures during the orientation period. The participants’ supervisors will complete the same measures in Study 2. Nurses’ turnover status, job satisfaction, and organizational commitment, at 12 months post-entry will be obtained. Department leaders will generate their department values profiles based on Schwartz’s definitions. This data will be used to examine the criterion-related validity of the value congruence based on PBVM, as well as its resistance to faking. Correlations will be calculated to estimate the psychometric properties of PBVM. These calculations will help to determine if the PBVM is more faking-resistant compared to the PVQ-RR across the selection and non-selection contexts, and if the PBVM has higher criterion-related validity using correlations between value congruence and job-related outcomes. We expect the PBVM to demonstrate high validity and resistance to faking. The proposed research, with collaborations between academics and practitioners, aims to validate the PBVM through three empirical studies, using selection and non-selection contexts and concurrent and predictive designs. If proven valid, the PBVM will offer organizations an effective assessment tool to select employees whose values align with their work environment
Helping manufacturing organizations adapt to Industry 4.0: Future-oriented I-O applications to workforce development
No full textManufacturing organizations and their employees are facing a challenging and exciting point of transition as the industry enters its next era of production, generally known as Industry 4.0. This era is characterized by major improvements to technologies and processes that collectively will result in the most advanced and sophisticated manufacturing work environments ever seen. Since mid-2021, Dr. Chris Cunningham and students from the UTC I-O psychology program have consulted with the Smart Factories Institute, to assist with workforce research, training and development needs assessment and development, and organizational management strategy development to help manufacturing organizations and workers through this critical transition period. This presentation will provide an overview of Industry 4.0 and its implications for manufacturing organizations, managers, and workers. Results of recently completed industry and workforce analyses will also be shared, along with highlights of upcoming initiatives of the Smart Factory Institute. This session is designed to highlight ways that I-O psychology can be applied to an industry that the field often ignores and to future work that is still being defined. For more information, visit: https://peakperformance.tovuti.io/courses-page/course/the-transformation-of-manufacturin