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Patterns and representation in play-based learning: a systematic meta-synthesis of empirical studies in K-13+ settings
Get PDFThis systematic review provides a comprehensive meta-synthesis that examines empirical research on the implementation of play-based learning in formal educational settings. The review aims to identify patterns in the enactment of play-based learning, including its representation across academic disciplines, methodologies, grade levels, geographic contexts, and key indicators of play—choice, wonder, and delight. A comprehensive search across nine databases yielded 1,475 studies, of which 87 met stringent inclusion criteria: empirical, K-13+ formal settings, and an intentional learning objective tied to play. We extracted data from each study and used thematic synthesis to analyze patterns across multiple dimensions. Findings indicate that play-based learning is predominantly explored in early childhood and elementary education, with limited research on its implementation in secondary and post-secondary contexts. Studies were concentrated in North America and Europe, highlighting a need for greater geographic diversity. Findings also reveal significant gaps in nature-based play and its role in formal learning environments. Limitations include potential selection bias due to English-language restrictions and the exclusion of studies without a curricular focus. This review underscores the need for broader research on play-based learning, particularly in underrepresented populations and adolescent education. By providing a systematic overview of current research trends and limitations, this meta-synthesis contributes to the growing body of knowledge on play-based learning and informs future research directions
Sparks and Developmental Outcomes in Out-of-School Time Programs: Emipirical Evidence and Theory Development
Get PDFWe examined relations among select components of the 4-H Thriving Model, focusing on youth sparks and four presumed determinants: program quality, developmental relationships, situational engagement, and dosage. Based on our results and results of previous studies, we propose a formal theory of youth program sparks. Three hundred fifty-six Texas 4-H youth from a variety of 4-H programs state-wide completed a questionnaire measuring sparks, program quality, developmental relationships, situational engagement, and 4-H program dosage. We measured two indicators of thriving: growth mindset and hopeful purpose. Sixty-eight percent of study participants reported being female, 28% reported being male, 1% reported being nonbinary/third gender, and .28% indicated being transgender. School grade levels ranged from sixth grade (n = 4) to “graduated from high school” (n=21). We found significant linear relations between sparks and three determinants: program quality, developmental relationships, and situational engagement. The relation between sparks and dosage was curvilinear. We found significant linear relations between sparks and thriving. Combined with results of previous studies, we propose a theory of youth program sparks. Using Zetterberg’s (1965) framework for theory construction, we propose scientific (Aristotelian) definitions of key concepts and propositions about relations among those concepts. The theory provides a basis for future research that can inform youth development policy
Development and Validation of the Youth Programs-Community Education Environment Scale (YP-CEES)
Get PDFThe current study focused on establishing the factor structure, reliability, discriminant validity, and construct validity of the Youth Programs – Community Education Environment Scale (YP – CEES) using a large diverse sample of 1,969 youth participating in relationship education programs in multi-session workshops facilitated by trained facilitators. Six subscales were developed based on the extant literature: facilitation quality, facilitator-participant relationship quality, cofacilitator relationship quality, facilitator coregulation skills, individual connection, and group engagement. Cronbach’s alpha reliability indicated high reliabilities for the total scale and the subscales. Confirmatory factor analyses established the factor structure with good model fit for a 6-factor measure. Discriminant validity was evident based on moderate covariances among subscale factors. Construct validity was also evident by moderate to high correlations between subscale scores and global measures of facilitator and program quality. Suggestions for using the YP-CEES are provided
Empowering Precision Agriculture with the Internet of Things, Artificial Intelligence, and Robotics
Get PDFAs the global population grows, agriculture faces increasing demands for higher productivity and sustainability. The incorporation of advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and robotics is revolutionizing farming by improving efficiency, enhancing decision-making, and promoting sustainability through optimized resource use. This publication provides insights into the implementation of these smart farming solutions and their benefits for farmers, crop consultants, and stakeholders. It also addresses the challenges of adopting these technologies, highlighting their crucial role in meeting future food demands sustainably
Designing for Dignity: A Model for Women and Newborn Healthcare Settings in Honduras
Get PDFMany women and infants in Honduras, primarily those from low-income and minority populations, lack access to dignified healthcare spaces that support the provision of quality care. Whether it is due to an unreasonable distance to the nearest healthcare facility or poor quality of the infrastructure that results in bypassing behavior, women and infants in Honduras face serious barriers to accessing quality services. This, in turn, results in adverse outcomes such as maternal mortality, low patient and staff satisfaction, and low utilization. This thesis proposes that the culturally relevant, patient-centered, and efficient design of maternity and newborn centers in Honduras can improve utilization and patient satisfaction, support quality care and positively impact desired maternal and infant outcomes.
New facilities for women and newborns should be designed to support safe and efficient care, privacy, dignity, cultural sensitivity, and equity because merely addressing the distance people must travel to receive quality care is not enough to achieve the desired outcomes. Focusing on the primary level of care with the goal of providing healthcare services for all women in the country, the aim is to address the quality of the spaces to prevent bypassing behaviors. Furthermore, evidence has shown that the design of labor and delivery spaces can impact the physiological progression of labor. Elements such as access to nature, positive distractions, privacy, visibility of care providers, and daylight can affect women’s levels of stress and anxiety, sense of safety, and experience. While most research on maternity and newborn spaces has been conducted in high-income nations, supportive healthcare design can also be achieved in resource-limited contexts.
This thesis used a mixed methods approach. A comprehensive literature review was completed to understand the impact of the built environment on maternal outcomes. Five site visits and six interviews were conducted to understand the needs of Honduran women. Finally, architectural case studies were evaluated to survey best practices for healthcare settings in low-resource contexts. The findings were used to establish design guidelines for maternity and newborn settings in Honduras. Each guideline was developed to include a definition of the issue, the rationale and significance of the guideline based on available evidence and design strategies illustrated by best practices.
The guidelines were then used to design a proposal for a small maternity and newborn center as a proof-of-concept demonstration. This project is located in the Department of Intibucá, Honduras, a priority region for maternal health. It includes a maternity waiting home, outpatient services for prenatal and postnatal care, and inpatient services for labor, delivery, and postpartum
Soil-Based Emissions and Context-Specific Climate Change Planning to Support the United Nations (UN) Sustainable Development Goal (SDG) on Climate Action: A Case Study of Georgia (USA)
Get PDFSoil-based emissions from land conversions are often overlooked in climate planning. The objectives of this study were to use quantitative data on soil-based greenhouse gas (GHG) emissions for the state of Georgia (GA) (USA) to examine context-specific (temporal, biophysical, economic, and social) climate planning and legal options to deal with these emissions. Currently, 30% of the land in GA has experienced anthropogenic land degradation (LD) primarily due to agriculture (64%). All seven soil orders were subject to various degrees of anthropogenic LD. Increases in overall LD between 2001 and 2021 indicate a lack of land degradation neutrality (LDN) in GA. Besides agricultural LD, there was also LD caused by increased development through urbanization, with 15,197.1 km2 developed, causing midpoint losses of 1.2 × 1011 kg of total soil carbon (TSC) with a corresponding midpoint social cost from carbon dioxide (CO2) emissions (SC-CO2) of USD = U.S. dollars (USD)). Most developments occurred in the Metro Atlanta and Coastal Economic Development Regions, which indicates reverse climate change adaptation (RCCA). Soil consumption from developments is an important issue because it limits future soil or forest carbon (C) sequestration potential in these areas. Soil-based emissions should be included in GA’s carbon footprint. Understanding the geospatial and temporal context of land conversion decisions, as well as the social and economic costs, could be used to create incentives for land management that limit soil-based GHG emissions in a local context with implications for relevant United Nations (UN) initiatives
Modality Distillation Using a SAM-Guided Multimodal Teacher for Unimodal Wildfire Segmentation and Temperature Prediction
No full textWildfires are one of the world’s most devastating natural disasters that affect the environment, communities, and more critically, humans that live in and around those communities. Due to the threat of large-scale destruction in landscapes and human inhabited areas, it has become increasingly more important to develop wildfire detection, management, and suppression strategies to mitigate and prevent these negative outcomes. Wildfire research encompasses many different areas. Most notably, the development of communication, navigation, remote sensing, and monitoring systems. In wildfire monitoring, limitations discovered in-ground and satellite observation have shifted the focus toward Unmanned Aerial Vehicle (UAV) based wildfire research, which has proven promising. Modern UAV-based wildfire detection methods primarily focus on using artificially intelligent deep neural networks with collected aerial wildfire imagery to classify, localize, or segment wildfires. While classification tasks are capable of achieving high accuracy in many domains with single modality input, such as RGB imagery only, segmentation tasks in domains containing dynamically changing environments can become more complicated, requiring multiple input types to prove valid in real-world applications. Additionally, wildfire research in computer vision largely focuses on the classification only of fire within an image or binary segmentation of fire itself. These tasks have become more trivial in recent years, and research needs to move toward more detailed understanding of wildfire using computer vision approaches. The practical application of wildfire segmentation is that it isolates fire location within an image, which can be used to identify different intensity regions or hotspots of the fire. With this knowledge, dangerous regions of the fire are found and this information can be communicated to protect firefighters or other personnel from getting too close to dangerous areas of the natural disaster. This paper explores binary wildfire segmentation and pixel-wise temperature prediction, in degrees Celsius, using radiometric temperature-labeled ground truth. A semi-supervised modality distillation approach is used, where a SAM-guided multimodal segmentation network is trained alongside a unimodal network, transferring knowledge for both segmentation and temperature regression. With this work, wildfire research can progress to more complex raw temperature inference, using only RGB image data input, potentially eliminating the use of IR sensors in the future
Micro Wind Turbine - Modelling and Testing
Get PDFThe global energy demand continues to rise as people consume more electricity to power their personal electronics, electric vehicles, and consumer products such as outdoor tools. To generate renewable energy, large scale solar and wind farms continue to receive the most commercial attention. However, portable wind energy turbines have the potential to generate sufficient power for cell phones and other electronic devices. There are two types of wind turbines, horizontal and vertical axis each having their pros and cons. Vertical-axis wind turbines are the main focus of this thesis, with a reduction in their form factor or size and portable applicability. However, a gap exists in the development and deployment of miniaturized VAWT to generate electricity in remote areas. To accomplish this research investigation, a series of tasks were undertaken including the design, modeling, analysis, fabrication and testing of small multi-blade vertical rotors for electricity generation. Eight different airfoil profiles were selected, and two distinct numerical studies were conducted on them. First, the aerodynamic capabilities of these airfoil profiles were virtually analyzed using two software packages, COMSOL and QBlade. Specifically, the airfoil performance was assessed including the lift and drag coefficients at different angles of attack for the incoming wind flow. Second, the airfoils were integrated into rotors and then fabricated using a Fused Deposition Modeling (FDM) 3D printing process. The number of turbine rotor blades was determined using the tip speed ratio. A small-scale wind turbine was available in the laboratory to support limited experimental testing. The wind turbine rotors were attached to various AC/DC electric generators and tested in the wind tunnel with supporting instrumentation. Representative experimental results were collected using National Instruments data acquisition hardware and software. Overall, vertical axis wind turbine rotors with airfoils having a lower camber radius had the highest lift and drag forces, which also translated to higher electricity generation. Also, turbine rotors with airfoil blades that utilized both lift and drag forces optimally generated more electricity as compared to turbine rotors with airfoils that were either lift or drag only. In terms of electric power, a mismatch in the AC/DC electric generator size to the rotors, and mechanical alignment leading to lower efficiency likely contributed to smaller values than anticipated. The numerical and experimental results offer a promising pathway for continued study on miniature VAWT systems