This study examines how pre-service teachers in early childhood education (ECE) and elementary education (ELE) integrate ChatGPT into mathematics lesson planning. Using a mixed-methods case study framed by the Technological Pedagogical Content Knowledge (TPACK) with Contextual Knowledge (XK) framework and AI literacy, we analyzed the experiences of 44 pre-service teachers (24 ECE, 20 ELE) in mathematics method courses at a university in the Midwestern United States. Data sources included pre- and post-assessments, documentation of ChatGPT interactions, lesson plans, and reflection papers. Findings reveal significant gains in participants' knowledge of and confidence in using ChatGPT, with increased willingness to incorporate generative AI tools into their teaching practices. Thematic analysis identified six categories of ChatGPT use in lesson planning, from content generation to final refinement, while highlighting challenges in adapting AI-generated content to meet developmentally appropriate practices and specific classroom needs. While both ECE and ELE groups followed similar patterns in ChatGPT usage, their approaches varied based on grade-level contexts. This study demonstrates how the development of integrated TPACK-XK competencies and AI literacy supports effective ChatGPT integration in math lesson planning. Findings contribute to understanding how teacher education programs can prepare future educators to integrate generative AI technologies while maintaining pedagogical integrity.
Phosphorus (P) availability is often limited in subtropical acidic soils due to fixation by iron and aluminum oxides, constraining nutrient uptake and productivity in Camellia oleifera plantations. However, the mechanisms by which the effects of artificial nitrogen (N) application and natural N fixation via legume intercropping on soil P dynamics remain poorly understood. In this study, the independent effects of legume intercropping and N application on soil P fractions, soil biochemical properties and leaf nutrient content were investigated in C. oleifera plantations in subtropical China. Six treatments were applied: monoculture with weeding, monoculture without weeding, intercropping with Cassia tora or peanut, and monoculture with low or high N application (25 or 50 g urea per plant). Soil P fractions, soil organic carbon, total N, pH, ammonium (NH4+-N), nitrate (NO3--N), acid and alkaline phosphatase activities, and leaf C, N, and P contents were measured at the growth (July) and mature (September) stages. Results showed that both legume intercropping and low N application independently enhanced total and labile soil P, increased soil organic carbon, and improved leaf nutrient contents compared to the control. High N initially reduced labile P but partially recovered by maturity. Phosphatase activities declined at maturity but remained higher in intercropped and fertilized plots, indicating improved P cycling. Nitrate N concentrations increased from the growth stage to the mature stage. These results suggest that legume intercropping and N application, when applied independently, each promote soil P availability and plant nutrient uptake, highlighting practical strategies to enhance soil fertility and sustain C. oleifera production in subtropical acidic soils.
Smart charging of electric-vehicle (EV) fleets must balance energy cost, transformer/feeder power limits, user satisfaction, and the operational value of on-site resources such as rooftop PV and battery energy storage systems (BESS). This work presents a scenario-based model predictive control (SB-SMPC) framework for grid-to-vehicle (G2V) and vehicle-to-grid (V2G) coordination that minimizes the net operating cost while satisfying the system constraints. The controller explicitly models stochasticity in base load, PV generation, and electricity prices via sampled scenarios, and it also integrates demand charge cost for distribution grid services. EV service quality is guaranteed through departure energy targets, connection-time policies, and a minimum state of charge (SoC) floor. BESS dynamics, round-trip efficiency, terminal SoC targets, and battery degradation costs are included to capture battery storage economics. This study compares V2G operations with and without BESS across daily horizons. Results show that SB-SMPC systematically limits transformer import, curtails PV only when economically justified, and shifts charging to low-price periods while meeting EV energy requirements; enabling V2G further reduces net costs when energy export cost and demand charges are favorable. Comparative results (with/without BESS) reveal that BESS helps to reduce net electricity cost around 4% and grid peaks around 10% as compared to without BESS installation. Imposing high demand charges further cuts the peaks about 11%. The sensitivity analysis further confirmed the robustness of the proposed framework under varying load, PV, and price conditions.
Purpose This study investigates how neurodiversity, inclusion, manager support, training and engagement predict two critical organisational outcomes: employee performance and absenteeism. The research aims to identify which workplace factors most strongly contribute to improved productivity and reduced absence, particularly within neurodiverse workforces. Design/methodology/approach The analysis is conducted using organisational survey data. Correlation analysis revealed significant bivariate relationships, including a strong positive link between engagement and job satisfaction (r = 0.83) and a negative association between inclusion and absenteeism (r = −0.297). Multiple regression models were used to assess performance and absenteeism as dependent variables and workplace factors as predictors. Cluster and segmented analyses further explored employee subgroups and neurodiversity-related patterns. Findings Regression results suggest that engagement (β = 0.52) and manager support (β = 0.46) are the strongest positive predictors of performance, while inclusion (β = 0.41) also contributes significantly. In the absenteeism model, manager support (β = −0.54) and inclusion (β = −0.51) were negatively associated with absenteeism. Neurodivergent employees reported higher engagement, performance and innovation, and lower absenteeism than neurotypical peers. The models achieved high predictive strength (R² = 0.89 for performance; R² = 0.84 for absenteeism), though multicollinearity among predictors warrants further investigation. This explanatory capacity highlights the interconnected impact of inclusion, support and engagement within a unified organisational culture, aligning with findings from previous research in organisational behavioural studies. Practical implications Organisations can improve performance and reduce absenteeism by investing in inclusive leadership, tailored training and engagement strategies. Neurodivergent employees, when supported, perform at higher levels, suggesting that inclusion is not just ethical but strategically valuable. Social implications This research underscores the societal value of neurodiversity inclusion in workplaces. By demonstrating that neurodivergent employees perform better and are more engaged when supported, it challenges deficit-based narratives and promotes equity. Inclusive practices not only benefit individuals but also reduce absenteeism and foster innovation, contributing to broader economic and social resilience. Organizations that embrace neurodiversity help dismantle stigma, improve mental health outcomes and create environments where diverse minds thrive. The study advocates for a shift from accommodation to empowerment, encouraging policymakers and business leaders to embed neurodiversity into diversity, equity, and inclusion (DEI) agendas for sustainable social impact. Originality/value This paper contributes to the growing literature on neurodiversity in organisations by applying multivariate statistical modelling to link inclusive workplace practices with performance and attendance outcomes. It highlights actionable levers engagement, managerial support and inclusive culture that organisations can prioritise to unlock the full potential of neurodiverse talent and reduce absenteeism.
