Journal of Advanced Education and Sciences

Techno-economic assessment of electric vehicles in India: evaluating baas models, ice parity, and next-generation platforms

2026-02-24T15:43:13+00:00

The rapid electrification of road transport presents a critical opportunity for decarbonization and energy security in emerging economies. This paper presents a comprehensive techno-economic assessment of passenger electric vehicles (EVs) in the India market, with emphasis on cost parity with internal combustion engine (ICE) vehicles, the viability of Battery-as-a-Service (BaaS) models, and the performance of next-generation EV platforms. A detailed comparison is conducted using representative Indian EV models and equivalent ICE vehicles, incorporating real-world parameters such as battery capacity, driving range, electricity and fuel tariffs, maintenance cost, and battery degradation. The study further contextualizes India’s EV landscape through a comparative market and technology review with global leaders, particularly the China EV ecosystem.
A mathematical cost model is developed to evaluate the total cost of ownership (TCO) and per-kilometer running cost of EVs and ICE vehicles under multiple usage scenarios. Results indicate that while EVs exhibit higher upfront acquisition cost (15–35% premium), their operating cost is 55–70% lower than comparable ICE vehicles under prevailing Indian electricity tariffs. When BaaS schemes are introduced, the initial purchase cost of EVs reduces by approximately 25–30%, significantly improving buyer affordability and payback period. Break-even analysis reveals that ICE parity is typically achieved within 3–5 years for private users with annual driving distances exceeding 12,000 km.
The findings demonstrate that next-generation EV platforms, characterized by higher energy density batteries and dedicated skateboard architectures, further enhance efficiency and lifecycle economics. The study also highlights the systemic impact of EV adoption on power systems, reinforcing the importance of coordinated charging and demand-side management strategies. The proposed framework provides policymakers, manufacturers, and consumers with a quantitative basis for evaluating EV adoption in the Indian context and supports the role of innovative ownership models such as BaaS in accelerating market penetration.

Examining the predictors of teacher performance: A SEM-PLS analysis of self-development programs and competence among senior high school teachers

2026-02-26T22:23:31+00:00

This study examined the influence of Teacher Self-Development Programs and Teacher Competence on teacher performance in senior high schools in Java, with a focus on Mathematics and Bahasa Indonesia teachers. The study was motivated by persistent challenges in instructional quality and the need to understand the factors that shape teacher performance within Indonesia’s evolving educational landscape. A quantitative approach was employed using a variance-based Structural Equation Modeling (SEM-PLS) design, complemented by data from national assessments and policy documents to strengthen contextual interpretation. A total of 400 teachers were selected through purposive sampling, and data were collected using a structured questionnaire based on validated reflective indicators. The measurement model demonstrated satisfactory reliability and validity, while the structural model revealed that Teacher Competence had a strong and significant direct effect on teacher performance. Teacher Self-Development Programs showed a marginally significant effect but contributed meaningfully when combined with competence, resulting in a model that explained 71.7% of the variance in teacher performance. The findings highlight the dominant role of competence in shaping performance and the supportive function of self-development initiatives. The study concludes that strengthening teacher competence, supported by coherent and continuous professional development mechanisms, is essential for improving instructional quality in senior secondary schools.

Optimal scheduling of residential loads with renewable energy and energy storage: a techno-economic analysis

2026-03-02T18:00:49+00:00

The increasing penetration of renewable energy resources and electric vehicles in residential power systems has intensified the need for intelligent load scheduling strategies to ensure economic and reliable operation. This paper presents an optimal scheduling framework for domestic electrical loads integrated with rooftop solar photovoltaic (PV), wind energy systems, battery energy storage systems (BESS), and grid connectivity under the Indian electricity mix. A typical residential load profile incorporating household appliances and electric vehicle charging demand is considered for a 24-hour scheduling horizon.
A mathematical model of the hybrid residential energy system is developed, accounting for renewable generation variability, battery charging–discharging constraints, time-varying electricity tariffs, and net-metering policies. The optimization objective is formulated to minimize the total daily energy cost while maintaining user comfort and operational constraints of the energy storage system. Solar and wind generation profiles are derived from typical Indian meteorological conditions, and residential demand patterns are modeled using standard household appliance usage schedules.
Simulation results demonstrate that the proposed optimal scheduling strategy reduces grid energy consumption by approximately 28–35% compared to an unscheduled baseline case. The daily electricity cost is reduced by nearly 30%, primarily due to effective utilization of renewable generation and strategic charging of the battery during off-peak tariff periods. Furthermore, coordinated scheduling of EV charging significantly alleviates peak demand stress, achieving peak load reduction of about 20% without compromising charging requirements. The inclusion of BESS enables improved self-consumption of renewable energy and enhances system flexibility under variable generation conditions.
The findings indicate that intelligent domestic load scheduling with integrated renewable energy sources and storage can substantially improve economic performance and grid friendliness of residential energy systems in India. The proposed framework provides a scalable and practical solution for future smart homes and supports national objectives related to renewable energy integration and electric mobility adoption.

The erosion of learner autonomy: modeling the mediating role of AI reliance under academic and economic pressure among Vietnamese EFL students

2026-03-09T07:35:00+00:00

The rapid growth of artificial intelligence (AI) writing tools has transformed how English as a Foreign Language (EFL) students complete academic writing tasks. While these tools provide linguistic support, concerns have emerged regarding their potential impact on learner autonomy. This study examines how academic and economic pressures influence Vietnamese EFL students’ reliance on AI writing tools and how this reliance affects learner autonomy. Survey data were collected from 235 students across three universities in Hanoi and analyzed using regression and mediation analysis. The results show that academic pressure significantly increases students’ reliance on AI tools, whereas economic pressure does not. Furthermore, AI reliance is negatively associated with learner autonomy and partially mediates the relationship between academic pressure and autonomy. The findings highlight the need for balanced pedagogical strategies that promote responsible AI use while supporting autonomous learning.

A structural model of Vietnamese EFL teachers’ readiness to integrate AI in English language teaching

2026-03-09T07:23:00+00:00

This study investigates Vietnamese EFL teachers’ readiness to integrate artificial intelligence (AI) into English language teaching, focusing on perceived competence, attitudes toward AI, and institutional support. A survey was administered to 312 teachers from 14 institutions, representing both public and private sectors. Using descriptive statistics and structural equation modeling, the study found that teachers reported moderate levels of competence and attitude, but low institutional support.
Perceived competence emerged as the strongest predictor of readiness (β = .42), followed by attitude toward AI (β = .36), while institutional support had a weaker but significant effect (β = .18). Notably, younger teachers and those from private institutions demonstrated higher readiness. The findings highlight the importance of combining teacher-centered training with system-level support to foster sustainable AI adoption in Vietnamese ELT.

How do annelids contribute to ecosystem balance?

2026-03-27T10:17:07+00:00

Annelids are major contributors to ecological stability in terrestrial, freshwater, and marine systems. Their activities influence soil formation, nutrient cycling, sediment turnover, water quality, and trophic dynamics. Earthworms and relatives (Clitellata: Polychaeta, Oligochaeta, and Hirudinea) act as primary agents of bioturbation in soils (Darwin, 1881; Edwards and Bohlen, 1996) ^{[8, 13}], while polychaetes dominate benthic processes in marine sediments (Fauchald and Jumars, 1979; Kristensen, 2001) ^{[17, 28]}. Through feeding, burrowing, and cast production, annelids regulate microbial communities, enhance nutrient availability, and modify habitats in ways that support biodiversity (Lavelle et al., 1997) ^[31]. This article reviews the principal ecological functions of annelids and their roles as ecosystem engineers across major habitat types.

Becoming a teacher teaching and learning simultaneously: Exploring the well-being of Indonesian in-service teachers during online teacher professional development programs

2026-03-16T02:26:49+00:00

Teacher well-being is crucial for fostering effective and sustainable teaching practices, yet it is often challenged by various factors, such as excessive teacher workload. This study examines the well-being of in-service teachers in Indonesia who maintained their full-time teaching responsibilities while participating in an online teacher professional development (oTPD) program. A total of 562 teachers in the program completed an online 17-item Likert-scale questionnaire and ten participants were purposively selected and invited for a series of follow-up semi structured interviews. Despite the challenges to manage the two roles, the participants reported high levels of well-being. They maintain their well-being by sustaining their positive emotions and seeking support from others. The finding suggests that teacher well-being can be maintained through effective coping mechanism strategies. It also highlights the need to design a more flexible and supportive oTPD program that acknowledges teacher’s professional and personal constraints. Further implications for well-being-centered pedagogical practices and directions for future research are discussed.

Beyond yields: multidimensional livelihood outcomes of conservation agriculture among smallholder farmers in northern Ghana

2026-03-16T21:40:45+00:00

Conservation agriculture (CA) is promoted globally as climate-smart, yet studies on its broader livelihood outcomes remain fragmented. This study evaluates the multidimensional livelihood impacts of CA promoted under the Ghana Agricultural Sector Investment Program (GASIP) across the five capitals in the Upper West Region. Using a mixed-methods approach, the study conducted 300 surveys, 10 key informant interviews, and 6 focus group discussions with farmers and the project implementation team. The results indicate significant gains in agronomic knowledge, psychosocial well-being, social cohesion, soil fertility, food access, productive assets, income, savings, and financial inclusion, supported by strong farmer-to-farmer knowledge diffusion and Village Savings and Loans Associations. At the same time, youth under-representation, persistent gendered land constraints, and varied financial and asset gains reveal important distributional limitations. We argue that integrated CA interventions linking training, mechanisation, irrigation, and local financial institutions can strengthen resilience, but must address targeting, equity, and long-term sustainability.

Impact of climate change on the fishing communities of lake Itezhi-Tezhi of Zambia

2026-03-31T10:28:51+00:00

Climate change poses growing challenges to inland fisheries and the livelihoods of communities that depend on them. This study examined the impacts of climate change on fishing communities around Lake Itezhi-Tezhi located at latitude -15.7592 and longitude 26.0175 in Southern Zambia. A mixed-methods approach was used, combining household surveys, key informant interviews, field observations and review of secondary data. Data were collected from 51 participants drawn from fishing communities and relevant institutions, with emphasis on community perceptions of rainfall patterns, lake water levels, fish catch volumes and associated socio-economic effects over the period 2015 to 2025.The results show that most respondents perceived noticeable changes in rainfall patterns and lake water levels, with 82 percent reporting changes in rainfall and 78 percent observing changes in water levels in the lake. Perceptions of fish catch trends indicated a general decline, as the majority of respondents (86%) reported reduced catches over the past decade, although a small proportion of 8% perceived stability or improvement. These environmental changes were associated with declining income from fishing and increased food insecurity among fishing households where 74% of participants report decline in fisher men income. The findings highlight the vulnerability of artisanal fishing communities to climate variability and environmental change, while also underscoring the value of local knowledge in understanding climate impacts. The study emphasizes the need for integrated climate adaptation strategies, improved fisheries management and livelihood diversification to strengthen community resilience around Lake Itezhi-Tezhi.