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FROM CLASSROOMS TO CLICKS: EXPLORING STUDENT ATTITUDES AND CHALLENGES IN THE SHIFT TO DIGITAL LEARNING IN HIGHER EDUCATION
Aim/Purpose This study is a cross-sectional survey that explores attitudes towards online classroom engagement, online assessments, exams, and challenges in digital learning. Background Educational institutions have adopted digital platforms with varying degrees of success. The COVID-19 pandemic has prompted researchers and academics to reflect on digital interventions and their impact on pedagogy, learning, and assessment. However, in the present circumstances, online teaching, learning, and assessment will require learners to bring their own ethics, unrestrained by external institutional rules. Methodology The sample consisted of 1,017 students in higher education across India. The researchers developed a tool, the Digital Learning Scale, which was built on three factors: attitude towards online classroom engagement, attitude towards online assessments, and challenges in digital learning. This tool was used to collect data. Contribution The study results prove the effect of online learning and online assessments in higher education institutions. Findings The significant findings of this study are: (1) approximately 50% of the students prefer that there should be a balance between online and offline teaching, learning and evaluation; (2) there is significant positive high correlation between the last online exam and last offline exam scores; (3) there is significant positive correlations between attitudes towards online class engagement, attitude towards online assessments and exams and challenges in digital learning; (4) 65% of the students agree that digital learning increases social isolation; (5) 55% of the students agree that incidence of cheating by the students in online exams is evident. Recommendations Educational institutions should invest in robust strategies to promote academic for Practitioners integrity, provide technical support, and offer training programs that equip students with the necessary digital skills for achieving successful learning outcomes. Impact on Society There is a pressing need to prioritise digital literacy and integrity initiatives. Future Research Five years post-pandemic, research should be conducted in higher education institutions on the impact of online learning. (2025), (Informing Science Institute). All rights reserved. -
The influence of leadership in building a learning organization /
The IUP Journal Of Organizational Behavior, Vol.15, Issue 1, pp.7-18, ISSN: 0972-687X. -
Effectiveness of activity based program in enhancing fine motor skills of children with dyspraxia /
Scholedge International Journal Of Multidisciplinary & Allied Studies, Vol.2, Issue 5, pp.502-510, ISSN No: 2394-336X. -
Structure-tuned Pr-doped NiFe2O4nanoceramics for enhanced pseudocapacitive performance: Insights from lattice distortion and charge transfer dynamics
In this study, Praseodymium-doped nickel ferrite (NiPrxFe2-xO4, x=0.000.02) nanoceramics were synthesized via an efficient solution combustion method to investigate the structural modifications and their impact on electrochemical performance. X-ray diffraction confirmed the formation of a single-phase cubic spinel structure across all compositions, with Pr3+substitution inducing measurable lattice distortions and variations in crystallite size. WilliamsonHall analysis revealed a doping-dependent microstrain, highlighting the role of Pr doping in tuning the structural framework. FTIR spectra further confirmed alterations in metaloxygen vibrations at tetrahedral and octahedral sites, supporting the lattice perturbations caused by ionic substitution. Electrochemical characterization using cyclic voltammetry, galvanostatic chargedischarge, and electrochemical impedance spectroscopy demonstrated superior pseudocapacitive behavior for the optimally doped sample (x=0.01), which exhibited a high specific capacitance of 69.2F/g and the lowest charge transfer resistance (0.30?). Scanning electron microscopy revealed a porous and roughened surface morphology in this composition, facilitating rapid ion diffusion and redox kinetics. This is quantitatively supported by a correlation between doping-induced lattice strain, crystallite size, and the resulting enhancement in charge transfer kinetics and redox-active site density. These findings position Pr-doped NiFe2O4nanoceramics as promising candidates for next-generation supercapacitor electrodes. 2025 Elsevier Ltd and Techna Group S.r.l. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
A Scientometric Analysis of Research Studies on 43 Years of Leadership in Online Education
Leadership in online education involves strategically managing digital learning environments to ensure effective instruction and engagement. This research aims to identify the publication trends and highlight trending research topics and scientific conversations in this field of leadership in online education. Using 947 records from the Scopus database, the evolution of leadership discourse in online education was examined using scientometric analysis to find the trends, most influential authors, institutions, publishing platforms, and countries. The extracted data spanned publications from 1981 to 2023. The trending topics evolved from knowledge management and school administration to e-learning and higher learning, and, after 2020, to challenges faced in imparting education due to Covid-19. The United States, China, and the United Kingdom emerged as leading contributors to this field. Co-authorship analysis highlighted international collaborations, which emphasised the growing global interest in leadership within virtual learning environments. These research findings could be helpful for researchers and managers in the field of education for adapting to the digital age. 2025, Commonwealth of Learning. All rights reserved. -
Community Consciousness and The Construction of Social Honour : A Study Among The Kurds in Finland
Research on honour has recently been overshadowed by discussions surrounding honour-related violence (HRV), particularly honour killings. Typically, inquiries into how the concept of honour, often associated with violent acts, is formed, and expressed on personal or communal levels remain unanswered or are only superficially explored. This study aims to uncover the social structures underlying the concept of honour, demonstrate its manifestation through social interactions, and elucidate how individuals respond to threats against their honour. Because of the many tragic instances of HRV within Kurdish diaspora communities, Kurds and Kurdish culture frequently feature in discussions concerning this phenomenon. Therefore, data for current research has been collected from Kurds living in the diaspora, specifically in Finland. The data were elicited through a combination of methods to be as comprehensive as possible. This included 24 semi-structured interviews with individual participants and four Focus Group Discussions involving 16 participants. A closer look at the data shows that the construction of Kurdish honour is based on a complex interaction of social structures. These structures can be broken down into three key elements: institutional, relational, and embodied factors. In this regard, the research has identified six structural components. The study demonstrates that the intensity of honour-related conflicts stems from an intricate interplay of structural factors. However, the relative weight of these factors determines the flashpoints of tension. Through the lens of structuration theory, the study demonstrates the role of everyday practices and dynamic social factors in shaping individuals' discursive consciousness around honour. Individuals' conceptualization of honour may sometimes diverge from its practical application, leading to a space for social negotiation where honour undergoes continuous reshaping into a dynamic equilibrium that impacts daily life. It's essential to recognize that this equilibrium varies among individuals. However, a threat to honour can prompt varying facework procedures, contingent upon individual characteristics and community expectations. Current Inquiry uncovers six distinct behavioural patterns individuals exhibit during a crisis of honour. The investigation of the participants' narratives reveals a diverse Kurdish culture, as evidenced by their different perceptions about the tolerable thresholds of honour violations and contradictory discourses concerning honour. The final significant finding is that the fear of dishonour typically outweighs the desire for honour among the Kurds, as indicated by both daily language use and chronological analysis of conflict cases. This observation holds significant implications, not only for reevaluating normative terminology but also for informing social and political preventive measures. -
Evaluating the impact of a multidimensional Well-being intervention for micro, small-, and medium-sized enterprise workers in Assam, India: A single-group feasibility study
Contemporary health research underscores the importance of comprehensive well-being, particularly within occupational environments that profoundly shape individual health experiences. The Micro, Small, and Medium Enterprises (MSME) sector represents a complex workplace ecosystem characterized by multifaceted challenges that potentially compromise worker welfare. In the northeastern Indian State of Assam, MSME sector workers represent a vulnerable population that experiences distinctive professional and personal stressors. This research aims to investigate an intervention that integrates holistic well-being strategies, specifically combining traditional Indian yoga practices with Western relaxation methodologies. The proposed approach seeks to address workers physical, psychological, and social dimensions of health within the challenging MSME sector context of Assam, India. The study is a single-group feasibility trial with pre, post- and follow-up assessments to assess the impact of the well-being intervention. A sample of 35 MSME workers from Assam, India (n=35), participated in a 3-week intervention program. Baseline, postintervention, and follow-up assessments after 3 weeks of physical, psychological, and social well-being were obtained via standardized scales. To analyze the quantitative data, repeated-measures ANOVA (RMANOVA) was performed within the intervention completing participants to evaluate the interventions effect. Two-tailed tests of significance were performed. The findings of the study indicated that the intervention led to significant improvements in physical, psychological, and social well-being, with effects being sustained and further enhanced at follow-up. Repeated-measures ANOVA with GreenhouseGeisser corrections revealed significant time effects for general health (r)' = .567), musculoskeletal pain (r)' = .825), perceived social support (r)' = .678), and mental well-being (r)' = .726), all p <. 001. The participants reported reduced general health concerns, decreased musculoskeletal pain, and increased perceived social support and mental well-being from preintervention to postintervention and follow-up. The study offers empirically grounded insights into the potential transformative effect of integrated multidimensional well-being intervention. Copyright 2023 DOI Foundation. The content of this site is licensed under a Creative Commons Attribution 4.0 International License. -
Development of an integrated well-being programme for micro, small-and medium-sized enterprise workers in India: A technical note
Workers in Indias micro, small- and medium-sized enterprise (MSME) sector often face a convergence of occupational risks, including long working hours, physical strain, economic insecurity, and limited access to health resources. Despite the sectors critical contribution to national productivity, structured programs addressing the holistic well-being of MSME workers remain scarce. This technical note outlines the development of an integrated well-being intervention designed to enhance physical, psychological, and social health among MSME workers across diverse Indian contexts. Drawing on both indigenous and global practices, the program combines simple yoga-based movements, breathing exercises, and mindfulness techniques with Western approaches such as Jacobsons Progressive Muscular Relaxation (JPMR). The intervention is delivered over two phasesa 21-day facilitator-led group session followed by a 21-day self-practice period to support skill development and habit formation. Designed for scalability and accessibility, the content uses culturally relevant language and experiential activities to ensure engagement in low-literacy and resource-limited settings. This note details the theoretical grounding, content structure, and delivery framework of the program, offering a practical, context-sensitive model that can be adapted for workplace well-being initiatives within the Indian MSME sector. Copyright (c) 2025 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. -
A review on extraction and separation of cellulose fibers from agro wastes
Over the past few decades, there was significant increase in research concerning resources that have certain desirable characteristics like renewability, ease of availability, economic value, excellent mechanicalthermal properties, biocompatibility and biodegradability. Cellulose is one such resource that possesses these characteristics and yet various sources that constitute ample quantities of lignocellulose are discarded, as their peculiarities and applications were not widely known to the population. Agro wastes, which are generated every year at a tremendous rate, are viewed as a promising substrate for the commercial extraction of cellulose. Hence in this review, an appropriate utilization of these agricultural by-products, with respect to extraction of cellulose is discussed, so as to ameliorate their applications in an aim to diminish the disposal rate of essential commodities. 2021 World Research Association. All rights reserved. -
A Review of Historical Context and Current Research on Cannabis Use in India
Background: The cultivation and use of cannabis is historically rooted in the Indian subcontinent and this rich heritage of cannabis use dates back to at least two thousand years. Cannabis remains an illicit substance in India despite its changing status globally with many countries legalizing cannabis use in recent years. Scientific research on cannabis use in India has also been sparse. Method: Extensive search of online databases resulted in the identification of 29 original research studies pertaining to one of three areas of cannabis research; a) prevalence of cannabis use b) psychological correlates of cannabis use, c) cannabis use in substance use treatment settings. Findings: We found that most Indian studies used very basic quantitative research designs and had poor scientific rigor. Samples were small, region specific and included only males. Data analyses were limited to descriptive methods. The criteria for cannabis use in most of the reviewed studies were not rigorous and prone to biases. Conclusion & Implications: With changing attitudes and loosening of restrictions on cannabis use, the prevalence of new users is rising dramatically particularly in the college going population. This presents a strong need for research on motivations and attitudes to cannabis use and how those can influence patterns of use, and also the short- and long-term effects of use. More studies with stronger research designs (both cross sectional and longitudinal) are required for the study of cannabis use and this knowledge will be critical for managing the growing substance epidemic, generating public health solutions as well as formulating effective policy frameworks. 2022 The Author(s). -
Environmental sustainability and management (ES & EM) practices among Service Sector Institutions in Kathmandu, Nepal
Environmental sustainability (ES) emerged in response to the felt negative consequences of overexploitation of the environment and natural resources. ES has gained momentum in recent decades in areas of social policy, means of production, development, economy and everyday individual behaviours. The drive towards ES has been firmly based in scientific research which has been dominated by Western developed countries. For a tiny developing country like Nepal, its overall contribution to global environmental pollution and degradation is minimal; however, it has been disproportionately negatively affected by global warming, pollution, etc. There is sparse research on the various measures or state of environmental sustainability standards, policies or behaviours in Nepal. In this quantitative cross-sectional study, five types of Service Sector Institutions (SSI) from Kathmandu, Nepal were studied for their environmental sustainability (ES) and environment management (EM) measures in place at their facilities. SSIs were chosen because they have the distinct characteristic of being directly involved with large sections of populations, and hence hold the potential to pioneer innovative and effective solutions towards fostering environmental sustainability. ES was defined in terms of three measures related to sustainable freshwater use, energy use and waste management. The measures for EM included organizational capacity building and attitudes towards ES. Data was collected directly from representatives of the SSIs through self-report interviews or forms. The 104 SSIs included 25 schools, 26 restaurants, 16 hotels/lodges, 18 banks and 17 health care organizations. Based on frequency distributions and ANOVA tests, it was found that the overall extent of ES and EM practices among the 102 SSIs was dismally low in Kathmandu, Nepal. As given in the figure, educational institutions performed significantly better across all five ES and EM measures indicating highest prevalence of sustainability measures and practices. Banks performed significantly worst across all categories compared to the four other SSIs, indicating least amount of efforts in ES and EM. All five measures of environmental sustainability (ES) and environmental management (EM) were also strongly positively correlated amongst each other. A huge amount of effort is still required to revamp the existing ES and EM policies and organizational norms in Nepal. Moreover, it remaining challenging to change peoples attitudes and behaviours in order to effect lasting positive changes in the future and conserve the local environment better. The Author(s) 2025. -
Enhanced Automated Oxygen Level controller for COVID Patient By Using Internet of Things (IoT)
The Internet of Things (IoT) shall be merged firmly and interact with a higher number of altered embedded sensor networks. It provides open access for the subsets of information for humankind's future aspects and on-going pandemic situations. It has changed the way of living wirelessly, with high involvement and COVID-related issues that COVID patients are facing. There is much research going on in the recent domain, like the Internet of Things. Considering the financial-economic growth, there isn't much significance as IoT is growing with industry 5.0 as the latest version. The newly spreading COVID-19 (Coronavirus Disease, 2019) will emphasize the IoT based technologies in a greater impact. It is growing with an increase in productivity. In collaboration with Cloud computing, it shows wireless communication efficiently and makes the COVID-19 eradication in a greater way. The COVID-19 issues which are faced by the COVID patients. Many patients are suffering from inhalation because of lung problems. The second wave attacks mainly on the lungs, where there is a shortage of breathing problems because of less supply of oxygen (insufficient amount of oxygen). The challenges emphasized as proposed are like the shortage of monitoring the on-going process. Readily being active in this pandemic situation, the mentioned areas are from which need to be discussed. The frameworks and services are given the correct data and information for supply of oxygen to the COVID patients to an extent. The Internet of Things also analyzes the data from the user perspective, which will later be executed for making on-demand technology more reliable. The outcome for the COVID-19 has been taken completely to help the on-going COVID patients live, which can be monitored through Oxygen Concentration based on the IoT framework. Finally, this article discusses and mentions all the parameters for COVID patients with complete information based on IoT. 2022 IEEE. -
Cloud Computing Application: Research Challenges and Opportunity
In a world with intensive computational services and require optimal solutions, cloud security is a critical concern. As a known fact, the cloud is a diverse field in which data is crucial, and as a result, it invites the dark world to enter and create a virtual menace to businesses, governments, and technology that is facilitated by the cloud. This article addresses the fundamentals of cloud computing, as well as security and threats in various applications. This research study will explore how security is remaining as a potential risk for cloud users across the globe by listing some of the cloud applications. Some viable solutions and security measures that could help us in analyzing cloud security threats are reviewed. The analyzed solutions include profound analytical thinking on how to render the solutions more impactful in each scenario. Several cloud security solutions are available to assist businesses in reducing costs and enhancing security. This study discover that if the risks are taken into consideration without any delay then the matter of solutions gets divided into four pillars, which will assist us in obtaining a more comprehensive knowledge. Visibility, compute-based security, network protection, and lastly identity security are referred as four pillars. 2022 IEEE. -
Anomalous indirect carrier relaxation in direct band gap atomically thin gallium telluride
We report ultrafast studies on atomically thin Gallium telluride, a 2D metal monochalcogenide that has appeared to display superior photodetection properties in visible frequencies. Pump photon energy-dependent spectroscopic studies reveal that photoinduced carriers in this direct band-gap material undergo indirect relaxation within ?30 ps of photoexcitation, which is at least an order slower than that of most 2D materials. Despite the direct band-gap nature, slow and indirect carrier relaxation places this layered material as a prime candidate in the multitude of atomically thin semiconductor-based photodetectors and highlights the potential for prospective optoelectronic applications. 2023 American Physical Society. -
Enhanced Sensing Performance of an Ammonia Gas Sensor Based on Ag-Decorated ZnO Nanorods / Polyaniline Nanocomposite
The development of low-cost ammonia sensors with high sensitivity and selectivity has gained considerable interest. Though the response of these sensors at room temperature is low and needs enhancement. In the present study high sensitivity ammonia gas sensors based on nanocomposite films of polyaniline (PANI) and with varying ZnO concentrations were synthesized and investigated. With a loading of 10 at% ZnO, the gas sensing response of 59 % was obtained for 120 ppm NH3 gas. The gas response was further enhanced by decorating the ZnO nanorods with different concentrations of silver (Ag) nanoparticles. The Ag-decorated ZnO nanorods were embedded in the PANi matrix using the in-situ oxidative polymerization technique. It was shown that PANi ZnO, p-n junction, and the introduction of porosity in nanocomposite act synergistically in increasing the resistance caused by the deprotonation of PANi by NH3. Among various compositions studied, 2 % loading of Ag in ZnO embedded in PANi matrix, thin films were found to be highly selective and sensitive towards NH3 gas at room temperature with a chemiresistive response of 70 % at 120 ppm and a recovery time of less than 120 s. The selectivity of the nanocomposite was also studied towards various reducing and oxidizing gasses. 2023 Wiley-VCH GmbH. -
Deterministic, Stochastic, and Deep Learning Approaches to Understand the Economic Fluctuations in India
In the present work, a new mathematical framework is proposed for studying the interrelation among population growth rate, GDP, inflation rate, and unemployment rate within deterministic and stochastic frameworks. The values of the parameters of the proposed model are estimated using real data from India. The local and global uniqueness of solutions is established for the stochastic model. The deterministic model is solved by using the Adams-Bashforth-Moulton predictor-corrector method, and Milstein's method is used for solving the stochastic model. Numerical simulations correlated quite strongly with observed data, while projections for the 20242030 period indicate that controlled population growth bodes well for the outlook of the economy for India, supporting economic prosperity alongside reduced inflation and better employment conditions. The findings presented in this work are correlational; therefore, to find the possible cause for this phenomenon, further research is required with detailed datasets. Comparing our model's GDP predictions with that obtained using a long short-term memory recurrent neural network model returned very high values of predictive accuracy, thus reinforcing the strength and reliability of our framework. 2025 John Wiley & Sons Ltd. -
Characterization of Erd?s matrices by their zero entries
An Erd?s matrix E is a bistochastic matrix whose sum of squares of entries (Frobenius norm squared) equals its maxtrace (maximum value of the trace of ?E, as ? varies over permutation matrices). We characterize all Erd?s E by the patterns of their zero entries; showing that each such skeleton has at most one E. We present an algorithm to find all n Erd?s matrices, which finds them up to n?5 quickly and also size n=6. We further show some presently known RCDS matrices (E in which the trace of ?E remains constant across all the permutations that avoid every zero-entry position in E) to be Erd?s. 2026 Elsevier Inc. -
Deterministic, Stochastic, and Deep Learning Approaches to Understand the Economic Fluctuations in India
In the present work, a new mathematical framework is proposed for studying the interrelation among population growth rate, GDP, inflation rate, and unemployment rate within deterministic and stochastic frameworks. The values of the parameters of the proposed model are estimated using real data from India. The local and global uniqueness of solutions is established for the stochastic model. The deterministic model is solved by using the Adams-Bashforth-Moulton predictor-corrector method, and Milstein's method is used for solving the stochastic model. Numerical simulations correlated quite strongly with observed data, while projections for the 20242030 period indicate that controlled population growth bodes well for the outlook of the economy for India, supporting economic prosperity alongside reduced inflation and better employment conditions. The findings presented in this work are correlational; therefore, to find the possible cause for this phenomenon, further research is required with detailed datasets. Comparing our model's GDP predictions with that obtained using a long short-term memory recurrent neural network model returned very high values of predictive accuracy, thus reinforcing the strength and reliability of our framework. 2025 John Wiley & Sons Ltd. -
Diabetes Mellitus Classification Using Machine Learning Algorithms with Hyperparameter Tuning
Diabetes Mellitus is a prevalent condition globally, marked by elevated blood sugar levels resulting from either insufficient production of insulin or the body cells' inability to respond appropriately to released insulin. For people with diabetes to lead healthy, normal lives, early identification and treatment of the condition are essential. With the need to move away from current traditional procedures, towards a noninvasive methodology, machine learning and data mining technologies can be very useful in the classification of diabetes. Creating an effective machine learning model for the classification of diabetes mellitus was the primary goal of this research. This work is primarily carried out on combined Pima Indian diabetes dataset and German Frankfurt diabetes dataset. The class imbalance issue has been resolved using Synthetic Minority Oversampling Technique. One-hot encoding is applied to convert categorial features to numerical and various single and ensemble classifiers with the best hyperparameters obtained using GridSearchCV method were employed on the pre-processed dataset. With an AUC of 0.98 and maximum accuracy of 98.79%, the Random Forest ensemble technique outperformed the other models, according to the experimental results. As a result, the algorithm might be used to predict diabetes and alert doctors to serious cases that call for emergency care. 2024 IEEE.