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The research paper examines the complex relationship between gamification, student engagement and academic performance in educational environments. The study employed a structural equation model that highlights important connections among key constructs within the educational setting.

This research aims to explore the connection between gamification, student engagement and academic performance in educational settings. The study employs various statistical techniques such as factor analysis, Kaiser–Meyer–Olkin (KMO), Bartlett’s test, component transformation matrix, correlation and regression analysis, descriptive statistics, ANOVA, coefficients and coefficient correlations, residual statistics and confirmatory factor analysis (CFA) to analyze the data.

It was found that active participation by the instructor and good time management skills have a positive impact on student engagement levels (β = 0.380, p < 0.001; β = 0.433 and p < 0.001). However, peer interaction does not significantly predict student engagement (β = −0.068 and p = 0.352). Additionally, there is a positive correlation between student engagement and performance (β = 0.280 and p < 0.001).

The study highlights the importance of innovative design to fully utilize gamification. Future research should consider design, user characteristics and educational context. The findings can guide informed decisions about gamification in education, fostering motivation and learning objectives.

The study presents a reliable tool for assessing student engagement and performance in educational settings, demonstrating high Cronbach’s alpha and robust reliability. It identifies student engagement and time management as significant predictors of Global Learning Outcome. The findings can inform decisions on implementing gamification in educational settings, promoting intrinsic motivation and aligning with learning objectives.

The research highlights the transformative impact of gamification on educational practices, highlighting its potential to enhance student experiences, motivate, promote diversity and improve long-term academic performance, highlighting the trend of integrating technology into education.

In today’s ever-changing education landscape, it is essential to incorporate innovative techniques to keep students engaged and enthusiastic about learning. Gamification is one such approach that has become increasingly popular. It is a concept that takes inspiration from the immersive world of games to enhance the overall learning experience.

This study investigates the behavior of viscous hybrid ferromagnetic fluids flowing through plain elastic sheets with the magnetic polarization effect. It examines flow in a porous medium using Stefan blowing and utilizes a versatile hybrid ferrofluid containing MnZnFe₂O₄ and Fe₃O₄ nanoparticles in the C2H2F4 base fluid, offering potential real-world applications. The study focuses on steady, laminar and viscous incompressible flow, analyzing heat and mass transfer aspects, including thermal radiation, Brownian motion, thermophoresis and viscous dissipation with convective boundary condition.

The governing expression of the flow model is addressed with pertinent non-dimensional transformations, and the finite element method solves the obtained system of ordinary differential equations.

The variations in fluid velocity, temperature and concentration profiles against all the physical parameters are analyzed through their graphical view. The association of these parameters with local surface friction coefficient, Nusselt number and Sherwood number is examined with the numerical data in a table.

This work extends previous research on ferrofluid flow, investigating unexplored parameters and offering valuable insights with potential engineering, industrial and medical implications. It introduces a novel approach that uses mathematical simplification techniques and the finite element method for the solution.

The purpose of this paper is to showcase the utilization of the magnetohydrodynamics-microrotating Casson’s nanofluid flow model (MHD-MRCNFM) in examining the impact of an inclined magnetic field within a porous medium on a nonlinear stretching plate. This investigation is conducted by using neural networking techniques, specifically using neural networks-backpropagated with the Levenberg–Marquardt scheme (NN-BLMS).

The initial nonlinear coupled PDEs system that represented the MRCNFM is transformed into an analogous nonlinear ODEs system by the adoption of similarity variables. The reference data set is created by varying important MHD-MRCNFM parameters using the renowned Lobatto IIIA solver. The numerical reference data are used in validation, testing and training sets to locate and analyze the estimated outcome of the created NN-LMA and its comparison with the corresponding reference solution. With mean squared error curves, error histogram analysis and a regression index, better performance is consistently demonstrated. Mu is a controller that controls the complete training process, and the NN-BLMS mainly concentrates on the higher precision of nonlinear systems.

The peculiar behavior of the appropriate physical parameters on nondimensional shapes is demonstrated and explored via sketches and tables. For escalating amounts of inclination angle and Brinkman number, a viable entropy profile is accomplished. The angular velocity curve grows as the rotation viscosity and surface condition factors rise. The dominance of friction-induced irreversibility is observed in the vicinity of the sheet, whereas in the farthest region, the situation is reversed with heat transfer playing a more significant role in causing irreversibilities.

To improve the efficiency of any thermodynamic system, it is essential to identify and track the sources of irreversible heat losses. Therefore, the authors analyze both flow phenomena and heat transport, with a particular focus on evaluating the generation of entropy within the system.

The study examines the IPO resilience grounded on the firm’s intrinsic factors.

We examine the association of IPO performance and post-listing firm’s performance with issuers' pre-listing financial and qualitative traits using panel data regression.

IPOs floated in the Indian market from July 2009 to March 31, 2022, evince the notable influence of issuers' pre-IPO fundamentals and legitimacy traits on IPO returns and post-listing earning power. Where the pandemic’s favorable impact is discerned on the post-listing year earning power of the issuer firms, the loss-making issuers appear to be adversely affected by the Covid disruption. Perhaps, the successful listing equipped the issuers with the financial flexibility to combat market challenges vis-à-vis failed issuers deprived of desired IPO proceeds.

High initial returns followed by a declining pattern substantiate the retail investors to be less informed vis-à-vis initial investors, valuers and underwriters, who exit post-listing after profit booking. Investing in the shares of the newly listed ventures post-listing in the secondary market can shield retail investors from the uncertainty losses of being uninformed. The IPO market needs stringent regulations ensuring the verification of the listing valuation, the firm’s credentials and the intent of utilizing IPO proceeds. Healthy development of the IPO market merits reconsidering the listing of ventures with weak fundamentals suspected to withstand the market challenges.

Given the tremendous rise in the new firm venturing into the primary market and the spike in IPOs countering the losses immediately post-opening, the study examines the loss-making and young firms IPOs separately, adding novelty to the study.

This study aims to analyze the Prandtl fluid flow in the presence of better mass diffusion and heat conduction models. By taking into account a linearly bidirectional stretchable sheet, flow is produced. Heat generation effect, thermal radiation, variable thermal conductivity, variable diffusion coefficient and Cattaneo–Christov double diffusion models are used to evaluate thermal and concentration diffusions.

The governing partial differential equations (PDEs) have been made simpler using a boundary layer method. Strong nonlinear ordinary differential equations (ODEs) relate to appropriate non-dimensional similarity variables. The optimal homotopy analysis technique is used to develop solution.

Graphs analyze the impact of many relevant factors on temperature and concentration. The physical parameters, such as mass and heat transfer rates at the wall and surface drag coefficients, are also displayed and explained.

The reported work discusses the contribution of generalized flux models to note their impact on heat and mass transport.

This investigation delves into the rationale behind the preferential applicability of the non-Newtonian nanofluid model over alternative frameworks, particularly those incorporating porous medium considerations. The study focuses on analyzing the mass and heat transfer characteristics inherent in the Williamson nanofluid’s non-Newtonian flow over a stretched sheet, accounting for influences such as chemical reactions, viscous dissipation, magnetic field and slip velocity. Emphasis is placed on scenarios where the properties of the Williamson nanofluid, including thermal conductivity and viscosity, exhibit temperature-dependent variations.

Following the use of the OHAM approach, an analytical resolution to the proposed issue is provided. The findings are elucidated through the construction of graphical representations, illustrating the impact of diverse physical parameters on temperature, velocity and concentration profiles.

Remarkably, it is discerned that the magnetic field, viscous dissipation phenomena and slip velocity assumption significantly influence the heat and mass transmission processes. Numerical and theoretical outcomes exhibit a noteworthy level of qualitative concurrence, underscoring the robustness and reliability of the non-Newtonian nanofluid model in capturing the intricacies of the studied phenomena.

Available studies show that no work on the Williamson model is conducted by considering viscous dissipation and the MHD effect past over an exponentially stretched porous sheet. This contribution fills this gap.

The study aims to explore how Soret and Dufour diffusions, thermal radiation, joule heating and magnetohydrodynamics (MHD) affect the flow of hybrid nanofluid (Al₂O₃-SiO₂/water) over a porous medium using a mobile slender needle.

To streamline the analysis, the authors apply appropriate transformations to change the governing model of partial differential equations into a group of ordinary differential equations. Following this, the authors analyze the transformed equations using the homotopy analysis method within Mathematica software, leading to the derivation of analytical solutions. This study investigates how changing values for porous medium, MHD, Soret and Dufour numbers and thermal radiation influence concentration, temperature and velocity profiles. In addition, the research assesses the effects on local Sherwood number, skin friction and Nusselt number.

In this investigation, the authors explore the movement of a needle away from its origin ( ε > 0). As the magnetic and porous medium parameters increase, there is a correspondence decrease in the velocity profile. Simultaneously, an increase in the Dufour number and thermal radiation parameter yields to a higher temperature profile, whereas arise in the Soret number results in an enhanced concentration profile. Furthermore, growth in the magnetic field parameter is correlated with a reduction in skin friction, Nusselt and Sherwood numbers. In addition, an examination of the data reveals that an escalation in the thermal radiation parameter is associated with an elevation in the Nusselt number. Moreover, an elevation in the Dufour number results in an augmentation in the Nusselt number.

These results have practical applications across diverse fields, including heat transfer enhancement, energy conversion systems, advanced manufacturing and material processing.

This study is distinctive in its investigation of the flow of hybrid nanofluid (Al₂O₃-SiO₂/water) over a slender, moving needle. The analysis includes joule heating, MHD, porous medium, thermal radiation and considering the effects of Soret and Dufour.

This study aims to identify mutually exclusive risk categories and determine whether these categories effectively capture the potential impact of risk disclosures on the initial returns of initial public offerings (IPOs) in the financial and non-financial sectors.

Data were collected from 131 Indian IPO prospectuses (104 non-financial and 27 financial) issued between 2015 and 2021. Content analysis was performed to identify mutually exclusive risk categories, and the effects of these categories on initial IPO returns were assessed by regression analysis

The findings revealed that risk factor disclosures have a significant impact on underpricing, but not all risk factors are relevant. In the current study, in the financial sector, IPO underpricing was mostly driven by technological and competitive risk factors. In the non-financial sector, underpricing was predominantly influenced by operating risk and compliance risk factors.

The limitations of this study include the use of sentence-based context analysis, which does not assess the quality of risk disclosures. The statistical data reduction technique used to generate mutually exclusive risk categories may also be a limitation.

This research has the potential to assist companies in standardizing the disclosure of risks within IPO prospectuses. The insights gained can inform market regulators in designing policies aimed at aiding investors in formulating investment strategies, ultimately enhancing transparency and clarity regarding information disclosure. Moreover, the findings offer valuable guidance to investors in selecting IPOs aligned with their risk tolerance levels.

From a societal perspective, this study represents advancements by guiding regulators towards developing and regulating standardized, mutually exclusive risk factors. Such measures can aid investors in enhancing their decision-making perspectives regarding IPOs, promoting a more informed and confident investment environment.

This study is a pioneering attempt to address knowledge gaps by identifying distinct categories of risk disclosures in IPO prospectuses and examining their potential influence on IPO underpricing in the financial and non-financial sectors in India.

This study aims to investigate the effect of externally applied magnetic force and heat transfer with a heat source/sink on the Couette flow with viscous dissipation in a horizontal rotating channel. The magnetic force is added to the governing equations. The effects of fluid flow parameters are observed under the applied magnetic force. In this system, the magnetic force is applied perpendicular to the plane of the fluid flow. In recent years, the magnetic field has renewed interest in aerospace technology. The physical and theoretical approach in the multidisciplinary field of magneto fluid dynamics (MFD) is applied in the field of aerospace vehicle design.

Authors use the perturbation method to solve and find the approximate solutions of differential equations. First, convert the partial differential equation to ordinary differential equation and calculate the approximate solutions in two cases. The first solution got by assuming heat generating in the fluid and the second one got when heat absorbing. After applying the external magnetic force, the effects of various fluid parameters velocity, temperature, skin friction coefficient and Nusselt number are found and discussed using tables and graphs.

It is found that the velocity of the fluid has decreased tendency when the rotation of the fluid and magnetic force on the fluid increases. The temperature of the fluid, Prandtl value and Eckert number increased when the heat source generated heat. When heat absorbs the heat, sink parameter increases and the temperature of the fluid decreases. Also, while heat absorbs, the temperature increases when the Prandtl value and Eckert number increase.

The skin friction coefficient on the surface increases, when the rotation parameter and the magnetic force parameter of the fluid increase. In the case of heat generating, the Nusselt number increased, while the Eckert number and Prandtl numbers increased. Also, the Nusselt number has larger values when the heat source parameter has near the constant temperature, and it has smaller values when the temperature varies. In the case of heat-absorbing, the Nusselt number decreased when the Eckert and Prandtl numbers increased. Also, the Nusselt number varies up and down while the heat absorbing parameter increases.

Manufacturing industries are facing dynamic challenges in today’s highly competitive world. In the recent past, integrating Industry 4.0 with the lean six sigma improvement methodologies has emerged as a popular approach for organizational excellence. The research aims to explore and analyze critical success factors of lean six sigma integrated Industry 4.0 (LSSI).

This research study explores and analyzes the critical success factors (CSFs) of LSSI. A three-phase study framework is employed. At first, the CSFs are identified through an extensive literature review and validated through experts’ feedback. Then, in the second phase, the initial list of CSFs is finalized using the fuzzy DELPHI technique. In the third phase, the cause-effect relationship among CFSs is established using the fuzzy DEMATEL technique.

A dyadic relationship among cause-and-effect category CSFs is established. Under the cause category, top management commitment toward integrating LSSI, systematic methodology for LSSI and organizational culture for adopting changes while adopting LSSI are found to be topmost CSFs. Also, under the effect category, organizational readiness toward LSSI and adaptability and agility are found to be the uppermost CSFs.

The study offers a framework to understand the significant CSFs for LSSI implementation. Insights from the study will help industry managers and practitioners to implement LSSI and achieve organizational excellence.

To the best of the authors’ knowledge, CSFs of LSSI are not much explored in the past by researchers. Findings will be of great value for professionals in developing long-term operations strategies.