Micro/nanoscale fabricated devices have widely been used in modern technology and bioengineering as they offer excellent heat transfer. Removal of excess heat, coolant selection, rapid mixing, and handling proportion of colloidal metallic nanogranules in the base fluid are the main challenges in micro/nanofluidic systems. To address these problems, the primary motivation of the intended mathematical flow problem is to investigate the thermal and flow aspects of blood-based ternary nanofluid in the presence of inclined magnetic field and thermal radiations through a microfluidic pump with elastic walls. Further, the pump inner surface is smeared with fabricated cilia. The embedded cilia blow in coordination to start metachronal travelling waves along the pump wall that assist homogenous mixing and manipulation. The entire analysis is conducted in moving frame and simplified under lubrication and Rosseland approximations. Numerical solution of various flow and thermal entities are computed via the shooting method and plotted for different values of the parameters of interest. A comparative glimpse allows us to conclude that the trimetallic blood-based nanofluid exhibits elevated heat transfer rate by 12–18%, bi-metallic by about 11–12%, and mono nanofluid by about 6% compared to the conventional blood model. The study also determines that the prolonged cilia commence augmentation in flowrate and pressure-gradient around the pump deep portion. Furthermore, the radiated ternary liquid under fragile magnetic field effects may contribute to the cooling process by eliminating unnecessary heat from the system. It is also noticed that around the ciliated wall, the heat transfer irreversibility effects are appreciable over the fluid frictional irreversibility.

No thermal process, even the biological systems, can escape from the long arms of the second law. All living things preserve entropy since they obtain energy from the nutrition they consume and gain order by producing disorder. The entropy generation in a biological and thermally isolated system is the main subject of current investigation. The aim is to examine the entropy generation during the convective transport of a ciliated nano-liquid in a micro-channel under the effect of a uniform magnetic field. Joint effects of electroosmosis and thermal radiation are also brought into consideration. To attain mathematical simplicity, the governing equations are transformed to wave frame where the inertial parts of the transport equations are dropped with the use of a long-wavelength approximation. This finally produces the governing equations in the form of ordinary differential equations which are solved numerically by a shooting technique. The analysis reports that the cilia motion contributes to enhance the flow and heat transfer phenomena. An enhancement in the flow is observed near the channel surface for higher cilia length and for smaller values of the electroosmotic parameter. The entropy generation in the ciliated channel is observed to be lessened by intensifying the thermal radiation and decreasing the Ohmic heating. The extended and flexible cilia structure contributes to augment the volumetric flow rate and to drop the total entropy generation in the channel.

The extent to which grades in the first few weeks of a course can predict overall performance can be quite valuable in identifying at-risk students, informing interventions for such students, and offering valuable feedback to educators on the impact of instruction on learning. Yet, research on the validity of such predictions that are made by machine learning algorithms is scarce at best. The present research examined two interrelated questions: To what extent can educators rely on early performance to predict students’ poor course grades at the end of the semester? Are predictions sensitive to the mode of instruction adopted (online versus face-to-face) and the course taught by the educator? In our research, we selected a sample of courses that were representative of the general education curriculum to ensure the inclusion of students from a variety of academic majors. The grades on the first test and assignment (early formative assessment measures) were used to identify students whose course performance at the end of the semester would be considered poor. Overall, the predictive validity of the early assessment measures was found to be meager, particularly so for online courses. However, exceptions were uncovered, each reflecting a particular combination of instructional mode and course. These findings suggest that changes to some of the currently used formative assessment measures are warranted to enhance their sensitivity to course demands and thus their usefulness to both students and instructors as feedback tools. The feasibility of a grade prediction application in general education courses, which critically depends on the accuracy of such tools, is discussed, including the challenges and potential benefits.

The present research examines the contribution of individual differences in chronotype and self-efficacy to the math performance of male and female students in STEM and no-STEM majors. Questionnaires assessing the selected individual differences were distributed to students of Middle Eastern descent enrolled in math courses of the general education curriculum. Summative assessment indices were used to measure performance comprehensively across the entire semester (course grades) and as a one-time occurrence (final test grades). The contribution of morningness and self-efficacy to both course and test performance of STEM students was sensitive to the interaction of gender and major. Instead, neither factor contributed to no-STEM students’ course and test performance. These findings were used to plan improvements in the instruction and advising of students in STEM majors, thereby complying with a key tenet of action research.

A higher education that can be defined as sustainable ensures the acquisition of competencies that are necessary to address the current and future needs of the society in which it exists. Because math competencies are an essential component of college students’ academic and professional success, poor performance outcomes are particularly problematic in the context of an education that aims to be sustainable. This research sought to identify dispositions that are predictive of math performance in the post-pandemic world to develop an early detection system for at-risk students of an understudied population (college students of Middle Eastern descent from Saudi Arabia). It specifically targeted female and male students in STEM or non-STEM majors who were enrolled in a math course of the general education curriculum. During the second semester of a return to entirely face-to-face instruction, their self-efficacy, math learning anxiety, math evaluation anxiety, and preference for morning or evening study activities were surveyed. In the post-pandemic world of this understudied population, the math performance of STEM male and female students was hurt by concerns about learning math. The math performance of non-STEM male students benefited from self-efficacy, whereas that of non-STEM female students was unaffected by any of the dispositions surveyed in the present investigation. These findings suggest that individual difference measures can inform early interventions intended to address performance deficiencies in selected groups of students with the overreaching goal of ensuring a sustainable education for all.

The present research compares the effects of mentally recreating the experience of realizing that a desirable goal had been achieved (outcome simulation exercise) with those of mentally recreating the actions that might lead to the desirable goal (process simulation exercise). It asked whether the performance benefits of process simulations over outcome simulations, which have been reported in students enrolled in face-to-face classes, would generalize to an online environment. The process simulation exercise was expected to foster attention to the antecedents of good grades, thereby improving class performance relative to the outcome simulation exercise which was intended to be merely motivational. College students from the Middle East, who were taking classes online due to the COVID-19 pandemic, participated. Type of simulation impacted students’ performance on assignments, but differently depending on the timing of the assessment. It did not influence behavioral engagement, midterm test performance, or predictions of performance before or after the test. Instead, process simulation enhanced students’ confidence in their predictions. These findings suggest that process simulation exercises may be useful learning props for activities that challenge students’ problem-solving skills (e.g., assignments) rather than engage well-practiced study habits (e.g., tests).