Final Grade Research Articles

The effect of problem-based learning on improving problem-solving, self-directed learning, and critical thinking ability for the pharmacy students: A randomized controlled trial and meta-analysis.

This study aimed to comprehensively evaluate the effect of PBL on problem-solving, self-directed learning, and critical thinking ability of pharmaceutical students through a randomized controlled trial (RCT) and meta-analysis of RCTs. In 2021, 57 third-year pharmacy students from China Pharmaceutical University were randomly divided into a PBL group and a lecture-based learning (LBL) group. Mean scores were compared between the two groups for problem-solving, self-directed learning, communication skills, critical thinking, and final exam grades. Students' feedback on the implementation of PBL was also collected. A meta-analysis was subsequently performed. Two authors independently conducted a comprehensive search of two databases (PubMed and CNKI). Eligible studies with effective data were included and the valuable data were extracted for analysis. Quality of involved studies was assessed by the Cochrane Collaboration's tool. All analyses of statistics were conducted using the 'metafor' package in R software. The PBL group had significantly higher mean scores for problem-solving (8.43±1.56) and self-directed learning (7.39±1.19) than the LBL group (7.02±1.72 and 6.41±1.28, respectively). The PBL group also showed better communication skills (8.86±1.47) than the LBL group (7.68±1.89). The mean level of critical thinking was significantly higher in the PBL group than the LBL group (p = 0.02). The PBL group also had better final exam grades (79.86±1.38) compared to the LBL group (68.1±1.76). Student feedback on PBL implementation was positive. The outcome of subsequent meta-analysis including 8 eligible studies involved 1819 participants showed that the use of PBL significantly improved problem-solving ability (SMD = 1.12, 95% CI = 0.25-1.99) and PBL was also associated with better performance in self-directed learning (SMD = 1.55, 95% CI = 0.64-2.45). However, there was no significant difference in the final exam score in the PBL group compared to the LBL control group (SMD = 0.23, 95% CI = -0.08-0.53). This study found that PBL is an effective teaching method for pharmacy students.

Student Attendance, Study Activities, Major, and Midterm Grades as Predictors of Final Course Grades of Undergraduate and Graduate Plant Materials Courses during the Eras before and after COVID-19

Data were collected from four plant materials courses over the span of 20 years. Two classes were at the undergraduate level, Trees and Shrubs for Sustainable Built Environments (HORT 306) and Plants for Sustainable Landscapes (HORT 308), and two classes were at the graduate level, Plants for Landscape Design (HORT 608) and Plants for Landscape Design II (HORT 609). Data from these courses were analyzed to determine trends in student performance and benchmarks that might be associated with student success. Data included student enrollment, midterm course grades, final course grades, number of unexcused absences, student-reported study times for various activities, student major, student experience (class rank), whether the courses were required, and perceived difficulty levels of the courses. Trends in grade distributions were fairly stable until the last 3 to 4 years before COVID-19, when mean final grades and the frequencies of A or B grades increased. Midterm grades were strongly positively correlated with final course grades across majors in all four courses before COVID-19 (R2 = 0.90, 0.74, 0.72, and 0.54 for HORT 306, HORT 308, HORT 608, and HORT 609, respectively; P ≤ 0.001) and continued to be positively correlated after COVID-19. The number of unexcused absences was negatively significantly correlated with final course grades across majors (R2 = −0.69, −0.63, −0.21, and −0.45 for HORT 306, HORT 308, HORT 608, and HORT 609, respectively) before COVID-19 (P ≤ 0.001) and continued to be similarly correlated after COVID-19. Fewer reductions from midterm to final grades were observed for fall courses than for spring courses, particularly for seniors. Self-reported time spent studying all aspects of the courses was either not significantly correlated (P ≤ 0.05) or surprisingly slightly negatively correlated with the final course grades for all four courses. Perceptions of courses as moderately difficult (range, 7.0–8.0 out of 10.0) were remarkably stable overall but varied considerably by major (range, 5.0–8.3) and experience (range, 7.5 for seniors to 8.1 for freshman). More than 96% of enrollment in the graduate courses both before and after COVID-19 comprised Horticulture and Landscape Architecture majors, whereas undergraduate enrollment included a wide diversity of majors; however, the majority of those students were horticulture or landscape architecture majors. Biological science students or students who were architectural design majors were the top-performing students in both undergraduate courses, whereas undeclared majors, social science majors, and those in probationary major categories were among the lower-performing students in both undergraduate courses.

Update from 2010 (standard operating procedure): protocol for the 2024 British Society of Gastroenterology Guidelines on colorectal surveillance in inflammatory bowel disease

IntroductionThe evolving landscape of inflammatory bowel disease (IBD) necessitates refining colonoscopic surveillance guidelines. This study outlines methodology adopted by the British Society of Gastroenterology (BSG) Guideline Development Group (GDG) for...

Comparing the effects of blended learning and traditional instruction on “Medical Genetics and Embryonic Development” in undergraduate medical students: a randomized controlled trial

Abstract Objectives The Shanghai Jiao Tong University School of Medicine is at the forefront of educational innovation to enhance student learning outcomes. Herein, this study aims to evaluate the effectiveness of blended learning compared to traditional on-site instruction in the “Medical Genetics and Embryonic Development” curriculum. Methods A randomized trial was conducted involving 338 second-year clinical medicine students during the 2023–2024 academic year. The students were divided into two groups: one received blended learning and the other, on-site instruction. Students’ performance was evaluated using ongoing assessments together with mid-term and final exams. Results Blended learning led to higher overall final grades, with no significant difference in quiz performance, but better exam scores compared to traditional learning. At the level of higher-order learning skills, students in the blended learning group performed better in karyotyping. However, the traditional on-site group slightly outperformed the blended learning group in case-based learning scores. Ultimately, approximately 92 % of students were satisfied with the blended learning course. Conclusions Blended learning does show promise in improving the self-learning skill and overall learning outcomes of medical students. Future studies should focus on optimizing blended learning strategies and assessing their long-term impacts on clinical competencies.

Hubungan Lama Penggunaan Gadget dengan Prestasi Belajar Siswa SDN Harapan Mulya Parongpong

Prolonged use of gadgets can affect elementary school students' learning achievement. Objective: This study aims to determine the relationship between the length of gadget use and the learning achievement of class IV and V students at SDN Harapan Mulya Parongpong. Method: This research uses a quantitative correlation design with the Spearman rho statistical test. The questionnaire used to assess the length of gadget use consists of 7 questions. To assess student learning achievement, it is seen from the final semester grades. This research was conducted on class IV and V students of SDN Harapan Mulya Parongpong, totaling 58 respondents. The sampling method used was total sumpling. Results: Based on the results of data analysis, it is known that 72.4% of respondents used gadgets in the short category and the remaining 27.6% used gadgets in the long category. Based on statistical tests using the Spearman rho test, the p value = 0.307 > a value (0.05). Conclusion: The conclusion is that there is no relationship between the length of gadget use and the learning achievement of class IV and V students at SDN Harapan Mulya Parongpong. The suggestion given is that future researchers can look for other factors that can influence learning achievement.

How self-beliefs, values, and belonging change and relate with performance during introductory computer science

ABSTRACT Background and Context First-year university computer science courses can provide barriers or bridges into CS for students. Understanding student motivation within this context can enable instructors to better support learning. Objective To understand how student motivation changes across the semester and relates to course performance and student background. Method Students were surveyed four times during the course on their motivation for CS and for the course. Differences across groups and time were analyzed, as were links with performance. Findings Starting the course, women reported lower belonging and self-beliefs than men. Student value for CS declined during the course, whereas self-beliefs and belonging increased. Self-beliefs, course importance, and cost predicted final course grades; interest predicted fluctuations in grades across the semester. Implications Intervening to bolster course value and reduce perceptions of course cost may be most fruitful for increasing final grades; fostering interest may be best to improve engagement and within-course performance.

The application of the “PICO” teaching model in clinical research course for medical students

Abstract Objectives This study aimed to compare the effectiveness of the “PICO”, which stands for Patient, Intervention, Comparison, and Outcome, teaching model with traditional didactic teaching in clinical research education. Methods 90 eight-year clinical medicine students participated in the study, with 45 students randomly assigned to the PICO group and 45 students to the Didactic group. The PICO group received instruction using the “PICO” teaching model, while the Didactic group received instruction using traditional teaching methods. Final grades, course satisfaction, and clinical research competencies were assessed through questionnaires. Results The PICO group achieved higher final grades compared to the Didactic group. Within the PICO group, there was a positive correlation between theoretical knowledge scores and group study and mock defense scores. Students in the PICO group reported greater satisfaction with the course design, particularly in meeting their learning needs and improving clinical research thinking and skills. The PICO group also had higher self-assessment scores in knowledge integration, practical application, and research literacy. Conclusions The findings highlight the advantages of using the “PICO” teaching model in clinical research education. It leads to improved theoretical knowledge, higher satisfaction levels, and enhanced clinical research competence among medical undergraduates.

Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course

Educational data mining is valuable for uncovering latent relationships in educational settings, particularly for predicting students' academic performance. This study introduces an interpretable hybrid model, optimised through Tree-structured Parzen Estimation (TPE) and Support Vector Regression (SVR), to predict overall scores (OT) utilising five assignments and one examination mark as predictors. Neural Network-based, Tree-Based, Ensemble-Based, and Boosting-based methods are evaluated against the hybrid TPE-optimised SVR model for forecasting final examination grades among 492 students enrolled in the TPP7155 (General Science) course at the University of Southern Queensland, Australia, during the 2020-2021 academic year. Additionally, Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive explanations (SHAP) techniques are employed to elucidate the inner workings of these prediction models. The findings highlight the superior performance of the proposed model, exhibiting the lowest Root Mean Squared Error (RMSE) and Relative Root Mean Squared Error (RRMSE), as well as the highest Willmott's index (WI), Legates–McCabe index (LM), and Nash–Sutcliffe Efficiency (NS). With assignment and examination marks identified as pivotal predictors of OT. SHAP and LIME analyses reveal the examination score (ET) as the most influential feature, impacting predicted OT by an average of ±4.93. Conversely, Assignment 1 emerges as the least informative feature, contributing merely ±0.64 to OT predictions. This research underscores the efficacy of the proposed interpretable hybrid TPE-optimised SVR model in discerning relationships among continuous learning variables, thereby empowering educators with early intervention capabilities and enhancing their ability to anticipate student performance prior to course completion.

Investigating Trends in Academic Achievement: A Longitudinal Analysis of Grade Fluctuations among Students

Grades are essential in replicating global learning outcomes and indicating student success in higher education retention or declaration. The main objective of the study was to investigate trends in academic achievement among the students and analyze grade fluctuations among students at higher education levels. The study employed multilevel descriptive research to achieve its objectives. This study employed a balanced qualitative approach, integrating a multidisciplinary approach and qualitative data collection techniques to align with the research objectives. A longitudinal analysis was conducted to identify patterns among postgraduate students. The Administrative Directorate of Punjab recorded the data of students who successfully passed the CGPA and corresponding marks of the last five (2012-2016) BS 4-year courses in 37 departments of 3 state universities in Punjab. The collected data were analysed by applying percentage-wise analysis of the results of the students. The study reveals a trend in students' final grades favoring A and B grades over C grades. Over five sessions, final CGPAs increased among university students in three public universities. A longitudinal analysis showed improvements in A and B grades from 2012 to 2016 while decreasing C grades. The study suggests that upholding higher educational standards can restore grade reliability and demonstrate discriminating decision-making abilities. It recommends conducting the study at various colleges in Pakistan and sharing results to enhance analytical skills.

Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues

Raman spectroscopy (RS) is a promising tool for cancer diagnosis. In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. Recently, it has been demonstrated that RS can perform an accurate classification of chondrosarcoma tissues. Chondrosarcoma is a cancer of bones, that can occur in the soft tissues near the bones. It is normally characterized by three different malignant degrees and a benign counterpart, knows as enchondroma. In line with these findings, in this paper, we exploited ML algorithms to distinguish, as well as possible, between the three grades of chondrosarcoma and to distinguish between chondrosarcoma and enchondroma. We obtained a high level of accuracy of classification by analyzing a dataset composed of a relatively small number of Raman spectra, collected in a previous study by one of the authors of this paper. Such spectra were acquired from micrometric tissue sections with a confocal Raman microscope. We tested the classification performances of a support vector machine (SVM) and a random forest classifier (RFC), as representatives of ML algorithms, and two versions of the multi-layer perceptron (MLPC) as representatives of deep learning (DL). These models, especially RFC and MLPC, showed excellent classification performances, with accuracy reaching 99.7%. This outcome makes the aforementioned models a promising route for future improvements of diagnostic devices focused on detecting cancerous bone tissues. Alongside the diagnostic purpose, the aforementioned approach allowed us to identify characteristic molecules, i.e., amino acids, nucleic acids, and bioapatites, relevant for obtaining the final diagnostic response, through the use of a tool named by us Raman Band Identification (RBI). The method to evaluate RBI is the most important contribution of this paper, because RBI could represent a relevant parameter for the identification of biochemical processes on the basis of the tumor progression and associated malignant degree. In turn, the spectral bands highlighted by RBI could provide precious indicators in an attempt to restrict the spectral acquisition to specific Raman bands. This last objective could help to reduce the amount of experimental data needed to obtain an accurate final grading outcome, with a consequent reduction in the computational cost.

An Empirical Study on the Learning Outcomes of Vocational Students in A Smart Classroom

Background and Aim: Smart Classrooms, as a form of rich-media learning environments, were increasingly being implemented and utilized. This study aimed to investigate the impact of Smart Classrooms on learning outcomes by examining 133 first-year vocational students from a vocational college in Yunnan Province, China. The research focused on an applied writing course and compared Cognitive, Behavioral, and Affective learning outcomes between the SEEWO Smart Classroom and traditional classrooms. Materials and Methods: In this study, 133 current vocational students participated. The participants were divided into two groups: a control group and a treatment group. The control group was taught in a traditional classroom while the treatment group was taught in a Seewo Smart Classroom. After a 10-week applied writing course, the course was evaluated using the course evaluation scale that had been used in the college for many years. This evaluation explored cognitive learning outcomes, behavioral learning outcomes, and affective learning outcomes in terms of final grades, classroom behavioral performance, and student course scoring. Results: Students in Smart Classrooms showed significant improvement in final exam scores, enhancing Cognitive learning outcomes. Behavioral outcomes, including participation and attendance, also increased. Student feedback favored Smart Classrooms over traditional settings, with no significant impacts from gender, age, or admission methods observed. Conclusion: Smart Classrooms notably enhanced Cognitive and Behavioral learning outcomes, indicating improved student performance and engagement. Positive student feedback underscores their potential to enhance educational experiences and outcomes compared to traditional classrooms.

Enhancing academic outcomes through industry collaboration: our experience with integrating real-world projects into engineering courses

This research investigates the integration of industry projects and mentorship into academic curricula, aiming to enhance student learning and professional readiness. By incorporating real-world projects and pairing students with industry mentors, this approach seeks to provide a unique blend of theoretical knowledge and practical application. Utilizing a mixed-methods research design, the study captures both quantitative and qualitative data to assess the educational outcomes of this innovative model. Quantitative metrics include final grades, attendance rates, participation rates, placement rates, project grades, and professional skills ratings, while qualitative feedback is gathered from students, mentors, and faculty. The study is set against the backdrop of two courses that have been redesigned to include elements of industry collaboration. The findings are expected to shed light on the effectiveness of this approach in preparing students for the demands of the modern workforce, offering insights into how industry mentorship and project-based learning can enhance academic curricula and better equip students for their future careers.

Exploring Intratumoral Budding in Colorectal Cancer Using Computational Pathology: A Biopsy-Based Evaluation

Owing to insufficient evidence, tumor budding (TB) is not currently evaluated in colorectal cancer (CRC) biopsies. This study investigates TB in CRC by establishing the value of intratumoral budding (ITB) in resection specimens and assessing the feasibility and clinical value of TB in biopsies. TB was assessed using an algorithm in all cases. In a test cohort of 555 primarily surgically treated CRC patients, we assessed the prognostic impact of ITB compared with peritumoral budding (PTB). The distribution of ITB in the uppermost 5 mm of resection specimens was analyzed to validate TB counting in biopsies. We further validated the prognostic and predictive impact of TB in biopsies of 285 rectal cancer patients, focusing on overall survival and response to neoadjuvant therapy. High-grade TB, whether intratumoral or peritumoral and in biopsies or resections, was associated with advanced pathological stage, lymphatic invasion, infiltrative tumor border, and poor overall survival in the test cohort. Superficial ITBs (0-3 mm from the lumen) accurately predicted the final TB grade based on PTB in 87% of tumors, with 87% of tumors having at least 1 superficial ITB hotspot. ITB (hazard ratio, 3.5; 95% CI, 1.1-10.8) was an independent predictor of overall survival, unlike PTB. In the validation cohort, TB presence in biopsies significantly reduced the likelihood of achieving a pathological complete response (odds ratio, 0.3; 95% CI, 0.1-0.7; P = .007). ITB is as prognostic as PTB, and evaluating both can improve risk stratification in CRC. TB assessment in biopsies can identify poor prognosis and predict response to neoadjuvant therapy.

Strengthening Online Psychology Students’ Sense of Belonging with Social Annotation: An Experimental Study

Sense of belonging is associated with postsecondary student success outcomes and has largely been studied within face-to-face course contexts. The increasing demand for online courses after the COVID-19 pandemic necessitates identifying ways instructors can foster belonging in their online courses. This study experimentally tested the effect of using social annotation on students’ sense of belonging in asynchronous online courses. Students in two psychology courses ( N = 44) were randomly assigned to complete annotation assignments individually (control) or in groups using a social annotation platform (treatment). Students completed a course-level sense of belonging measure at the end of their courses and indicated their perceptions of social annotation. Sense of belonging was significantly higher in the social annotation condition, particularly for the introductory-level psychology course, and students reported positive perceptions of social annotation. Course performance did not differ between annotation conditions, and sense of belonging was not associated with final grades. These findings document the viability of social annotation as an evidence-based tool for promoting a sense of belonging in online psychology courses.

Speaking Skill Assessment Instrument Validity: An Investigation into Instructors’ Perceptions

To EFL learners, speaking the target language with satisfactory fluency is a highly significant aspect of learning the language. Assessment of learners’ progress and achievement in speaking skills is equally significant to identify the course of further action, whether it is for feedback, placement, or grading. At the English Language Institute (ELI), King Abdulaziz University in Saudi Arabia, learners’ proficiency in spoken English is assessed for end-of-the-term grading using Interview and Speaking Project as test instruments. The Interview questions are random, while the Speaking Project involves collection of materials on a chosen topic and report writing, followed by presentation and question-answer session. An empirical research study was conducted to examine ELI teachers’ perceptions on the reliability and validity of the two assessment instruments to accurately measure learners’ proficiency in speaking skill and meeting the requirements to reflect the learning outcomes designed for the speaking English course. The data were collected through a survey questionnaire and a structured interview. The surveyed instructors were also encouraged to express their opinions on the role of formative assessment in determining learners’ final grades in English speaking skill.

Cangrelor use in ticagrelor-loaded ST-elevation myocardial infarction patients with high residual platelet reactivity: a randomized controlled trial

Abstract Background Despite the use of potent P2Y12 inhibitor, many patients still present with high platelet reactivity (HPR) at the time of primary percutaneous coronary intervention (PCI). HPR is associated with impaired myocardial reperfusion and the subsequent poor outcome. Purpose We sought to determine the impact of Cangrelor -a rapid and potent intravenous P2Y12 inhibitor- on myocardial reperfusion in patients with HPR admitted for primary PCI in a randomized trial. Methods Patients pre-treated with ticagrelor and aspirin with residual HPR (baseline platelet reactivity unit (PRU) > 208) were randomly assigned in a 1:1 ratio to receive cangrelor (experimental group) or not (control group) just before PCI. The primary endpoint was optimal myocardial reperfusion defined as a final myocardial blush grade (MBG) 3 assessed by an independent core laboratory. Results After screening of 128 patients, a total of 60 patients were with HPR were enrolled and randomized. The ticagrelor loading dose to PRU measurement times were 83 ± 32 and 90 ± 47 minutes in the experimental and control groups, respectively. Baseline PRU were 245 ± 30 and 252 ± 35 in the experimental and standard group, respectively. A final MBG 3 was observed in 21/30 (55%) and 17/30 (45%) the experimental and standard groups (p=0.29). A final TIMI flow grade 3 was observed in 30/30 (100%) and 27/30 (90%) the experimental and standard groups (p=0.24). Peak troponin levels after PCI were 51381 ± 50047 and 51078 ± 63960 ng/L (p=0.98) in the experimental and standard group, respectively. At the end of the PCI, control PRU were 36 ± 57 and 198 ± 107 (p<0.0001) in the experimental and standard group, respectively. One patient of the experimental group presented an in-hospital major bleeding (BARC 3). Conclusion In ticagrelor-loaded STEMI patients with residual HPR at the time of PCI, cangrelor use was associated with a more effective platelet inhibition but failed to significantly improve the rates of optimal final myocardial blush grades.

Prediction of Final Grade of Advanced Mathematics based on BP Neural Network

In recent years, with the continuous expansion of college enrollment, the number of students is increasing year by year, so the scale of classroom teaching is also getting larger and larger, so that it is difficult for teachers to track and understand the learning situation of each student, which affects the quality of teaching to a certain extent. At the same time, every year, a certain number of students in colleges and universities fail the exam, repeat the grade, or even drop out. If these problems cannot be solved in time, they will seriously affect the psychological health and future development of students, and also affect the employment rate of graduates, and thus affect the development of schools. How to predict the situation of students, so that students in the study of trouble, hesitation, timely interference, so that students successfully complete the university study life. Through the analysis of the failed students, it is found that about 80% of the failed students are advanced mathematics. Therefore, this paper will use the machine learning technology based on BP neural network to analyze the scores of senior students in the final exam of advanced mathematics. According to the different scores, the scores will be divided into four categories: excellent, good, medium and failed. Through the establishment of the grade prediction model, the paper predicts the grade of the college students in the final exam of higher mathematics, and then gives the students learning guidance.

Investigating different answers to one Euclidean geometry problem: a case study of grade 12 mathematics examinations in South African secondary schools

This article investigates the tendency for distinctly different answers to a problem in Euclidean Geometry as shown in some grade 12 examination memos for secondary schools in South Africa. The study is based on a qualitative analysis of some examples in the final grade 12 examinations where solutions to specific problems are given in distinctly different forms. Both primary and secondary data were applied to the investigation. The secondary data was the literature review of studies on the problems students come across when solving Euclidean geometry problems, and the primary data was acquired from the example of a memorandum where distinctly different answers were given to the solution of a problem. The approach to the problem-solution presentation using distinctly different answers is appreciated as it broadens the understanding of problem-solving. However, does this approach not leave the markers ignorant of other solution options, thus disadvantaging the learners and denying them a pass?

Using Nobel Prize case-based learning in Medical Immunology to cultivate critical thinking dispositions for medical undergraduates

BackgroundCritical thinking has been regarded as an essential skill for college students, which is especially imperative for medical students to possess the ability to have in-depth insight into complex clinical situations. Medical Immunology is an overarching principle connecting multiple medical subjects, which emphasizes that immunity is both beneficial and harmful to the host, thus putting higher demands on students’ critical thinking. The utilization of Nobel Prize stories has been cited as a thematic framework for classroom teaching of other courses, showing numerous educational benefits. Therefore, this study rejuvenated a case-based teaching approach by creating and introducing a vibrant material library centered on numerous iconic Nobel Prize cases in Medical Immunology and evaluating its effects on the critical thinking of medical students.MethodsA total of 70 second-year medical undergraduates from the Beijing University of Chinese Medicine were divided into a control group and an experimental group of 35 cases each. Throughout the semester, the control received the traditional teaching method, and the experimental group adopted case-based teaching based on the Nobel prize-centered material library. The process of teaching design and practice was described using “Antitoxin and immunoserum therapy” as a classical example. A unified assessment of the critical thinking dispositions of participants was conducted at the beginning and end of the semester using the Critical Thinking Disposition Inventory-Chinese Version (CTDI-CV).ResultsIntra-group longitudinal comparisons and inter-group parallel evaluations indicated that, compared with the conventional teaching approach, Nobel Prize case-based learning induced a statistically significant increase in the overall score of the CTDI-CV, as well as the scores within the subdimensions of truth-seeking, analyticity, and maturity in judgment (p < 0.05). Pearson correlation analysis further indicated a positive correlation between the total score of the CTDI-CV and the final grade (p < 0.05), which emphasized the crucial role of critical thinking dispositions in academic achievement.ConclusionThe case-based classroom teaching centered on Nobel Prize cases for Medical Immunology can effectively improve the critical thinking dispositions of medical undergraduates, which contributes to cultivating high-level medical and healthcare talents with excellent comprehensive quality in the new era.

Family climate and academic performance in nursing students of a Higher Technological University Institute of Ecuador

Family climate (FC) was related to academic performance (AR) of university nursing students. The sample consisted of 172 students of a Higher Technological University Institution of Ecuador. The approach was quantitative, descriptive-correlational-transectional. A survey was used, and a FF-SIL questionnaire of family functionality, proposed by Ortega Veitía et al. (1999), composed of 14 items. The instrument is used to determine the functionality between existing relationships of each of the family members. Academic performance was collected from the students' final grades in their midterm grades, added to their final average. Jamovi 2.5.6 software was used. Frequencies and percentages were calculated by levels. The Test-Spearman test was used for correlation. There was a high percentage of students with moderately functional and functional families. However, 27.7% showed a dysfunctional or severely dysfunctional family climate. The group obtained an average academic performance of 7.49 points. A significant correlation was obtained between the variable’s family climate and academic performance. Spearman's Rho was also applied to see the relationship between family climate and the father's level of education, obtaining a significant but negative correlation; but no correlation was found for the relationship between family climate and the mother's level of education. Family climate is related to academic performance, although other intervening factors cannot be omitted. Family climate is affected by the father's level of education.