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This article introduces a model for accurately predicting students’ final grades in the CS1 course by utilizing their grades from the first half of the course. The methodology includes three phases: training, testing, and validation, employing four regression algorithms: AdaBoost, Random Forest, Support Vector Regression (SVR), and XGBoost. Notably, the SVR algorithm outperformed the others, achieving an impressive R-squared ( R 2 ) value ranging from 72% to 91%. The discussion section focuses on four crucial aspects: the selection of data features and the percentage of course grades used for training, the comparison between predicted and actual values to demonstrate reliability, and the model’s performance compared to existing literature models, highlighting its effectiveness.

In this study, we investigated the within-field distribution of sweet corn insect pests in relation to adjacent habitats and determined the level and specific causes of defective kernels affecting the quality of the final product at the processing cannery. Sap beetles [primarily Carpophilus lugubris (Murray, 1864) (Coleoptera: Nitidulidae)] and stink bugs [primarily Euschistus servus (Say) ((Heteroptera: Pentatomidae)] infested 27.6% and 73.6% of the fields, respectively. Densities of stink bugs were highest along field edges adjacent to wheat, soybean, vegetable crops, and woodlots. Levels of kernel injury were consistently higher in truckloads of ears harvested first from the outer rows. Earworm damage was confined to the ear tip and had no measurable impact on the quality of the final product. Sap beetles and blemished kernels were the major causes of defective kernels in the cannery, even though stink bugs were more abundant in the fields. Defective kernels were more positively related to physiological blemishes than to other causal factors. For all fields, defective kernel levels averaged less than 1%, resulting in excellent quality of the processed product throughout the entire season. Results provided a better understanding of the quality control issues, resulting in practical implications for improvements in field monitoring and decision-making in the cannery to minimize grading problems.

Student success rate is a significant indicator of the quality of the educational services offered at higher education institutions (HEIs). It allows students to make their plans to achieve the set goals and helps teachers to identify the at-risk students and make timely interventions. University decision-makers need reliable data on student success rates to formulate specific and coherent decisions to improve students’ academic performance. In recent years, EDM has become an effective tool for exploring data from student activities to predict their final grades. This study presents a case study for predicting the students’ final grades based on their activities in Moodle Learning Management System (LMS) and attendance in online lectures conducted via Zoom by applying statistical and machine learning techniques. The data set consists of the final grades for 105 students who study Object-Oriented Programming at the University of Plovdiv during the 2021–2022 year, data for their activities in the online course (7057 records), and attendance to lectures (738). The predictions are based on 46 attributes. The Chi-square test is utilized to assess the association between students’ final grades and event context (lectures, source code, exercise, and assignment) and the relationships between attendance at lectures and final results. The logistic regression model is utilized to assess the actual impact of event context on “Fail” students in a multivariate setup. Four machine learning algorithms (Random Forest, XGBoost, KNN, and SVM) are applied using 70% of training data and 30% of test data to predict the students’ final grades. Five-fold cross validation was also utilized. The results show correlations between the students’ final grades and their activity in the online course and between students’ final grades and attendance at lectures. All applied machine learning algorithms performed moderately well predicting the students’ final results, as the Random Forest algorithm obtained the highest prediction accuracy—78%. The findings of the study clearly show that the Random Forest algorithm may be used to predict which students will fail after eight weeks. Such data-driven predictions are significant for teachers and decision-makers and allow them to take measures to reduce the number of failed students and identify which types of learning resources or student activities are better predictors of the student’s academic performance.

To verify the effect of the interactive teaching model in English teaching, the author proposes the application of the multiple regression model in the interactive teaching of English classrooms. Authors, by collecting data on each relevant factor, a multiple regression system with regression simulation computing capability was designed and implemented, and the model was solved and analyzed based on Matlab software. Experimental results show that: According to the multiple regression model, the average grade is 1.3732, which shows that the interactive teaching effect is obvious. Conclusion: The application of the multiple regression model in English classroom interactive teaching is of great significance to the reform of college English teaching.

This study compared the differences between students entering university directly from high school vs. those transferring from other higher education institutions for the variables of the academic self-control model (general resourcefulness, academic resourcefulness, academic self-efficacy, preparedness, failure attributions, and university adaptation). The goals of the research were to test the following: (1) the full academic self-control model using a large sample of undergraduate students to predict university adaptation and final grades; (2) if the pathways of association implied by the model are equally predictive regardless of whether students are direct entry, university transfer, or college transfer; and (3) if the means of the variables differed among these three groups. Results replicated previous studies showing that, for the entire sample, general resourcefulness, preparedness, explanatory style for failure, and academic self-efficacy were strongly predictive of academic resourcefulness, which, in turn, was strongly associated with university adaptation and grade. Moreover, the indirect and direct pathways of the model were found to be equivalent for the three student groups. Comparisons of the groups’ means for the psychological variables revealed the university transfer group to have the most favourable scores followed by the college transfer group. The findings suggest that both college and university transfer students bring valuable skills to undergraduate programs and the keys to their university adaptation and academic achievement are the same as for direct entry students.

School coexistence is a fundamental aspect for good academic performance. The objective of the study was to identify school coexistence indices, and to analyze differences in academic performance according to these indices in students from public schools in the province of Biobío, Chile. This cross-sectional study involved 730 children (53.8% boys; 12 ± 1.2 years). School coexistence indices as a quality of interpersonal relationships between school bodies, the perception of violence and aggressiveness from a gender perspective, and the perception of levels of safety and unsafety in different school areas as well as academic performance through accumulated final grades (AFG) and grade point averages (GPA) were measured. A total of 40.9% and 41.3% of schoolchildren agreed or strongly agreed that stronger students are violent toward weaker students and boys are violent toward one another, respectively. The school areas most classified as unsafe or very unsafe were the restrooms (20.4%), followed by the playgrounds (10%), and the gym and fields (9.5%). Schoolchildren who classified the relationships within the school bodies as bad, or very bad, presented significantly lower AFG in subjects such as math, language (Spanish), and physical education and health as well as GPA. In the same line, those who perceived greater violence and aggressiveness among peers and higher insecurity in different school areas presented significantly poorer academic performance. In conclusion, students perceived violence and aggressiveness among themselves, and the school areas perceived as unsafe were identified. Furthermore, students who perceived poorer school coexistence indices presented a weaker academic performance.

The European Higher Education Area (EHEA) university learning framework, structured around the European Credit Transfer and Accumulation System (ECTS), integrates classroom hours with independent, non-classroom workloads outside the university, where students engage in self-directed learning. This study aimed to develop a standardized protocol to monitor and quantify non-presential study hours to identify and adjust anomalous workload values. Over a two-year period, data were gathered from two distinct student groups (local Spanish students and international exchange students) enrolled in the same fourth-year architecture course at the University of Alicante. The data analysis allowed for an exploration of correlations among three key variables: non-presential study hours, final grades, and student satisfaction (self-assessed course perceptions). The results reveal a direct proportional relationship among these variables, whereby an increase in weekly study hours corresponds with both higher final grades and improved student satisfaction with the course.

El artículo presenta los resultados de una investigación cuya finalidad es conocer la autopercepción de dominio que tienen los estudiantes de las competencias investigativas en el momento de la realización del Trabajo de Fin de Grado. El estudio se contextualiza en el grado de Pedagogía de la Universidad de Barcelona, y en él participaron 109 estudiantes (60,15% del alumnado matriculado), que contestaron un cuestionario. El enfoque adoptado para las dimensiones del cuestionario fue el de la competencia investigativa como conjunto de competencias específicas del acto de investigar, que siguen la lógica del método científico y su proceso. Los resultados, coincidentes parcialmente con los de otras investigaciones de otros contextos universitarios, muestran niveles medios altos de percepción en general de las competencias investigativas, siendo mayor en escritura  y técnicas  de recogida y análisis cualitativo y menor en búsquedas bibliográficas especializadas, citación y técnicas cuantitativas, aspectos de especial relevancia en el ámbito académico.

Mathematical knowledge is assessed at school, in national assessments of knowledge and as part of international research studies. Different knowledge assessments have distinct aims, but they should nevertheless be broadly comparable. In recent decades, Slovenian primary schools have seen a major increase in the share of students with above-average achievements. However, a comparison of final grades in Grade 9 of primary school with results from the national assessment of knowledge indicates the potentially subjective nature of school grades in mathematics, which would seem to question their purpose. The national assessment of knowledge, whose results correspond with the results of international studies (TIMSS), could be used to adjust knowledge assessment criteria and gradually ensure that knowledge assessment becomes fairer and more objective.

This article builds on a study set within the Swedish educational system and focuses on lower secondary teachers’ use of national test results when awarding final grades of English as a foreign language (EFL). In Sweden, teachers are entrusted with the responsibility of assessing their own students’ competences as well as assigning grades. To support them, there are compulsory national tests to be used as important advisory tools; however, they are not exams in a strict decisive sense. After a brief contextualization and conceptualization regarding language education in Sweden, including the assessment, teachers’ somewhat contradictory perceptions and use of results from the national EFL test for 11–12-year-olds are described and discussed. Data emanate from large-scale teacher questionnaires conducted for three years (2013, 2016 and 2019), which are analyzed from quantitative as well as qualitative angles. Results indicate that a number of teachers struggle with factors related to the language construct as well as to the educational context and consequences at individual, pedagogical and structural levels. This is discussed from various angles, linked not least to the policy, curriculum and other frame factors. Furthermore, the need for further research in direct collaboration with teachers is emphasized.