Final Grades Of Students Research Articles

Evaluation of Self-Directed Learning Readiness Among Medical Students in Sharjah, the United Arab Emirates.

Self-directed learning (SDL) has become an essential learning principle in medical curricula and a requirement of the professional accreditation standards. It has been advocated that SDL is an effective learning strategy for medical students to develop competence in knowledge acquisition and in promoting life-long learning. Although it has been presumed that problem-based learning (PBL) improves the learner's SDL readiness (SDLR), its effects arestill debatable. This study aimed to investigate the readiness for self-directed learning readiness (SDLR) among undergraduate medical students in problem-based learning (PBL) and non-PBL programs, examining the influence of gender, academic performance, and program year level. This cross-sectional study used a validated instrument, the SDLR instrument (SDLRI), to assess self-directed learning readiness. It consists of 20 items classified into the following four domains: learning motivation (six items), planning and implementation (six items), self-monitoring (four items), and interpersonal communication (four items) based upon a five-point Likert scale. Additionally, demographic data like academic year level, gender, and the student's final grade from the previous semester were collected. Questionnaires were administered to students in their first, third, and fifth (final) academic year across three different medical colleges in the United Arab Emirates (UAE). One of these colleges adopts a hybrid problem-based learning (PBL) approach, while the other two follow non-PBL programs. A total of 386 responses were collected, with 200 students (51.8%) from the hybrid PBL program and 186 students (48.2%) from the non-PBL programs. The overall mean SDLR score was 59.0±18.2. In both programs, the high-achieving students scored SDLR of 64.7±18.0 (n=112), which was statistically significantly higher than the eight medium- and low-achieving students, 57.8±17.2 (n=224). However, the overall SDLR score showed no significant difference in gender or between PBL and non-PBL programs. Although the SDLR increased as PBL students advanced in the program, it decreased in the non-PBL curricula. However, this difference was not statistically significant. The high-achieving students displayed a higher level of SDLR than 10 of the medium- or low-achieving students, regardless of the educational program. This highlights the essential effect of the intrinsic factor for undertaking SDL and implies that students should initiate the process. Moreover, enhancing personal development and SDL educational practices might be effective in improving SDLR if partly implemented in medical programs.

The Impact of Online Learning during the Covid-19 Pandemic on Academic Outcomes for Newly-Struggling High School Students

The Covid-19 pandemic caused worldwide closures of schools resulting in a sudden shift to online instruction for students. For many students, this shift caused a decrease in academic performance. This study was conducted to explore whether particular demographic variables were associated with decreased academic outcomes for newly-struggling students as well as to determine if there was a relationship between these demographic variables and the frequency of D and F final course grades. Student final course grades were collected from a Midwestern United States high school’s student information system. The data were used to compare academic performance between the fall semester of 2019 during in-person learning and the fall semester of 2020 when the Covid-19 pandemic resulted in school closures and a shift to online learning. Logistic regression analysis was used to answer each of the research questions. The findings from this study suggest that there was a significant relationship between low household income status and status as a newly-struggling student. Additionally this study suggests a significant relationship between low household income status and an increased frequency of D and F final course grades between semesters when compared with sample group peers. Conversely, while special education students did see an increase in frequency of D and F final course grades between semesters it was a significantly lower increase between semesters than their newly-struggling sample group peers.

Perceived Enablers of and Barriers to Serious Game as Oral Histology Learning Strategy for Undergraduate Dental Students.

Previously, we reported the serious game HistoRM as an innovative learning approach for an oral histology course. This study aimed to examine the impact of HistoRM on summative assessment and the enablers and barriers factors affecting HistoRM as an interactive learning strategy in an oral histology course. A crossover randomized controlled trial was performed. Study participants were first-year dental students at the Universitas Indonesia. The average final grades of students who participated in HistoRM serious game were significantly higher than those of students who did not participate in this trial (p < 0.001). Positive responses of HistoRM were observed in the learning content, games and learning experience domains. The enabler factors most recognized by the students were the game method, which helped students to understand the learning materials; the immediate feedback provided following each gameplay; as well as the fun and interesting gameplay. The barrier factors most recognized by the students were some challenges of the gameplay, which resulted in a longer time needed to study. While the HistoRM serious game can stimulate student motivation and engagement in learning oral histology, overcoming the barriers is essential for the implementation of serious games as a complementary learning approach in the dental curriculum.

Сотрудничество психологов, педагогов и родителей в сопровождении школьников при подготовке к выпускным экзаменам

&lt;p style="text-align: justify;"&gt;One of the functions of the psychological service at school is psychological support of graduates in preparation for examination. The results of the survey of students showed that one of the reasons for anxiety and even fear is the topic of the period of preparation for examination and the examination process itself. Together with subject teachers, programs were created, the essence of which is to take into account the psychological aspects of time planning and self-regulation, as well as the content of the preparation plans and stages of work with examination tasks for each of the academic disciplines to be passed by graduates. Another no less &amp;ldquo;problematic&amp;rdquo; topic for graduates is the nature of the attitude of significant adults to the way graduates prepare for examination. Within the framework of psychological and pedagogical support of schoolchildren in preparation for the external examination, meetings of psychologist with parents of graduates were held, which were also conducted with the use of interactive methods. Such cooperation of subject teachers, school psychologist and parents has received positive feedback from students of final grades after testing the proposed recommendations on trial tests.&lt;/p&gt;

SOCIODEMOGRAPHIC DIFFERENCES IN PREVALENCE, INTENSITY AND PSYCHOSOCIAL CONSEQUENCES OF ADOLESCENT GAMBLING IN MOSTAR

Introduction: Adolescents are a risk group to develop problem gambling considering growing up in the era of widespread gambling activities, what is confirmed by the increasing prevalence of gambling among young people. Their gambling activities can develop into pathological gambling with numerous and harmful psychosocial consequences over time and with intensification.Objective: The objective of this study is to determine the prevalence of different gambling activities (type and intensity), the rate of problematic gamblers and the psychosocial consequences of adolescent gambling in Mostar.Subjects and methods: A total of 402 participants (198 males and 204 females) -students of final grades of high schools in Mostar participated in the study. Average age of participants was 17. Data was collected by filling out questionnaires in which the Gambling Activities Questionnaire and Canadian Adolescent Gambling Inventory were applied.Results: Significant differences were found in the intensity of gambling, harmful psychosocial consequences and the risk of gambling in adolescents in regard to gender and school -young men from the Electrical Engineering School and Secondary Transportation School gamble more intensively and have more psychosocial consequences of gambling and show a higher risk for the development of problem gambling compared to girls and students who attend Gymnasium.Conclusion: This study confirms a relatively high prevalence of problem gambling among adolescents in Mostar and the differences in intensity, risks of gambling and harmful psychosocial consequences with regard to gender, school and age, which confirms the importance of establishing and implementing preventive programs.Keywords: gambling, adolescents, gambling intensity, gambling prevalence, psychosocial consequences

Improving Students’ Knowledge and Engagement in Immunology Course Using Video-Based Learning and Concept Mapping in Modified E-tivities

E-tivities were implemented in the online class of Immunology at the Department of Pharmacy UII using video-based learning (VBL) and concept mapping exercises to enhance student motivation and knowledge. The class measurement method was used by comparing the previous academic year's lecture evaluation and outcomes (the 2021 semester without video and concept mapping) and the 2022 semester (with E-tivities using VBL and concept mapping). According to the evaluation results, the combination of learning methods with learning video and concept mapping increased the student's interest and enthusiasm for learning. Furthermore, the student's mastery of the material increased from 8% to 41%, resulting in an increase in the student's final grade. The combination of video-based learning and concept mapping increased student motivation and knowledge

Hubungan Penggunaan Gadget Dan Stres Dengan Insomnia Pada Remaja Kelas Akhir Di SMK Kesehatan Logos Kabupaten Bogor Tahun 2023

Sleep is something that must be fulfilled, if it it fulfilled it will cause disturbances in a person's biology and psychology. Many factors influence insomnia, including disease, fatigue, environment, stress, medication, diet, and alcohol and nicotine. The use of gadgets can also affect insomnia because addiction to bluelight gadgets will shift your sleep rhythm, causing insomnia. This research aims to determine the relationship between intensity of gadget and stress with insomnia in final class adolescents at Logos Health Vocational School. The research method used is Cross-Sectional. involving 99 final grade students of Logos Health Vocational School. By using the Chi-Square Statistical Test and the results of this research, the P value = 0.001, which means that the value is &lt;0.05. Conclusion: There is a relationship between the intensity of gadget and stress and insomnia in final class adolescents at Logos Health Vocational School, Kabupaten Bogor in 2023. The results of this research are expected to provide benefits for parents and schools in efforts to prevent the occurrence of insomnia, as well as handling stress and use. gadgets.

Analysis of Student Behavior Based on the History of Learning Activities in the Learning Management System Using the Pearson Correlation Method

The purpose of this study is to identify student learning behavior in online learning and to determine the relationship between student learning behavior and learning achievement based on learning history data (Learning logs) on the Learning Management System (LMS), including the performance of assignments and quizzes, utilization interaction features (forums and chat), as well as active access to learning resources (files and URLs). Pearson Correlation method is used to analyze the level of relationship between learning behavior and students’ achievement. The research object is 105 students at Muhammadiyah University of Enrekang who programmed introductory information technology (PTI) courses from 5 different classes but taught by the same lecturer. The total number of processed activity histories (after data preprocessing) is 6500 records, while the total number of logs before data preprocessing is 19386 records. Correlation analysis linking student behavior to student learning achievement is quite strong and unidirectional, as evidenced by the correlation value between learning behavior and student final grades which show an average number of 0.80 and all are positive, with confidence interval values reaching95%. This shows that the higher the learning activities that students participate in in online learning (the more active), the stronger the effect on student learning achievement. It also shows that student activity in completing assignments is the variable that most influences learning achievement with a correlation value of 0.88 (very strong).

Prediction of Student’s Academic Performance through Data Mining Approach

The universities and institutes produce a large amount of student data that can be used in a disciplinary way and useful information can be extracted by using an automated approach. Educational Data Mining (EDM) is an emerging discipline used in the educational environment to deal with big student data and extract useful information. The data mining of students’ data can help the At-risk students as well as the stakeholders by the early warning. This study aims to predict the performance of the students based on student-related data to increase the overall performance. In existing studies, insufficient attributes and complexity of network models is a problem. The student’s current records and grades need to be analyzed. In this approach, the Levenberg Marquardt Algorithm (MLA) deep learning algorithm is used. The data consists of the class test, attendance, assignment and midterm scores. The neural network model consists of four input variables, three hidden and one output layer. The performance of the deep neural network is evaluated by accuracy, precision, recall and F1 score. The proposed model gained a higher accuracy of 88.6% than existing studies. The study successfully predicts the student's final grades using current academic records. This research will be beneficial to the students, educators and educational authorities as a whole.

Prediction of Student’s Academic Performance through Data Mining Approach

The universities and institutes produce a large amount of student data that can be used in a disciplinary way and useful information can be extracted by using an automated approach. Educational Data Mining (EDM) is an emerging discipline used in the educational environment to deal with big student data and extract useful information. The data mining of students’ data can help the At-risk students as well as the stakeholders by the early warning. This study aims to predict the performance of the students based on student-related data to increase the overall performance. In existing studies, insufficient attributes and complexity of network models is a problem. The student’s current records and grades need to be analyzed. In this approach, the Levenberg Marquardt Algorithm (MLA) deep learning algorithm is used. The data consists of the class test, attendance, assignment and midterm scores. The neural network model consists of four input variables, three hidden and one output layer. The performance of the deep neural network is evaluated by accuracy, precision, recall and F1 score. The proposed model gained a higher accuracy of 88.6% than existing studies. The study successfully predicts the student's final grades using current academic records. This research will be beneficial to the students, educators and educational authorities as a whole.

The Effect of Extracurricular Activities and Learning Motivation on the Students’ Mathematics Learning Achievement

This study aims to show (1) there is a significant positive effect of extracurricular activities on students' mathematics learning achievement at SMAN 2 Tolitoli (2) there is a significant positive effect of learning motivation on students' mathematics learning achievement at SMAN 2 Tolitoli (3) there is a significant positive effect of extracurricular activities and learning motivation on students' mathematics learning achievement at SMAN 2 Tolitoli. The sample used in this study amounted to 59 people from class XI MIPA. The instruments used in this study are questionnaires to see the perceptions of students regarding extracurricular activities and learning motivation, and the final grades of students' semester exams to see how students' mathematics learning achievement is. The data of this study were analysed using descriptive statistics and inferential statistics. The results obtained from this study are (1) there is a significant positive effect of extracurricular activities on student mathematics learning achievement with a contribution of 14.5% (2) there is a significant positive effect of learning motivation on student mathematics learning achievement with a contribution of 9.9%, (3) there is a significant positive effect of extracurricular activities and learning motivation on student mathematics learning achievement with a contribution of 16.1%. Further research is needed to deepen the influence of extracurricular activities and learning motivation on students' mathematics learning achievement. Further research is also needed to look at other factors that influence mathematics learning achievement, so that it can be of concern to teachers.

Research on Knowledge Graph Multiple Environment-Aware Recommendation Algorithm for Teaching Course Recommendation

Abstract With the rapid development of education informatization and intelligence, personalized teaching and course recommendations have gradually become an important research direction in the field of education technology. A knowledge graph, as a structured knowledge representation and organization, provides rich semantic information and a relationship network for teaching course recommendations. Based on this research background, this paper focuses on the research of knowledge graph multivariate environment-aware recommendation algorithms for teaching courses. The article firstly constructs the ontology of course resources, researches and analyzes the methods and steps of acquiring and processing data in order to build the knowledge graph, and then constructs the framework of the recommendation model combining multivariate perception in order to further analyze and explore the user’s course-aware representation learning and the user’s course-aware embedded learning. Embedded Learning, and finally, the teaching course of a school as an empirical study, it is shown that the performance of Ripple_mlp+ and Ripple_mlp in this article are higher than the benchmark algorithms through the experimental class and the control class of the pre and post-test scores have been sorted out and counted. The experimental students’ scores are steadily increasing, and the overall scores are better than the control class. In the experimental class, the significance value is 0.013, indicating that there is a significant difference between the midterm and final grades of the experimental class. Through the paired samples t-test on the midterm and final grades of the experimental class, after analyzing and comparing the midterm and final grades of students at different levels, it can be concluded that the t-value of the superior students is −3.326. The value of significance is 0.049, indicating that there is a significant difference between the midterm and final grades of the exceptional students. The T-value for intermediate students is −0.134, and the value of significance is 0.045, which indicates that there is a significant difference in the midterm final grades of intermediate students. The T-value of −1.623 and the value of significance is 0.534 for advanced students indicates that the difference in midterm final grades of advanced students is not significant.

Intelligent Assessment and Feedback: Managing Student Learning States in Industrial Education

Abstract Students are the main body of the classroom, and their learning status reflects the quality of classroom teaching to a certain extent. This paper aims to manage students’ learning status in industrial education classrooms by designing a student learning status assessment system. The collected video data from industrial education classrooms are processed by binarization and histogram equalization. The key technologies, such as face detection and eye movement analysis, are used to detect the learning status of students in the industrial education classroom, and the functional modules, such as data acquisition and statistical analysis, are combined to form this paper’s student learning status assessment system based on facial feature detection. It is found that the face detection algorithm of this paper’s system improves the detection accuracy by 11.35% compared with the baseline algorithm when the standard difficulty is difficult, and this paper’s algorithm is able to successfully detect and display the students’ facial features through 68 key feature points. The system in this paper is able to detect students’ learning states, such as concentration, fatigue, and doubt, by analyzing their eye movement frequency and other indicators. After applying the system discussed in this paper, the final grades of students in industrial education have significantly improved.

Research on the Optimization of English Teaching Content in Colleges and Universities by Combining Decision Tree and Big Data Technology

Abstract English teaching in colleges and universities is facing the growth of personalized teaching demand, and the traditional education model is challenging to meet the diverse learning needs of students. Big data and decision tree technology provide a new way for teaching content optimization, which can achieve a high degree of matching between educational resources and students’ needs, and improve teaching effectiveness and learning efficiency. This study explores the application of decision trees and big data technology in optimizing English teaching content in colleges and universities. By constructing an ontology tree model of learning resources and adopting similarity calculation and personalized recommendation algorithms, the study achieves personalized learning resource recommendations for students. The study utilizes comparative experimental methods to analyze achievement changes between the experimental and control classes after customized learning. The personalized teaching program’s effectiveness can be confirmed by the fact that the average final grade of students in the experimental class is 1.5 points higher than that of the control class. The Analysis of CET-4 scores found that personalized teaching improved students’ English listening, reading, and writing skills. This paper combines decision trees and big data technology to optimize teaching content, effectively enhancing students’ English learning outcomes and providing new teaching strategies for English education in colleges and universities.

Penerapan Metode Team Games Tournament Guna Meningkatkan Minat Belajar Siswa Kelas 5 SD 067090 Jl. Halat Kota Medan

After the passing of the Covid-19 Pandemic, it gave new impacts and challenges in the world of teaching and learning, especially for grade 5 students at SD 067090 Halat who experienced a decrease in their interest in learning. The main factor for this to happen is distance learning which makes students spend more time with smartphones. The impact after the pandemic was over, students became lazy to study at school. This decrease in learning interest affects the final grades of students later. This cannot be allowed to continue because it will not only affect the final grades of students but will also affect the development of students' traits, attitudes and ethics. The problem that exists in grade 5 students at SD Negeri 067090 is the decline in student interest in learning. The monotonous class atmosphere with only material explanations and doing assignments is one of the reasons students feel bored studying in class. Team Games Tournament is a learning procedure that provides opportunities for groups to compete with other groups so that students are passionate about learning. The system applied in this method emphasizes games (games) as learning activities that aim to spur the motivation and spirit of competition in students both physically and mentally with predetermined rules so as to make students enthusiastic during the learning process.

Unobtrusive measurement of self-regulated learning: A clickstream-based multi-dimensional scale

Self-regulated learning has seen a large increase in research interest due to its importance for online learning of higher education students. Several ways to measure self-regulated learning have been suggested. However, most measurements are either obtrusive, necessitating time and effort from students and potentially influencing the learning process, or only partially portable across courses. In the current study, we develop clickstream-based scales of four self-regulated learning phases that we show are portable across courses. The final scales are based on the COPES model and include two strong and reliable dimensions, enactment and adaptation, one dimension that performs reasonably, task definition, and a weaker one, goal-setting. By considering portability as the main criterion in the scale construction process, we ensured reliable transfer to both similar and dissimilar courses. When considering convergent validity, the created scale has higher bivariate and partial correlations with final student grades than the often-used self-reported MSLQ-SRL scale. We discuss limitations and future research to improve the scale further and facilitate adoption.

The Impacts of a Standards-Based Grading System Emphasizing Formative Assessment, Feedback, and Re-Assessment: A Mixed Methods, Cluster Randomized Control Trial in Ninth Grade Mathematics Classrooms

We investigated the impact in ninth-grade mathematics classrooms of Proficiency-based Assessment and Reassessment of Learning Outcomes (PARLO), a standards-based grading system. Key components of PARLO are basing student final grades on the number of learning outcomes on which the student is high-performance or proficient, providing students with formative feedback, and encouraging students to reassess for full credit after further study. Our mixed-methods study employed a cluster randomized control trial with 2,736 participating ninth graders at 14 Treatment and 15 Control schools. Data included student achievement tests, interviews with 35 teachers, and student surveys. The program improved student performance on end-of-course algebra and geometry tests by a statistically significant 0.33 SD but did not impact students’ value of or expectancies for success in mathematics. However, treatment effects on mathematics performance were moderated by these psychological antecedents of motivation, such that students with higher math expectancies and value benefited more from the treatment. Furthermore, teacher interviews suggested that PARLO may have also had positive effects on growth mindsets, mastery goals, autonomy, and relatedness.

Flipped classroom in neurophysiology: performance analysis of a system focusing on intrinsic students' motivation.

Introduction: Teaching methodologies promoting active learning result in higher-order knowledge application, a desirable outcome in health disciplines like Physiology. Flipped-classroom (FC) promotes active learning and engagement in the classroom. Although specialized research keeps accumulating, the advantages of FC for improving academic outcome and ultimately patient care remain controversial and open to further analysis. Objective: This study evaluates the benefits of applying FC to the Neurophysiology module of a Human Physiology course. Methods:We compare final grades of students exposed to standard lecturing (five-years) vs. FC (six-years), and study the FC impact on student motivation, study time and rewards. Differing from conventional FC, we performed no pre-class/in-class assessments, relying on the students' internal motivation to experience our FC model. A printed student workbook was designed as pre-class material for each session. Reading times respect the expected daily study time of students in our system. Results and discussion: Concerning academic performance, our long-term study reports a significant increase in average scores for FC groups. Overall, students get better scores in multiple choice tests than in problem-solving questions. A more detailed analysis uncovers that our FC model helps students to obtain better scores, reducing variability in performance due to assessment methods. Based on our open-ended survey questions, most students rate the FC environment and in-class activities positively and perceive a positive effect of FC on teachers' performance. An objective automatic Sentiment analysis of open-ended answers reveals that FC is positively appreciated by students, associating positive perceptions to their understanding of physiological concepts, and negative evaluations to their time management.

Designing the Decision Support System to Determine the Major and Higher Education Institution based on Preferences of Prospective Students

There are several factors considered by students toward determining the major and higher education institution. As a result, determining the best choices for further studies becomes difficult. Moreover, there are many choices of higher education. This study contributes to developing a decision support system (DSS) to help students determine the major and higher education institution considered several criteria based on Analytical Hierarchy Process (AHP). Several criteria and subcriteria were chosen by distributing 186 questionnaires to final grade students. Based on the result, criteria and subcriteria used were tuition fee, scholarship, infrastructure (library, classroom, laboratory, transportation, teaching staff), curriculum, quality (accreditation, study period, achievement), reputation, and international collaboration. According to these criteria and sub-criteria, a DSS was built to help students determine their major and higher education institution according to their preferences. The algorithm used was AHP, which was then built with Borland Delphi. Context Diagram, Data Flow Diagram (DFD), and Entity Relationship Diagram (ERD) were made as a guide to design the DSS. This DSS was tested using black box test, beta test and compatibility test with manual calculations. The black box test showed that the DSS has performed the functions according to the design. Later, the beta test resulted in a correctness score of 20.4, reliability of 16.8, usability of 25.5, which means they were in the very good category and integrity of 3.4, which means good. Meanwhile, based on manual calculations, the DSS provides output in accordance with the results of manual calculations. Finaly, he DSS was proven to be used as a decision-making tool in determining the major and higher education institution for students

Investigating the impact of a gamified learning analytics dashboard: Student experiences and academic achievement

AbstractBackgroundThe substantial growth in gamification research has connected gamified learning to enhanced engagement, improved performance, and greater motivation. Similar to gamification, personalized learning analytics dashboards can enhance student engagement.ObjectivesThis study explores the student experiences and academic achievements using a gamified dashboard in a large, introductory STEM course.MethodsWe examined two groups of students enrolled in different sections of a one‐semester‐long physical geology course with a total enrollment of 223 students. The only difference between the groups was that one had access to the dashboard. The data collection included students' assignments, overall performances, and exam scores. Students in both sections completed a Science Literacy Concept Inventory survey at the beginning and end of the term. Additionally, students completed an end‐of‐term survey containing open‐ended questions on their experience and interactions with specific elements.ResultsStudents shared mostly positive comments about their experience with the dashboard, and the final grade of students with access to the dashboard was 13% higher, on average, compared to their peers in the non‐dashboard section.ConclusionWith low costs and little time invested, gamified dashboards could have a significant impact on student performance in large STEM lecture courses.