Статті в журналах: "Student performance"

1

Johargy, Dr Ayman, Dr Pushpamala Ramaiah, and Dr Ibtesam Nomani Lamia Ahmed Elsayed Grace Lindsey. "Student Nurses Academic Performance- Multidimensional Constructs." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 818–22. http://dx.doi.org/10.31142/ijtsrd23144.

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Laxmi, A. Sindura, and Sandeep Patil. "The Student Performance Monitoring Using ARM9." International Journal of Scientific Research 1, no. 7 (June 1, 2012): 66–69. http://dx.doi.org/10.15373/22778179/dec2012/27.

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3

Sugiarto, Meilani. "ANALISIS PERCEIVED ENJOYMENT SEBAGAI VARIABEL ANTISEDEN TECHNOLOGY ACCEPTANCE MODEL." Performance 24, no. 1 (October 2, 2017): 58. http://dx.doi.org/10.20884/1.performance.2017.24.1.315.

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Young people was active users of the information technology, especially internet. Even some of them tend to make the internet as a medium of the main support daily activities. These study indicate that internet use among young people, especially college student tend to have a model of its own behavior, making it attractive for further investigation. These study focus on the influence of perceived enjoyment as variables anticedent in the Technology Acceptance Model (TAM). The respondents of these study were college student as internet users in Yogyakarta, the province is considering a student city. These study conducted on 130 respondents. According to the structural analysis with SEM method, shows that perceive enjoyment has a role as anticedent variable on TAM, because those variable has significant effects on variables in technology acceptance model.

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4

Shetty, Isha D., Dipshi Shetty, and Sneha Roundhal. "Student Performance Prediction." International Journal of Computer Applications Technology and Research 8, no. 5 (April 24, 2019): 157–60. http://dx.doi.org/10.7753/ijcatr0805.1003.

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5

Zeluff, Karen A. "Improving Student Performance." Academic Therapy 24, no. 1 (September 1988): 95–98. http://dx.doi.org/10.1177/105345128802400116.

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6

Setemen, K., and I. K. Purnamawan. "Student performance assessment strategies by involving peer students." Journal of Physics: Conference Series 1810, no. 1 (March 1, 2021): 012064. http://dx.doi.org/10.1088/1742-6596/1810/1/012064.

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7

Pervin, Mst Maleka, Nafiza Ferdowsh, and Israt Jahan Munni. "Teacher-student interactions and academic performance of students." Dhaka University Journal of Biological Sciences 30, no. 1 (February 3, 2021): 87–93. http://dx.doi.org/10.3329/dujbs.v30i1.51812.

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The main goal of this study was to investigate the influence of teacherstudent interaction on academic performance of the students. Hundred participants (50 teachers and 50 students) were selected through purposive sampling technique to conduct this research. Teacher and student feedback were measured by using the Questionnaire on Teacher Interaction (QTI) as well as students’ academic performance was calculated by using last year grade point average (GPA) of each student. Pearson product moment correlation was used which indicated a positive significant correlation (r = 0.70, p < 0.05) between teacher-student interaction and academic performance of the students. The findings indicated the importance of teacher-student relationships to attain academic success of the students. The results suggest providing appropriate academic resources and aids for the teachers to meet the individual needs of their students. Dhaka Univ. J. Biol. Sci. 30(1): 87-93, 2021 (January)

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8

Foos, Paul W. "Effects of Student-Written Questions on Student Test Performance." Teaching of Psychology 16, no. 2 (April 1989): 77–78. http://dx.doi.org/10.1207/s15328023top1602_10.

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Effects of student-written test questions on student test performance were examined in an Introductory Psychology class. Before each of three tests, randomly assigned students wrote essay questions, multiple-choice questions, or no questions. All tests contained essay and multiple-choice items but no questions written by students. Question writers performed significantly better than nonwriters on the first two tests; the difference on the third test was marginally significant. No differences were found between students who wrote essay and those who wrote multiple-choice questions. Question writing appears to be an effective study technique.

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9

PURCARU, Monica A. P. "ASPECTS REGARDING THE LEVEL OF PERFORMANCE IN MATHEMATICS." Review of the Air Force Academy 18, no. 2 (January 22, 2021): 57–62. http://dx.doi.org/10.19062/1842-9238.2020.18.2.6.

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In the present paper addressing the issue of advanced performance in mathematics, we seek to answer to the following study questions: “What are the main factors that lead to the achievement of advanced performance?”; “Which is the profile of the teacher able to train the Olympic students in Mathematics?”; “Why do teachers want for their students to achieve advanced performance in mathematics?”; “Why do the students want to reach a high degree of performance in Mathematics?”; “What difficulties could significantly impede on student progress?”; “What is the connection between enthusiasm and advanced performance in Mathematics?”; “ Why does an Olympic student participate in competitions?”.

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10

Liu, Chen-Chung, Gwo-Dong Chen, Chin-Yeh Wang, and Ching-Fang Lu. "Student Performance Assessment Using Bayesian Network and Web Portfolios." Journal of Educational Computing Research 27, no. 4 (December 2002): 437–69. http://dx.doi.org/10.2190/el2a-tqf1-pyvm-n51v.

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Web-based curriculum development allows students to develop their learning portfolio and interact with peers on a Web learning system. This system contains Web portfolios that record in detail students' learning activities, peer interaction, and knowledge progress. However, teachers cannot easily diagnose students' learning processes and regulate effective strategies according to student activity performance without the model of activity performance on Web learning systems. This study proposes a novel methodology that employs Bayesian network software to assist teachers in efficiently deriving and utilizing the student model of activity performance from Web portfolios in an online manner. Teachers can assess and diagnose performances with the model of learning activity on Web learning systems. The model of activity performance also allows teachers to manage various activity performances in Web learning systems so that desired strategies can be achieved to promote learning effectiveness.

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11

Ziyi (Kevin), Wang. "CLASSIFICATION FOR STUDENT PERFORMANCE." Young Scholars Journal, no. 3-4 (2022): 10–14. http://dx.doi.org/10.29013/ysj-22-3.4-10-14.

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12

Castolo L, Carmencita, and Rosemariebeth R. Dizon. "Evaluating Student Teacher Performance." i-manager's Journal on School Educational Technology 2, no. 4 (May 15, 2007): 31–34. http://dx.doi.org/10.26634/jsch.2.4.834.

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13

McDaniel Mohr, Tanga. "Iclickers and student performance." International Review of Economics Education 14 (September 2013): 16–23. http://dx.doi.org/10.1016/j.iree.2013.10.006.

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14

Aslam, M. M. Haris, Ahmed F. Siddiqi, Khuram Shahzad, and Sami Ullah Bajwa. "Predicting Student Academic Performance." International Journal of Knowledge Management 10, no. 3 (July 2014): 18–35. http://dx.doi.org/10.4018/ijkm.2014070102.

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The biggest challenge in nurturing an academic community is encouraging knowledge sharing among its members. Literature on communities, however, has paid less attention on the role of outcome expectations in encouraging the knowledge sharing behaviors. This study examines the effects of Personal Outcome Expectations (POE) and Community-related Outcome Expectations (COE) on the knowledge sharing behaviors of students and its consequent impact on their academic performance. In order to study these relationships a survey of university students was conducted. Based on structural equation modeling approach, it was found that COE have significant impact on knowledge sharing among the students.

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15

Jalomo Jr., Romero. "Assessing Minority Student Performance." New Directions for Community Colleges 2000, no. 112 (2000): 7–18. http://dx.doi.org/10.1002/cc.11201.

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16

Davis, Summer, Xihe Zhu, and Justin Haegele. "High School Student Fitness Test Attributions: Does BMI or Performance Matter?" Journal of Teaching in Physical Education 40, no. 1 (January 1, 2021): 49–57. http://dx.doi.org/10.1123/jtpe.2019-0123.

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Purpose: To examine differences in fitness test performance and the attributions made for the performances between high school students of different weight status. Methods: High school students (n = 185) completed the Progressive Aerobic Cardiovascular Endurance Run and the push-up fitness tests and then completed the modified Causal Dimension Scale to assess their attributions for their performances. Results: Students of a healthy weight performed higher than overweight/obese students on both fitness tests. There were no significant differences in attribution dimension scores for either test between healthy weight and overweight/obese students. Student performance played a significant role on the attribution dimension scores for both tests. Students primarily attributed their push-up and Progressive Aerobic Cardiovascular Endurance Run performance to ability. Conclusion: As student performance is significantly associated with attribution dimension scores, improving fitness test performance should subsequently foster adaptive attributions, creating a high expectancy for future success.

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17

Ariani, Mohsen Ghasemi, and Fatemeh Mirdad. "The Effect of School Design on Student Performance." International Education Studies 9, no. 1 (December 29, 2015): 175. http://dx.doi.org/10.5539/ies.v9n1p175.

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<p class="apa">The present study aims at exploring the influence of school design on student performance. The participants consisted of 150 students who studied at two Iranian public school and private school in Mashhad City. School Design and Planning Laboratory (SDPL) model of Georgia University (and Tanner (2009)) was used as an appraisal indicator of school design and some of its design characteristics such as unrestricted and functional views, indoor and outdoor spaces, and natural life were explained to students. In addition, student performance, defined by the average of their final achievement scores, was compared to measures of school environmental characteristics. To this end, design characteristics of these schools and students’ performances have been studied. Quantitative data, subjected to a set of descriptive statistics, showed that school design was a strong factor for students of private school. In fact, the finding indicated that characteristics of physical learning space and deign of private school had fundamental effects on student performance. That is, learning space as a strong component can motivate students to study and progress.</p>

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18

Kim, Kyong-Jee, Yeon Ji Lee, Mi Jin Lee, and Young Hyo Kim. "e-Learning for enhancement of medical student performance at the Objective Structured Clinical Examination (OSCE)." PLOS ONE 16, no. 7 (July 1, 2021): e0253860. http://dx.doi.org/10.1371/journal.pone.0253860.

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This study aimed to investigate the impact of student e-learning on the development of clinical competencies. The study participants were 3rd year students (n = 43) at a private mid-sized medical school located in a South Korean suburb on a four-year medical program. Educational intervention was implemented to enhance student clinical performance. Students engaged in learning activities that intended to promote their self-directed learning abilities and clinical performances using e-learning resources. Intervention was conducted for the duration of six months during the 3rd year and its effectiveness was investigated by comparing student performances in OSCEs in a pre- and post- comparison format and also by comparing them with national scores. In addition, student perceptions of the impact of e-learning on their OSCE performances were assessed using a questionnaire, which included 36 items that elicited student perceptions of their experiences of e-learning and readiness for e-learning. Student OSCE scores improved significantly after educational intervention in all domains of clinical competencies assessed and for total scores (p < 0.001). Furthermore, students achieved higher OSCE scores than national average scores in the post-test, whereas they had performed lower than national average scores in the pre-test. Students showed neutral or slightly positive responses to the effectiveness of e-learning, and their perceptions of e-learning were not associated with their e-learning readiness scores. The study shows student OSCE performance improved significantly after educational intervention, which indicate the effectiveness of e-learning to support student learning of clinical performance. Despite significant improvements in student OSCE scores after e-learning, their perceptions of its effectiveness were neutral. Furthermore, student perceptions of e-learning were not associated with their readiness for it. Suggestions are made to help students use e-learning more effectively to enhance their clinical competencies.

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19

Warnars, Harco Leslie Hendric Spits, Arif Fahrudin, and Wiranto Herry Utomo. "Student performance prediction using simple additive weighting method." IAES International Journal of Artificial Intelligence (IJ-AI) 9, no. 4 (December 1, 2020): 630. http://dx.doi.org/10.11591/ijai.v9.i4.pp630-637.

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In the world of student education is an important component where the role of students is as someone who is psychologically ready to receive lessons or other input from the school. However, each student has different performance and development, therefore it is important to do monitoring so that student performance will always be monitored by the school for improving student quality maintenance. Also, in the process of valuing education for students needs to be done by giving an appreciation in the form of giving gifts or just giving words and motivation so that students can perform better in learning and participating in other activities at school. In terms of selecting students with good performance or those who have a very declining development using the school method not only assess students by one criterion but with several criteria to produce a decision that can be accepted by many people. Performance Students must also be monitored by the school or the related rights. In this paper, the student performance prediction was assessed with 5 criteria components and the result shows there are 10 very satisfy students, 10 satisfying students, 10 well students, and 10 Enough students from sample 40 students.

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S. Satheesbabu, P. Gokulakrishnan, R. Karthikeyan,. "MACHINE LEARNING BASED STUDENT PERFORMANCE ANALYSIS SYSTEM." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (March 17, 2021): 1174–81. http://dx.doi.org/10.17762/itii.v9i1.251.

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The academic output of the student is normally stored in various formats in the student administration system (files, documents, records, photographs and other formats). These data can be collected for valuable knowledge from the students. However, it is difficult to analyze the increasing amount of data of students through conventional statistical techniques and database management tools. For universities to gather valuable information, a tool is therefore required. This helpful knowledge can be used to predict the success of students. Leistungs analyze learning results is a framework that aims for success in the areas of student interest at various levels and dimensions. This paper proposes a complete structure as a rule-based recommendation method not only for analyzing and forecasting the success of students but also for presenting their reasons. The proposed system analyzes demographic details for pupils, studies and psychological features so that students, teachers and parents can collect all possible knowledge. To seek maximum accuracy in academic predictions across a range of powerful techniques of data mining. The system successfully recognizes the limitations of the student and makes adequate recommendations. The practical case study on 200 students indicates the excellent performance of the proposed system compared to the current framework.

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21

Yan, Chenghao. "Research on Student Academic Performance Prediction Methods." Highlights in Science, Engineering and Technology 24 (December 27, 2022): 257–63. http://dx.doi.org/10.54097/hset.v24i.3940.

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Student academic performance prediction can not only detect students' academic problems in advance, but also optimize teaching methods and provide students with personalized teaching methods, considering the complex relationship between academic performance and other factors, this paper uses linear regression and random forest to predict student academic performance.

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22

Davis, James N., and Mary Ann Lyman-Hager. "Computers and L2 Reading: Student Performance, Student Attitudes1." Foreign Language Annals 30, no. 1 (March 1997): 58–72. http://dx.doi.org/10.1111/j.1944-9720.1997.tb01317.x.

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23

N, Patel Karan. "Attendance and Performance Monitoring System Implementation." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 3088–94. http://dx.doi.org/10.22214/ijraset.2022.45671.

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Abstract: Attendance Management is very important for every organization. Taking attendance of lot student is very time consuming process. It is difficult to analyze attendance of students how frequently one is skipping classes. And also there will be some proxy attendance of student in traditional system. The possible solution to this problem is to use an automatic attendance system which uses face recognition techniques. This system will mark attendance electronically and recorded attendance will be stored in a database. The preparation of a question paper for the Internal Assessment Exam can be automatically generated with the help of teachers according to RBT levels. The Internal Assessment is very important for students. This system will give individual student reports based on the performance of student in internal assessment, exactly in which type of RBT level the student need to improve themselves.

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24

Martin, Andre Anthony. "Exploring the impact of teacher quality on student academic achievement in primary schools." American Journal of Social Sciences and Humanities 8, no. 1 (February 1, 2023): 35–45. http://dx.doi.org/10.55284/ajssh.v8i1.845.

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There has been debate among scholars, policymakers, and practitioners regarding the effects of teacher quality on students' academic performance. This quantitative descriptive study seeks to determine the impact of teacher quality on students' performance and the relationship between teacher quality and student performance. Student performance was measured using regional assessments in mathematics and language arts. A survey was conducted to collect primary data from teachers, and both sets of data were analyzed using the t-test, ANOVA, and Pearson’s correlation coefficient (r) to test for performance differences and relationships between student performance and teacher quality. The findings revealed no significant differences in the academic performances among students taught by trained and untrained teachers, degree and non-degree teachers, and teachers with varying years of experience and hours of professional development. The interactions of the teacher quality variables had no practical effect on student performance, and there were no significant relationships between student performance and the teacher quality variables of experience and professional development. There are implications for reorganizing or advancing teacher professional development, training, certification and licensing. The study adds to the scarce literature in the region and can guide policy development in teacher workforce planning, retention, and hiring.

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25

Amalia, Hilda, Ari Puspita, Ade Fitria Lestari, and Frieyadie Frieyadie. "APPLICATION OF DECISION TREE AND NAIVE BAYES ON STUDENT PERFORMANCE DATASET." Jurnal Pilar Nusa Mandiri 18, no. 1 (March 9, 2022): 53–58. http://dx.doi.org/10.33480/pilar.v18i1.2714.

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Student performance is the ability of students to deal with the entire academic series taken during school. Student performance produces two labels, namely successful and unsuccessful students. Successful students can graduate with excellent, excellent, and suitable performance labels. At the same time, students who have a label on average are students who get poor performance. Measurement of student performance is needed for every educational institution to take strategic steps to improve student performance. This study aimed to obtain a data mining method that worked well on student performance datasets. In this study, student performance datasets were processed, which had 11 indicators with one result label. Student performance datasets are processed using data mining methods, namely decision tree and nave Bayes, while the tool used for dataset processing is WEKA. The research results from processing student performance datasets obtained that the accuracy value for the decision tree method was 94.3132%, and the accuracy produced by the naive Bayes method was 84.8052%.

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26

Hadi, Cholichul, Hung Chiao, Suen Mein-Woei, Dimas Agung Trisliatanto, and Muh Fitrah Ramadhan Umar. "What Predicts Students’ Academic Performance." International Journal of Social Service and Research 2, no. 4 (April 29, 2022): 277–90. http://dx.doi.org/10.46799/ijssr.v2i4.100.

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The Performance of a higher education institution was one of the important factors determining success in producing quality graduates. Academic achievement obtained by students was considered to the success of a student and the learning system at the institution. The academic quality was also inseparable from the background of the student itself. Besides, the system and climate of teaching and learning are created in the educational environment. This study aimed to describe students' academic Performance and the factors that influence the improvement in academic performance of undergraduate students majoring in Psychology at Airlangga University. This research used a quantitative approach with a descriptive survey research design. Based on the results of research conducted, it concluded that student performance, the program of study performance, and university performance on student's academic performance, both simultaneously and partially for undergraduate students at the Faculty of Psychology, Airlangga University.

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27

Vignery, Kristel. "From networked students centrality to student networks density: What really matters for student performance?" Social Networks 70 (July 2022): 166–86. http://dx.doi.org/10.1016/j.socnet.2022.01.001.

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28

Siefken, Jason. "Registration Delay and Student Performance." Journal of the Scholarship of Teaching and Learning 17, no. 2 (May 11, 2017): 45–52. http://dx.doi.org/10.14434/josotl.v17i2.20754.

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Tracking the difference between the time a first-year student is allowed to register for a course and the time he or she does register for a course (a student’s registration delay), we notice a negative correlation between registration delay and final grade in a course. The difference between a student who registers within the first two minutes they are allowed to and one who waits three weeks to register is approximately a full GPA point (on a 9 point scale). Registration delay may be a useful factor in helping to identify at-risk students, and should be taken into account as a confounding variable when doing educational studies on multi-section courses.

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Alami, Manizheh. "Causes of Poor Academic Performance among Omani Students." International Journal of Social Science Research 4, no. 1 (March 2, 2016): 126. http://dx.doi.org/10.5296/ijssr.v4i1.8948.

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Nowadays, poor academic performance is among the main concerns of teachers, syllabus designers, curriculum developers and the whole educational body. The issue becomes worse in non-English speaking countries where the medium of instruction at colleges/ universities is English but students are exposed to English for a limited number of hours before beginning their study at college/university. To answer the question ‘what are the causal factors that affect students’ poor performances in non-English speaking countries like Oman? 151 essays written by students who enrolled for post foundation program at Salalah College of Technology were examined carefully. The factors involved in students’ low academic achievements categorized into four macro groups; student-related factors, teacher- related factors, family- related factors and some other factors such as marriage, health problem, toxic friendships and transportation problem. The findings show that while student-related factors have the highest impact on students’ performance, teacher-related factors had the lowest effect.Keywords: Academic performance, student- related factors, Teacher-related factors, Family-related factors

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Sapsani, Georgia, and Nikolaos Tselios. "Facebook Use, Personality Characteristics and Academic Performance." International Journal of Web-Based Learning and Teaching Technologies 14, no. 2 (April 2019): 1–14. http://dx.doi.org/10.4018/ijwltt.2019040101.

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The present article examines the relationship between student personality, use of social media and their academic performance and engagement. Specifically, this article examines the relationship of students' Facebook (FB) use and personality characteristics using the Big Five Personality Test. This is focused on (a) student engagement; (b) time spent preparing for class; (c) time spent in co-curricular activities; and (d) academic performance. 204 higher education students participated in the study. Results illustrate that FB time was significantly positively correlated to student engagement and time spent preparing for class. Sharing links activity was positively correlated with student engagement and playing FB games with time spent preparing for class. However, sending private messages and status updates were significantly negatively correlated with student engagement and time spent preparing for class. Also, viewing videos was negatively correlated with time spent in co-curricular activities. Chatting on FB and viewing photos found to be the most popular activities. Moreover, students' extraversion, conscientiousness, openness to experience were positively correlated to student engagement. In addition, extraversion had a positive relationship with time spent in co-curricular activities, although agreeableness had a negative relationship. Implications of the study for the instructors and the students are also discussed.

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Moharekar, Tejashree T., and Dr Urmila R. Pol. "ACADEMIC PERFORMANCE PREDICTION APPLICATION (APPA)." YMER Digital 20, no. 12 (December 10, 2021): 179–96. http://dx.doi.org/10.37896/ymer20.12/17.

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The research study offers a thorough description of the process of deployment after training and testing of the classification model respectively. The performance of students is a crucial prerequisite to help students that don’t perform well in the examination and can impact the final semester result. To overcome the difficulties they come across while learning and assist them to achieve the best results. The researcher uses the advantages of the React-Native platform to build an "APPA" mobile application capable of delivering student performance prediction-related solutions. It also provides a proposed model of student academic success prediction. The further study highlights the further scope of the mobile App built for predicting student performance.

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Pliner, Erika M., April A. Dukes, Kurt E. Beschorner, and Arash Mahboobin. "Effects of Student Interests on Engagement and Performance in Biomechanics." Journal of Applied Biomechanics 36, no. 5 (October 1, 2020): 360–67. http://dx.doi.org/10.1123/jab.2020-0029.

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There is a need for pedagogical techniques that increase student engagement among underrepresented groups in engineering. Relating engineering content to student interests, particularly through biomechanics applications, shows promise toward engaging a diverse group of students. This study investigates the effects of student interests on engagement and performance in 10th grade students enrolled in a summer program for students underrepresented in the science, technology, engineering, and mathematics fields. The authors assessed the effects of interest-tailored lectures on student engagement and performance in a 5-week program with bioengineering workshops, focusing on the delivery of biomechanics content. A total of 31 students received interest-tailored lectures (intervention) and 23 students received only generic lectures (control) in biomechanics. In addition, the authors assessed the effects of teaching method (lecture, classroom activities, and laboratory tours) on student engagement. The authors found interest-tailored lectures to significantly increase student engagement in lecture compared with generic lectures. Students that received interest-tailored lectures had an insignificant, but meaningful 5% increase in student performance. Students rated laboratory tours higher in engagement than other teaching methods. This study provides detailed examples that can directly assist student teaching and outreach in biomechanics. Furthermore, the pedagogical techniques in this study can be used to increase engagement of underrepresented students in engineering.

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Chen, David, and Jolon Faichney. "Flipping a Programing Class to Improve Student Performance and Student Satisfaction." International Journal of Adult Vocational Education and Technology 10, no. 1 (January 2019): 27–39. http://dx.doi.org/10.4018/ijavet.2019010103.

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Flipped classrooms are an instructional strategy that is becoming popular in educational contexts, particularly higher education. The principle of Flipped Classroom is that events that have traditionally taken place inside the classroom now take place outside the classroom and vice versa. Various studies have reported increased student performance and satisfaction after switching to a flipped classroom. However, most of these studies are based on students' perceptions of their own learning, not based on teachers' assessment of students' achievements. This article presents the results of flipping a computer programming course. It first describes how this course was flipped, then it presents the results of comparing the average marks awarded to students between those that took the course offering in flipped mode and those that took the course in the traditional mode. The comparison showed an increase in student performance in a flipped mode. Furthermore, the increase in student performance was sustained for 3 years, which is the full duration of this study. The comparison of student satisfaction showed an increase in student satisfaction in one campus, while the student satisfaction remained steady in another campus.

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34

Gurung, Regan A. R. "Pedagogical Aids and Student Performance." Teaching of Psychology 30, no. 2 (April 2003): 92–95. http://dx.doi.org/10.1207/s15328023top3002_01.

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I tested whether students' reported use and perceived helpfulness of textbook pedagogical aids and other instructional methods (e.g., group discussion) related to better exam performance. More than 200 undergraduates rated 10 commonly used pedagogical aids and instructional techniques. Students reported using boldface and italics terms and practice test questions most often, and they considered boldface and italicized terms, practice test questions, and online quizzes most helpful. The reported use of pedagogical aids and their perceived helpfulness did not relate to student performance on exams. Furthermore, the rated helpfulness of key terms related to worse scores on exams. Pedagogical aids may be useful teaching tools and learning enhancers, but this commonsensical hypothesis must be tested.

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Ivanova-Nedelcheva, Albena. "Challenges in addressing low student performance." Annual of Konstantin Preslavsky University of Shumen, Faculty of mathematics and informatics XXIII C (2022): 71–77. http://dx.doi.org/10.46687/eyan2364.

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This article presents basic ideas for improving student achievement. Basic guidelines for motivating students, teachers and parents are proposed. Specific educational products resulting from these activities are presented. In the article, we present opportunities implemented in the STE(A)M center of High School Sava Dobroplodni. The learning material is "translated" by the teachers so that it can meet the students' interests and activities. We jointly implement numerous projects aimed at in-depth understanding of the educational material. We believe that students learn willingly when the material is close in subject matter and content.

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Karnes, Frances A., and Victor D'Ilio. "Student Leaders and Social Performance as Measured by the Social Performance Survey Schedule." Psychological Reports 65, no. 3 (December 1989): 961–62. http://dx.doi.org/10.2466/pr0.1989.65.3.961.

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There is a paucity of research on the social skills of student leaders, although studies have been conducted on other groups of students and adults. In this study, the Social Performance Survey Schedule was administered to 114 student leaders in Grades 6 to 11. Consistent with previous research applying the survey on diverse populations, girls engaged in more positive social behaviors, fewer negative behaviors, and had higher over-all performance than boys. Suggestions for those who may have contact with such students were made.

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Saragih, Arfah Habib, Joansyah Adwie, and Adang Hendrawan. "Determinants and Consequences of Students Learning Satisfaction During Covid-19 Pandemic." Jurnal Ilmiah Akuntansi dan Bisnis 16, no. 1 (January 5, 2021): 1. http://dx.doi.org/10.24843/jiab.2021.v16.i01.p01.

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This study examines the effect of student perception in online learning on student satisfaction and its impact on student learning performance and intention to use in the future. The regression analysis method was used based on the survey results from 157 students. Results indicate that students' perceptions of online learning had a positive effect on student satisfaction, intention to use, and student learning performance. Further, student satisfaction has a positive effect on student learning performance but does not affect the intention to use. The implications for lecturers, students, and faculties are also discussed. Keywords: student perception, online learning, student satisfaction, student performance, intention to use, covid-19 pandemic

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Tubulingane, Booysen Sabeho. "University Library Services and Student Academic Performance." International Journal of Library and Information Services 10, no. 2 (July 2021): 1–17. http://dx.doi.org/10.4018/ijlis.20210701.oa1.

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In many countries, university libraries are required to demonstrate quantitatively their value to their institutions. Consequently, many universities spend a large part of their institutional budgets on acquiring new library books, paying for high online journal subscription fees, and recruiting library staff. However, few studies have been conducted to evaluate the contribution of the university libraries to the students' success. Thus, this study, which applied a quantitative survey methodology to quantify the contribution of a Namibian university library to student academic performance, was conducted. The study determined the contribution of the university library services to students' academic performance. Additionally, the study established a relationship between students' library service satisfaction and academic performance. Analysis of library user satisfaction, student age, and gender were also examined.

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Ramlal, Porika, Kappala Manjusha, and Sania Khan. "The nexus between emotional intelligence and academic performance." Knowledge and Performance Management 6, no. 1 (September 16, 2022): 38–48. http://dx.doi.org/10.21511/kpm.06(1).2022.04.

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This paper attempts to understand how emotional intelligence (EI) can affect students’ academic performance by investigating the relationship between EI and student performance. A structured questionnaire comprising 25 questions was developed on a five-point Likert scale employing the five components of EI stated by Daniel Goleman. The five elements are self-analysis, self-control, self-motivation, empathy, and social skills. 350 MBA students from premier institutes in Warangal, India, were taken as a sample through a convenience sampling technique. Correlation analysis was performed amongst students’ EI and their cumulative grade point average (CGPA). The coefficient value obtained showed a minimal linear relationship between EI and student performance. For further analysis, students were segregated gender-wise, male and female, and then a correlation was performed. In the case of female students, a negative relationship is exhibited between EI and performance. In contrast, in the case of male students, a positive relationship is exhibited that is higher than the overall coefficient. Moreover, correlation is applied to each component separately to identify which of the five components has higher linear relationship. The findings concluded that self-control and empathy followed by self-motivation had linear relationship, especially in the case of male students. Finally, it was difficult to correlate the EI of female students with their performance.

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Widerman, Eileen. "Performance Evaluation Using a Rubric: Grading Student Performance in Practice Courses." Journal of Baccalaureate Social Work 8, no. 2 (March 1, 2003): 109–25. http://dx.doi.org/10.18084/1084-7219.8.2.109.

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This article promotes performance evaluation using a rubric as a useful approach to assessing the extent to which social work students meet the complex learning objectives of practice courses. This approach permits assessment of qualitative competencies, such as use-of-self, and facilitates the reduction of multiple evaluation criteria to a single grade. It guides students in completing assignments, details performance expectations, and provides meaningful feedback to both student and instructor. Using a process recording as an example, the article describes how to construct, introduce, apply, and evaluate a rubric. The importance of grounding the rubric in the knowledge base of the course and submitting its content for student and peer input are stressed as a means to enhance its validity and address some of the disadvantages associated with its use. The author encourages social work educators to develop, explore, and empirically assess this, and other, nontraditional approaches to assessment.

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Bennett, Guinevere S. "Comparison of interactive video test performance to overall class performance in a biomechanics course." Journal of Chiropractic Education 32, no. 1 (March 1, 2017): 32–35. http://dx.doi.org/10.7899/jce-16-00013.

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Objective: This study compared interactive video test performance and students' overall class performance. The hypothesis was that there would be a difference in video test performance compared to overall class performance. Methods: A total of 30 students participated in the pilot study from a master's level biomechanics course. Students completed four interactive video tests using EduCanon; content of videos included base of support, lever systems, scapulohumeral rhythm, and postural analysis. This content was reviewed with class discussion after completion of the interactive video test. The tests administered counted toward the participation portion of the final student grade. Student performance on the EduCanon interactive video test was compared to overall class grade using a paired t-test. Results: All 30 students completed the 4 EduCanon interactive video tests. Final class grades were greater compared to cumulative EduCanon test performance. There was no difference between performance using interactive video testing compared to students' overall class performance (t[29] = −1.43, p = .16). Conclusion: The results of this study did not support improved student assessment performance with incorporation of interactive video testing in the classroom environment. Continued research into new testing strategies is recommended to identify additional effective testing in the classroom.

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Sun, Lizhi, Danhui Chen, and Qingping Yang. "Key Influencing Factors Affecting the Student Academic Performance and Student Satisfactions Ratings: Evidence from Undergraduate Students in China." Global Research in Higher Education 5, no. 3 (September 5, 2022): p19. http://dx.doi.org/10.22158/grhe.v5n3p19.

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This paper has developed a sound and practical method to evaluate the key teaching quality including the student academic performance and student satisfaction ratings. The method makes use of the existing data already readily available in a Chinese university, focusing on the identification of key influencing factors affecting the student academic performance and student satisfactions ratings. The data analyses have shown the university student academic performance is significantly affected student gender, age, previous academic performance, settlements and occupations of parents. There is significant difference in the student ratings for different genders and academic positions of teaching staff. The student performance and satisfaction ratings also significantly vary in different years of intakes and different Schools/programs. The student’s university academic performance can be accurately predicted using artificial neural networks with a prediction error of about 7%. This approach can help the university to improve the student academic performance and student satisfactions.

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Kinash, Shelley, Vishen Naidu, Diana Knight, Madelaine-Marie Judd, Chenicheri Sid Nair, Sara Booth, Julie Fleming, Elizabeth Santhanam, Beatrice Tucker, and Marian Tulloch. "Student feedback: a learning and teaching performance indicator." Quality Assurance in Education 23, no. 4 (September 7, 2015): 410–28. http://dx.doi.org/10.1108/qae-10-2013-0042.

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Purpose – The paper aims to disseminate solutions to common problems in student evaluation processes. It proposes that student evaluation can be applied to quality assurance and improving learning and teaching. The paper presents solutions in the areas of: presenting outcomes as performance indicators, constructing appropriate surveys, improving response rates, reporting student feedback to students and student engagement as a feature of university quality assurance. Design/methodology/approach – The research approach of this paper is comparative case study, allowing in-depth exploration of multiple perspectives and practices at seven Australian universities. Process and outcome data were rigorously collected, analysed, compared and contrasted. Findings – The paper provides empirical evidence for student evaluation as an instrument of learning and teaching data analysis for quality improvement. It suggests that collecting data about student engagement and the student experience will yield more useful data about student learning. Furthermore, findings indicate that students benefit from more authentic inclusion in the evaluation process and outcomes. Research limitations/implications – Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further and apply to their own university contexts. Practical implications – The paper includes recommendations at the institution- and sector-wide levels to effectively use student evaluation as a university performance indicator and as a tool of change. Originality/value – This paper fulfils an identified need to examine student evaluation processes across institutions and focuses on the role of student evaluation in quality assurance.

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Omama Farooq, Syed Afzal Moshadi Shah , Shakir Hafeez. "Smartphone Addiction Factors Effecting University Student Performance." NUML International Journal of Business & Management 16, no. 2 (March 8, 2022): 1–13. http://dx.doi.org/10.52015/nijbm.v16i2.70.

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Smartphone addiction is a growing social issue globally, especially among young consumers. Few studies have examined the role of smartphone addiction and student performance in Pakistan. However, how daily life disturbance, positive anticipation, withdrawal, cyberspace orientation, overuse, tolerance, and student academic performance has not been examined in the literature in Pakistan. The purpose of the study is to examine the effect of daily life disturbance, positive anticipation, withdrawal, cyberspace orientation, overuse, and tolerance on student academic performance. The study has adopted a self-administered survey-based approach. A total of 375 responses were gathered from the university students in Pakistan. The study has used SPSS 25.0 version to analyse the data and report the findings. The findings indicate that ‘overuse’ has the most indirect effect on students’ performance, followed by Cyberspace and oriented relationship, tolerance, positive anticipation, and daily life disturbance. The study demands a particular intervention by the students to self-regulate their behaviour. Parents and teachers play their role in controlling mobile addiction. Policymakers may introduce policy-related interventions to control the excessive use of mobile phones. The study lays down future directions and discusses the limitations towards the end.

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Becker, Craig, Nelson Cooper, Kemal Atkins, and Susanne Martin. "What Helps Students Thrive? An Investigation of Student Engagement and Performance." Recreational Sports Journal 33, no. 2 (October 2009): 139–49. http://dx.doi.org/10.1123/rsj.33.2.139.

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Graduation rates, academic success, and health status are top priorities of universities related to student success. Overall it has been found that students academically and socially integrated to the campus are more likely to remain in college and graduate. This article presents a strategy and results of a study that analyzed the overall relationship Student Affairs programs had with student GPA and health status. The goal of this research was to discover what helps students thrive, not just survive at school. To study thriving, the theoretical model of salutogenesis was adapted to investigate factors related to student success as measured through academic performance and health status. Using electronically collected data from a sample of 691 students, the results of relationships between student engagement in Student Affairs programs, student academic performance, and health status have been reported. Emphasis areas for student affairs programs are suggested.

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Abrami, Philip C., and Deborah A. Mizener. "Student/instructor attitude similarity, student ratings, and course performance." Journal of Educational Psychology 77, no. 6 (December 1985): 693–702. http://dx.doi.org/10.1037/0022-0663.77.6.693.

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Smith, Lyle R. "Lesson Complexity, Student Performance, and Student Perception in Mathematics." Journal of Experimental Education 57, no. 3 (April 1989): 219–27. http://dx.doi.org/10.1080/00220973.1989.10806507.

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Natishan, M. E., L. C. Schmidt, and P. Mead. "Student Focus Group Results on Student Team Performance Issues." Journal of Engineering Education 89, no. 3 (July 2000): 269–72. http://dx.doi.org/10.1002/j.2168-9830.2000.tb00524.x.

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Pido, Muhamad Risman, Melizubaida Mahmud, and Sudirman Sudirman. "Teacher Performance on Student Learning Outcomes." Journal of Economic and Business Education 1, no. 1 (February 20, 2023): 21–29. http://dx.doi.org/10.37479/jebe.v1i1.16928.

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The purpose of this study was to determine the effect of teacher performance on student learning outcomes in integrated social studies subjects for class VIII at SMP Negeri 7 Telaga Biru, Gorontalo Regency. This study uses a quantitative approach, with survey research methods. The data used are primary data obtained from distributing questionnaires to Class VIII students at SMP Negeri 7 Telaga Biru, Gorontalo Regency. The number of sampling in this study amounted to 80 respondents. The data analysis technique used simple linear regression. The results showed that there was an influence of teacher performance on student learning outcomes in integrated social studies subjects for class VIII at SMP Negeri 7 Telaga Biru, Gorontalo Regency. The magnitude of the influence of teacher performance on student learning outcomes reached 48.8% while the remaining 51.2% was influenced by variables not examined.

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Alvi, Abdul Khaliq, Umar Safder Kayani, and Allah Bux Lakhan. "RELATIONSHIP OF SOCIAL MEDIA ADDICTION WITH ACADEMIC PERFORMANCE: MEDIATING ROLE OF STUDENT ENGAGEMENT." Gomal University Journal of Research 38, no. 02 (July 13, 2022): 160–70. http://dx.doi.org/10.51380/gujr-38-02-03.

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The current research addresses the issue of student academic performance while identifying its potential predictors. social media addiction is predicting variable and student performance is dependent variable whereas student engagement is mediating variable. Current research proposes following research hypotheses; firstly to examine the direct impact of Social Media addiction on the student academic performance and student engagement while checking the direct impact of social media addiction on the student engagement respectively. Secondly, current research examines mediating effect of student engagement in relation between social media addiction and student academic performance. Students of Govt. universities are the target population. 250 university students were selected with the help of the snowball sampling technique. Results reveal that all three hypotheses are accepted over significant outcomes of statistical procedures. In future research, other potential predictors of student academic performance like use of Facebook, use of Twitter may include in addition to target students of private universities along with students of Govt. universities and compare the results.

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