Factors Affecting Student Performance in Law School Economics Courses

1980 ◽  
Vol 12 (1) ◽  
pp. 54 ◽  
Author(s):  
John J. Siegfried
Keyword(s):  
Student Performance ◽  
Law School ◽  
Factors Affecting ◽  
Economics Courses

The Impact of PowerPoint on Student Performance and Course Evaluations in Economics Courses: An Experiment at Six Institutions

2008 ◽  
Author(s):  
Lisa Daniels ◽  
John C. Kane ◽  
Brian P. Rosario ◽  
Thomas A. Creahan ◽  
Carlos F. Liard-Muriente ◽  
...  
Keyword(s):  
Student Performance ◽  
Course Evaluations ◽  
Economics Courses ◽  
The Impact

scholarly journals An examination of the factors affecting the performance of Management Accounting students at the Durban University of Technology

2020 ◽  
Author(s):  
◽  
Stephanie Caroline Singh
Keyword(s):  
South Africa ◽  
Student Performance ◽  
Positive Impact ◽  
Management Accounting ◽  
Cost Accounting ◽  
Accounting Students ◽  
Factors Affecting ◽  
Five Factors ◽  
University Of Technology ◽  
The Impact

The success of a module at a university of technology is measured by student performance. At the Durban University of Technology in the Department of Management Accounting, students in their second year of study struggle with conceptualising content in Cost Accounting two which affects their performance. The purpose of this study was to identify the factors which may impact on the performance of Cost Accounting two students and to determine if these factors have a significant association with a student’s performance in Cost Accounting two. Many studies have identified various factors which may influence students’ academic performance. For the purpose of this study, five factors that may affect student performance were identified and examined. The independent variables or factors identified were attendance, age, gender, grade 12 results and language. The dependent variable for this study was performance (in Cost Accounting two). In order to measure the performance of students included in the study, the percentage achieved in Cost Accounting two for the semester was used. Although studies have been conducted on student performance at universities across South Africa and around the world, limited studies were conducted on the performance of Cost Accounting two students within South Africa. The study aimed to identify the factors that affect the performance of Cost and Management Accounting students at a university of technology and the impact of those factors on performance. The study found that only student attendance has a positive impact on student performance in Cost Accounting two. The findings of this study may be useful to the Department of Management Accounting at the DUT and other universities of technology. It is hoped that the current study will be useful to other teachers of cost and management accounting at universities on which factors influence the academic achievement of students.

Ecological Assessment: Implications for Teachers of Learning Disabled Students

1982 ◽  
Vol 5 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Timothy E. Heron ◽  
William L. Heward
Keyword(s):  
Student Performance ◽  
Global Assessment ◽  
Learning Disabled ◽  
Ecological Assessment ◽  
Assessment Data ◽  
Disabled Students ◽  
Factors Affecting ◽  
Behavior Difficulties ◽  
Starting Point ◽  
Criterion Referenced

Results obtained from normative or criterion-referenced assessments are sufficient to determine the starting point for most students' academic or social instruction. However, some students' learning/behavior difficulties are subtle and complex and, thus, necessitate a more global assessment to ensure the most appropriate instructional approach. This paper discusses the rationale for conducting an ecological assessment, a model for conceptualizing ecological assessment data, factors affecting student performance, sources of ecological assessment data, and implications of such data for the teacher of learning disabled students.

THE IMPACT OF LECTURE CAPTURE ON STUDENT PERFORMANCE IN ECONOMICS COURSES

2014 ◽  
Vol 14 (3) ◽  
pp. 83-92
Author(s):  
Neil Terry ◽  
Neil Meredith ◽  
Kyle Williams ◽  
Duane Rosa
Keyword(s):  
Student Performance ◽  
Lecture Capture ◽  
Economics Courses ◽  
The Impact

Factors Affecting Students’ Performance in Distributed Pair Programming

2017 ◽  
Vol 57 (2) ◽  
pp. 513-544 ◽  
Author(s):  
Stelios Xinogalos ◽  
Maya Satratzemi ◽  
Alexander Chatzigeorgiou ◽  
Despina Tsompanoudi
Keyword(s):  
Student Performance ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Pair Programming ◽  
Individual Student ◽  
Broadband Internet ◽  
Factors Affecting ◽  
Final Exams ◽  
The Individual ◽  
Pair Compatibility

Pair Programming has been shown to increase productivity and code quality not only in professional software development but also in the context of programming education. The provision of broadband Internet access gave rise to Distributed Pair Programming (DPP) enabling two programmers to collaborate remotely. To gain insight into the benefits of DPP, we performed an empirical study on an object-oriented programming course where 62 students carried out assignments through a DPP platform. The goal of the study is to investigate, in the context of DPP, whether prior programming skills (assessed at the level of student, his or her partner and pair) and pair compatibility are related to student performance. To further examine the effect of DPP on learning outcomes, we have studied whether a pair’s performance on DPP assignments is related to the students’ grade. The findings indicate that the student’s actual skill and the pair’s actual skill affect his or her performance in an object-oriented programming course. The results also suggested that there is no association between pair compatibility and his or her own performance. Finally, pair performance on DPP assignments is related to the individual student performance in the final exams. Such evidence can be used to guide instructors when planning DPP assignments and especially when forming student pairs.

scholarly journals Role of FCBF Feature Selection in Educational Data Mining

2020 ◽  
Vol 39 (4) ◽  
pp. 772-778
Author(s):  
Maryam Zaffar ◽  
Manzoor Ahmad Hashmani ◽  
K.S. Savita ◽  
Syed Sajjad Hussain Rizvi ◽  
Mubashar Rehman
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Prediction Model ◽  
Student Performance ◽  
Performance Prediction ◽  
Prediction Models ◽  
Educational Data Mining ◽  
Action Plans ◽  
Factors Affecting ◽  
Academic Organization

The Educational Data Mining (EDM) is a very vigorous area of Data Mining (DM), and it is helpful in predicting the performance of students. Student performance prediction is not only important for the student but also helpful for academic organization to detect the causes of success and failures of students. Furthermore, the features selected through the students’ performance prediction models helps in developing action plans for academic welfare. Feature selection can increase the prediction accuracy of the prediction model. In student performance prediction model, where every feature is very important, as a neglection of any important feature can cause the wrong development of academic action plans. Moreover, the feature selection is a very important step in the development of student performance prediction models. There are different types of feature selection algorithms. In this paper, Fast Correlation-Based Filter (FCBF) is selected as a feature selection algorithm. This paper is a step on the way to identifying the factors affecting the academic performance of the students. In this paper performance of FCBF is being evaluated on three different student’s datasets. The performance of FCBF is detected well on a student dataset with greater no of features.

scholarly journals PENGARUH FAKTOR-FAKTOR PROFESIONAL, PERSONAL, LINGKUNGAN, TEKNOLOGI INFORMASI DAN KEPUASAN TERHADAP PRESTASI MAHASISWA MELALUI PENGGUNAAN E-LEARNING BERKELANJUTAN SEBAGAI VARIABEL MEDIASI

2021 ◽  
Vol 5 (2) ◽  
pp. 417
Author(s):  
Metodius Manek ◽  
Justine Tanuwijaya
Keyword(s):  
Student Achievement ◽  
Student Performance ◽  
Formal Education ◽  
Descriptive Analysis ◽  
Sustainable Use ◽  
Research Needs ◽  
Personal Factors ◽  
Factors Affecting ◽  
Determinant Factors ◽  
E Learning

Penggunaan e-learning berkelanjutan sangat urgen diciptakan dan dikembangkan di setiap lembaga pendidikan formal karena dapat memutus rantai penyebaran covid-19 sekaligus meningkatkan prestasi peserta didik pada era normal baru ini.  Dengan demikian perlu diketahui faktor-faktor determinan yang dapat mewujudkan penggunaan e-learning berkelanjutan. Tujuan penelitian ini untuk membuktikan secara empiris pengaruh faktor-faktor profesional, personal, lingkungan, teknologi informasi dan kepuasan terhadap prestasi mahasiswa di Fakultas Ekonomi dan Bisnis Universitas Trisakti melalui penggunaan e-learning berkelanjutan sebagai variabel mediasi. Metode yang digunakan adalah metode kuantitatif melalui penyebaran 50 item kuesioner berskala Likert 5 poin via google form kepada 279 responden. Data penelitian dianalisis dengan analisis deskriptif dan pengujian hipotesis dengan menggunakan SEM. Hasil penelitian membuktikan bahwa faktor determinan yang paling signifikan mempengaruhi penggunaan e-learning berkelanjutan adalah faktor-faktor personal. Terbukti secara empiris juga bahwa penggunaan e-learning berkelanjutan mempengaruhi prestasi mahasiswa, sehingga perlu diberi perhatian serius pada faktor-faktor personal. Hasil penelitian diharapkan berkontribusi pada pihak manajemen FEB untuk menciptkan dan mengembangkan e-learning yang mendukung efektivitas dan prestasi mahasiswa. Saran untuk penelitian selanjutnya perlu memberikan pemahaman tentang e-learning sebelum membuat penelitian dengan tema yang sama atau membuat penelitian tentang tingkat literasi terhadap cakupan makna e-learning berkelanjutan.  Sustainable use of e-learning is very urgent created and developed in any formal education institutions because it can break the chain of covid-19 while improving the achievement of students in this new normal era. Therefore, it takes determinant factors that can realize the use of sustainable e-learning. The purpose of this study is to empirically prove the influence of professional, personal, environmental, information technology and satisfaction factors on student achievement at the Faculty of Economics and Business, Trisakti University through the use of sustainable e-learning as a mediating variable. The method used is quantitative method through the deployment of 50 item 5-point Likert scale questionnaire via google form to 279 respondents. The research data were analyzed using descriptive analysis and hypothesis testing using SEM. The results of this study prove that the most significant determinant factors affecting the use of sustainable e-learning are personal factors. It is also empirically proven that the use of sustainable e-learning affects student achievement. Therefore, it is necessary to pay serious attention to personal factors. This finding is expected can give contribution for management of Faculty of Economics and Business for creating and developing e-learning which supports effectiveness and student performance. Therefore, the suggestion is that further research needs to provide an understanding of e-learning before making research with the same theme or making research on the level of literacy on the scope of meaning of sustainable e-learning.

scholarly journals Factors Affecting Learning Gains among Students in Microbiology Class: A Preliminary Study Between a U.S. Community College and a Canadian Comprehensive University

Fine Focus ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 12-33
Author(s):  
Naowarat Cheeptham ◽  
Archana Lal
Keyword(s):  
Community College ◽  
Student Performance ◽  
Higher Learning ◽  
Learning Gains ◽  
Comprehensive University ◽  
Factors Affecting ◽  
Student Demographics ◽  
Post Test ◽  
Major Factors ◽  
Science Classes

Though in the past, serious concerns have been raised about students’ interest and learning gains in STEM courses, not much research has been done to examine the differences in learning science at community colleges and universities. The purpose of this paper is to close this gap. This paper analyzes the influence of students’ demographics, preparedness, major, and attitudes on their learning gains in an introductory microbiology class at a community college vs. a university. Student demographics, information about their preparedness level, major, and attitudes were collected in a questionnaire and students’ learning gains were assessed by comparing student performance on a pre- and post-test on four different topics in microbiology. Our results indicate that students’ majors and attitudes such as their willingness to actively participate in the classroom discussions and spend time outside the classroom to learn are major factors that enhance their learning. Age and marital status positively impact learning gains while gender, employment status, and citizenship status show no impact on learning gains in students. Our results also indicate that students at the community college who had less exposure to science classes in high school or biology classes in college achieved statistically higher learning gains despite having overall lower scores on two of the four post-tests.

scholarly journals A Practical Model for the Evaluation of High School Student Performance Based on Machine Learning

2021 ◽  
Vol 11 (23) ◽  
pp. 11534
Author(s):  
Mostafa Zafari ◽  
Abolghasem Sadeghi-Niaraki ◽  
Soo-Mi Choi ◽  
Ali Esmaeily
Keyword(s):  
Machine Learning ◽  
High School ◽  
High School Students ◽  
Student Performance ◽  
Support Vector ◽  
School Students ◽  
Online Questionnaire ◽  
Factors Affecting ◽  
Original Dataset ◽  
Artificial Neural Network Ann

The objective of this research is to develop an machine learning (ML) -based system that evaluates the performance of high school students during the semester and identify the most significant factors affecting student performance. It also specifies how the performance of models is affected when models run on data that only include the most important features. Classifiers employed for the system include random forest (RF), support vector machines (SVM), logistic regression (LR) and artificial neural network (ANN) techniques. Moreover, the Boruta algorithm was used to calculate the importance of features. The dataset includes behavioral information, individual information and the scores of students that were collected from teachers and a one-by-one survey through an online questionnaire. As a result, the effective features of the database were identified, and the least important features were eliminated from the dataset. The ANN accuracy, which was the best accuracy in the original dataset, was reduced in the decreased dataset. On the contrary, SVM performance was improved, which had the highest accuracy among other models, with 0.78. Moreover, the LR and RF models could provide the same performance in the decreased dataset. The results showed that ML models are influential for evaluating students, and stakeholders can use the identified effective factors to improve education.

Sign in / Sign up

Export Citation Format

Share Document