scholarly journals Implementasi Fuzzy C-Means dan Possibilistik C-Means Pada Data Performance Mahasiswa

2020 ◽  
Vol 6 (2) ◽  
pp. 39-48
Author(s):  
Gadis Retno Apsari ◽  
Mohammad Syaiful Pradana ◽  
Novita Eka Chandra
Keyword(s):  
Objective Function ◽  
Grade Point Average ◽  
Student Performance ◽  
Fuzzy Clustering ◽  
Performance Data ◽  
Grade Point ◽  
Fuzzy C Means ◽  
Student Performance Data ◽  
Minimum Objective Function

Students are the most important component in a university, especially private universities especially Universitas Islam Darul ‘ulum (Unisda) Lamongan. One of the most important roles of students for higher education is achievement. This study aims to determine the role of Fuzzy Clustering in classifying student performance data. The data includes GPA (Grade Point Average), ECCU (Extra-Curricular Credit Unit), attendance, and students' willingness to learn. So that groups of students who have the potential to have achievements can be identified. In this case, the grouping of student performance data uses Fuzzy Clustering by applying the Fuzzy C-Means (FCM) and Possibilistic C-Means (PCM) algorithms with the help of Matlab. In the FCM algorithm, the membership degree is updated so as to produce a minimum objective function value. Meanwhile, the PCM algorithm uses a T matrix, which shows the peculiarities of the data which are also based on minimizing the objective function.

The Relation between Methods of Graphing Student Performance Data and Achievement: A Meta-Analysis

1986 ◽  
Vol 8 (3) ◽  
pp. 5-13 ◽  
Author(s):  
Lynn S. Fuchs ◽  
Douglas Fuchs
Keyword(s):  
Student Performance ◽  
Analysis Of Variance ◽  
Meta Analysis ◽  
Performance Data ◽  
Effect Sizes ◽  
Education Practice ◽  
Equal Interval ◽  
Data Source ◽  
Student Performance Data ◽  
Over Time

This meta-analysis investigated the effects on achievement of type of graphing paper employed in displaying student performance data collected over time. The data source was 15 controlled studies with 16 effect sizes. The average weighted unbiased effect sizes for 6-cycle and equal interval paper, respectively, were .53 and .46. Hedges's analogue to analysis of variance indicated this difference was not statistically reliable. Implications for special education practice are discussed.

The Role of Institutional Selectivity in the Prediction of Podiatric Medical School Performance

2010 ◽  
Vol 100 (6) ◽  
pp. 479-486 ◽  
Author(s):  
Kevin M. Smith ◽  
Simon Geletta
Keyword(s):  
Medical School ◽  
Grade Point Average ◽  
School Performance ◽  
Ethnic Origin ◽  
First Year ◽  
Grade Point ◽  
Medical College ◽  
Institutional Selectivity ◽  
Admission Test

Background: This pilot study explores the influence of preadmission data on podiatric medical school performance, specifically, the role of undergraduate institutional selectivity. This type of study has never been described in the podiatric medical education literature. We conducted a longitudinal analysis of preadmission data on 459 students from the graduating classes of 2000 to 2009 at the College of Podiatric Medicine and Surgery at Des Moines University. Methods: Multivariate linear regression was used to assess the relationship between performance during the first year of podiatric medical school and a set of independent variables that represent certain preadmission student characteristics. Student demographic characteristics, such as race/ethnicity and sex, were also included in the regression analysis as control variables. Results: The regression analysis revealed that ethnic origin, undergraduate grade point average, Medical College Admission Test biological science and verbal reasoning scores, and institutional selectivity together had a significant effect on the dependent variable (F = 18.3; P < .001). The variance for the independent variable/constant variables was 32%. Almost twice as many students were dismissed or withdrew in poor academic standing who attended undergraduate institutions in the lowest selectivity category. Conclusions: This analysis revealed that in the College of Podiatric Medicine and Surgery, some preadmission variables, such as institutional selectivity, undergraduate grade point average, ethnic origin, and Medical College Admission Test verbal reasoning and biological science scores, are statistically significant in predicting first-year podiatric medical school grade point average. The selectivity of a student’s undergraduate institution should be considered when screening potential podiatric medical school applicants. (J Am Podiatr Med Assoc 100(6): 479–486, 2010)

scholarly journals PerformanceVis: Visual analytics of student performance data from an introductory chemistry course

2019 ◽  
Vol 3 (4) ◽  
pp. 166-176
Author(s):  
Haozhang Deng ◽  
Xuemeng Wang ◽  
Zhiyi Guo ◽  
Ashley Decker ◽  
Xiaojing Duan ◽  
...  
Keyword(s):  
Student Performance ◽  
Visual Analytics ◽  
Performance Data ◽  
Introductory Chemistry ◽  
Student Performance Data

scholarly journals The Role of Motivational Strategies in Prediction of Grade Point Average Among Students of Kermanshah University of Medical Sciences

2020 ◽  
Vol 8 (2) ◽  
Author(s):  
Mehdi Mirzaei-Alavijeh ◽  
Yahya Pasdar ◽  
Naser Hatamzadeh ◽  
Laleh Solaimanizadeh ◽  
Shiva Khashij ◽  
...  
Keyword(s):  
Grade Point Average ◽  
Motivational Strategies ◽  
Medical Sciences ◽  
Grade Point

School climate and culture : a case study on the impact of student perception

2018 ◽  
Author(s):  
◽  
Lindsay N. Kearns
Keyword(s):  
School Climate ◽  
Grade Point Average ◽  
Student Performance ◽  
Negative Impact ◽  
Student Perception ◽  
Low Grade ◽  
Chi Square ◽  
Grade Point ◽  
School Climate And Culture ◽  
The Impact

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This study takes a deeper look into the factors that create school climate and culture and how those factors are perceived by students. A quantitative study was conducted by administering a survey to 199 students at one rural Midwest high school. A chi-square test was performed to determine differences between two groups; high and low-grade point average and high and low attendance. Many statistically significant findings were found especially among the low-grade point average and low attendance groups. While students appeared to be overall pleased with some areas within the school such as safety, the biggest negative impact was seen in student stress levels and lack of connections with faculty members. The results suggest that a positive climate and culture can also influence student grade point average and attendance which can further impact student performance areas that toward which educators strive.

School Related Daydreams and Test Anxiety

1983 ◽  
Vol 3 (2) ◽  
pp. 133-138 ◽  
Author(s):  
Steven R. Gold ◽  
Scott W. Minor
Keyword(s):  
Grade Point Average ◽  
Test Anxiety ◽  
Cognitive Activity ◽  
Grade Point Averages ◽  
Grade Point ◽  
Mediating Role ◽  
Negative Thoughts ◽  
Self Talk ◽  
The Relationship

Current models of test anxiety emphasize the mediating role of negative and disruptive internal cognitive activity. Highly test anxious students have been reported to engage in more negative thoughts and fewer positive thoughts during an actual exam. The present study examined the relationship between school related daydreams and level of test anxiety. It was hypothesized that daydream outcome and mood would be correlated with self reported test anxiety, grade point average and self reported arousal and self talk during an exam. Overall the grade point average was the measure most relevant to daydreams. Students with high grade point averages tended to have more happy and successful daydreams and fewer failure daydreams. Self talk during the exam was unrelated to daydream measures. Suggestions for further research were presented.

PLCs on steroids

2017 ◽  
Vol 98 (5) ◽  
pp. 67-71
Author(s):  
Michael J. Wasta
Keyword(s):  
Professional Learning Communities ◽  
Learning Communities ◽  
Student Performance ◽  
Professional Learning ◽  
Teacher Practice ◽  
Performance Data ◽  
Team Members ◽  
Improve Instruction ◽  
Student Performance Data

Research on educators’ professional learning communities (PLCs) suggest that while they often help teachers to make sense of student performance data, they tend to spend relatively little time studying what teachers actually do in the classroom. Evidence suggests that, given modest amounts of guidance and support, PLCs can collect useful data on teacher practice, and team members can identify specific, actionable ways in which to improve instruction.

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