This document presents a conceptual framework for predicting student academic performance using classification algorithms. The framework uses factors like socioeconomic status, psychological attributes, cognitive attributes, and lifestyle to analyze student performance based on their semester GPA. The document proposes classifying student performance into three classes (first class, second class, third class) based on their first semester GPA. Various classification algorithms like Naive Bayes, random forest, and bagging are evaluated on the student data to identify the best model for predicting performance. The conceptual framework is intended to guide the development of a recommendation system that can help educational institutions identify at-risk students early and improve student outcomes.
Clustering Students of Computer in Terms of Level of ProgrammingEditor IJCATR
Educational data mining (EDM) is one of the applications of data mining. In educational data mining, there are two key domains, i.e. student domain and faculty domain. Different type of research work has been done in both domains.
In existing system the faculty performance has calculated on the basis of two parameters i.e. Student feedback and the result of student in that subject. In existing system we define two approaches one is multiple classifier approach and the other is a single classifier approach and comparing them, for relative evaluation of faculty performance using data mining
Techniques. In multiple classifier approach K-nearest neighbor (KNN) is used in first step and Rule based classification is used in the second step of classification while in single classifier approach only KNN is used in both steps of classification.
But in proposed system, I will analyse the faculty performance using 4 parameters i.e., student complaint about faculty, Student review feedback for faculty, students feedback, and students result etc.
For this proposed system I will be going to use opinion mining technique for analyzing performance of faculty and calculating score of each faculty.
Data Mining Techniques for School Failure and Dropout SystemKumar Goud
Abstract: Data mining techniques are applied to predict college failure and bum of the student. This is method uses real data on middle-school students for prediction of failure and drop out. It implements white-box classification strategies, like induction rules and decision trees or call trees. Call tree could be a call support tool that uses tree-like graph or a model of call and their possible consequences. A call tree is a flowchart-like structure in which internal node represents a "test" on an attribute. Attribute is the real information of students that is collected from college in middle or pedagogy, each branch represents the outcome of the test and each leaf node represents a class label. The paths from root to leaf represent classification rules and it consists of three kinds of nodes which incorporates call node, likelihood node and finish node. It is specifically used in call analysis. Using this technique to boost their correctness for predicting which students might fail or dropout (idler) by first, using all the accessible attributes next, choosing the most effective attributes. Attribute choice is done by using WEKA tool.
Keywords: dataset, classification, clustering.
Assessment and Evaluation System in Engineering Education of UG Programmes at...ijtsrd
Assessment is one of the most critical dimensions in engineering education process it focuses not only on identifying how many of the predefined education goals and objectives outcomes have been achieved but also works as a feedback component for educators to upgrade their teaching practices. The assessment can be seen as a link that it forms with other education processes. Lamprianou et al. 2009 point out that assessment is associated with the educational objectives of "evaluation, diagnosis, guidance, selection, placement, administration, prediction or grading. Assessment is one main factors that contribute to a high quality teaching and learning environment and student's performance as whole. It also makes clearer what teachers expect from students Biggs et al., 1999 . The perceived difficulty in this process is how assessment system, approaches and schemes can be standardized and adapted across the premier institutes NITs of in the country. Credit system has been used widely by many HEIs in India for over 20 years but no nationally agreed and rationalized framework of credit and Credit Transfer and Accumulation System is developed. The purpose of the literature review is to outline research studies in the assessment and evaluation systems being practicedand to highlight the studies that can be used in the research project undertaken. Specifically, the literature review attempts to address the following research questions What researches are undertaken nationally and internationally into the assessment system in higher education, especially engineering education What are the key findings from these researches What are the limits delimitations of these researches Are there research findings could be applied to engineering education at UG in NITs in India Are there any prime concern for future research in this area From this literature review, it is apparent that a very few number of studies have been conducted in higher education institutions but no research was found in the context of Engineering Education specific to UG programmes and NITs. However, many innovations are on the way to improvise the assessment and evaluation mechanisms in the engineering education especially in the context of Outcome Based Education OBE . J. P. Tegar | Shreya Gupta "Assessment and Evaluation System in Engineering Education of UG Programmes at Premier Institutes (NITs) in India - A Review of Literature" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30921.pdf Paper Url :https://www.ijtsrd.com/humanities-and-the-arts/education/30921/assessment-and-evaluation-system-in-engineering-education-of-ug-programmes-at-premier-institutes-nits-in-india--a-review-of-literature/j-p-tegar
Predictive and Statistical Analyses for Academic Advisory Supportijcsit
The ability to recognize students’ weakness and solving any problem may confront them in timely fashion is
always a target of all educational institutions. This study was designed to explore how can predictive and
statistical analysis support the academic advisor’s work mainly in analysis students’ progress. The sample
consisted of a total of 249 undergraduate students; 46% of them were Female and 54% Male. A one-way
analysis of variance (ANOVA) and t-test were conducted to analysis if there was different behaviour in
registering courses. Predictive data mining is used for support advisor in decision making. Several
classification techniques with 10-fold Cross-validation were applied. Among of them, C4.5 constitutes the
best agreement among the finding results.
Clustering Students of Computer in Terms of Level of ProgrammingEditor IJCATR
Educational data mining (EDM) is one of the applications of data mining. In educational data mining, there are two key domains, i.e. student domain and faculty domain. Different type of research work has been done in both domains.
In existing system the faculty performance has calculated on the basis of two parameters i.e. Student feedback and the result of student in that subject. In existing system we define two approaches one is multiple classifier approach and the other is a single classifier approach and comparing them, for relative evaluation of faculty performance using data mining
Techniques. In multiple classifier approach K-nearest neighbor (KNN) is used in first step and Rule based classification is used in the second step of classification while in single classifier approach only KNN is used in both steps of classification.
But in proposed system, I will analyse the faculty performance using 4 parameters i.e., student complaint about faculty, Student review feedback for faculty, students feedback, and students result etc.
For this proposed system I will be going to use opinion mining technique for analyzing performance of faculty and calculating score of each faculty.
Data Mining Techniques for School Failure and Dropout SystemKumar Goud
Abstract: Data mining techniques are applied to predict college failure and bum of the student. This is method uses real data on middle-school students for prediction of failure and drop out. It implements white-box classification strategies, like induction rules and decision trees or call trees. Call tree could be a call support tool that uses tree-like graph or a model of call and their possible consequences. A call tree is a flowchart-like structure in which internal node represents a "test" on an attribute. Attribute is the real information of students that is collected from college in middle or pedagogy, each branch represents the outcome of the test and each leaf node represents a class label. The paths from root to leaf represent classification rules and it consists of three kinds of nodes which incorporates call node, likelihood node and finish node. It is specifically used in call analysis. Using this technique to boost their correctness for predicting which students might fail or dropout (idler) by first, using all the accessible attributes next, choosing the most effective attributes. Attribute choice is done by using WEKA tool.
Keywords: dataset, classification, clustering.
Assessment and Evaluation System in Engineering Education of UG Programmes at...ijtsrd
Assessment is one of the most critical dimensions in engineering education process it focuses not only on identifying how many of the predefined education goals and objectives outcomes have been achieved but also works as a feedback component for educators to upgrade their teaching practices. The assessment can be seen as a link that it forms with other education processes. Lamprianou et al. 2009 point out that assessment is associated with the educational objectives of "evaluation, diagnosis, guidance, selection, placement, administration, prediction or grading. Assessment is one main factors that contribute to a high quality teaching and learning environment and student's performance as whole. It also makes clearer what teachers expect from students Biggs et al., 1999 . The perceived difficulty in this process is how assessment system, approaches and schemes can be standardized and adapted across the premier institutes NITs of in the country. Credit system has been used widely by many HEIs in India for over 20 years but no nationally agreed and rationalized framework of credit and Credit Transfer and Accumulation System is developed. The purpose of the literature review is to outline research studies in the assessment and evaluation systems being practicedand to highlight the studies that can be used in the research project undertaken. Specifically, the literature review attempts to address the following research questions What researches are undertaken nationally and internationally into the assessment system in higher education, especially engineering education What are the key findings from these researches What are the limits delimitations of these researches Are there research findings could be applied to engineering education at UG in NITs in India Are there any prime concern for future research in this area From this literature review, it is apparent that a very few number of studies have been conducted in higher education institutions but no research was found in the context of Engineering Education specific to UG programmes and NITs. However, many innovations are on the way to improvise the assessment and evaluation mechanisms in the engineering education especially in the context of Outcome Based Education OBE . J. P. Tegar | Shreya Gupta "Assessment and Evaluation System in Engineering Education of UG Programmes at Premier Institutes (NITs) in India - A Review of Literature" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30921.pdf Paper Url :https://www.ijtsrd.com/humanities-and-the-arts/education/30921/assessment-and-evaluation-system-in-engineering-education-of-ug-programmes-at-premier-institutes-nits-in-india--a-review-of-literature/j-p-tegar
Predictive and Statistical Analyses for Academic Advisory Supportijcsit
The ability to recognize students’ weakness and solving any problem may confront them in timely fashion is
always a target of all educational institutions. This study was designed to explore how can predictive and
statistical analysis support the academic advisor’s work mainly in analysis students’ progress. The sample
consisted of a total of 249 undergraduate students; 46% of them were Female and 54% Male. A one-way
analysis of variance (ANOVA) and t-test were conducted to analysis if there was different behaviour in
registering courses. Predictive data mining is used for support advisor in decision making. Several
classification techniques with 10-fold Cross-validation were applied. Among of them, C4.5 constitutes the
best agreement among the finding results.
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Predicting instructor performance using data mining techniques in higher educ...redpel dot com
Predicting instructor performance using data mining techniques in higher education
for more ieee paper / full abstract / implementation , just visit www.redpel.com
A Model for Predicting Students’ Academic Performance using a Hybrid of K-mea...Editor IJCATR
Higher learning institutions nowadays operate in a more complex and competitive due to a high demand from prospective
students and an emerging increase of universities both public and private. Management of Universities face challenges and concerns of
predicting students’ academic performance in to put mechanisms in place prior enough for their improvement. This research aims at
employing Decision tree and K-means data mining algorithms to model an approach to predict the performance of students in advance
so as to devise mechanisms of alleviating student dropout rates and improve on performance. In Kenya for example, there has been
witnessed an increase student enrolling in universities since the Government started free primary education. Therefore the Government
expects an increased workforce of professionals from these institutions without compromising quality so as to achieve its millennium
development and vision 2030. Backlog of students not finishing their studies in stipulated time due to poor performance is another
issue that can be addressed from the results of this research since predicting student performance in advance will enable University
management to devise ways of assisting weak students and even make more decisions on how to select students for particular courses.
Previous studies have been done Educational Data Mining mostly focusing on factors affecting students’ performance and also used
different algorithms in predicting students’ performance. In all these researches, accuracy of prediction is key and what researchers
look forward to try and improve.
Application of Higher Education System for Predicting Student Using Data mini...AM Publications
The aim of research paper is to improve the current trends in the higher education systems to understand
from the outside which factors might create loyal students. The necessity of having loyal students motivates higher
education systems to know them well, one way to do this is by using valid management and processing of the students
database. Data mining methods represent a valid approach for the extraction of precious information from existing
students to manage relations with future students. This may indicate at an early stage which type of students will
potentially be enrolled and what areas to concentrate upon in higher education systems for support. For this purpose
the data mining framework is used for mining related to academic data from enrolled students. The rule generation
process is based on the classification method. The generated rules are studied and evaluated using different
evaluation methods and the main attributes that may affect the student’s loyalty have been highlighted. Software that
facilitates the use of the generated rules is built which allows the higher education systems to predict the student’s
loyalty (numbers of enrolled students) so that they can manage and prepare necessary resources for the new enrolled students.
The effect of the OSGIPE learning model based on the Indonesian National Qual...IJAEMSJORNAL
This research is a package that was carried out in a period of 3 years to develop a learning model based on the framework of Indonesia's national qualifications in an effort to improve students' vocational high school soft skills. The first year conducted two years ago, a draft learning model was found, namely the OSGIPE model. In the second year, a formative evaluation was carried out on the OSGIPE model through one on one, small group, and limited field trials. There was a significant increase in students' soft skills amounting to 23.05%. In the third year which is this year, a summative evaluation through wide field trials it have been carried out and still show that there is a significant increase in students' soft skills amounting to 23.44 %. It means that the OSGIPE model was feasible and effectively used to improve the soft skills of vocational high school technology students. So, the OSGIPE model can be used as an operational product concistently.
E-Learning Readiness Assessment Tool for Philippine Higher Education Institut...IJITE
The growth of internet technologies changed learning strategies globally. The Philippines is no exemption. Due to its usefulness and potential, E-learning is becoming popular. But before these benefits would be enjoyed, it is very important for an institution to be assessed. This is to identify the needs and factors that directly affect their readiness. This study presents a readiness assessment tool for Philippine Higher Education Institutions. It also serves as a needs assessment instrument.
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and science were studied and compared. The purpose of this research is to predict the academic major of high school students using Bayesian networks. The effective factors have been used in academic major selection for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on each other, discretization data and processing them was performed by GeNIe. The proper course would be advised for students to continue their education.
The focus of this study is to seek the relevance of investing in Information Technology (IT) by the students. The research takes into account 50 students studying at different disciplines at Dhaka University. The respondents were visited randomly to get the relevant data. The result of the study suggests that students’ academic quality and knowledge enhancement have a relationship with investment in IT though the relationship is not significant. The result of hypothesis testing shows that students those have invested in personal computer and internet secure comparatively higher cumulative grade point average (CGPA) rather than those who haven’t invested on these IT tools. But the likelihood of investing higher amount in IT will pay-off better CGPA is not found thus there is no association of good result and investing heavily on IT. However, the findings of this exploratory study offer insights that the money invested in IT for academic purpose is more advantageous than otherwise be invested especially for those students whose academic curriculum mainly decorated in accordance with the modern up-to-date era of Information Technology. Eventually, this study will help concerned students, guardians and academicians understanding how important IT is for student’s academic performance.
A PRELIMINARY SURVEY ON AUTOMATED SCREENING TOOLS TOWARDS LEARNING DISABILITIESijma
Subsequently, there exist various kinds of screening tools for learning disabilities but most of these
screening tools only restricted to static binary output, less attractive, stressful, boring, and time consuming
which lead to incomplete activities and unfulfilled objectives. In addition, most of them only targeted on
dyslexia, dyscalculia and autism. This preliminary study aims to identify current automated screening tools
tailoring for learning disabilities domain. It is guided by several important steps starting from the selection
from multiple digital databases (information sources), categorization (study selection), comparison (search
and data selection) and summarization of appropriate literature reviews, leading towards a more thorough
analysis. Findings indicate that there are various kinds of screening tools available in the market with such
different techniques and methods, majorly are interactive and attractive multimedia approaches and
artificial intelligence approaches. Thus, the findings are beneficial in the enhancement of future works
towards screening and diagnosis in learning disabiliti
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Predicting instructor performance using data mining techniques in higher educ...redpel dot com
Predicting instructor performance using data mining techniques in higher education
for more ieee paper / full abstract / implementation , just visit www.redpel.com
A Model for Predicting Students’ Academic Performance using a Hybrid of K-mea...Editor IJCATR
Higher learning institutions nowadays operate in a more complex and competitive due to a high demand from prospective
students and an emerging increase of universities both public and private. Management of Universities face challenges and concerns of
predicting students’ academic performance in to put mechanisms in place prior enough for their improvement. This research aims at
employing Decision tree and K-means data mining algorithms to model an approach to predict the performance of students in advance
so as to devise mechanisms of alleviating student dropout rates and improve on performance. In Kenya for example, there has been
witnessed an increase student enrolling in universities since the Government started free primary education. Therefore the Government
expects an increased workforce of professionals from these institutions without compromising quality so as to achieve its millennium
development and vision 2030. Backlog of students not finishing their studies in stipulated time due to poor performance is another
issue that can be addressed from the results of this research since predicting student performance in advance will enable University
management to devise ways of assisting weak students and even make more decisions on how to select students for particular courses.
Previous studies have been done Educational Data Mining mostly focusing on factors affecting students’ performance and also used
different algorithms in predicting students’ performance. In all these researches, accuracy of prediction is key and what researchers
look forward to try and improve.
Application of Higher Education System for Predicting Student Using Data mini...AM Publications
The aim of research paper is to improve the current trends in the higher education systems to understand
from the outside which factors might create loyal students. The necessity of having loyal students motivates higher
education systems to know them well, one way to do this is by using valid management and processing of the students
database. Data mining methods represent a valid approach for the extraction of precious information from existing
students to manage relations with future students. This may indicate at an early stage which type of students will
potentially be enrolled and what areas to concentrate upon in higher education systems for support. For this purpose
the data mining framework is used for mining related to academic data from enrolled students. The rule generation
process is based on the classification method. The generated rules are studied and evaluated using different
evaluation methods and the main attributes that may affect the student’s loyalty have been highlighted. Software that
facilitates the use of the generated rules is built which allows the higher education systems to predict the student’s
loyalty (numbers of enrolled students) so that they can manage and prepare necessary resources for the new enrolled students.
The effect of the OSGIPE learning model based on the Indonesian National Qual...IJAEMSJORNAL
This research is a package that was carried out in a period of 3 years to develop a learning model based on the framework of Indonesia's national qualifications in an effort to improve students' vocational high school soft skills. The first year conducted two years ago, a draft learning model was found, namely the OSGIPE model. In the second year, a formative evaluation was carried out on the OSGIPE model through one on one, small group, and limited field trials. There was a significant increase in students' soft skills amounting to 23.05%. In the third year which is this year, a summative evaluation through wide field trials it have been carried out and still show that there is a significant increase in students' soft skills amounting to 23.44 %. It means that the OSGIPE model was feasible and effectively used to improve the soft skills of vocational high school technology students. So, the OSGIPE model can be used as an operational product concistently.
E-Learning Readiness Assessment Tool for Philippine Higher Education Institut...IJITE
The growth of internet technologies changed learning strategies globally. The Philippines is no exemption. Due to its usefulness and potential, E-learning is becoming popular. But before these benefits would be enjoyed, it is very important for an institution to be assessed. This is to identify the needs and factors that directly affect their readiness. This study presents a readiness assessment tool for Philippine Higher Education Institutions. It also serves as a needs assessment instrument.
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and science were studied and compared. The purpose of this research is to predict the academic major of high school students using Bayesian networks. The effective factors have been used in academic major selection for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on each other, discretization data and processing them was performed by GeNIe. The proper course would be advised for students to continue their education.
The focus of this study is to seek the relevance of investing in Information Technology (IT) by the students. The research takes into account 50 students studying at different disciplines at Dhaka University. The respondents were visited randomly to get the relevant data. The result of the study suggests that students’ academic quality and knowledge enhancement have a relationship with investment in IT though the relationship is not significant. The result of hypothesis testing shows that students those have invested in personal computer and internet secure comparatively higher cumulative grade point average (CGPA) rather than those who haven’t invested on these IT tools. But the likelihood of investing higher amount in IT will pay-off better CGPA is not found thus there is no association of good result and investing heavily on IT. However, the findings of this exploratory study offer insights that the money invested in IT for academic purpose is more advantageous than otherwise be invested especially for those students whose academic curriculum mainly decorated in accordance with the modern up-to-date era of Information Technology. Eventually, this study will help concerned students, guardians and academicians understanding how important IT is for student’s academic performance.
A PRELIMINARY SURVEY ON AUTOMATED SCREENING TOOLS TOWARDS LEARNING DISABILITIESijma
Subsequently, there exist various kinds of screening tools for learning disabilities but most of these
screening tools only restricted to static binary output, less attractive, stressful, boring, and time consuming
which lead to incomplete activities and unfulfilled objectives. In addition, most of them only targeted on
dyslexia, dyscalculia and autism. This preliminary study aims to identify current automated screening tools
tailoring for learning disabilities domain. It is guided by several important steps starting from the selection
from multiple digital databases (information sources), categorization (study selection), comparison (search
and data selection) and summarization of appropriate literature reviews, leading towards a more thorough
analysis. Findings indicate that there are various kinds of screening tools available in the market with such
different techniques and methods, majorly are interactive and attractive multimedia approaches and
artificial intelligence approaches. Thus, the findings are beneficial in the enhancement of future works
towards screening and diagnosis in learning disabiliti
The International Journal of Mechanical Engineering Research and Technology is an international online journal published Quarterly offers fast publication schedule whilst maintaining rigorous peer review. The use of recommended electronic formats for article delivery expedites the process All submitted research articles are subjected to the immediate rapid screening by editors consultation with Editorial Board or others working in the field of appropriate to ensure that they are likely to be the level of interest and importance of appropriate for the journal.
ISSN 2454-535X
International Journal of Mechanical Engineering Research and Technology aims to provide the best possible service to authors of original research articles, and the fairest system of peer review.
The International Journal of Mechanical Engineering Research and Technology is an international online journal in English published Quarterly. This offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. All submitted research articles are subjected to immediate rapid screening by the editors, in consultation with the Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal.
Data Mining Techniques in Higher Education an Empirical Study for the Univer...IJMER
Nowadays, ones of the biggest challenges that educational institutions face is the explosive
growth of educational data. and how to use these data to improve the quality of managerial decisions.
Data mining, as an analytical tools that can be used to extract meaningful knowledge from large data
sets, can be used to achieve this goal.
This paper addresses the applications of Educational Data Mining (EDM) to extract useful information
from registration information of student at university of Palestine in Gaza strip. The data include five
years period [2005-2011] by providing analytical tool to view and use this information for decision
making processes by taking real life example such as grade and GPA for the students. abstract should
summarize the content of the paper.
Accurate prediction and early identification of student at-risk of attrition are of high concern for higher
educational institutions (HEIs). It is of a great importance not only to the students but also to the
educational administrators and the institutions in the areas of improving academic quality and
efficient utilisation of the available resources for effective intervention. However, despite the different
frameworks and various models that researchers have used across institutions for predicting performance,
only negligible success has been recorded in terms of accuracy, efficiency and reduction of student
attrition. This has been attributed to the inadequate and selective use of variables for the predictive models.
AN INTEGRATED SYSTEM FRAMEWORK FOR PREDICTING STUDENTS’ ACADEMIC PERFORMANCE ...ijcsit
Accurate prediction and early identification of student at-risk of attrition are of high concern for higher educational institutions (HEIs). It is of a great importance not only to the students but also to the educational administrators and the institutions in the areas of improving academic quality and efficient utilisation of the available resources for effective intervention. However, despite the different frameworks and various models that researchers have used across institutions for predicting performance, only negligible success has been recorded in terms of accuracy, efficiency and reduction of student
attrition. This has been attributed to the inadequate and selective use of variables for the predictive models. This paper presents a multi-dimensional and an integrated system framework that involves considerable learners’ input and engagement in predicting their academic performance and intervention in HEIs. The purpose and functionality of the framework are to produce a comprehensive, unbiased and efficient way of predicting student performance that its implementation is based upon multi-sources data and database
system. It makes use of student demographic and learning management system (LMS) data from the institutional databases as well as the student psychosocial-personality (SPP) data from the survey collected from the student to predict performance. The proposed approach will be robust, generalizable, and possibly give a prediction at a higher level of accuracy that educational administrators can rely on for providing timely intervention to students.
Accurate prediction and early identification of student at-risk of attrition are of high concern for higher educational institutions (HEIs). It is of a great importance not only to the students but also to the educational administrators and the institutions in the areas of improving academic quality and efficient utilisation of the available resources for effective intervention. However, despite the different frameworks and various models that researchers have used across institutions for predicting performance, only negligible success has been recorded in terms of accuracy, efficiency and reduction of student attrition. This has been attributed to the inadequate and selective use of variables for the predictive models. This paper presents a multi-dimensional and an integrated system framework that involves considerable learners’ input and engagement in predicting their academic performance and intervention in HEIs. The purpose and functionality of the framework are to produce a comprehensive, unbiased and efficient way of predicting student performance that its implementation is based upon multi-sources data and database system. It makes use of student demographic and learning management system (LMS) data from the institutional databases as well as the student psychosocial-personality (SPP) data from the survey collected from the student to predict performance. The proposed approach will be robust, generalizable, and possibly give a prediction at a higher level of accuracy that educational administrators can rely on for providing timely intervention to students. --
A COMPARATIVE ANALYSIS OF SELECTED STUDIES IN STUDENT PERFORMANCE PREDICTIONIJDKP
Predicting student success has long been an interest of institutions of higher education as well as
organisations responsible for preparing high-stake, standardised tests administered at national and
international levels. This study discusses how performance prediction studies have evolved from those that
use demographic data and high school grades to predict success in college to those that utilise
sophisticated data collected in non-traditional educational platforms to predict end-of-course performance
and to those that show how student progress can be tracked in a continuous manner. A total of 56 studies
published since the nineties are discussed. Views on strengths and weaknesses as well as observed
opportunities for improvement are presented. The consistently high results reported in many of the studies
shall convince the reader that automated solutions to the problem of predicting student progress and
performance can either be tailored for specific settings or can be adopted from similar settings in which
they have been utilized successfully. A recommendation on how to build upon recent success is provided
Similar to IRJET- A Conceptual Framework to Predict Academic Performance of Students using Classification Algorithm (20)
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.