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Using institutional data to predict student course selections in higher education

Ivana Ognjanovic, Dragan Gasevic, Shane Dawson
2016 The Internet and higher education  
In such cases, institutions may give a priority for course selection to students with higher academic achievement (i.e. higher GPA); and (iv) where the overlap between course offerings is not permitted  ...  Although complex, accurate predictions regarding a student's future course selection can be developed through the analysis of student data extracted from institutional information systems (e.g. students  ... 
doi:10.1016/j.iheduc.2015.12.002 fatcat:mu3rpfdtyzg23kpq25uw2tmcpe


Priti Shailesh Patel, Dr. Dharmendra Bhatti, Dr. Desai S.G.
2018 Indian Journal of Computer Science and Engineering  
, Faculty_Nameen, Schoolbranches_Descar,School_Avg, School_Year for Arabic higher education institute to develop an intelligent decision support system. [7] In this, some papers are focus on dropout ratio  ...  This Recent era many educational data are using by researchers for fining hidden pattern of students learning ability, students' academic performance, student's behaviour towards study and so many issues  ...  Data collection: In this paper, we are representing parameters which highly affect the decision of students' course selection. For this we used M.Sc.  ... 
doi:10.21817/indjcse/2018/v9i2/180902007 fatcat:bnec2sadl5ba5kwzee7ryufoom

Data Mining Model for Predicting Student Enrolment in STEM Courses in Higher Education Institutions

Stephen Kahara Wanjau, George Okeyo, Richard Rimiru
2016 International Journal of Computer Applications Technology and Research  
In this paper, educational data mining was used to predict enrollment of students in Science, Technology, Engineering and Mathematics (STEM) courses in higher educational institutions.  ...  Feature selection was used to rank the predictor variables by their importance for further analysis. Various predictive algorithms were evaluated in predicting enrollment of students in STEM courses.  ...  predicting enrollment in STEM courses in higher education institutions.  ... 
doi:10.7753/ijcatr0511.1004 fatcat:pbhbh6u3i5c4bo5m3e7ogvqr4u

The Benefits of Learning Analytics to Higher Education Institutions: A Scoping Review

Adedayo Taofeek Quadri, Nurbiha A Shukor
2021 International Journal of Emerging Technologies in Learning (iJET)  
It is recommended that higher education institutions adopt the use of learning analytics in their online teaching and learning.  ...  This review aims at reviewing some of the benefits available through using learning analytics in higher education institutions (HEI) for the students, teaching staff and the management.  ...  Acknowledgement Authors would like to thank Universiti Teknologi Malaysia under the University Fundamental Research Grant vot 21H04 for funding the research.  ... 
doi:10.3991/ijet.v16i23.27471 fatcat:z4gw2fkgdjgidjhnckzyyjcnui

Data Mining Application in Higher Learning Institutions

2008 Informatics in Education. An International Journal  
This paper presents the capabilities of data mining in the context of higher educational system by i) proposing an analytical guideline for higher education institutions to enhance their current decision  ...  This knowledge can be extracted from historical and operational data that reside in the educational organization's databases using the techniques of data mining technology.  ...  Section 3 presents data mining as a key to the current problem in educational system. Section 4 presents a guideline to data mining application in higher learning institution proposed by the authors.  ... 
doi:10.15388/infedu.2008.03 fatcat:m42lgsb2uvdopcqxfyynieikn4


Jai Ruby .
2014 International Journal of Research in Engineering and Technology  
In higher education institutions a substantial amount of knowledge is hidden and need to be extracted using Knowledge Discovery process.  ...  The extracted information that describes student performance can be stored as intelligent knowledge for decision making to improve the quality of education in institutions.  ...  Key uses of EDM [2] include learning and predicting student performance in order to recommend improvements to current educational practice.  ... 
doi:10.15623/ijret.2014.0305139 fatcat:553qw22qjbdtxjcj4nnsiwwdi4

Logistic Modeling of University Choice Among Student Migrants to Karnataka for Higher Education

Veena Andini, Sandeep Rao
2018 Social Science Research Network  
primary data collected from students who migrated to Karnataka.  ...  This provides them with opportunities to collaborate with the state government in order to introduce educational policies which can influence the students' migration decisions.  ...  H3: Current level of course has no significant effect on predicting the selection of private university for higher education in Karnataka by migrant students.  ... 
doi:10.2139/ssrn.3181130 fatcat:nxbeicpnwbeyzbwhvttdlkamea

Students' Dropout Risk Assessment in Undergraduate Courses of ICT at Residential University A Case study

Sweta Rai, Ajit Kumar Jain
2013 International Journal of Computer Applications  
The information generated will be useful for better planning and implementation of educational program and infrastructure under measurable condition to increase the enrollment rate of students in ICT courses  ...  The present case study describes the results of the educational data mining aimed at predicting the undergraduate courses of computer science (BCA and B.Tech.) students' instant dropout or after first  ...  Beikzadeh and Delavari [7] give knowledge to use data mining method in higher education.  ... 
doi:10.5120/14645-2965 fatcat:q72j4qaqxrfm7cxjpo7uudlvcm

Data mining for Education Sector, a proposed concept

Ammar Al-Rawahnaa
2020 Journal of Applied Data Sciences  
The use of Data mining in education will be useful in developing a student-focused strategy and in providing the correct tools that institutions would be able to use for quality improvement purposes.  ...  In higher education the potential influence of data mining on the learning processes and outcomes of the students was realized.  ...  Higher education institutions can use classification methods, to analyze student characteristics, or use estimates to predict the likelihood of various outcomes such as perseverance, performance in an  ... 
doi:10.47738/jads.v1i1.6 fatcat:z24msgdcuzerjogrm4s2l3cwsa

Data Mining Techniques Applying on Educational Dataset to Evaluate Learner Performance Using Cluster Analysis

Minimol Anil Job
2018 European Journal of Engineering Research and Science  
This paper discusses how application of data mining can help the higher education institutions by enabling better understanding of the student data and focuses to consolidate clustering algorithms as applied  ...  in the context of educational data mining.  ...  One way to achieve highest level of quality in higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, detection of abnormal values in  ... 
doi:10.24018/ejers.2018.3.11.966 fatcat:a7phsvyyqvcgtmabcopiogih2e

Prediction of Final Result and Placement of Students using Classification Algorithm

Neelam Naik, Seema Purohit
2012 International Journal of Computer Applications  
Data mining techniques aim to discover hidden knowledge in existing educational data, predict future trends and use it for betterment of higher educational institutes as well as students.  ...  The objective of this study is to use prediction technique using data mining for producing knowledge about students of Masters of Computer Application course before admitting them to the course.  ...  One has to concentrate on challenges faced by higher educational institutes to improve quality of higher education.  ... 
doi:10.5120/8945-3111 fatcat:pd5uk6iiujdhhcbevwvlgchhtm

Predicting Student Academic Performance in KSA using Data Mining Techniques

Nawal Ali Yassein, Rasha Gaffer M Helali, Somia B Mohomad
2017 Journal of Information Technology & Software Engineering  
The main objective of higher education institutions is to provide quality education to its students.  ...  The specific objective of the proposed research work is to find out if there are any patterns in the available data (student and courses records) that could be useful for predicting students' performance  ...  It is remarkable that most often attracting the attention of researchers and becoming the reasons for applying data mining at higher education institutions are focused mainly on retention of students,  ... 
doi:10.4172/2165-7866.1000213 fatcat:kuly26r4mbf6ti6kdcbosmrixm

Student Dropout Risk Assessment in Undergraduate Course at Residential University [article]

Sweta Rai
2014 arXiv   pre-print
Student dropout prediction is an indispensable for numerous intelligent systems to measure the education system and success rate of any university as well as throughout the university in the world.  ...  In this study, the descriptive statistics analysis was carried out to measure the quality of data using SPSS 20.0 statistical software and application of decision tree and association rule were carried  ...  The use of data mining technique to analyze an educational database is absolutely expected to be great benefit to the higher educational institutions.  ... 
arXiv:1405.3727v1 fatcat:jwdjjakbezbdvh73vsmag2alle

Survey of Learning Analytics based on Purpose and Techniques for Improving Student Performance

Suchithra R, V.Vaidhehi V.Vaidhehi, Nithya Easwaran Iyer
2015 International Journal of Computer Applications  
The data collection method is to use the existing learning management system in the higher education institution.  ...  In many cases, Higher education institutions in India are not aware of the courses needed by the students.  ... 
doi:10.5120/19502-1097 fatcat:xqkosoycsrcffhju5urvm2cpsu

Data Mining in Higher Education

Dina A. Aziz AlHammadi, Mehmet Sabih Aksoy
2013 Periodicals of Engineering and Natural Sciences (PEN)  
This paper focuses on the research completed in the area of data mining in the higher education sector: colleges and universities.  ...  We will look at the different implementation of data mining and to what extent was it utilized and benefited from.  ...  Acknowledgements The authors would like to thank Research Center in the College of Computer and Information Sciences, King Saud University for its support to complete this study.  ... 
doi:10.21533/pen.v1i2.17 fatcat:rttarozzkzhnxczj2xbjeqosuy
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