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Big Data in Educational Data Mining and Learning Analytics
English

B R Pra kash, Dr.M. Hanuman thappa, Vasantha Kavitha
2014 International Journal of Innovative Research in Computer and Communication Engineering  
Educational data mining and learning analytics are used to research and build models in several areas that can influence learning systems.  ...  Key educational applications of relationship mining include discovery of associations between student performance and course sequences and discovering which pedagogical strategies lead to more effective  ...  , and integration of psychometric modeling frameworks into machine-learned models.  ... 
doi:10.15680/ijircce.2014.0212044 fatcat:grxjrjggnvbibiritlajwizn7e

Predictive Model of Postgraduate Student's Dropout and Delay Using Machine Learning Algorithms

2021 International Journal of Advanced Trends in Computer Science and Engineering  
Age, money management skills, number of children, and health expenses are the other factors that contribute to higher dropout or delay at the university.  ...  Therefore, many scholars have used the Decision Tree to predict student performance with greater success.  ...  Machine learning is an emerging trend in education, where it is applied in learning historical data and using it to predict learners' future behavior [6] .  ... 
doi:10.30534/ijatcse/2021/591022021 fatcat:adunrwkecnd63ivpqdwzf6jcly

Academic libraries as active contributors to student wellness

Elizabeth Ramsey, Mary C. Aagard
2018 College & Undergraduate Libraries  
Colleges and universities have come to realize that student wellness is a factor in student retention and success.  ...  in this essential form of outreach.  ...  In implementing Hettler's model and others like it, colleges are creating learning opportunities for wellbeing that may impact students for the rest of their lives.  ... 
doi:10.1080/10691316.2018.1517433 fatcat:gflq7spacvem3hdjhcun5g7r7m

Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning

David C. Mohr, Mi Zhang, Stephen M. Schueller
2017 Annual Review of Clinical Psychology  
We provide a layered, hierarchical model for translating raw sensor data into markers of behaviors and states related to mental health.  ...  Personal sensing refers to collecting and analyzing data from sensors embedded in the context of daily life with the aim of identifying human behaviors, thoughts, feelings, and traits.  ...  ACKNOWLEDGEMENTS This work was supported by the National Institutes of Mental Health with grants P20MH090318, R01MH100482, and R01MH095753 to Dr. Mohr, and K08MH102336 to Dr. Schueller.  ... 
doi:10.1146/annurev-clinpsy-032816-044949 pmid:28375728 pmcid:PMC6902121 fatcat:rxu55uc7jvaeplcrzaeotkmv6i

COVID-19 Tweets Textual Analytics Using Machine Learning Classification for Fear Sentiment

2020 International Journal of Advanced Trends in Computer Science and Engineering  
With the huge number of messages seem in user interfaces, it obstruct user accessibility to useful information hide in disorganized, incomplete and unstructured text message.  ...  The volume of COVID 19 microblogging messages is increasing exponentially with the popularity of COVID 19 microblogging services.  ...  FUTURE STUDIES Corporations and small businesses can also benefit through such analyses and machine learning models to better understand consumer sentiment and expectations.  ... 
doi:10.30534/ijatcse/2020/221952020 fatcat:tvlslsmkubfsnnbov7ox3pmma4

Assessment of Academic Performance with The E-mental Health Interventions in Virtual Learning Environment Using Machine Learning Techniques: A Hybrid Approach

A. Sheik Abdullah, R. M. Abirami, A. Gitwina, C. Varthana
2021 Journal of Engineering Education Transformations  
There is a need and evaluation for the assessment and estimation of the impact of e-mental health interventions with the students learning through the virtual learning environment.  ...  The act of virtual learning is defined through learning and practicing in an environment using digital/electronic content for self-paced through online teaching and mentoring.  ...  A Virtual Learning Environment is a platform to students for delivering learning materials through the web.  ... 
doi:10.16920/jeet/2021/v34i0/157109 fatcat:nqyt727fhvbnrcxazrb2kx3fcu

Machine learning and medical devices: The next step for tissue engineering

Hannah A. Pearce, Antonios G. Mikos
2021 Engineering  
Acknowledgements The authors acknowledge support from the National Institutes of Health (P41 EB023833 and R01 AR068073).  ...  Through machine learning, the technology builds an individual profile to understand the wearer's cardiovascular behaviors that fall within a normal and healthy range for that person.  ...  Harnessing the power of machine learning is the next step in the evolution of medical device development and is key f or the continued success of tissue engineering.  ... 
doi:10.1016/j.eng.2021.05.014 fatcat:m3klaxs74ffxrfmq5rat3crjxy

The Future of Work: What It Is and How Our Resilience in the Face of It Matters

Suri Duitch
2021 Kinesiology Review  
Preparing students for future success in this environment requires educators to think more broadly and holistically about their roles.  ...  Beyond this, the potential for future pandemics and other transformational events and trends mean that work is in a state of permanent flux.  ...  And with machine learning, more jobs in health care and other fields will be automated and permanently disappear from the labor market (Selingo, 2017) .  ... 
doi:10.1123/kr.2021-0044 fatcat:u5sdyxri25gfrclbr6ds6b3jmy

Improving the Field's Understanding of Suicide Protective Factors and Translational Suicide Prevention Initiatives

Robert J. Cramer, Raymond Tucker
2021 International Journal of Environmental Research and Public Health  
World Health Organization data show that approximately 800,000 persons die by suicide each year [...]  ...  This investigation through the lens of the Integrated Motivational Volitional model of suicide (IMV) [6] provides a useful framework of understanding how upstream suicide prevention efforts that foster  ...  The use of natural language processing and machine learning techniques may enhance the identification of the level of care needed. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijerph18031027 pmid:33503803 fatcat:dbupxp6hxbazjbyi6u66ntpwh4

Un análisis bibliométrico sobre el uso y la adopción de la educación en línea en la enseñanza superior

Martin Ortega Azurduy
2021 Educación Superior  
metadata obtained and present the state, structure, and trends in the study of the adoption and use of e-learning in higher education.  ...  This bibliometric analysis identifies and presents the articles that have given shape to the current research trends on the adoption and use of e-learning in higher education using structural equation  ...  There is an increased interest in Microsoft Academic through machine learning understanding the impact of psychological parsing of accessible text strings (metadata + aspects, as drivers  ... 
doi:10.53287/ibsf4872ts39b fatcat:gjyug23wmzgpdaarv7ggmjbnr4

Artificial Intelligence in Health, Human Service Delivery and Education: A Brief Conceptual Overview

Randy Basham
2019 Journal of Health Science  
However, there are emerging applications of AI in the improvement of human welfare, health, and educational attainment. Each of these will be addressed in the conceptual review to follow.  ...  Artificial intelligence has been the subject of substantial optimism and being of service to improving human lifestyles.  ...  Machine learning statistical and predictive models of group and individual behaviors could be enhanced to improve community interventions.  ... 
doi:10.17265/2328-7136/2019.02.002 fatcat:ky2n6dz25naelhmuntjhlq6lq4

Educational Sustainability through Big Data Assimilation to Quantify Academic Procrastination Using Ensemble Classifiers

Syed Muhammad Raza Abidi, Wu Zhang, Saqib Ali Haidery, Sanam Shahla Rizvi, Rabia Riaz, Hu Ding, Se Jin Kwon
2020 Sustainability  
Throughout this research, we concentrate on predictive measures to identify and forecast procrastinator students by using ensemble machine learning models (i.e., Logistic Regression, Decision Tree, Gradient  ...  Ubiquitous online learning is continuing to expand, and the factors affecting success and educational sustainability need to be quantified.  ...  The approach we build through machine learning allows for a fine-grained study of procrastination and its connection with learning outcomes that can help understand more successful rearrangements of online  ... 
doi:10.3390/su12156074 fatcat:ponzclqabveqrlog77znuehpme

Recent Advances in Computational Epidemiology

Madhav V. Marathe, Naren Ramakrishnan
2013 IEEE Intelligent Systems  
This approach has been tremendously successful in informing public health policy. Nevertheless, a potential weakness is its inability to capture the complexity of human interactions and behaviors.  ...  and college students.  ...  Health scientists have developed verbal or conceptual behavioral models to understand the role of behaviors in public health. 24, 25 But these models are typically informal and it's quite demanding to  ... 
doi:10.1109/mis.2013.114 pmid:25505373 pmcid:PMC4258713 fatcat:6psjez7lfvdmbik64g2i4xdtbu

Incorporating Health Education in the Curriculum: The Kenyan Experience

Lewis Ngesu, Alice Gichohi
2018 International Journal of Trend in Scientific Research and Development  
The most recent challenges in health could be tackled by incorporating health education at all levels of learning.  ...  It is based on health promoting social models. The young person is the heart of these models in a dynamic environment.  ...  It demonstrates the usefulness of educational and preventive action in studies have shown a positive correlation between health behavior and with multiple students' success.  ... 
doi:10.31142/ijtsrd18832 fatcat:kplbv32jhfd2bbgkjm76uzmf4u

My Teacher Is a Machine: Understanding Students' Perceptions of AI Teaching Assistants in Online Education

Jihyun Kim, Kelly Merrill Jr., Kun Xu, Deanna D. Sellnow
2020 International Journal of Human-Computer Interaction  
Based on the present study's findings, more research is needed to better understand the nuances associated with the learning experience one may have from an AI teaching assistant.  ...  Her research focuses on strategic instructional communication in a variety of contexts including risk, crisis, and health.  ...  behavioral learning through various ways.  ... 
doi:10.1080/10447318.2020.1801227 fatcat:qfwuyhpbb5cr3ll3b7r7phjsze
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