research-article

Academic analytics landscape at the University of Phoenix

Author:

Mike SharkeyAuthors Info & Claims

LAK '11: Proceedings of the 1st International Conference on Learning Analytics and Knowledge

Pages 122 - 126

https://doi.org/10.1145/2090116.2090135

Published: 27 February 2011 Publication History

Get Access

Abstract

The University of Phoenix understands that in order to serve its large population of non-traditional students, it needs to rely on data. We have created a strong foundation with an integrated data repository that connects data from all parts of the organization. With this repository in place, we can now undertake a variety of analytics projects. One such project is an attempt to predict a student's persistence in their program using available data indicators such as schedule, grades, content usage, and demographics.

Cited By

View all

Rivera-Baena OPatiño-Rodríguez CÚsuga-Manco OHernández-Barajas F(2023)ADHE: A Tool to Characterize Higher Education Dropout PhenomenonRevista Facultad de Ingeniería Universidad de Antioquia10.17533/udea.redin.20230519Online publication date: 2-May-2023
https://doi.org/10.17533/udea.redin.20230519
Ahmad ASchneider JGriffiths DBiedermann DSchiffner DGreller WDrachsler H(2022)Connecting the dots – A literature review on learning analytics indicators from a learning design perspectiveJournal of Computer Assisted Learning10.1111/jcal.12716Online publication date: 26-Jul-2022
https://doi.org/10.1111/jcal.12716
Wong BLi KChoi S(2018)Trends in learning analytics practices: a review of higher education institutionsInteractive Technology and Smart Education10.1108/ITSE-12-2017-006515:2(132-154)Online publication date: 18-Jun-2018
https://doi.org/10.1108/ITSE-12-2017-0065
Show More Cited By

Index Terms

Academic analytics landscape at the University of Phoenix
1. Applied computing
  1. Education

Recommendations

Experience-based analytics
CASCON '15: Proceedings of the 25th Annual International Conference on Computer Science and Software Engineering

Data has been called the new oil. Despite of its high value, only one percent of the world's data has been extracted for its insights. Data analytics is currently available only to the technical elite of data and IT experts, completely out of reach for ...
Educational data mining with Python and Apache spark: a hands-on tutorial
LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge

Enormous amount of educational data has been accumulated through Massive Open Online Courses (MOOCs), as well as commercial and non-commercial learning platforms. This is in addition to the educational data released by US government since 2012 to ...
Survey of the Different Type of Data Analytics Algorithms

From as early as 1854 to today, society has been gathering, processing, transforming, modeling and visualizing data to help drive data-driven decisions. The qualitative definition of big data can be defined more conclusively as data that has high volume,...

Comments

Information & Contributors

Information

Published In

LAK '11: Proceedings of the 1st International Conference on Learning Analytics and Knowledge

February 2011

195 pages

ISBN:9781450309448

DOI:10.1145/2090116

Conference Chairs:
Phillip Long
University of Queensland, Australia
,
George Siemens
Athabasca University, Canada
,
Program Chairs:
Gráinne Conole
Open University, UK
,
Dragan Gašević
Athabasca University, Canada

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 February 2011

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

LAK 2011

Sponsor:

Gates
TEKRI
Kaplan
Desire2Learn
University of Queensland

LAK 2011: 1st International Conference on Learning Analytics and Knowledge

February 27 - March 1, 2011

Alberta, Banff, Canada

Acceptance Rates

Overall Acceptance Rate 236 of 782 submissions, 30%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

12
Total Citations
View Citations
586
Total Downloads

Downloads (Last 12 months)14
Downloads (Last 6 weeks)5

Reflects downloads up to 17 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Rivera-Baena OPatiño-Rodríguez CÚsuga-Manco OHernández-Barajas F(2023)ADHE: A Tool to Characterize Higher Education Dropout PhenomenonRevista Facultad de Ingeniería Universidad de Antioquia10.17533/udea.redin.20230519Online publication date: 2-May-2023
https://doi.org/10.17533/udea.redin.20230519
Ahmad ASchneider JGriffiths DBiedermann DSchiffner DGreller WDrachsler H(2022)Connecting the dots – A literature review on learning analytics indicators from a learning design perspectiveJournal of Computer Assisted Learning10.1111/jcal.12716Online publication date: 26-Jul-2022
https://doi.org/10.1111/jcal.12716
Wong BLi KChoi S(2018)Trends in learning analytics practices: a review of higher education institutionsInteractive Technology and Smart Education10.1108/ITSE-12-2017-006515:2(132-154)Online publication date: 18-Jun-2018
https://doi.org/10.1108/ITSE-12-2017-0065
Alblawi AAlhamed A(2017)Big data and learning analytics in higher education: Demystifying variety, acquisition, storage, NLP and analytics2017 IEEE Conference on Big Data and Analytics (ICBDA)10.1109/ICBDAA.2017.8284118(124-129)Online publication date: Nov-2017
https://doi.org/10.1109/ICBDAA.2017.8284118
Leitner PKhalil MEbner M(2017)Learning Analytics in Higher Education—A Literature ReviewLearning Analytics: Fundaments, Applications, and Trends10.1007/978-3-319-52977-6_1(1-23)Online publication date: 18-Feb-2017
https://doi.org/10.1007/978-3-319-52977-6_1
Inventado PScupelli PLink CEloranta V(2015)Data-driven design pattern productionProceedings of the 20th European Conference on Pattern Languages of Programs10.1145/2855321.2855336(1-13)Online publication date: 8-Jul-2015
https://dl.acm.org/doi/10.1145/2855321.2855336
Brooks CThompson CTeasley SKiczales GRussell DWoolf B(2015)Who You Are or What You DoProceedings of the Second (2015) ACM Conference on Learning @ Scale10.1145/2724660.2728668(245-248)Online publication date: 14-Mar-2015
https://dl.acm.org/doi/10.1145/2724660.2728668
Softic STaraghi BEbner MDe Vocht LMannens EVan de Walle R(2015)Mining and Visualizing Usage of Educational Systems Using Linked DataImmersive Education10.1007/978-3-319-22017-8_2(17-26)Online publication date: 1-Aug-2015
https://doi.org/10.1007/978-3-319-22017-8_2
Abhyankar KGanapathy S(2014)Technology-Enhanced Learning Analytics System Design for Engineering EducationInternational Journal of Information and Education Technology10.7763/IJIET.2014.V4.4274:4(345-350)Online publication date: 2014
https://doi.org/10.7763/IJIET.2014.V4.427
Tibola L(2014)A proposal of engineering education architecture: Improve engineer's competencies through practice labs and 3D virtual worlds2014 12th IEEE International Conference on Industrial Informatics (INDIN)10.1109/INDIN.2014.6945615(791-794)Online publication date: Jul-2014
https://doi.org/10.1109/INDIN.2014.6945615
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Experience-based analytics

Educational data mining with Python and Apache spark: a hands-on tutorial

Survey of the Different Type of Data Analytics Algorithms