Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer-journals/frontiers-of-cyberlearning-framing-learning-analytics-and-educational-2033pmA48F
References (48)
-
Hongwei Zhu, S. Madnick, Yang Lee, Richard Wang (2014)
Data and Information Quality Research: Its Evolution and Future -
A. Doan, Pedro Domingos, A. Halevy (2001)
Reconciling schemas of disparate data sources: a machine-learning approach -
D. Larose (2006)
Data mining methods and models -
I. Jung (2005)
ICT-Pedagogy Integration in Teacher Training: Application Cases WorldwideJ. Educ. Technol. Soc., 8
-
T. Dasu, T. Johnson (2003)
Exploratory Data Mining and Data Cleaning -
C. Romero, Sebastián Ventura (2010)
Educational Data Mining: A Review of the State of the ArtIEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40
-
Thilo Kleickmann, Dirk Richter, Mareike Kunter, Jürgen Elsner, M. Besser, S. Krauss, J. Baumert (2013)
Teachers’ Content Knowledge and Pedagogical Content KnowledgeJournal of Teacher Education, 64
-
Paulo Blikstein (2013)
Multimodal learning analytics -
Larry Cuban (2009)
Oversold and underused : computers in the classroom -
George Siemens (2012)
Learning analytics: envisioning a research discipline and a domain of practiceProceedings of the 2nd International Conference on Learning Analytics and Knowledge
-
P. Long, George Siemens (2014)
Penetrating the fog: analytics in learning and educationTD Tecnologie Didattiche, 22
-
C. Kenny (2006)
Overselling the Web?: Development and the Internet -
W. Carlsen (1999)
Domains of Teacher Knowledge -
Dirk Tempelaar, B. Rienties, B. Giesbers (2015)
In search for the most informative data for feedback generation: Learning analytics in a data-rich contextComput. Hum. Behav., 47
-
DoanAnhai, DomingosPedro, Y. HalevyAlon (2001)
Reconciling schemas of disparate data sourcesSigmod Record
-
Rebecca Ferguson, T. Hoel, Maren Scheffel, H. Drachsler (2016)
Guest Editorial: Ethics and Privacy in Learning AnalyticsJ. Learn. Anal., 3
-
J. Daniel (2012)
Making Sense of MOOCs: Musings in a Maze of Myth, Paradox and PossibilityJournal of interactive media in education, 2012
-
J. Daniel (2010)
Mega-Schools, Technology and Teachers: Achieving Education for All -
(1996)
c ○ 1997 Kluwer Academic Publishers. Manufactured in The Netherlands. Statistical Themes and Lessons for Data Mining -
Leah Macfadyen, S. Dawson (2010)
Mining LMS data to develop an "early warning system" for educators: A proof of conceptComput. Educ., 54
-
C. Romero, Sebastián Ventura, Enrique García (2008)
Data mining in course management systems: Moodle case study and tutorialComput. Educ., 51
-
H. Jagadish (2015)
Big Data and Science: Myths and RealityBig Data Res., 2
-
S. Dawson, Negin Mirriahi, D. Gašević (2015)
Importance of Theory in Learning Analytics in Formal and Workplace SettingsJ. Learn. Anal., 2
-
Kimberly Arnold, M. Pistilli (2012)
Course signals at Purdue: using learning analytics to increase student successProceedings of the 2nd International Conference on Learning Analytics and Knowledge
-
Rob Kitchin, Tracey Lauriault (2014)
Towards Critical Data Studies: Charting and Unpacking Data Assemblages and Their Work -
A. Pardo, George Siemens (2014)
Ethical and privacy principles for learning analyticsBr. J. Educ. Technol., 45
-
Craig Dalton, L. Taylor, Jim (alphabetical) (2016)
Critical Data Studies: A dialog on data and spaceBig Data & Society, 3
-
George Siemens, R. Baker (2012)
Learning analytics and educational data mining: towards communication and collaborationProceedings of the 2nd International Conference on Learning Analytics and Knowledge
-
L. Shulman (1986)
Those Who Understand: Knowledge Growth in TeachingEducational Researcher, 15
-
A. Iliadis, Federica Russo (2016)
Critical data studies: An introductionBig Data & Society, 3
-
Cathy O'Neil (2016)
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy -
W. Bramble, S. Panda (2008)
Economics of Distance and Online Learning: Theory, Practice and Research -
S. Dawson, D. Gašević, Negin Mirriahi (2016)
Challenging Assumptions in Learning AnalyticsJ. Learn. Anal., 2
-
Sharon Slade, P. Prinsloo (2013)
Learning AnalyticsAmerican Behavioral Scientist, 57
-
P. Baepler, C. Murdoch (2010)
Academic Analytics and Data Mining in Higher EducationThe International Journal for the Scholarship of Teaching and Learning, 4
-
A. Pardo (2014)
Designing Learning Analytics Experiences -
Marcus Birgersson, Gustav Hansson, U. Franke (2016)
Data Integration Using Machine Learning2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW)
-
P. Prinsloo, Sharon Slade (2016)
Student Vulnerability, Agency and Learning Analytics: An ExplorationJ. Learn. Anal., 3
-
J. Borup, Charles Graham, Jeffery Drysdale (2013)
The nature of teacher engagement at an online high schoolBr. J. Educ. Technol., 45
-
Margaret Lloyd, N. Bahr (2010)
Thinking critically about critical thinking in higher educationThe International Journal for the Scholarship of Teaching and Learning, 4
-
DeLaina Tonks, S. Weston, D. Wiley, M. Barbour (2013)
“Opening” a new kind of school: The story of the Open High School of UtahThe International Review of Research in Open and Distributed Learning, 14
-
R. Baker, P. Inventado (2014)
The Cambridge Handbook of the Learning Sciences: Educational Data Mining and Learning Analytics -
R. Kozma (2008)
Comparative Analysis of Policies for ICT in Education -
T. Moe, John Chubb (2009)
Liberating Learning: Technology, Politics, and the Future of American Education -
W. Bramble, S. Panda (2008)
Organizational and Cost Structures for Distance and Online Learning -
B. Daniel (2015)
Big Data and analytics in higher education: Opportunities and challengesBr. J. Educ. Technol., 46
-
Z. Pardos (2015)
Commentary On "Beyond Time-on-Task: The Relationship Between Spaced Study and Certification in MOOCs"J. Learn. Anal., 2
-
J. Masuch, M. Delgado-Restituto (2013)
Review of the State of the Art
- Publisher
- Springer Singapore
- Copyright
- © Springer Nature Singapore Pte Ltd. 2018
- ISBN
- 978-981-13-0649-5
- Pages
- 33 –47
- DOI
- 10.1007/978-981-13-0650-1_2
- Publisher site
- See Chapter on Publisher Site
Abstract
[This chapter reviews key challenges of learning analytics and educational data mining. It highlights early generation learning analytics pitfalls that could compromise the future of their use in technology-delivered instruction, especially if teachers are not well trained and adequately equipped with both technical and sociocritical literacy of this new field. Among the issues are potential for bias and inaccuracy in the algorithms involved, the propensity toward closed proprietary systems whose algorithms cannot be scrutinized, and the paucity of learning models typically considered. The new learning analytics and educational data mining systems bring with them a set of claims, aspirations, and mystique. These underlying technologies could be harbingers of future breakthroughs: a new generation of artificial intelligence systems adaptively responding to students’ interactions with online teaching environments.]
Published: Nov 4, 2018