scholarly journals Learning Analytics Research, Theory and Practice: Widening the Discipline

2014 ◽  
Vol 1 (3) ◽  
pp. 4-6 ◽  
Author(s):  
Abelardo Pardo ◽  
Stephanie Teasley
Keyword(s):  
Big Data ◽  
Learning Analytics ◽  
Theory And Practice ◽  
Special Issue ◽  
Broad Audience ◽  
Learning Research ◽  
Depth View

This article introduces the special issue presenting five papers from SoLAR’s Learning Analytics and Knowledge 2014 conference. The authors of these papers were invited to expand their original papers to provide a more in-depth view of their work and one that would reach out to a broad audience. The papers included here provide a view into the diversity of LA research presented at LAK 14 and demonstrate exciting new avenues by which the field is expanding. We believe that the papers presented here move the field ahead by contributing to a wider discourse about how we can effectively and ethically utilize “big data” to inform learning research and theory, and the resulting practices that support learning.

scholarly journals Learning as a Machine. Crossovers Between Humans and Machines

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Mireille Hildebrandt
Keyword(s):  
Learning Process ◽  
Learning Analytics ◽  
Active Participation ◽  
Theory And Practice ◽  
Academic Disciplines ◽  
Special Issue ◽  
Rich Diversity ◽  
Current Thinking ◽  
Multidisciplinary Nature ◽  
The Rich

This article introduces the special issue from SoLAR’s 2016 Learning Analytics and Knowledge conference. The field of learning analytics (LA) draws heavily on theory and practice from a range of diverse academic disciplines. In so doing, LA research embodies a rich integration of methodologies and practices, assumptions and theory to bring new insights into the learning process. Reflecting this rich diversity, the theme of LAK 2016 highlights the multidisciplinary nature of the field and embraces the convergence of these disciplines to provide theoretical and practical insights to challenge current thinking in the field.  This overview introduces six articles, each of which expands on an invited talk or paper from the conference, with the added goal of offering a small taste of the rich experience that comes from  active participation in the conference. 

scholarly journals LAK16 Editorial

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Carolyn Penstein Rosé ◽  
Shane Dawson ◽  
Hendrik Drachsler
Keyword(s):  
Learning Process ◽  
Learning Analytics ◽  
Active Participation ◽  
Theory And Practice ◽  
Academic Disciplines ◽  
Special Issue ◽  
Rich Diversity ◽  
Current Thinking ◽  
Multidisciplinary Nature ◽  
The Rich

This article introduces the special issue from SoLAR’s 2016 Learning Analytics and Knowledge conference. The field of learning analytics (LA) draws heavily on theory and practice from a range of diverse academic disciplines. In so doing, LA research embodies a rich integration of methodologies and practices, assumptions and theory to bring new insights into the learning process. Reflecting this rich diversity, the theme of LAK 2016 highlights the multidisciplinary nature of the field and embraces the convergence of these disciplines to provide theoretical and practical insights to challenge current thinking in the field.  This overview introduces six articles, each of which expands on an invited talk or paper from the conference, with the added goal of offering a small taste of the rich experience that comes from  active participation in the conference.

scholarly journals Scientometrics as an Important Tool for the Growth of the Field of Learning Analytics

2014 ◽  
Vol 1 (2) ◽  
pp. 1-4 ◽  
Author(s):  
Negin Mirriahi ◽  
Dragan Gasevic ◽  
Shane Dawson ◽  
Phillip D. Long
Keyword(s):  
Learning Process ◽  
Learning Analytics ◽  
Theory And Practice ◽  
Allocation Of Resources ◽  
Special Issue ◽  
Learner Interactions ◽  
Digital Environments ◽  
Insight Into

This article introduces the special issue from SoLAR’s Learning Analytics and Knowledge conference. Learning analytics is an emerging field incorporating theory and practice from numerous disciplines to investigate how learner interactions in digital environments can provide actionable data about the learning process. As the field continues to expand there is a timely opportunity to evaluate its ongoing maturation. This evaluation could be in part informed by regular scientometric analyses from both the Journal and Conference publications. These analyses can collectively provide insight into the development of learning analytics more broadly and assist with the allocation of resources to under-represented areas for example.

Learning Analytics Considered Harmful

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus
Keyword(s):  
Big Data ◽  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Research Community ◽  
Current Status ◽  
Online Course ◽  
Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

Guest Editorial: Special Issue on Big Data

2020 ◽  
pp. -1--1
Author(s):  
Arun Sangaiah ◽  
Ford Gao ◽  
Krishn Mishra
Keyword(s):  
Big Data ◽  
Guest Editorial ◽  
Special Issue ◽  
Editorial Special Issue

Call for Special Issue Papers: Multimedia Big Data Analytics for Engineering Education

Big Data ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 87-88
Author(s):  
Priyan Malarvizhi Kumar ◽  
Hari Mohan Pandey ◽  
Gautam Srivastava
Keyword(s):  
Big Data ◽  
Engineering Education ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Special Issue ◽  
Multimedia Big Data

Special Issue on Software and Systems Reuse in the Big Data Era

2021 ◽  
Vol 176 ◽  
pp. 110921
Author(s):  
Apostolos Ampatzoglou ◽  
Peng Xin
Keyword(s):  
Big Data ◽  
Special Issue

Dave Snowden on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 12-17 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Theory And Practice ◽  
Content Type ◽  
Face To Face ◽  
The Relationship ◽  
A Company ◽  
Practical Implications ◽  
Scientific Officer

Purpose Dave Snowden has been an important voice in knowledge management over the years. As the founder and chief scientific officer of Cognitive Edge, a company focused on the development of the theory and practice of social complexity, he offers informative views on the relationship between big data/analytics and KM. Design/methodology/approach A face-to-face interview was held with Dave Snowden in May 2015 in Auckland, New Zealand. Findings According to Snowden, analytics in the form of algorithms are imperfect and can only to a small extent capture the reasoning and analytical capabilities of people. For this reason, while big data/analytics can be useful, they are limited and must be used in conjunction with human knowledge and reasoning. Practical implications Snowden offers his views on big data/analytics and how they can be used effectively in real world situations in combination with human reasoning and input, for example in fields from resource management to individual health care. Originality/value Snowden is an innovative thinker. He combines knowledge and experience from many fields and offers original views and understanding of big data/analytics, knowledge and management.

Sign in / Sign up

Export Citation Format

Share Document