Quantitative and Qualitative Analysis of the Learning Analytics and Knowledge Conference 2018

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Bibliographic Details
Title: Quantitative and Qualitative Analysis of the Learning Analytics and Knowledge Conference 2018
Language: English
Authors: Ochoa, Xavier (ORCID 0000-0002-4371-7701), Merceron, Agathe (ORCID 0000-0003-1015-5359)
Source: Journal of Learning Analytics. 2018 5(3):154-166.
Availability: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: http://learning-analytics.info/journals/index.php/JLA/
Peer Reviewed: Y
Page Count: 13
Publication Date: 2018
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Educational Research, Data Analysis, Conferences (Gatherings), Foreign Countries, Conference Papers, Peer Evaluation, Writing Evaluation, Writing for Publication, Authors, Discourse Analysis, Educational Trends
Geographic Terms: Australia
ISSN: 1929-7750
Abstract: LAK-18, the 8th International Conference on Learning Analytics and Knowledge, was hosted by the University of Sydney, Australia, from March 5 to 9, 2018. Traditionally, authors of papers that have received high scores through the review process of the conference are invited to extend their paper and submit it for a special issue of this journal. The chairs of LAK-18 have adopted a double-blind review process that has proven useful in maintaining the technical quality of the conference. Papers submitted to the special issue undergo a rigorous review process that is blind only, not double-blind, as a shorter version of the paper has been already published. The theme for LAK-18 was "Towards User-Centred Analytics". Though several of the papers receiving high scores in the review process explicitly dealt with this issue, it has been decided to devote a complete special issue of the journal to this theme and invite those papers in this special issue to come. Thus, the present special issue LAK-18 covers a broad range of themes, which reflect well the diversity and the vibrancy of the community, but excludes User-Centred Analytics. This editorial describes the story behind this special issue. This story begins with the contributions submitted to the conference and finishes with a short introduction to the papers in this issue. The two first episodes of the story, contribution type and country, include both tracks, research and practitioner. The reminder episodes refer only to the research track.
Abstractor: As Provided
Number of References: 1
Entry Date: 2018
Accession Number: EJ1199896
Database: ERIC
Description
Abstract:LAK-18, the 8th International Conference on Learning Analytics and Knowledge, was hosted by the University of Sydney, Australia, from March 5 to 9, 2018. Traditionally, authors of papers that have received high scores through the review process of the conference are invited to extend their paper and submit it for a special issue of this journal. The chairs of LAK-18 have adopted a double-blind review process that has proven useful in maintaining the technical quality of the conference. Papers submitted to the special issue undergo a rigorous review process that is blind only, not double-blind, as a shorter version of the paper has been already published. The theme for LAK-18 was "Towards User-Centred Analytics". Though several of the papers receiving high scores in the review process explicitly dealt with this issue, it has been decided to devote a complete special issue of the journal to this theme and invite those papers in this special issue to come. Thus, the present special issue LAK-18 covers a broad range of themes, which reflect well the diversity and the vibrancy of the community, but excludes User-Centred Analytics. This editorial describes the story behind this special issue. This story begins with the contributions submitted to the conference and finishes with a short introduction to the papers in this issue. The two first episodes of the story, contribution type and country, include both tracks, research and practitioner. The reminder episodes refer only to the research track.
ISSN:1929-7750