The Technology, Knowledge and Learning (TKNL) journal invites submissions for a special issue “Big data in higher education: Research methods and analytics supporting the learning journey” to be published in 2017.
One of the promises of big data in higher education is to enable a new level of evidence-based research into learning and instruction and make it possible to gain highly detailed insight into student performance and their learning trajectories as required for personalizing and adapting curriculum as well as assessment. In the new era of data-driven learning and teaching, researchers need to be equipped with an advanced set of competencies that encompass areas needed for computationally intensive research (e.g., data-management techniques for big data, working with interdisciplinary teams who understand programming languages as well as cognitive, behavioral, social and emotional perspectives on learning) and professional knowledge (including heuristics) that incline a researcher toward computational modeling when tackling complex research problems.
This special issue on data analytics focuses on the enabling computational approaches and challenges in research that support the journey of a learner from pre-university experiences, to marketing and recruitment, to personalized learning, adaptive curriculum and assessment resources, to effective teaching, to post-university life-long learning.
Authors are encouraged to submit any of the manuscript types outlined below, including Work-in-Progress reports which highlight implemented systems in higher education and Emerging Technology reports focusing on data analytics applications. Interested scholars should submit a 1-page proposal including a tentative title, information about contributing author(s), abstract, article type (see below), keywords, and key references to David Gibson (email@example.com) by 15 July 2016 – early submissions are encouraged. All proposals will be reviewed by the special issue review board who will recommend full submissions from among the proposals. All full manuscript submissions will undergo rigorous double-blind peer review by at least three reviewers of the special issue review board and regular TKNL reviewers who will recommend revisions or acceptance.
Important dates and manuscript submission process
Proposal submission: 15 July 2016
Full manuscript invitation: 01 September 2016
Deadline for full manuscript submissions: 31 December 2016
Manuscripts returned to authors for revision: 01 March 2017
Final manuscripts due: 31 May 2017
Publication of the Special Issue (TKNL 22/3): 15 October 2017
Select “S.I.: Big Data in Higher Education” when submitting your full manuscript via the editorial portal: www.editorialmanager.com/tknl
Please see descriptions below for manuscript types and requirements to be accepted for this special section – http://www.springer.com/10758?detailsPage=societies
Original Research: Original research papers primarily report findings from original quantitative, qualitative, or mixed methods studies. The purpose of the reported study is expected to be theoretically well-ground, using a sound methodological approach, and providing a comprehensive source for practical implications. Original research manuscripts are expected to be between 4,500 and 8,000 words including references, tables, and figures.
Work-in-Progress Study: Work-in-progress studies provide early insights into leading research projects or document progressions of excellent on-going research. The idea of this article type is to showcase the progression of scholarly empirical work from the initial design and piloting of a research project to large-scale testing and implementation. This may include validity testing of instruments, revisions of learning environments, project snapshots and preliminary results, or replication of empirical studies. Work-in-progress study manuscripts are expected to be between 4,500 and 8,000 words including references, tables, and figures.
Integrative Review: An integrative review provides an overview and synthesizes relevant literature using an adequate method such as: Chronological (organized around a specific timeline), publication type (grouped by sources of research evidence), trends (identify different streams of the research over time), thematic (organized around topics or ideas), or methodological (grouped by research studies or projects). Integrative review manuscripts are expected to be between 4,000 and 8,000 words including references, tables, and figures.
Emerging Technology Report: An emerging technology reports reviews new developments in educational technology by assessing the potentials and key challenges for leading digital learning environments. Emerging technology report manuscripts are limited to 3,000 words including references, tables, and figures.
To learn more about the general scope of the journal, please visit the Springer website: www.springer.com/10758
We look forward to your manuscripts!
Lead Editor, Special Issue
Associate Professor David C. Gibson, Curtin University
Professor Dirk Ifenthaler