Fostering An Impactful Field of Learning Analytics
DOI:
https://doi.org/10.18608/jla.2019.63.1Keywords:
Editorial, implementation, rigour, open science, peer review, impact, research, transparencyAbstract
Over 2019 the breadth of articles published in the Journal of Learning Analytics reflects the diversity of contributions to the field, including quantitative, qualitative and design-based studies and contributions through the different submission types (Research, Practical, Data and Tools, and Book Review). This year we have also published two special sections. The first is a set of empirical papers related to the emerging area of Human-Centered Learning Analytics. In this section, five sets of authors each address the core challenge of how to design and implement learning analytics in ways that are people- rather than technology-centric to achieve impact in the field. The second is a new format for the journal, an invited dialogue around a critical community issue. In this section Neil Selwyn asks the intentionally provocative question “what’s the problem with learning analytics?”, which is engaged with by four respondents from the community, representing a variety of different perspectives. Both of these special sections tackle, in their own way, a central issue for the learning analytics community: how we ensure that the work we do has positive impact in the world.
References
Kitto, K., Buckingham, S. S., & Gibson, A. (2018). Embracing imperfection in learning analytics. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK '18). ACM, New York, NY, USA, 451-460. https://doi.org/10.1145/3170358.3170413
Stuart, H. H., Levine, R. A., & Utts, J. (2019) Coup de Grâce for a Tough Old Bull: “Statistically Significant” Expires. The American Statistician, 73:sup1, 352-357. https://doi.org/10.1080/00031305.2018.1543616
Prager, E. M., Chambers, K. E., Plotkin, J. L., McArthur, D. L., Bandrowski, A. E., Bansal, N., Martone, M. E., Bergstrom, H. C., Bespalov, A. & Graf, C. (2019), Improving transparency and scientific rigor in academic publishing. Brain and Behavior, 9(1). https://doi.org/10.1002/brb3.1141
Tennant, J.P., Dugan, J.M., Graziotin, D. et al. (2017) A multi-disciplinary perspective on emergent and future innovations in peer review [version 3; peer review: 2 approved]. F1000Research, 6:1151 https://doi.org/10.12688/f1000research.12037.3
Tracy, S. J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative inquiry, 16(10), 837-851. https://doi.org/10.1177/1077800410383121
Wise, A. F., Knight, S., & Ochoa, X. (2018). When Are Learning Analytics Ready and What Are They Ready For. Journal of Learning Analytics, 5(3), 1-4. https://doi.org/10.18608/JLA.2018.53.1E
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons License, Attribution - NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) license that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
