Special Section on Human Creativity and Learning Analytics

2024-06-24

Guest Editors:

Arnon Hershkovitz, Ph.D., School of Education, Tel Aviv University, Israel, arnonhe@tauex.tau.ac.il

Davide Fossati, Ph.D., Department of Computer Science, Emory University, Atlanta, GA, USA, davide.fossati@emory.edu

Nilufar Baghaei, Ph.D., School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia, n.baghaei@uq.edu.au

Aims & Scope

Creativity is a thinking ability that enables problem-solving in an innovative manner and produces original and valuable products. Creativity has been identified as crucial to human inventive potential in all disciplines, and its influence dominates various spheres of life. In recent years, there has been growing recognition that creativity is an essential skill for the 21st century that can be nurtured and should be included in the curriculum from an early age. International organizations have identified creativity as a core skill to be developed to promote personal growth, lifelong learning, and workmanship (e.g., OECD, 2018; World Economic Forum, 2020), and recent has supported this notion (Karwowski et al., 2020; Lucas & Venckute, 2020; Rubenstein et al., 2022). Following its importance, student assessment programs already put creativity in the limelight (OECD, 2024).

The research on creativity is pervasive, and throughout recent decades, researchers proposed various definitions, conceptualizations, and assessment methods (Henriksen et al., 2021; Israel-Fishelson & Hershkovitz, 2022; Lucas & Venckute, 2020). One of the most useful taxonomies of creativity is the “4 Ps of creativity:” (1) Person, referring to the personality, qualities, behaviours, and self-perceptions of the creator; (2) Process, referring to the cognitive processes involved in creating ideas, including motivation, thinking, and learning; (3) Product, referring to the concrete embodiment of the creative idea or the artifact created; and (4) Press, referring to environmental impacts on the person. In the educational context, these conceptualizations may refer to different aspects of learning processes and can be looked at from different points of view (Li et al., 2022; Loveless, 2002).

Over the last few decades—especially since the early 2000s—research on creativity in learning and teaching has grown and spanned many areas, including, e.g., teaching and learning of creativity, interconnections between creativity and learning-related variables, influencing factors on creativity, and creativity-supporting learning environments. Within this wide scope, studies have differed from each other by their definition of creativity, unit of observation, data collection, and data analysis, among others.

Learning Analytics plays an important role in the extension and expansion of this growing line of research, as it enables new approaches to the study of human creativity in educational contexts (Marrone & Cropley, 2022). For once, computational approaches that have been an integral part of the Learning Analytics toolset—and new ones that can be suggested—may help in assessing creativity in unprecedented ways, therefore meaningfully enhancing our understanding of creative processes (Chou et al., 2024; Hershkovitz et al., 2019; Kovalkov et al., 2021; Manske & Hoppe, 2014). Following that, Learning Analytics can inform educators and learners regarding creativity, hence support its improvement, in an ongoing feedback cycle.

At this point in time, research in this area is still in its infancy, hence the Learning Analytics research community can significantly benefit from understanding the state-of-the-art in the field and from thinking together about how to promote it. To advance the study of human creativity using Learning Analytics, we welcome various types of submissions to this special section, including (but not limited to):

  • Empirical studies that implement Learning Analytics approaches to study human creativity in educational contexts
  • Methodological papers introducing novel, validated approaches to measure human creativity
  • Systematic reviews of the study of creativity using Learning Analytics
  • Critical perspectives that question the value of studying human creativity using Learning Analytics.

 

Submission Instructions

An initial abstract submission of 500-1000 words (including title, outline of the proposed article, 3-5 keywords, and key references) is required; authors will receive initial feedback regarding the abstract. Abstracts should be uploaded to the submission system by October 1, 2024.

Full papers will undergo the standard double-blind reviewing process. Therefore, if based on your abstract, you are invited to submit a full paper, this invitation is just that and should not be taken as an indication for acceptance of the final paper.

Final submissions will take place through JLA’s online submission system at http://learning-analytics.info. When submitting a paper, select the section “Special Section: Human Creativity and Learning Analytics”. All submissions should follow JLA’s standard manuscript guidelines and template available on the journal website. Queries may be sent to the special section editors.

 

Important Dates

  • Abstracts submission (mandatory): October 1, 2024
  • Full manuscripts submission: December 15, 2024
  • Completion of first review round: February 28, 2025
  • Revised manuscripts due: March 31, 2025
  • Final decision notification: April 30, 2025
  • Revised/final manuscripts due: May 15, 2025
  • Publication of Special Section: August 2025, in JLA 12(2)

 

References

Chou, E., Fossati, D., & Hershkovitz, A. (2024). A code distance approach to measure originality in computer programming. The 16th International Conference on Computer Science Education.

Henriksen, D., Creely, E., Henderson, M., & Mishra, P. (2021). Creativity and technology in teaching and learning: a literature review of the uneasy space of implementation. Educational Technology Research and Development, 69(4), 2091–2108. https://doi.org/10.1007/S11423-020-09912-Z/FIGURES/1

Hershkovitz, A., Sitman, R., Israel-Fishelson, R., Eguíluz, A., Garaizar, P., & Guenaga, M. (2019). Creativity in the acquisition of computational thinking. Interactive Learning Environments, 27(5–6), 628–644. https://doi.org/10.1080/10494820.2019.1610451

Israel-Fishelson, R., & Hershkovitz, A. (2022). Studying interrelations of computational thinking and creativity: A scoping review (2011–2020). Computers & Education, 176(February 2021), 104353. https://doi.org/10.1016/j.compedu.2021.104353

Karwowski, M., Jankowska, D. M., Brzeski, A., Czerwonka, M., Gajda, A., Lebuda, I., & Beghetto, R. A. (2020). Delving into creativity and learning. Creativity Research Journal, 32(1), 4–16. https://doi.org/10.1080/10400419.2020.1712165

Kovalkov, A., Paasen, B., Segal, A., Pinkwart, N., & Gal, K. (2021). Automatic creativity measurement in Scratch programs across modalities. IEEE Transactions on Learning Technologies, 14(6), 740–753. https://doi.org/10.1109/TLT.2022.3144442

Li, Y., Kim, M., & Palkar, J. (2022). Using emerging technologies to promote creativity in education: A systematic review. International Journal of Educational Research Open, 3, 100177. https://doi.org/10.1016/J.IJEDRO.2022.100177

Loveless, A. (2002). Literature review in creativity, new Technologies and learning.

Lucas, B., & Venckute, M. (2020). Creativity – A transversal skill for lifelong learning. An overview of existing concepts and practices. In P. Kampylis & R. Cachia (Eds.), JRC Research Reports. Publications Office of the European Union. https://ideas.repec.org/p/ipt/iptwpa/jrc121862.html

Manske, S., & Hoppe, H. U. (2014). Automated indicators to assess the creativity of solutions to programming exercises. Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014, 497–501. https://doi.org/10.1109/ICALT.2014.147

Marrone, R. L., & Cropley, D. H. (2022). The role of learning analytics in developing creativity. In Y. Wang, S. Joksimović, M. O. Z. San Pedro, J. D. Way, & J. Whitmer (Eds.), Social and Emotional Learning and Complex Skills Assessment. Advances in Analytics for Learning and Teaching (pp. 75–91). Springer. https://doi.org/10.1007/978-3-031-06333-6_5

OECD. (2018). The Future of Education and Skills: Education 2030. OECD Education Working Papers, 23. https://doi.org/10.1111/j.1440-1827.2012.02814.x

OECD. (2024). New PISA results on creative thinking: Can students think outside the box? (PISA in Focus, No. 125).

Rubenstein, L. D. V., Thomas, J., Finch, W. H., & Ridgley, L. M. (2022). Exploring creativity’s complex relationship with learning in early elementary students. Thinking Skills and Creativity, 44, 101030. https://doi.org/10.1016/J.TSC.2022.101030

World Economic Forum. (2020). The future of jobs report 2020. https://www.weforum.org/reports/the-future-of-jobs-report-2020/digest