Log data from co-creation platforms can trace social practices of professional learning despite a streetlight effect¶

Strategy · All strategies
Evidence · 5 claims (4 for, 1 mixed) · 2 studies (1 associational, 1 theoretical), q2 · 0 of 2 report an effect size · 5 claims rest on one study

Description¶

The study demonstrates that traces from digital co-creation platforms can evidence social practices of knowledge appropriation, maturation and scaffolding at large scale, using ILSs as the unit of analysis and log-based indicators. The authors acknowledge a "'streetlight effect'": the analysis "relies only on the data already available about certain KAM practices mediated by Graasp, whereas additional interactions may have taken place through other face-to-face or digital channels." They recommend designing ICT tools with social-practice tracking in mind and gathering complementary evidence from other physical and digital spaces.

Design Implications¶

Context¶

Requirements¶

• Platforms must track authoring, sharing, editing and student-mode use; adoption requires an operational rule (more than 10 student-mode users)

Constraints¶

• Observational design without full sight of all variables; ILS qualitative characteristics and temporal evolution within each ILS were not analyzed

Target Learners¶

• teachers using co-creation platforms

Target Learning Goals¶

• understanding social dimensions of teacher professional learning

Affordances¶

• Knowledge Appropriation Model Kam

Claims¶

• Expert scaffolding is associated with ILS adoption, but the fading stage shows a comparatively low rate (8.27%) and was a non-significant predictor [+W]
• ILS adoption rate increases across knowledge maturation stages, from 3.38% for individually created ILSs to 43.94% for published ILSs [+W]
• ILS reuse and edition as a proxy for knowledge appropriation relates to about four times higher adoption (19.77% vs 4.51%) [+W]
• Logistic regression shows all traced KAM practices except fading are significant positive predictors of adoption, with maturation strongest (odds ratios up to 12.36) and model AUC = 0.79 [+W]
• Engagement inferred from log data must be treated with caution because digital traces reflect unevenly distributed social and material conditions [~W]

Related Strategies¶

Examples¶

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Key Sources¶

• María Jesús Rodríguez-Triana, Luis P. Prieto, Tobias Ley, Ton de Jong, Denis Gillet. (2020). Social practices in teacher knowledge creation and innovation adoption: a large-scale study in an online instructional design community for inquiry learning. International Journal of Computer-Supported Collaborative Learning. https://doi.org/10.1007/s11412-020-09331-5