Quasi-experimental study evaluates student performance in digital engineering education using TISE-VALORIZE framework, suggesting improved learning outcomes.
A Correction on: Johan MC, Langi AZR, Nugraha IGBB, Imbar RV and Sinaga P (2026) Orchestrating value co-creation in digital education using the TISE-VALORIZE framework: from knowing to becoming. Front. Educ. 11:1827542. doi: 10.3389/feduc.2026.1827542In the abstract, the Methods section was duplicated overwriting the Results section. This has been corrected to read: Introduction: AI can automate technical activities, but it cannot teach skills that only people have. This study proposes the TISEVALORIZE framework and presents a preliminary empirical examination of its association with student performance outcomes in digital engineering education. Methods: A posttest-only quasi-experimental study with non-equivalent cross-cohort groups involved 138 undergraduate engineering students: one intervention group implementing TISE-VALORIZE (n = 53) and two control groups receiving conventional instruction (n = 42; n = 43). Student performance was evaluated through Structured Academic Activities assessed using a Bloom's Taxonomy-aligned rubric. Results: The intervention group showed higher mean scores (M = 94.98, SD = 7.21) and lower score variance (Var = 52.01) than Control 1 (M = 88.70, SD = 18.33, Var = 335.78) and Control 2 (M = 86.54, SD = 17.05, Var = 290.98). A one-way ANOVA indicated a significant group difference, F(2, 135) = 4.41, p = .014, η² = .061, and Tukey post-hoc analysis showed a significant difference between the intervention group and Control 2, while the difference between the intervention group and Control 1 did not reach significance. Discussion: These preliminary results suggest that the framework may support more consistent learning outcomes. However, direct measures of cognitive load, motivation, and related psychological processes were not included in the present study. These findings provide preliminary support for the framework's potential to improve performance consistency, while larger-scale studies with direct measures of cognitive and motivational processes are needed. The original version of this article has been updated.
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