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Orchestrating value co-creation in digital education using the Tise-Valorize framework

From knowing to becoming

Bibliographic Data

ID22164175
AuthorsMeliana Christianti Johan (0009-0000-7217-9415, Bandung Institute of Technology), Armein Z R Langi (0000-0001-9516-1461, Bandung Institute of Technology), I Gusti Bagus Baskara Nugraha (0000-0003-1197-8947, Bandung Institute of Technology), Radiant Victor Imbar (0000-0001-6752-0746, Maranatha Christian University), Parlindungan Sinaga (0000-0003-0333-6522, Indonesia University of Education)
Year2026
Volume11
Publication date2026-04-29
Open AccessYes
TypeARTICLE
VenueFrontiers in Education (JOURNAL)
Journal identifiersISSN: 2504-284X • E-ISSN: 2504-284X
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2026.1827542
OpenAlexW7159641369
LanguageEN
References cited29

Introduction AI can automate technical activities, but it cannot teach skills that only people have. This study proposes the TISE-VALORIZE 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, η 2 = .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

Academic achievement · Cognition · Empirical research · Engineering education · Higher education · Higher Education Practises and Engagement · Persona Design and Applications · Service and Product Innovation

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