Objective - Deeper learning involves intricate neural interactions, the result of a whole learning experience that is less foreseeable and can rapidly emerge beyond the curriculum, motivational shifts, and learning outcomes among learners. This paper examined the respondents' learning outcomes from using digital tools and interactive, design-oriented tasks espoused by the quadruple helix engagement framework.

Methodology - Respondents comprised 116 year-1 computing informatics students in a higher technological education institution in Brunei. Guided by the tenets of Scholarship in Teaching and Learning (SoTL), the study employed a context-sensitive approach, intervention-enacted action research tailored to the structure of a 14-week semester in Professional Ethics.

Findings - It was framed by the use of digitally supported teaching tools, extensive in-class interactions, and the monitoring of students' learning levels. Data collected from student reflections, activity feedback, peer scores, and other task-related artifacts were inductively analyzed using Bloom's and Krathwohl's taxonomies as indices in scaling learning outcomes. Periodic validation of results emerged from the exchanges among the lecturer-researcher and two co-researchers in pedagogy and curriculum design, respectively. Findings showed that respondents demonstrated learning outcomes that scaled to metacognition-based higher-order thinking skills, such as analyzing (C4) and evaluating (C5), two levels higher than the projected conceptual-procedural-related learning outcomes, such as applying (C3), understanding (C2), and remembering (C1).

Novelty - Spiraling students' tasks both individually and collaboratively as the structure of teaching generated interactive engagement and expanded students' conceptual and affective learning outcomes.

Type of Paper - Empirical

Keywords: learning outcomes, metacognitive skills, higher order thinking skills, quadruple helix engagement, digital-driven tools, cognitive tasks, SoTL, taxonomy, learning outcomes

JEL Classification: D91, J24.

URI: https://gatrenterprise.com/GATRJournals/JBER/vol11.1_3.html

DOI: https://doi.org/10.35609/jber.2026.11.1(3)

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