Effects of an 80-10-10 Multilingual CTCA-Harlybot Model on Achievement and Critical Thinking in Mobile and Adaptive Systems

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Authors: Alli Olawale Abdurrazaq, Peter Akinsola Okebukola, Toyin Enikuomehin, Deborah O. Agbanimu, Uchenna Ugwuoke, Victoria Abokunwa, Bashir Oyeniran Ayinde
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References: 15

Abstract

Abstract This study compared the effects of three instructional approaches on university students’ achievement (retention) and critical-thinking skills in a Mobile and Adaptive Systems course: (a) traditional lecture, (b) Harlybot-supported Culturo-Techno-Contextual Approach (CTCA) delivered in 100% English (monolingual), and (c) Harlybot-supported CTCA using an 80% English + 10% Nigerian Pidgin + 10% Yoruba strategic code-switching model (80-10-10 multilingual). A pre-post quasi-experimental design with 75 second-year undergraduates was employed. Cognitive Task Analysis (CTA) had previously identified the OSI Model as the most difficult concept, justifying the intervention focus. MANCOVA (covariates: pre-tests) revealed no significant differences in achievement (retention) or critical-thinking scores across the three conditions (p > .05). However, the 80-10-10 multilingual group consistently displayed the highest adjusted means on both outcomes, with moderate-to-large effect sizes (η² = .09–.14). Qualitative data from think-aloud protocols and post-intervention focus groups explained the pattern: brief, culturally anchored code-switches at OSI encapsulation/de-encapsulation moments reduced extraneous cognitive load and increased germane processing without compromising academic identity. The findings extend Okebukola’s Eco-Techno-Cultural Theory by quantifying the optimal cultural-linguistic dosage (≤ 20%) for cognitively demanding computing topics in African multilingual universities.

Fields of Study & Subjects

Visual and Cognitive Learning Processes Intelligent Tutoring Systems and Adaptive Learning Teaching and Learning Programming

Publication details

Journal / source
Research Square
Publication date
18 February 2026
Language
EN
Document type
Preprint