Understanding Congolese Students’ Behavioural Intentions Toward Learning Management Systems: An Extended TAM Approach

This study empirically validates a technology acceptance model (TAM)-based framework for predicting technology adoption, integrating core constructs—perceived usefulness (PU), perceived ease of use (PEOU), and social norms (SN)—to examine their influence on behavioural intention and actual usage. Using partial least squares structural equation modelling (PLS-SEM), the measurement model demonstrated strong reliability and validity, while the structural model confirmed all hypothesised relationships. PU emerged as the most influential predictor of intention, and behavioural intention fully mediated the link between perceptual antecedents and usage. The model explained 42.3% of the variance in intention and 34.3% in usage, with Q² values confirming substantial predictive relevance. These findings contribute to the literature by reaffirming the centrality of intention in technology adoption and by highlighting the complementary role of social norms in shaping user behaviour. The study offers theoretical and practical insights for designing inclusive digital strategies, particularly in emerging economies.

Authors

Institutions

Publication Details

Journal
Journal of Applied Research in Technology & Engineering
Published
2026-01-22
DOI
https://doi.org/10.4995/jarte.2026.25061
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Understanding Congolese Students’ Behavioural Intentions Toward Learning Management Systems: An Extended TAM Approach

Rodrigue Kalumendo, Tabiaki Tandele Rufin, Ntumba Malu Pierre, Paluku Norbert Vagheni
Journal of Applied Research in Technology & Engineering
Technology Adoption and User Behaviour
article

Understanding Congolese Students’ Behavioural Intentions Toward Learning Management Systems: An Extended TAM Approach

Rodrigue Kalumendo, Tabiaki Tandele Rufin, Ntumba Malu Pierre, Paluku Norbert Vagheni
article en

Abstract

This study empirically validates a technology acceptance model (TAM)-based framework for predicting technology adoption, integrating core constructs—perceived usefulness (PU), perceived ease of use (PEOU), and social norms (SN)—to examine their influence on behavioural intention and actual usage. Using partial least squares structural equation modelling (PLS-SEM), the measurement model demonstrated strong reliability and validity, while the structural model confirmed all hypothesised relationships. PU emerged as the most influential predictor of intention, and behavioural intention fully mediated the link between perceptual antecedents and usage. The model explained 42.3% of the variance in intention and 34.3% in usage, with Q² values confirming substantial predictive relevance. These findings contribute to the literature by reaffirming the centrality of intention in technology adoption and by highlighting the complementary role of social norms in shaping user behaviour. The study offers theoretical and practical insights for designing inclusive digital strategies, particularly in emerging economies.

Journal of Applied Research in Technology & EngineeringVol. 7(1)
Université de Notre-Dame du Kasai (CD), Universite Adventiste de Lukanga (CD)
Reduced inequalities
Openalex Percentile: Top 81%
Technology Adoption and User Behaviour
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.