Attitude is the strongest predictor of behavioral intention for new users, while perceived usefulness is strongest for light, medium and heavy users¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2012 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Path analyses show all C-TAM-TPB predictors influence acceptance, but significance varies by user type; variance explained in BI ranges from .39 (medium) to .71 (heavy). → Pynoo 2012
Evidence¶
Pynoo 2012¶
Pynoo, B., Tondeur, J., Van Braak, J., Duyck, W., Sijnave, B. & Duyck, P. (2012). Teachers' acceptance and use of an educational portal. Computers & Education, 58(4), 1308-1317. https://doi.org/10.1016/j.compedu.2011.12.026
q2 · i? · associational · r2
Path analyses per user type in AMOS 6.0 tested the C-TAM-TPB model. The abstract reports that "the strongest predictors of behavioral intention to use the portal are attitude (‘new’) and perceived usefulness (‘light’, ‘medium’ and ‘heavy’)."
"The strongest predictors of behavioral intention to use the portal are attitude (‘new’) and perceived usefulness (‘light’, ‘medium’ and ‘heavy’), with variance explained ranging from .39 (‘medium’) to .71 (‘heavy’)."
Discussion¶
Related Claims¶
- User types differ significantly in acceptance of the portal, with perceived behavioral control more important for heavy users and subjective norms and ease of use more important for light and medium users — reports the opposite
- Perceived usefulness, attitude, and behavioral intention form a significant TAM pathway predicting GenAI adoption among law students — related
- Perceived usefulness and perceived ease of use of GenAI tools significantly predict teachers' attitudes and behavioural intention — related
- The extended TAM model explains 42.3% of the variance in intention to use mobile library applications — related
- Attitude is the most powerful predictor of behavioral intention to use MALL among higher education learners in Vietnam. — related
- Perceived usefulness, rather than perceived ease of use, was the primary predictor of LLM adoption across TAM-based studies — related
Page metadata
| Field | Value |
|---|---|
status |
review |
generated |
by process:wiki-ingest on 2026-10-29 |
trust |
unverified — no one has confirmed this page's content |
Frontmatter is the page's machine-readable record — see the Schema & Guide.