Claims

Perceived mobility of an m-learning app positively influences both perceived usefulness and perceived ease of use in out-of-classroom settings

Claim · All claims
Evidence · 1 study · associational r2 · q3
Currency · newest study 2025 · 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.

q3 i? Mobility significantly predicts perceived ease of use (β = 0.59, p < 0.001) and perceived usefulness (β = 0.37, p < 0.001) among adult m-learning app users. → Chenxi Liu 2025

Evidence

Chenxi Liu 2025

Chenxi Liu, Ana-Paula Correia, Young Min Kim. (2025). Determining mobile learning acceptance outside the classroom: an integrated acceptance model. Education Tech Research Dev. https://doi.org/10.1007/s11423-025-10514-w

q3 · i? · associational · r2

Structural equation modeling of survey data from 639 valid MTurk responses tested the proposed model. The path analysis shows mobility significantly predicts PEOU (β = 0.59, p < 0.001) and PU (β = 0.37, p < 0.001), supporting H6a and H6b.

"The latent path analysis supports variation of perceived ease of use (PEOU) is related to MO and Compatibility (COM) (β = 0.59, p < 0.001; β = 0.30, p < 0.01, respectively). Also, expected change of PU is associated with MO, COM, service quality (SQ), PEOU (β = 0.37, p < 0.001; β = 0.39, p < 0.001; β = 0.26, p < 0.001; β = 0.13, p < 0.05, respectively)."

Discussion

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