Extended TAM with perceived contextual value (PCV) for mobile learning acceptance¶

Theory · All theories
Evidence · no claims cited

Description¶

The article extends Davis' Technology Acceptance Model, which predicts actual system use via perceived usefulness (PU), perceived ease of use (PEOU), attitude, and behavioral intention (BI), by adding a mobile-learning-specific exogenous construct. Building on Lee/Jun's perceived contextual value and Huang et al.'s perceived mobility value, "this study proposes to add PCV as a mobile learning specific construct to predict BI in the mobile adapted TAM." The resulting model tests paths from PU, PEOU and PCV to BI, and from PCV and PEOU to PU, with PCV operationalized from items adapted from Akour (2009), Huang et al. (2007) and Lee/Jun (2007).

Design Implications¶

Context¶

Requirements¶

• Reflective measurement models for each construct with outer loadings above 0.70 and AVE above 0.50
• Survey items measured on a five-point Likert scale following exposure to the system stimulus

Constraints¶

• The path model excluded further external variables validated in prior mobile learning studies, treating TAM as parsimonious

Target Learners¶

• students and young professionals using mobile technology

Target Learning Objectives¶

• predicting behavioral intention to use mobile language learning applications

Claims¶

Related Theories¶

• UTAUT framework for technology acceptance
• Technology Acceptance Model (revised by Venkatesh and Davis) as a framework for evaluating L2 learners' acceptance of writing technologies

Examples¶

• CoLaLe app prototype with geo-fence triggered vocabulary learning sessions
• TAM-grounded post-session survey instrument with five domains and 15 open-ended questions

Key Sources¶

• Stephan Böhm and Georges Philip Constantine. (2015). Impact of Contextuality on Mobile Learning Acceptance: An Empirical Study Based on a Language Learning App. 11th International Conference Mobile Learning 2015. https://isbnsearch.org/isbn/9789898533364