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

Theory · All theories
Evidence · 3 claims (2 for, 1 against) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 3 claims rest on one study

Description¶

The study applies the Technology Acceptance Model, adapted from Venkatesh and Davis's (2000) revised TAM, in which intention to use new technologies is based on perceived usefulness and perceived ease of use. Perceived usefulness is "the degree to which a person believes that using a particular system would enhance his or her job performance", and ease of use is learning the technology being perceived as "free from effort". The revision adds job relevance, output quality, and result demonstrability as influences on perceived usefulness, operationalized here as academic relevance. The framework structured the survey and interview analysis of ASR acceptance.

Design Implications¶

Context¶

Requirements¶

• Survey items measuring perceived usefulness, perceived ease of use, and intention to use, scored on a Likert scale
• Adaptation of job relevance to the learners' academic context

Constraints¶

• Result Demonstrability subscale showed low internal consistency (α =.52) in this study; Intention to Use α =.60

Target Learners¶

• adult second language learners using new writing technologies

Target Learning Objectives¶

• technology acceptance for L2 writing

Claims¶

• Esl Learners Positive Perceptions Asr Writing [+M]
• Tam Construct Means Asr Writing Study [+M]
• Some ESL learners felt their English was not high enough to use ASR because their speech was not always intelligible to it, although overall perceived usefulness was positive [-W]

Related Theories¶

• Extended TAM with perceived contextual value (PCV) for mobile learning acceptance
• UTAUT framework for technology acceptance
• Meta-UTAUT model of technology acceptance applied to MALL in EFL learning

Examples¶

• TAM-grounded post-session survey instrument with five domains and 15 open-ended questions

Key Sources¶

• Johnson, C., & Cardoso, W. (2021). Speaking to write: examining language learners’ acceptance of automatic speech recognition as a writing tool. In N. Zoghlami et al. (Eds), CALL and professionalisation: short papers from EUROCALL 2021 (pp. 167-171). Research-publishing.net. https://doi.org/10.14705/rpnet.2021.54.1327