Design intervention programs building academic self-efficacy (vicarious learning, progressive mastery, positive feedback) before and alongside AI integration for students with motor disabilities¶

Strategy · All strategies
Evidence · 1 claim (1 mixed) · 1 study (1 qualitative), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The article's practical implications recommend designing intervention programs focused on academic self-efficacy for students with motor disabilities, because higher self-efficacy was associated with greater AI use. It states that "Interventions based on Bandura's theory, such as vicarious learning, progressive mastery experiences, and positive feedback, may be relevant to differences in academic confidence and patterns of AI use." Programs should develop long-term capabilities while considering possible technological dependency from excessive AI use.

Design Implications¶

Context¶

Requirements¶

• Integration of AI as a structural pedagogical component within university inclusion frameworks rather than a peripheral or auxiliary resource

Constraints¶

• The authors caution against a techno-deterministic perspective assuming mere provision of AI automatically addresses educational inequalities, and note AI cannot replace structural accessibility transformations or professional support

Target Learners¶

• university students with motor disabilities

Target Learning Goals¶

• academic self-efficacy, strategic and responsible AI use, academic autonomy and participation

Claims¶

• Some students described confidence in programming that depended on AI being available [~W]

Related Strategies¶

Examples¶

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Key Sources¶

• Suriá-Martínez R, García-Castillo F, López-Sánchez C and García del Castillo JA (2026). Between perceived competence and artificial intelligence: academic self-efficacy profiles in university students with motor disabilities. Front. Educ. 11:1956192. https://doi.org/10.3389/feduc.2026.1956192