Student and instructor motivation as an intermediate outcome is influenced by system robustness, learning analytics visualisation, and recognition of adaptive learning's advantages¶

Claim · All claims
Evidence · 1 study · qualitative r3 · q2
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Motivational aspects of students' and instructors' use of adaptive systems were influenced by determinants related to learning analytics methods, system robustness, and recognition of the advantages of adaptive learning. → Mirata 2023

Evidence¶

Mirata 2023¶

Mirata, V., & Bergamin, P. (2023). Role of organisational readiness and stakeholder acceptance: an implementation framework of adaptive learning for higher education. Education Tech Research Dev. https://doi.org/10.1007/s11423-023-10248-7

q2 · i? · qualitative · r3

Qualitative Delphi data (Fig. 2 connections); the article reports motivation was influenced by the robustness of the system and learning analytics capabilities. One expert criticised the Swiss system's analytics: "Moodle logs’ data are insufficient, and the feedback system is laborious".

"a well-functioning adaptive 1583 Role of organisational readiness and stakeholder acceptance:… 1 3 learning system and the visualisation of students’ success in it could increase the enthusi- asm of the lecture and the motivation of the students"

Discussion¶

Related Claims¶

• Acceptability of adaptive learning by all stakeholders was the most frequently mentioned outcome, strongly connected to stakeholder recognition of its advantages — related
• Instructor motivation to use adaptive learning acts as a facilitator influencing student acceptability of adaptive learning — related
• AI-supported adaptive systems are reported to enhance adult learner engagement, motivation, and outcomes when aligned with learner goals and prior knowledge — a broader claim this one bears on