A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour

Eight reviews (12.1%) also mentioned the role of ITS in teaching course content. Most prevalent was the use of ITS in the medical and scientific fields, for example, as virtual patient simulators or case studies to nursing, medical or dental students and staff (Buchanan et al., 2021; Hwang et al., 2022; Saghiri et al., 2022). In scientific settings, students performed experiments using lab equipment, with support tailored to their needs (Crompton & Burke, 2023). Personalised tutoring was also frequently mentioned in addition to teaching content. Rangel-de Lázaro and Duart (2023) discussed the use of an interactive tutoring component for a Java programming course throughout the Covid-19 pandemic. Intelligent feedback and hints can be embedded into programming tasks, helping with specific semantic or syntactic issues (Crow et al., 2018), and specifically tailored hints and feedback were also provided on tasks to solve problems (Zawacki-Richter et al., 2019).

Student ITS acceptance

Student acceptance of ITS was addressed in four reviews (6.1%), including Rangel-de Lázaro and Duart (2023) who found five papers focused on Engineering Education (4.7% of studies). Chu et al. (2022) found that the most frequently discussed ITS issues were related to affect (n = 17, 41.5%) with the most common topics being student attitudes (n = 6, 33.33%) and opinions of learners or learning perceptions (n = 6, 33.33%), followed by emotion (n = 3, 18.75%). Technology acceptance model or intention of use, self-efficacy or confidence, and satisfaction or interest were less discussed. Harmon et al. (2021) found a limited amount of evidence of positive effects of AI on learning outcomes in their review on pain care in nursing education. The reactions of participants varied and were affected by many factors, including technical aspects (e.g., accessibility or internet speed), a lack of realism, poor visual quality of nonverbal cues, and the ability to ask avatars a question. Saghiri et al. (2022) examined artificial intelligence (AI) and virtual teaching models within the context of dental education and evaluated students’ attitudes towards VR in implant surgery training, where they also found current ITS capacity to impact on student acceptance, suggesting that future tools need to account for differentiation of oral anatomy.

Curating learning materials

Three reviews (4.5%) addressed the use of material curation when using ITS. Zawacki-Richter et al. (2019) found three studies (2.1%) that discussed this function, which relate to the presentation of personalised learning materials to students, and only one study was identified by Zhang et al. (2023). Crow et al. (2018) concluded that when designing systems to intelligently tutor programming, it would be valuable to consider linking supplementary resources to the intelligent and adaptive component of the system and have suggested this for future ITS development.

Facilitating collaboration between learners

Two reviews (3.0%) discussed findings related to ITS facilitating collaboration, which can help by, for example, generating questions and providing feedback on the writing process (Alam & Mohanty, 2022). Zawacki-Richter et al. (2019) only found two primary studies that explored collaborative facilitation and called for further research to be undertaken with this affordance of ITS functionality.