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Do teaching staff trust stakeholders and tools in learning analytics? A mixed methods study.

Asma Shannan AlzahraniYi-Shan TsaiNaif AljohaniEmma Whitelock-WainwrightDragan Gasevic
Published in: Educational technology research and development : ETR & D (2023)
Learning analytics (LA) has gained increasing attention for its potential to improve different educational aspects (e.g., students' performance and teaching practice). The existing literature identified some factors that are associated with the adoption of LA in higher education, such as stakeholder engagement and transparency in data use. The broad literature on information systems also emphasizes the importance of trust as a critical predictor of technology adoption. However, the extent to which trust plays a role in the adoption of LA in higher education has not been examined in detail in previous research. To fill this literature gap, we conducted a mixed method (survey and interviews) study aimed to explore how much teaching staff trust LA stakeholders (e.g., higher education institutions or third-parties) and LA technology, as well as the trust factors that could hinder or enable adoption of LA. The findings show that the teaching staff had a high level of trust in the competence of higher education institutions and the usefulness of LA; however, the teaching staff had a low level of trust in third parties that are involved in LA (e.g., external technology vendors) in terms of handling privacy and ethics-related issues. They also had a low level of trust in data accuracy due to issues such as outdated data and lack of data governance. The findings have strategic implications for institutional leaders and third parties in the adoption of LA by providing recommendations to increase trust, such as, improving data accuracy, developing policies for data sharing and ownership, enhancing the consent-seeking process, and establishing data governance guidelines. Therefore, this study contributes to the literature on the adoption of LA in HEIs by integrating trust factors.
Keyphrases
  • electronic health record
  • health information
  • big data
  • healthcare
  • systematic review
  • social media
  • quality improvement
  • medical students
  • clinical practice
  • global health
  • medical education