| Sumario: | Background: Although blended learning (BL) has multiple educational prospects, it also poses challenges such as keeping students motivated. Objectives: This study investigates students' perceptions of how learning analytics (LA) can be used to support the design of a BL environment in order to promote students' basic need for relatedness, which is a dimension of motivation. Hence, it is hypothesized that sharing LA trends with students and illustrating which course adaptations were performed based on these trends, will result in positive student perceptions and can support students' basic need satisfaction for relatedness. Methods: A quasi‐experimental intervention study was executed using a mixed‐method approach (N = 257 students) in a BL course in university‐based teacher education. The intervention focuses on three types of learning management system LA data (general, content, and background) that are actively used by the instructor. General data consists of generated time on task, content data deals with the content of a learning path and background data includes information about students' previous education. Results and Conclusions: The results show that students' perceptions regarding these LA are positive and most in favour of content data. Moreover, the qualitative data illustrate that students acknowledge the potential value of LA for stimulating relatedness. Implications: Important recommendations for the use of LA in BL environments are (1) interest and commitment by the instructor by means of a powerful course intervention, (2) to consider gathering LA data anonymously on the group level, (3) instructors should communicate about the nature of the collected data, (4) actively process this input and, (5) use it in a formative manner. Lay Description: What is currently known about the subject matter: Motivation can decrease in the online part of blended learning courses.Learning Analytics can offer instructors' insight into students' online activities.Students' LA perceptions are positive, but show also averse to any form of data collection that might put them under surveillance of the instructor. What this paper adds to this: Three types of LA data, consisting of both quantitative and qualitative data, provide a broad and varied insight into students' online activities.Students' perceptions regarding these different types of LA data are positive.LA data informs instructors to adapt the learning environment in order to support students' needs.Students believe LA can promote students' basic need for relatedness (which is a dimension of motivation), if the instructor applies LA to enrich the learning environment. Implications of study findings for practitioners: Instructors should actively process the LA data and show involvement with a powerful intervention.It is crucial to communicate to students in a transparent way about the gathering of LA data and why specific types of data have been chosen and will be used.When designing blended learning courses, it is important to only use LA data on students' performances in a formative manner.It is important to gather LA data on a group level (e.g., per group of students who follow the same face‐to‐face part) in the LA design, rather than the student level.
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