Learning analytics aims to improve learning and teaching in digital learning environments by optimizing them. Real-time feedback, suggestions, directions, and interventions are structured in the digital learning environments. In order to structure more effective interventions, it is crucial to ascertain which of these services offered to students is chosen by students. Within the scope of this research, a digital learning environment that can offer interventions to students based on learning analytics was presented. The digital learning environment can provide instructional, supportive and motivational interventions to students. In this context, the aim of this study is to determine which intervention strategies are more successful in which students and which learners prefer them. The students had a 14-week learning experience in the digital learning environment. Analytic Hierarchy Process was used to determine learner preferences. Students primarily prefer motivational and supportive interventions that can offer interventions based on their learning processes. Interventions based on assessment tasks are their last choice. When the intervention types were examined at a more granular level, it was found that the students' primary preferences were to see their individual performances. Detailed information about preferences of the intervention types of the students was discussed.