This analysis draws from the focus groups involving first- and second-year students from the BSc Industrial Management program who took Introduction to Economics (first year) and Introduction to Macroeconomics (second year) at New Uzbekistan University in the Spring semester. Participants included students from both the Treatment group (who received weekly email notifications and conditional access to materials contingent on quiz completion) and the Control group (who had unrestricted access and no targeted email reminders).

Participants include Dilnoza (first year, Treatment) and Mukhammadali (second year, Control), along with Utkirbek and Sevara (second year, Treatment). Interviews were conducted on Teams in 60-minute sessions.

The discussions covered overall course experience, understanding of engagement monitoring, responses to interventions, most helpful elements, challenges, and recommendations.

Overall Course Experience

All four participants described a broadly positive experience with the course.

Utkirbek (Treatment) found no part of the course especially challenging, though he felt the lecture notes were long and preferred to prepare his own instead.

Mukhammadali (Control) emphasized the value of the smaller tutorial groups over large lectures, noting that the more intimate setting allowed him to engage more freely with the professor. As he was not part of the Treatment group and wasn't prompted to keep up with the weekly quizzes, he relied mainly on tutorial questions before the midterm, only incorporating the online quizzes afterward once a classmate in the Treatment group (Dilshod) told him they were also useful for review.

Sevara (Treatment) followed the weekly online quizzes consistently, testing herself immediately after each lecture before reviewing any materials, a method that initially yielded disappointing scores (40 to 60%), improving to 80 to 100% once she reviewed presentation slides or the textbook beforehand. This taught her that simply understanding a topic wasn't always enough; some quiz questions required applying logic or knowledge from earlier topics. She identified the project's biggest benefit as keeping her consistently on track, in contrast to her past economics courses, where she typically crammed the night before exams and sometimes skipped tests altogether. She reported no challenges with the lecture content itself, only occasional technical delays with Hero not displaying quizzes on time.

Dilnoza (Treatment) described her overall experience as very positive, largely because having all course materials accessible in one place made studying and exam preparation much more manageable compared to her other courses. She reported no real challenges for herself, though after the midterm she had to wait for new materials to be uploaded. She initially found the course concepts difficult to grasp.

Understanding of Engagement Monitoring and Learning Analytics

Utkirbek and Sevara became aware of monitoring mainly through in-class verbal reminders rather than the email notifications, both recalling clear awareness only mid-semester. Sevara had assumed monitoring applied only to the quizzes rather than her overall engagement. Dilnoza similarly understood monitoring to be limited to the quizzes rather than her overall progress, and said she either didn't receive, didn't notice, or couldn't recall the email notifications, becoming aware instead through the lecturer's verbal reminders in class.

Mukhammadali (Control) said he received no formal monitoring, but still felt tracked through the lecturer's personal, verbal check-ins during tutorials asking whether he'd completed the quizzes, which he found mildly uncomfortable given he hadn't completed many. He rated the overall sense of monitoring as fairly strong, pointing to manual attendance-taking as an anti-cheating measure.

Impact of Interventions (Emails, Conditional Access, and Monitoring)

Utkirbek received mostly in-class feedback rather than emails and felt existing reminders were weak on their own; he proposed a written explanation at the start of the semester plus grade-linked incentives as more effective. Being asked directly about his quiz completion put mild pressure on him, which he said motivated him to engage. He felt, though, that quiz timing alone shouldn't be judged too strictly, since students may study on different schedules.

Sevara reported no specific interventions or announcements affecting her behavior; monitoring made no difference to her motivation, as she was already self-driven and completed her quizzes on time throughout.

Dilnoza said monitoring clearly motivated her studying, prompting repeated review of quiz material, and completing quizzes became a consistent weekly habit over time. She received only one email reminder and felt more in-class notification would help less self-motivated students.

On the data collection itself, all four were comfortable, with none raising serious concerns about fairness, privacy, or accuracy. Mukhammadali and Sevara, both welcomed it, framing it as a contribution toward improving education for future students. Dilnoza was open to having her own data shared, viewing it as a way to track her academic progress.

Most Helpful Elements of the Learning-Analytics Approach

Utkirbek and Sevara found the online quizzes and tutorial questions most valuable overall. Utkirbek particularly liked that quizzes were online rather than paper-based and could be completed flexibly without a strict deadline, using them alongside tutorial questions for exam preparation and to clarify gray areas. Sevara named online quizzes as her top resource, supported by lecture notes and tutorial questions. Dilnoza was less certain about which specific element helped most, but found the lecture notes helpful for grasping initially difficult concepts, and the question-of-the-week, tutorial, and assignment questions engaging; she also valued having all materials centralized on one platform.

Mukhammadali wasn't part of the Treatment group, so he prepared mainly with tutorial questions and only picked up online quizzes later, after a classmate in the Treatment group recommended them.

Challenges and Problems

The most common complaint was that Hero only showed an overall score, not which questions were wrong. Utkirbek, Sevara, and Mukhammadali all raised this, saying it made exam review harder.

Recommendations from Students

Summary of How Learning Analytics Was Experienced

Overall, students described the learning analytics framework as supportive of their learning and assessment preparation, though which specific resource helped most varied by student. Sevara found the weekly online quizzes most valuable, since testing herself after each lecture revealed gaps in her understanding and kept her studying consistently through the semester. Dilnoza also repeated the quizzes regularly to improve her scores, but considered the lecture notes her most useful resource for grasping difficult concepts. Mukhammadali valued the tutorial sessions most, for the closer interaction with the instructor, and began using the quizzes for revision after the midterm once a classmate recommended them. Utkirbek engaged actively with the available materials but argued that quiz completion alone shouldn't be used to measure engagement, since students follow different study schedules.

Students were generally comfortable with their learning data being collected for educational purposes. They recommended providing feedback after quizzes, improving the usability of the HERO platform, and introducing participation marks to encourage more consistent completion of weekly activities. Overall, students viewed the learning analytics framework as supporting engagement, self-regulated learning, and assessment preparation.