Does learning analytics actually cut workload? The evidence is mixed.
A 2022 review of 144 learning analytics studies found that the most common goals were enhancing learning experience and providing personal recommendations [1]. These goals can reduce teacher workload by automating tasks like identifying struggling students or suggesting resources. But the same review noted that many practices still require significant teacher involvement, and called for 'more cost-effective ways of offering personalised support' [1]—a clear signal that current tools often shift work rather than eliminate it.
A 2023 study of 725 students and teachers using Moodle learning analytics found that both groups wanted 'more straightforward assessment criteria' and 'new methods for improving students' abilities related to independent learning' [2]. This suggests that when analytics systems are not well-designed, they can create confusion and extra work for teachers who have to interpret unclear data or adjust their grading. The study's authors concluded that more attention is needed to harmonize expectations between students and teachers [2].
Can learning quality stay the same? Only if the analytics are designed with learning outcomes in mind.
A 2022 paper on balanced learning design planning argued that learning analytics should be used to 'enhance LD [learning design] by using learning analytics' and to 'ensure constructive alignment and assessment validity' [4]. This means analytics can maintain or even improve quality if it helps teachers align activities with learning outcomes. However, the same paper noted that this requires careful planning and testing in real-world contexts [4], implying that off-the-shelf analytics tools may not automatically preserve quality.
A 2023 study on embodied teamwork learning used multimodal analytics (combining dialogue, location, and timing data) to identify differences between high- and low-performing teams [3]. This kind of detailed feedback can help teachers target their interventions more precisely, potentially saving time while improving learning quality. But the study was conducted in a highly controlled simulation setting [3], so its results may not generalize to typical classrooms where data collection is less comprehensive.
What should a teacher or administrator actually expect?
The evidence suggests that learning analytics can reduce workload without harming quality, but only when implemented thoughtfully. The 2022 review of 144 studies highlighted that the most effective practices are those that provide 'personal recommendations' and 'satisfy personal learning needs' [1]—tasks that are time-consuming for humans but relatively easy for algorithms. However, the 2023 Moodle study [2] and the balanced design paper [4] both warn that without clear criteria and alignment with learning outcomes, analytics can create more work and even reduce quality by misdirecting attention.
In practice, this means that a teacher who uses analytics to flag students who are falling behind (rather than manually checking every submission) is likely to save time. But if the analytics system produces confusing reports or requires constant tweaking, the workload may actually increase. The key takeaway from these four studies is that learning analytics is a tool, not a solution—it works best when it supports human judgment, not when it tries to replace it.
About These Sources
This answer is built on 4 peer-reviewed studies — published from 2022 to 2023, 1 in Q1 journals, collectively cited 89 times — selected as the most relevant from 4 studies that passed quality screening, drawn from 47 papers retrieved from a database of over 500 million.
Sources used in this answer
An analysis of learning analytics in personalised learning
A 2022 review of 144 learning analytics studies found that the most common objectives were enhancing learning experience and providing personal recommendations, but noted a need for more cost-effective ways to offer personalized support [1].
The Impact of Moodle Learning Analytics on Students’ Performance and Motivation
A 2023 survey of 725 students and teachers using Moodle learning analytics found that both groups wanted clearer assessment criteria and better support for independent learning, indicating that poorly designed analytics can create confusion rather than reduce workload [2].
METS: Multimodal Learning Analytics of Embodied Teamwork Learning
A 2023 study of embodied teamwork learning used multimodal analytics (dialogue, location, timing) to identify differences between high- and low-performing teams in a healthcare simulation, showing potential for targeted teacher feedback but in a controlled setting [3].
Balanced Learning Design Planning
A 2022 paper on balanced learning design planning argued that learning analytics should be used to enhance alignment with learning outcomes and assessment validity, but noted that this requires careful testing in real-world contexts [4].