Multiple studies have looked at different aspects of feedback to students: 
- Valence
- Assignment

Learning Analytics of Feedback in Education

Learning Analytics of Student Demographics

Learning Analytics References

- Assessing and measuring reading comprehension

Learning Analytics of Academic Performance

- Feedback in education
- Achievement gap in education 
- Self regulation in education
- Student demographics
- Academic performance
- Data architecture

San Jose State University

University of Georgia

Learning analytics (LA) is the idea that datasets acquired through teaching or learning activities can be used to enhance student learning, academic progress, and teaching practices.

Learning Analytics

The goal of this study is to better understand the cognitive processing of confirmatory (positive) feedback and critical (negative) feedback to improve the delivery of feedback. To do this, researchers collected learning analytics via a behavioral assessment game and an eye tracker to investigate attention allocation to different feedback valences (positive and negative feedback). This study evaluates if there is a difference in the participants' attendance between confirmatory feedback and critical feedback.


Eye Tracking the Feedback Assigned to Undergraduate Students in a Digital Assessment Game-
Goal of the Study

The goal of this study is to work toward developing more effective feedback-targeting systems for tutoring software, to improve user performance. In this study, researchers built a tutoring software system that uses Natural Language Processing (NLP) to provide adaptive feedback to students in an online learning task. 
- The researcher's system models the interaction between a student's natural language response and the software, which interprets students' responses and provides the best feedback action. This framework allows for the optimization of a reward signal. 
- Researchers showed that natural-language based targeting policies were able to choose optimal feedback from fewer exercises compared to multiple-choice based policies. The natural-language policies were effective even when tested on novel interactions. 

Adaptive Natural-Language Targeting for Student Feedback- Goal of Study

Focuses of Learning Analytics

The goal of this study is to quantitatively analyze how STEM instructors at the college level use their time on the first day of classes and to qualitatively analyze how their messages can be characterized in order to understand the learning environment being established within the course.

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