This dataset contains the assessment of student submissions by student peers and by instructors during a Social Media course taught in 2013 at the Swiss Federal Institute of Technology in Lausanne (EPFL) with 60 Master’s level university students. The dataset allows for training and testing algorithms that predict the grades of instructors based on the grades of student peers.
The dataset was created by the REACT Group at EPFL and is owned by EPFL.
It is available for download from http://go.epfl.ch/peer-dataset and consists of three files: two with grades and one with student-report mapping. The following files are available in the tab-separated values (TSV) format:
- grades_studens_all.tsv contains grades assigned by the students
- grades_instructors_all.tsv has the grades assigned by the instructors
- students_reports_mapping.tsv contains the mapping between student ids and their report ids.
All participants of the assessment were instructed to use a 5-point Likert-type scale for grading the reports. Since the course was about social media, the grade scale was inspired by the 5-star rating system often found in social media (e.g., used for product review on Amazon.com): 5 stars – I love the report; 4 stars – I like the report; 3 stars – The report is OK; 2 stars – I don’t like the report; 1 star – I hate the report. In total there are 1346 grades: 1106 by the students and 240 by the instructors.
Educational objective
Peer assessment is seen as a powerful supporting tool to achieve scalability in the evaluation of complex assignments in large courses, possibly virtual ones, as in the context of massive open online courses (MOOCs). However, the adoption of peer assessment is slow, due in part to the lack of ready-to-use systems. Furthermore, the validity of peer assessment is still under discussion.
The objective of peer assessment in the context of the social media course was twofold: First, it aimed at assessing the work of students. Second, it aimed at introducing students to the challenges and opportunities related to ratings in social media platforms.
Further details can be found in the paper
Andrii Vozniuk, Adrian Holzer and Denis Gillet (2016). Peer Assessment dataset. Journal of Learning Analytics, 3(2), 322–324. http:dx.doi.org/10.18608/jla.2016.32.18