Peer and self assessment in massive online classes
By Chinmay Kulkarni, Pang Wei Koh, Huy Le, Daniel Jin hao Chia, Kathryn Papadopoulos, Justin Cheng, Daphne Koller, Scott R. Klemmer. ACM Trans. Comput. Hum. Interact., 2013
465 citations recorded by the source corpus.
Subfields: Computer Science Applications, Developmental and Educational Psychology, Education
View Paper: https://www.semanticscholar.org/paper/f004b4bee56e19aec7f4e52d18066c906150470c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Science Applications
- Juho Leinonen
- Nea Pirttinen
- Arto Hellas
- Pushmeet Kohli
- Sahil Bhatia
- Rishabh Singh
- René F. Kizilcec
- Paul Denny
In Developmental and Educational Psychology
In Education
Citations in the corpus
- Neuro-Symbolic Program Corrector for Introductory Programming Assignments (2018, background): “These approaches can be categorized into two broad categories – peer-grading [14, 15] and automated grading techniques [8, 17, 26, 27, 29].”
- How Much Information?: Effects of Transparency on Trust in an Algorithmic Interface (2016, methodology): “Peer assessment is a proven method for scaling the grading of a large number of assessments, such as is required in massive open online courses (MOOCs) [14, 19].”
- WILDS: A Benchmark of in-the-Wild Distribution Shifts (2020, unknown): “Datasets from massive open online courses are a potential source of large-scale data (Kulkarni et al., 2015).”
- Automated Correction for Syntax Errors in Programming Assignments using Recurrent Neural Networks (2016, background): “These approaches can be categorized into two broad categories – peer-grading [11] and automated grading techniques [18, 13].”
- Efficient Mechanisms for Peer Grading and Dueling Bandits (2018, background): “…the grading task to the students who participate in the course (Aziz et al., 2016; Caragiannis et al., 2015, 2016a; de Alfaro and Shavlovsky, 2014; Kulkarni et al., 2013; Kurokawa et al., 2015; Piech et al., 2013; Raman and Joachims, 2014; Shah et al., 2013; Walsh, 2014), and there have been…”
- Crowdsourcing programming assignments with CrowdSorcerer (2018, background): “Course participants in various institutions and MOOCs evaluate assignment responses that the participants themselves have submitted as a part of their coursework – research suggests that peers can give actionable and accurate feedback [13].”