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Engaging first‐year students through online collaborative assessments
Author(s) -
Kelly D.,
Baxter J.S.,
Anderson A.
Publication year - 2010
Publication title -
journal of computer assisted learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.583
H-Index - 93
eISSN - 1365-2729
pISSN - 0266-4909
DOI - 10.1111/j.1365-2729.2010.00361.x
Subject(s) - student engagement , mathematics education , psychology , active learning (machine learning) , collaborative learning , relation (database) , online discussion , pedagogy , computer science , world wide web , database , artificial intelligence
Abstract Substantial increases in the size of many undergraduate classes in recent years have limited the ways in which students can engage with their disciplines and become active participants in their learning. This paper presents a methodology which uses a basic WebCT platform to improve the way in which students in large classes learn. The approach, termed the Collaborative Online Assessment approach, provides a structured, scaffolded learning environment for students to engage with their peers in collaborative assessments. Results from a year‐long application of the approach with first‐year psychology students are presented. These show that the approach facilitates active student engagement throughout the academic year, and is associated with improved marks in the final written exam. This improvement in exam performance is significantly greater for students not intending to major in psychology (traditionally poorer performers). The paper discusses the implications of these findings in relation to learning theories and provides a critique for further improvement of the approach.