This commentary paper examines the issue of contract cheating in higher education, drawing on research and current debate in the field of academic integrity. Media coverage of this issue has reflected significant concerns in the field about students' use of custom academic writing services, along with sector and national calls for action that would lead to making such essay mills illegal. However, recent studies have revealed the complex nature of contract cheating, with a relatively low proportion of students engaging in outsourcing behaviours involving a third party. This paper focuses on how universities and colleges can respond to this emergent concern, and proposes that institutions extend and establish strategies to embed the values, principles and practices aligned to academic integrity. As part of this endeavour, five areas of consideration are offered for higher education institutions that relate to: determining academic integrity strategy; reviewing institutional policy; understanding students; re-visiting assessment practices; and implications for staff professional development.
This paper describes the design and evaluation of a computer-assisted learning program called Link, which was designed to be used by psychology students to review their understanding of correlation. Unlike existing computer-assisted learning programs that were reviewed, Link makes use of data from authentic research studies in psychology and provides learner activities that are specifically designed to address students' misconceptions about correlation. A summative evaluation study of Link involving fifty psychology students was carried out to assess the effect on students' understanding of correlation. It was found that the use of Link significantly contributed to students' general understanding of correlation. However, it was found that students use of paper-based instructional materials could also achieve this. The implication of this research outcome is considered in relation to the design and use of computer-assisted learning applications for statistics in higher education.
IntroductionThis paper describes the design and evaluation of Link,
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