Designing assessment tasks to prevent cheating in a large first-year statistics unit

The year of 2020 has witnessed a drastic change in education sector due to the COVID-19 pandemic. There has been a surge of online, non-invigilated assessments which required rethinking to ensure academic integrity due to e-cheating. We redesigned and implemented learning materials/activities constructively to transform student learning from surface to deep learning, even though teacher-student and student-student interactions were reduced. Assessments were redesigned at higher levels of Bloom's taxonomy (e.g. evaluate) to provide opportunities for students to express their understanding and minimize academic dishonesty. The assessments became online, non-invigilated and open book. A comparison of students' examination performances before and during the COVID-19 pandemic of a large first-year statistics unit shows that students' grades were not inflated or deflated due to the new assessments. The newly designed assessments were as good as or even better than the pre-COVID-19 assessments to quantify students learning while upholding academic integrity.