# Towards digitalisation of summative and formative assessments in academic teaching of statistics

arXiv: https://arxiv.org/abs/1811.02391 · HTML: https://mlsanity.com/paper/1811.02391/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Nov 2018.

## Built on by (most cited first, 1 of 1)

- [A Data Mining Approach for Detecting Collusion in Unproctored Online Exams](https://mlsanity.com/paper/2302.07014/) (2023)

## Abstract (arXiv)

Web-based systems for assessment or homework are commonly used in many different domains. Several studies show that these systems can have positive effects on learning outcomes. Many research efforts also have made these systems quite flexible with respect to different item formats and exercise styles. However, there is still a lack of support for complex exercises in several domains at university level. Although there are systems that allow for quite sophisticated operations for generating exercise contents, there is less support for using similar operations for evaluating students' input and for feedback generation. This paper elaborates on filling this gap in the specific case of statistics. We present both the conceptional requirements for this specific domain as well as a fully implemented solution. Furthermore, we report on using this solution for formative and summative assessments in lectures with large numbers of participants at a big university.