Intended learning outcomes and target groups

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Integrity Games is developed for academic integrity training for university students – primarily students on year 1-3 of their education. It is most likely relevant for more advanced students as well.

The general aim of Integrity Games is to develop knowledge and begin developing academic integrity, by engaging students in reflections of realistic dilemmas involving academic integrity. The cases cover three general topics central to academic integrity:

  1. Citation practice, including avoiding plagiarism and self-plagiarism

  2. Collaboration and getting help on individual assignments

  3. Collecting, analyzing and reporting data

The tool contains one or more cases under each topic presenting the student with dilemmas and common grey area issues in an engaging and thought-provoking way.

While examples of severe misconduct – such as plagiarism and fabrication of data – are included in the cases, the main focus is on the grey area issues where research shows that students are most often in doubt about the appropriate course of action.

For each of the above mentioned topics, Integrity Games aims to contribute to the development of the knowledge and skills listed below.

Items marked with * are considered the primary aims and the games’ efficacy towards these aims has been tested in a randomized controlled experiment.

  • Knowledge of the core values and principles of academic integrity and how they are applied*

  • Knowledge of common grey zones and the reasons why they are “grey”*

  • Knowledge of what is strictly forbidden

  • Skills in identifying academic integrity aspects of a given situation

  • Skills in identifying actions that are in accordance with each of the core principles of academic interity

  • Competences in weighing actions according to multiple values, principles, and groups*

  • Competences in assessing the interplay between the ethically good practice and epistemically good in concrete cases.

In addition, the tool aims to contribute to the following motivational aims:

  • Motivation to develop further AI knowledge skills and competences (positive nudging)*

  • Acceptance of core values and principles under academic and research integrity

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