Honnor, Thomas;
Abourashchi, Niloufar;
Rassias, Matina;
(2022)
Empowering Non-specialists to Interpret and Disseminate Statistics Through Structured Assessments.
In:
Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics.
International Association for Statistical Education: Rosario, Argentina.
Text
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Abstract
Assessment is an important tool for quantifying each student’s relative ability but when carefully designed can also be used to educate and empower students. Because the importance of statistical understanding is becoming increasingly recognised, there is a subsequent growth in non-specialist students taking statistics service courses. The assessments for such courses can define students’ personal course aims and level of engagement and set the tone for their future interactions with the subject. We have designed and implemented a modernised assessment pattern, with assessments structured to build upon each other and lead students from the foundations of probability to interpretation and communication of authentic statistical analyses. We discuss our experiences having implemented this new assessment pattern across three courses, totaling more than 600 students.
Type: | Proceedings paper |
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Title: | Empowering Non-specialists to Interpret and Disseminate Statistics Through Structured Assessments |
Event: | Bridging the Gap: Empowering and Educating Today’s Learners in Statistics |
DOI: | 10.52041/iase.icots11.t13a1 |
Publisher version: | https://iase-web.org/Conference_Proceedings.php?p=... |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10164335 |
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