OnlineHE_Toolkit

99 The European Commission's support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. Project Number: 2020-1-RO01-KA226-HE-095434 It is used in higher education and supports the particularly demanding conditions of teaching. Makes teaching interactive and more interesting. Enhances the learning outcome. Supports formative evaluation. 12. Web link https://www.mentimeter.com/ 13. References/ online sources Mohin, M., Kunzwa, L., & Patel, S. (2020). Using Mentimeter to enhance learning and teaching in a large class . https://doi.org/10.35542/osf.io/z628v Rudolph, J. (2018). A brief review of Mentimeter – a student response system. Journal of Applied Learning and Teaching , 1 (1), 35–37 . h ttps://doi.org/10.37074/jalt.2018.1.1.5 Duzhin, F. and Gustafsson, A. (2018) Machine Learning-Based App for SelfEvaluation of Teacher-Specific Instructional Style and Tools. Education Sciences, 8(1), pp.7. Hill, D. L., & Fielden, K. (2018). Using Mentimeter to promote student engagement and inclusion [Conference or Workshop Item]. Pedagogy in Practice seminar, Fusehill Street, Carlisle, UK. University of Cumbri a. https://www.cumbria.ac.uk/about/events/university- events/carlisle---fusehill-street/pedagogy-in-practice- seminar.php Wan, K., Cheung, G. and Chan, K. (2017) Prediction of Students’ Use and Acceptance of Clickers by Learning Approaches: A Cross- Sectional Observational Study. Education Sciences, 7(4), pp.91. Features . (n.d.). Mentimeter. Retrieved July 24, 2021, fro m https://www.mentimeter.com/features 14. Additional notes N/A