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Conference Paper/Proceeding/Abstract 774 views

Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)

David Gallimore Orcid Logo

Swansea Academy of Learning and Teaching annual conference 2015

Swansea University Author: David Gallimore Orcid Logo

Abstract

Teaching large groups of students sitting at some distance in enormous lecture halls can often be problematic. The lecturer is often left unclear as to depth of the learning taking place, if any at all. Numerous approaches have been suggested to evaluate the level of student interaction and learning...

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Published in: Swansea Academy of Learning and Teaching annual conference 2015
Published: 2015
URI: https://cronfa.swan.ac.uk/Record/cronfa29030
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first_indexed 2016-06-29T18:23:50Z
last_indexed 2018-02-09T05:13:46Z
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spelling 2016-06-29T14:54:19.3117564 v2 29030 2016-06-29 Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers) cff2e3d0e99fe3103d6ebc9ec2ffbce2 0000-0001-6053-538X David Gallimore David Gallimore true false 2016-06-29 HNU Teaching large groups of students sitting at some distance in enormous lecture halls can often be problematic. The lecturer is often left unclear as to depth of the learning taking place, if any at all. Numerous approaches have been suggested to evaluate the level of student interaction and learning in lead lectures. These range from the students simply being asked to hold up cards for voting to more complex web based solutions using the students’ smart phones or tablets. One technique that has been used widely in Swansea University is the Turning Technologies student engagement system, more commonly known as “clickers”. These have been shown to increase engagement of students when being taught in large groups, and can enhance their learning. Competitive elements such as quizzes can be set up using clickers and the students can compete based on formal groups, seating area of the lecture hall, or gender. The aim of this presentation is to demonstrate the often less used element of clickers that allow the academic to evaluate the learning that has been achieved in the lecture. This is by using the Manage tab of the Turning Technologies software. At the most basic level this data can inform the lecturer which area of the topic the students find the most difficult. More usefully the data can also be analysed by demographic and academic categories such as educational background, age range, gender, and any almost any parameters the lecturer feels is relevant. Conference Paper/Proceeding/Abstract Swansea Academy of Learning and Teaching annual conference 2015 Student response system, clickers, evaluation, student feedback, 2 7 2015 2015-07-02 COLLEGE NANME Nursing COLLEGE CODE HNU Swansea University 2016-06-29T14:54:19.3117564 2016-06-29T14:53:57.6120173 Faculty of Medicine, Health and Life Sciences School of Health and Social Care - Nursing David Gallimore 0000-0001-6053-538X 1
title Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
spellingShingle Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
David Gallimore
title_short Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
title_full Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
title_fullStr Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
title_full_unstemmed Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
title_sort Pedagogical evaluation employing Turning Technology student response system (or how to make your teaching better using Clickers)
author_id_str_mv cff2e3d0e99fe3103d6ebc9ec2ffbce2
author_id_fullname_str_mv cff2e3d0e99fe3103d6ebc9ec2ffbce2_***_David Gallimore
author David Gallimore
author2 David Gallimore
format Conference Paper/Proceeding/Abstract
container_title Swansea Academy of Learning and Teaching annual conference 2015
publishDate 2015
institution Swansea University
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Health and Social Care - Nursing{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Health and Social Care - Nursing
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description Teaching large groups of students sitting at some distance in enormous lecture halls can often be problematic. The lecturer is often left unclear as to depth of the learning taking place, if any at all. Numerous approaches have been suggested to evaluate the level of student interaction and learning in lead lectures. These range from the students simply being asked to hold up cards for voting to more complex web based solutions using the students’ smart phones or tablets. One technique that has been used widely in Swansea University is the Turning Technologies student engagement system, more commonly known as “clickers”. These have been shown to increase engagement of students when being taught in large groups, and can enhance their learning. Competitive elements such as quizzes can be set up using clickers and the students can compete based on formal groups, seating area of the lecture hall, or gender. The aim of this presentation is to demonstrate the often less used element of clickers that allow the academic to evaluate the learning that has been achieved in the lecture. This is by using the Manage tab of the Turning Technologies software. At the most basic level this data can inform the lecturer which area of the topic the students find the most difficult. More usefully the data can also be analysed by demographic and academic categories such as educational background, age range, gender, and any almost any parameters the lecturer feels is relevant.
published_date 2015-07-02T03:35:25Z
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