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The use of an Electronic Voting System to Enhance Student Learning


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Presentation delivered at the Plymouth e-Learning Conference, 23-24 April 2009.

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The use of an Electronic Voting System to Enhance Student Learning

  1. 1. The use of an Electronic Voting System to Enhance Student Learning James Davenport, Alan Hayes, Nitin Parmar University of Bath [ Friday 24 April 2009 ] Presentation slides Research Paper @nrparmar | #pelc09
  2. 2. Goals <ul><li>Adopt a blended approach to tutorials through the introduction of an Electronic Voting System. </li></ul><ul><li>Enhance feedback given to students. </li></ul><ul><li>Utilise the feedback given to students to promote deep learning. </li></ul><ul><li>Enhance the opportunities for students to feedback to the teaching team. </li></ul><ul><li>Do this for final year undergraduate students studying on the BSc(Hons) Computer Science programme. </li></ul>
  3. 3. What is an EVS? <ul><li>Allows for effective student participation </li></ul><ul><li>Immediate [anonymous] submission of responses </li></ul><ul><li>Graphical output of results </li></ul><ul><li>Response data saved for later analysis </li></ul>[ Project website: ]
  4. 4. Advantages of an EVS <ul><li>Enables the student to benchmark their progress against their peers. </li></ul><ul><li>Supports the students actively engaging with their learning. </li></ul><ul><li>Enables the lecturer to identify those areas that the cohort are struggling with. </li></ul><ul><li>Promotes peer interaction and support. </li></ul><ul><li>Enables the students to anonymously feed back to the lecturer. </li></ul><ul><li>However </li></ul><ul><li>EVS ‘multiple-choice’ approach can obviate against deep learning. </li></ul>
  5. 5. EVS and Surface Learning An Ethernet address is how long? <ul><li>4 bytes </li></ul><ul><li>6 bytes </li></ul><ul><li>16 bytes </li></ul><ul><li>Variable length </li></ul>
  6. 6. EVS and Surface Learning The answer is B (6 bytes) If you didn’t get that, you’re pretty confused: re-read sections 2.2 and 3.2 of the book.
  7. 7. EVS and surface learning (2) 100 Mbps twisted pair length limit is <ul><li>60 metres </li></ul><ul><li>100 metres </li></ul><ul><li>195 metres </li></ul><ul><li>500 metres </li></ul>
  8. 8. EVS and surface learning (2) The correct answer is B: 100m <ul><li>However, this is the sort of factual answer: </li></ul><ul><li>I don’t expect you to know , and would give you in an exam question; </li></ul><ul><li>You should always check in real life, especially if equipment installation depends on it; </li></ul><ul><li>As I showed in the Library, isn’t what it seems in practice </li></ul>
  9. 9. FACT(!) Students will already know the answers to 70% of all questions asked using ARS (Draper, 2008) CHALLENGE Get the students to think ! This will encourage deep(er) learning Towards Deeper learning
  10. 10. EVS and deep learning Internet and Ethernet <ul><li>An internet is impossible without Ethernet </li></ul><ul><li>The Internet needs Ethernet </li></ul><ul><li>Today’s Internet depends on Ethernet </li></ul><ul><li>Totally independent concepts </li></ul>
  11. 11. EVS and deep learning I hope that made you think <ul><li>Certainly false </li></ul><ul><li>Was false in the beginning, and may well be false again. </li></ul><ul><li>True in practice today. </li></ul><ul><li>True, but not as helpful as C. </li></ul>
  12. 12. Observations on Deep Learning <ul><li>Students are presented a question for which there is not a single correct answer. </li></ul><ul><li>Notable silence when the question is first presented. </li></ul><ul><li>Peer engagement occurred naturally. </li></ul><ul><li>Survey of students reveals that 80% of the cohort felt that such discussion led to a better understanding of the subject matter. </li></ul>
  13. 13. Student Opinion What about this technology ? <ul><li>Revolutionises problem classes </li></ul><ul><li>Useful extra, but shouldn’t dominate </li></ul><ul><li>OK 1-2 times/term </li></ul><ul><li>Never again </li></ul><ul><li>Abstain </li></ul>
  14. 14. Student Opinion <ul><li>“ .. it gives a good view on how the rest of the class is doing in comparison and lets you know how much harder you should be working” </li></ul><ul><li>“ It was useful to be able to see my answer in comparison to other peoples. This gave me an easy way to benchmark my learning against others to see how I was doing on the course” </li></ul>
  15. 15. Costs <ul><li>Hardware start up costs are not insubstantial </li></ul><ul><li>Training for staff - 1 hour per lecturer. Additional online support material. </li></ul><ul><li>Learning curve for a lecturer to receive training, install and experiment – 4 hours. </li></ul><ul><li>5 hours preparation for each 50 minute session. As of now, we are not sure how reusable this material is. </li></ul><ul><li>Estimated to be 50% given the rate of evolution of the subject discipline. </li></ul>
  16. 16. Conclusions <ul><li>It is possible to convert a relatively sceptical lecturer into a strong user of this system in the appropriate context. </li></ul><ul><li>This technology does enable the lecturer to gauge levels of misapprehension in a way that would be hard in an examination-only course of this size. </li></ul><ul><li>It is possible to use EVS to help students with deeper points than mere factual knowledge. </li></ul><ul><li>When used at this level the lecturer has to be prepared to improvise. If a significant number of students choose the wrong answer, there is a need to address this before continuing. </li></ul><ul><li>The students like it! </li></ul>
  17. 17. Contact Details <ul><li>Alan Hayes Director of Teaching, Department of Computer Science [email_address] </li></ul><ul><li>Nitin Parmar </li></ul><ul><li>Learning Technologist [e-Learning team] Learning and Teaching Enhancement Office [email_address] </li></ul><ul><li> </li></ul><ul><li> </li></ul>
  18. 18. Questions?