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Frequency Based Detection Of Task Switches

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Nair, R., Voida, S. and Mynatt, E.D. Frequency-based detection of task switches". In Proceedings of the 19th British HCI Group Annual Conference (HCI 2005; Edinburgh, Scotland). Springer-Verlag (2005), Vol 2. 94-99.

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Frequency Based Detection Of Task Switches

  1. 1. Frequency-based detection of task switches Rahul Nair Yahoo! Research Berkeley [email_address] Steve Voida & Elizabeth Mynatt Georgia Institute of Technology {svoida, mynatt}@cc.gatech.edu
  2. 2. A Question <ul><li>How did you know that this talk was beginning? </li></ul>
  3. 3. A Question <ul><li>How did you know that this talk was beginning? </li></ul><ul><li>Increase in movement </li></ul><ul><li>Fiddling with the projector </li></ul><ul><li>New presenter looking around </li></ul>
  4. 4. A Question <ul><li>How did you know that this talk was beginning? </li></ul><ul><li>Increase in movement </li></ul><ul><li>Fiddling with the projector </li></ul><ul><li>New presenter looking around </li></ul><ul><li>The amount of activity in the room changed </li></ul>
  5. 5. Frequency-based detection of task switches Rahul Nair Yahoo! Research Berkeley [email_address] Steve Voida & Elizabeth Mynatt Georgia Institute of Technology {svoida, mynatt}@cc.gatech.edu
  6. 6. People are particular about Displays <ul><li>Users have a “working set” of windows related to each task (Henderson 1986) </li></ul><ul><li>There are distinct differences in window layouts for each task (Hutchins 2004) </li></ul><ul><li>As interested in hiding windows as they are in displaying task windows (Hutchins 2004) </li></ul>
  7. 7. A frequency-based approach <ul><li>There is a shift in the window interaction frequencies as users “setup” for each task </li></ul><ul><li>The shift could be either an increase or decrease in the average time between interactions </li></ul><ul><li>Rearranging windows is as significant as opening or closing them </li></ul>
  8. 8. Software design <ul><li>Tracks the low level window manipulation </li></ul><ul><li>Uses a sliding window algorithm to compare current interaction speed with session average </li></ul><ul><li>If the window average exceeds the thresholds of the session average a switch is logged </li></ul><ul><li>Best results with a 7 interaction window and a thresholds of 0.67 and 1.5 </li></ul>
  9. 9. Software design <ul><li>If a switch is detected the software asks the user for confirmation </li></ul><ul><li>Uses an IM style popup window </li></ul><ul><li>Ignored popups are considered to be false positives </li></ul><ul><li>5 minute timeout between successive popups </li></ul>
  10. 10. Study Design <ul><li>6 participants </li></ul><ul><ul><li>2 Professors, 3 grad students, 1 IT professional </li></ul></ul><ul><li>Installed on their primary work machine </li></ul><ul><li>2 week study </li></ul><ul><li>Followed by questionnaires and interviews </li></ul>
  11. 11. Results 21.33 48 225 IT Professional (IP) 40.66 37 91 Graduate Student 3 (G3) 53.92 117 217 Graduate Student 2 (G2) 33.51 123 367 Graduate Student 1 (G1) 56.58 43 76 Professor 2 (P2) 94.74 54 57 Professor 1 (P1) Accuracy (%) Switches confirmed Switches detected Subject
  12. 12. User Feedback <ul><li>P1 was very appreciative and said that almost all her tasks were detected </li></ul><ul><li>P2 felt that short tasks were not always detected </li></ul><ul><ul><li>Rapid task switching behavior </li></ul></ul><ul><li>IP had the lowest accuracy but was the most enthusiastic </li></ul><ul><ul><li>co-opted out log files to fill out project time cards </li></ul></ul><ul><ul><li>Noticed all switches but was over sensitive </li></ul></ul>
  13. 13. The Instant Messaging (IM) Effect <ul><li>Some of the variance can be explained by IM usage </li></ul><ul><li>High accuracy subjects did not use IM while low accuracy subjects were regular IM users </li></ul><ul><li>The software detected IM usage as a task switch while the users felt that IM was not a new task </li></ul><ul><li>Users felt that IM was a side channel of information and were irritated when it was detected as a new task </li></ul>
  14. 14. Advantages <ul><li>Can have extremely high accuracy </li></ul><ul><li>Low computational cost </li></ul><ul><li>Fewer privacy concerns since actual document and activity data is not being tagged </li></ul><ul><li>Can spot a task switch without requiring identification of the task itself </li></ul><ul><li>Time management applications </li></ul>
  15. 15. Future Work <ul><li>Integrating web browser URL information </li></ul><ul><li>Dynamically adapting to users by adjusting window sizes, threshold values and popup timeouts </li></ul><ul><li>Allow users to explicitly ignore windows like IM, etc… </li></ul>
  16. 16. <ul><li>Questions? </li></ul><ul><li>Rahul Nair </li></ul><ul><li>[email_address] </li></ul><ul><li>www.rahulnair.net </li></ul>
  17. 17. <ul><li>Consider a situation where the algorithm is evaluating the n+1 th window event. t i is the time between the i th and (i-1) th event </li></ul><ul><li>Task average, = </li></ul><ul><li>Moving average, = </li></ul><ul><li>Ratio = </li></ul>Algorithm

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