Baker Rodrigo Ocumpaugh Monitoring Protocol

The Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP) is a momentary time-sampling method for quantitative field observations such as those used in classroom observation. BROMP was originally developed by Ryan Baker to study student engagement in online learning.[1] Afterwards, it was adapted for use in the Philippines by Ma. Mercedes Rodrigo, and to study student emotion.[2] It was systematized by Jaclyn Ocumpaugh in two coding manuals, the first in 2012,[3] and the second in 2015.[4] It was adapted for use in India by Chokanath Hymavathy and Viola Krishnamani.[5] It was adapted for use in informal science education settings by Adriana de Carvalho.[6] Since its development, BROMP has been used in over 50 published scientific articles,[4] by researchers at several universities.

As a momentary time-sampling method for classroom observation, a BROMP observer records students' emotions and behavior according to a pre-defined coding schema. BROMP observers view different students in turn, and take notes using an Android app that records data.[7] This app synchronizes with an internet time server. BROMP observations are carried out by field observers trained and certified through a multi-day training process; according to the 2015 coding manual, there are around 130 BROMP-certified coders in 3 countries.[4] Training methods involve both training in coding affect and engagement, and training in observing students non-obtrusively. It is distinguished from other coding systems for emotion, such as Facial Action Coding System, by its use of holistic coding methods.

BROMP has been used with several coding schemes. According to the 2015 coding manual, the most common coding scheme, the "PSLC" scheme (named after the Pittsburgh Science of Learning Center), consists of:

Behavior Affect
On task Boredom
On-task Conversation Confusion
Off-task Frustration
Gaming the system Engaged Concentration
Other Other

BROMP has been used to collect data for the development of automated detectors of student engagement and affect for commercial systems such as Cognitive Tutor.[8] It has also been used to study and refine commercial products such as Reasoning Mind.[9]

Though originally developed for studying online learning, BROMP is now used for research in traditional classrooms as well. BROMP is being used by the Chennai Corporation to study the engagement of children in classes using different teacher practices.[5] It has also been used in informal science education, as part of the instructional design and refinement practices of the Black Rock Forest.[10]

See also

References

  1. ↑ Baker, Ryan; Corbett, Albert; Koedinger, Kenneth; Wagner, Angela (2004). "Off-task behavior in the cognitive tutor classroom: when students game the system". Proceedings of the International Conference on Computer-Human Interaction. Association for Computing Machinery. pp. 383–3gf90.
  2. ↑ Rodrigo, Mercedes (2007). "Affect and Usage Choices in Simulation Problem Solving Environments". Proceedings of the International Conference on Artificial Intelligence in Education. IOS Press. pp. 145–152.
  3. ↑ Ocumpaugh, Jaclyn; Baker, Ryan; Rodrigo, Mercedes (2012). Baker-Rodrigo Observation Method Protocol (BROMP) 1.0. Training Manual version 1.0. (PDF). EdLab.
  4. 1 2 3 Ocumpaugh, Jaclyn; Baker, Ryan; Rodrigo, Mercedes (2015). Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP) 2.0 Technical and Training Manual. (PDF). EdLab.
  5. 1 2 Hymavathy, Chokanath; Krishnamani, Viola; Sumathi, C.P. (2014). "Analyzing learner engagement to enhance the teaching-learning experience". Proceedings of the International Conference on MOOC, Innovation and Technology in Education (MITE). IEEE. pp. 67–70.
  6. ↑ "Program News". Archived from the original on 27 September 2015. Retrieved 15 February 2015.
  7. ↑ Ocumpaugh, Jaclyn; Baker, Ryan; Rodrigo, Mercedes; Salvi, Aatish; van Velsen, Martin; Aghababyan, Ani; Martin, Taylor (2015). "HART: the human affect recording tool". Proceedings of the 33rd International Conference on the Design of Communication. Association for Computing Machinery.
  8. ↑ Baker, Ryan (2012). "Towards Sensor-Free Affect Detection in Cognitive Tutor Algebra". Proceedings of the International Conference on Educational Data Mining. International Educational Data Mining Society. pp. 126–133.
  9. ↑ Mulqueeny, Kevin; Kostyuk, Victor; Baker, Ryan; Ocumpaugh, Jaclyn (2015). "Incorporating Effective e-Learning Principles to Improve Student Engagement in Middle-School Mathematics". International Journal of STEM Education. Springer. 2 (15). doi:10.1186/s40594-015-0028-6.
  10. ↑ "About Black Rock Forest Consortium". Retrieved 17 November 2015.
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