Congratulations to Nanjie ‘Jimmy’ Rao, and Dr. Sharon Lynn Chu for getting their submission titled Enhancing the Visual Efficiency for Communicating Students’ Personal Relevant Information nominated for “Best Short Paper” in the 21st IEEE International Conference on Advanced Learning Technologies! An abstract of the work can be found below:
During instruction, using information that is directly relevant to students within a lesson creates a more personalized lesson that may better resonate with the students. However, in a class, each student has highly varied individual experiences and it is untenable for the teacher to remember all of the experiences. Furthermore, teaching already involves substantial multitasking that may be quite cognitively overwhelming, even with non-personalized lessons. Therefore, providing support to the teacher to incorporate students’ individual experiences is crucial to enable truly personalized teaching.
We propose that visualizing students’ individual experiences for the teacher during instruction may help him or her adapt the lesson in real-time to the students in the class. This paper investigates the kind of visualization that would enable a teacher to uptake a student’s experiences the most effectively. We conducted a within-subjects study to assess the impact that three forms of visualization (plain text, graphical mind map, and story illustration) would have on visual efficiency during a hypothetical teaching scenario.
Visual efficiency was measured in terms of response accuracy (RA), response time (RT), and mental effort (ME). Results showed that both story illustration and, to a lesser extent, graphical mind map, decreased mental effort and reduced the amount of time needed to perceive the personal relevant information without sacrificing much accuracy. The overall results support the claim that visual efficiency of the uptake of students’ individual experiences information during teaching can be improved by using proper visualization design. We discuss the implications of the study results for the design of visualizations to support real-time personalized instruction.