Linking attentional processes and conceptual problem solving: visual cues facilitate the automaticity of extracting relevant information from diagrams

Abstract

This study investigated links between visual attention processes and conceptual problem solving. This was done by overlaying visual cues on conceptual physics problem diagrams to direct participants’ attention to relevant areas to facilitate problem solving. Participants (N = 80) individually worked through four problem sets, each containing a diagram, while their eye movements were recorded. Each diagram contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Problem sets contained an initial problem, six isomorphic training problems, and a transfer problem. The cued condition saw visual cues overlaid on the training problems. Participants’ verbal responses were used to determine their accuracy. This study produced two major findings. First, short duration visual cues which draw attention to solution-relevant information and aid in the organizing and integrating of it, facilitate both immediate problem solving and generalization of that ability to new problems. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers’ attention necessarily embodying the solution to the problem, but were instead caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, this study demonstrates that when such cues are used across multiple problems, solvers can automatize the extraction of problem-relevant information extraction. These results suggest that low-level attentional selection processes provide a necessary gateway for relevant information to be used in problem solving, but are generally not sufficient for correct problem solving. Instead, factors that lead a solver to an impasse and to organize and integrate problem information also greatly facilitate arriving at correct solutions.

Student understanding of graph slope and area under a graph: A comparison of physics and nonphysics students

“…In addition to students' scores and explanations on problems with graphs that we analyzed in the previous studies [10,11,14], we used eye tracking in this study to investigate where students allocate visual attention during problem solving. Measurement of eye movements is an increasingly used method in PER [37][38][39][40][41][42][43][44][45][46][47][48][49]. There are a number of eye-tracking studies on understanding of graphs [36,39,46,[48][49][50][51].…”

Machine learning predicts responses to conceptual tasks using eye movements

“…We used eye-movement and correctness data from over 400 students collected from solving four different conceptual tasks ( Fig. 1) in our previous studies [1,2,21].…”

“…Research has shown that short duration visual cues can facilitate students to improve their performance on physics conceptual questions and near transfer tasks [1]. Research has also shown that visual cues can shift students' attention from areas of a diagram associated with incorrect responses to those associated with correct responses [2]. This shift in visual attention can facilitate students to re-represent a task, by activating the relevant domain knowledge thereby enabling them to correctly solve the task [3].…”

How do Multimedia Hints Affect Students’ Eye Movements in Conceptual Physics Problems?

“…Another limitation is that we failed to find a significant difference between the visual + text condition and visual + text + audio condition on the PTPA on either expert areas or novice areas even though the performance difference between these two conditions was significant. This departs from prior research [2] and must be investigated further.…”

“…Correct solvers also look at the part of a diagram that is closely related to incorrect answer or "novice area" less frequently than the incorrect solvers. To investigate whether drawing a solver's visual attention to the expert areas in a problem diagram could improve problem-solving performance, a follow-up study [2] found that visual cues on the expert areas could improve performance on physics problems with diagrams. Moreover, it also found that the cued participants spent less time on the expert areas of the transfer problems than the uncued participants.…”