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Expertise-related differences in task selection : Combining eye tracking measures and thinking-aloud protocols. Loredana Mihalca University of Koblenz-Landau, Campus Landau, Germany Fred Paas Erasmus University Rotterdam, the Netherlands. Background. Surface features vs. Structural features.
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Expertise-related differences in task selection:Combining eye tracking measures and thinking-aloud protocols Loredana Mihalca University of Koblenz-Landau, Campus Landau, Germany Fred Paas Erasmus University Rotterdam, the Netherlands
Background Surface features vs. Structural features • cover stories that are irrelevant for task completion • salient and easy to recognize • vs. • task aspects that are necessary to reach a solution • generally not salient • more difficult to perceive the control over selection of tasks with different structural features (Corbalan, Kester, & Van Merriënboer, 2011) Species and traits in inheritance tasksa Solution steps in inheritance tasks
Background Expertise differences in perceiving structural features • The information-reduction hypothesis (Haider & Frensch, 1999): • expertise optimizes learners' attention allocation, by neglecting surface features and focusing more on structural task features • with repeated practice, ‘redundant information is perceptually ignored whenever this is possible’ (Haider & Frensch, 1999, p.188) • Learners have significantly fewer fixations of shorter duration on surface features and more fixations of longer duration on structural features.
Background Questions Research questions • Does students' prior knowledge affect • performance accuracy? • selective attention allocation to task features during selection processes? • verbalizations of task features during selections? • Do students' eye fixations reveal a trade-off between surface and structural task features during the learning process? • Is there a relationship between the information revealed by eye tracking and the information revealed by thinking-aloud protocols during task selections?
Background Questions Design Hypotheses • H1: high prior knowledge students will achieve a higher performance than low prior knowledge students • H2: high prior knowledge students will… • have fewer fixations of shorter duration on surface features • have more fixations of longer duration on structural features • verbalize more relevant information (structural features) • …during task selection processes than low prior knowledge students • H3: because of learning, students' viewing behavior will reveal a trade-off between surface and structural task features • H4: there will be a positive correlation between indices of visual attention and conceptual processing of task features during selection processes.
Background Questions Design Participants: 26 students of higher professional education (age M = 21.15 years, SD = 2.34); • low prior knowledge students (n = 13, pre-test scores M = 4.00,SD = 1.63) • high prior knowledge students (n = 13, pre-test scores M = 8.23,SD = 1.01) t(24) = 7.94, p < .001, d = 3.12 Domain: Genetics, inheritance laws of Mendel • Tobii 1750 eye tracking system, 50 Hz frame rate • Clear View 2.7.1 • Audacity 1.2.6
Procedure Training phase: 3 genetics tasks Task selections: 3 times CRR warm- up warm- up solve task solve task solve task pre-t 1 1 2 3 post-t pre-test (10 multiple-choice items) task selection (TA) post-test (10 multiple choice items) solving the selected task (no TA) • warming-up task: • Thinking-aloud (TA)
Area of interest 1 Surface features Area of interest 2 Structural features
Steps to reach the solution: Steps to reach the solution
Learning outcomes • Training: t(24) = 1.05, n.s. • Post-test: t(24) = 5.11, p < .001, d = 2.01 • Pre-to-post-test performance gain: t(25) = - 4.28, p < .001, d = .72 • Pre-to-post-test time decrease: t(25) = 3.59, p < .001, d = .77 • increase in overall efficiency
Background Questions Design Results Number of fixations on surface vs. structural features • Expertise: F < 1 • N of task selections: F(2, 46) = 3.10, p =.05 • task selection 2 < task selection 1 (p = .059) • task selection 3 < task selection 1 (p < .05) • Expertise x N of task selections: F < 1 Expertise: F < 1 N of task selections: F < 1 Expertise x N of task selections: F < 1
Results Background Questions Design Fixation duration on surface vs. structural features • Expertise: F < 1 • N of task selections: F(2, 46) = 3.48, p < .05 • task selection 2 < task selection 1 (p < .05) • task selection 3 < task selection 1 (p < .05) • Expertise x N of task selections: F < 1 Expertise: F < 1 N of task selections: F < 1 Expertise x N of task selections: F < 1
Background Questions Design Results Average fixation duration on surface vs. structural features Expertise: F < 1 N of task selections: F < 1 Expertise x N of task selections: F(2, 36) = 3.04, p = .06 Expertise: F < 1 N of task selections: F < 1 Expertise x N of task selections: F < 1
Background Questions Design Results Verbal utterances
Results Background Questions Design Eye movements and main categories of the TA protocols
Results Background Questions Design Discussion Discussion • High prior knowledge students… • achieved a higher post-test performance • verbalized more task-relevant information during selection processes compare the tasks mostly based on the structural features (quality of cognitive schemas) • …than low prior knowledge students • No differences between low and high prior knowledge students in viewing behavior during task selections • longer fixation durations: productive vs. unproductive processing ? • low intrinsic cognitive load ? • less processing demands of structural task features for high prior knowledge students ?
Results Background Questions Design Discussion Discussion • Significant differences in viewing behavior between the task selections • with practice, students' attention allocation is less affected by surface task features • however, the pattern of eye fixations on structural task features is more stable across task selections • Indices of visual attention were strongly related to the conceptual processing of surface vs. structural features during task selection processes • Combined used of eye tracking and thinking-aloud for a better understanding of task selection processes.
Thank you for attention! For more information: mihalca@uni-landau.de