Search results for "graph understanding"
showing 3 items of 3 documents
Changes in students’ understanding of and visual attention on digitally represented graphs across two domains in higher education : a postreplication…
2020
Domain-specific understanding of digitally represented graphs is necessary for successful learning within and across domains in higher education. Two recent studies conducted a cross-sectional analysis of graph understanding in different contexts (physics and finance), task concepts, and question types among students of physics, psychology, and economics. However, neither changes in graph processing nor changes in test scores over the course of one semester have been sufficiently researched so far. This eye-tracking replication study with a pretest–posttest design examines and contrasts changes in physics and economics students’ understanding of linear physics and finance graphs. It analyze…
Visual attention while solving the test of understanding graphs in kinematics: an eye-tracking analysis
2019
This study used eye-tracking to capture students' visual attention while taking a test of understanding graphs in kinematics (TUG-K). A total of N = 115 upper-secondary-level students from Germany and Switzerland took the 26-item multiple-choice instrument after learning about kinematics graphs in the regular classroom. Besides choosing the correct alternative among research-based distractors, the students were required to judge their response confidence for each question. The items were presented sequentially on a computer screen equipped with a remote eye tracker, resulting in a set of approx. 3000 paired responses (accuracy and confidence) and about 40 h of eye-movement data (approx. 500…
Epistemic network analyses of economics students' graph understanding. An eye-tracking study
2020
Learning to solve graph tasks is one of the key prerequisites of acquiring domain-specific knowledge in most study domains. Analyses of graph understanding often use eye-tracking and focus on analyzing how much time students spend gazing at particular areas of a graph&mdash