Eye tracking student strategies for solving stoichiometry problems involving particulate nature of matter diagrams

This study compared how students obtained and used information from particulate nature of matter (PNOM) diagrams as well as balanced chemical equations when asked questions about stoichiometry concepts such as limiting and excess reagents, and yield. The comparisons were made in terms of visual behaviors by examining eye fixations while students responded to a 30-item online instrument. Statistically significant differences were found between visual behaviors of high- and low-performers on seven items, mostly those that dealt with correctly identifying the limiting reagent for each diagram. High-performing students were found to have spent more time examining PNOM diagrams and transitioned more frequently between parts of the diagrams and other areas of interest (AOIs) than low-performing students did. This study gives an example of how underlying strategies students used to respond to conceptual stoichiometry questions may be triangulated by the use of both quantitative and qualitative techniques in relation to eye tracking visual behaviors

Gaze transitions when learning with multimedia

Eye tracking methodology is used to examine the influence of interactive multimedia on the allocation of visual attention and its dynamics during learning. We hypothesized that an interactive simulation promotes more organized switching of attention between different elements of multimedia learning material, e.g., textual description and pictorial visualization. Participants studied a description of an algorithm accompanied either by an interactive simulation, self-paced animation, or static illustration. Using a novel framework for entropy-based comparison of gaze transition matrices, results showed that the interactive simulation elicited more careful visual investigation of the learning material as well as reading of the problem description through to its completion

Unterstützung adaptiver Benutzungsschnittstellen mittels Eye-Tracking zur Erkennung von Expertise oder Verstehen

Studien zeigen, dass Erledigen von Aufgaben am Computer von der Wahrnehmungsfähigkeit des Anwenders abhängt. Die Kommunikation zwischen Anwender und Computersystemen erfordert hohe Anforderungen an die Benutzerschnittstelle, die für eine Interaktion zwischen Benutzer und Software verantwortlich ist. Eine adaptive Benutzerschnittstelle vereinfacht und verbessert die Interaktionsmöglichkeit und passt sich automatisch an die Bedürfnisse und Fähigkeiten des Anwenders. Ein wichtiger Schritt zur Realisierung von adaptiven Systeme, ist die automatische Erkennung der Benutzerfähigkeiten, um eine Anpassung der Benutzungsschnittstelle an den Benutzer vornehmen zu können. Das Ziel dieser Bachelorarbeit ist es, festzustellen, ob bzw. wie sich die Analyse der Augenbewegung (Eye-Tracking) dazu eignet, die Fähigkeiten des Anwenders bezüglich Verständnis und Expertise anhand des jeweiligen Blickverhaltens zu erkennen, um diese Information für eine adaptive Benutzungsschnittstelle verwenden zu können. In dieser Arbeit werden Experimente zur Erkennung von Benutzerfähigkeiten anhand der Blickdaten analysiert und Erkenntnisse für eine adaptive Benutzerschnittstelle ermittelt. Die Ergebnisse der Studien zeigen, dass keine Unterschiede zwischen Benutzern bezüglich der Augenbewegungsdaten erkannt werden.Studies showed that completing a task with a computer depends on the perception of the user. The communication between user and computer systems requires high demands to the user interface, which is responsible for interaction between users and software. An adaptive user interface simplifies and improves the interactions and automatically adapts to the needs and abilities of the user. An important step towards the realization of such adaptive systems is the automatic recognition of the user skills to adapt the user interface to the user. The aim of this thesis is to determine whether and how the analysis of eye movements (Eye-Tracking) can be used, to recognize the skills of the user with respect to comprehension and expertise based on the respective eye gaze to use this information for an adaptive user interface. In this work experiments for the detection of user skills based on the gaze data are analyzed and findings for an adaptive user interface are determined. The results of the studies show, that there are no differences between users with respect to the eye movement data

Gaze scribing in physics problem solving.

Eye-tracking has been widely used for research purposes in fields such as linguistics and marketing. However, there are many possibilities of how eye-trackers could be used in other disciplines like physics. A part of physics education research deals with the differences between novices and experts, specifically how each group solves problems. Though there has been a great deal of research about these differences there has been no research that focuses on noticing exactly where experts and novices look while solving the problems. Thus, to complement the past research, I have created a new technique called gaze scribing. Subjects wear a head mounted eye-tracker while solving electrical circuit problems on a graphics monitor. I monitor both scan patterns of the subjects and combine that with videotapes of their work while solving the problems. This new technique has yielded new information and elaborated on previous studies