Eliane Wiese

Learn More
Can experimenting with three-dimensional (3D) physical objects in mixed-reality environments produce better learning and enjoyment than flat-screen two-dimensional (2D) interaction? We explored this question with EarthShake: a mixed-reality game bridging physical and virtual worlds via depth-camera sensing, designed to help children learn basic physics(More)
In order to better understand how humans acquire knowledge, one of the essential goals in cognitive science is to build a cognitive model of human learning. Moreover, a cognitive model that better matches student behavior will often yield better instruction in intelligent tutoring systems. However, manual construction of such cognitive models is time(More)
Instruction often employs visual representations to support deep understanding. However, students‟ prior misconceptions may override the meaning in these scaffolds. We investigate fraction bars, a common representation intended to promote sense-making. Our prior work found that students often did not use the fraction bars effectively. This difficulty(More)
What types of scaffolds support sense making in mathematics? Prior work has shown that grounded representations such as diagrams can support sense making and enhance student performance relative to analogous tasks presented with more abstract, symbolic representations. For grounded representations to support students’ learning of symbolic representations,(More)
This paper proposes grounded feedback as a way to provide implicit verification when students are working with a novel representation. In grounded feedback, students’ responses are in the target, to-be-learned representation, and those responses are reflected in a more-accessible linked representation that is intrinsic to the domain. By examining the(More)
Problems with many solutions and solution paths are on the frontier of what non-programmers can author with existing tutor authoring tools. Popular approaches such as Example Tracing, which allow authors to build tutors by demonstrating steps directly in the tutor interface. This approach encounters difficulties for problems with more complex solution(More)
Teaching students to write code with good style is important but difficult: in-depth feedback currently requires a human. AutoStyle, a style tutor that scales, offers adaptive, real-time holistic style feedback and hints as students improve their code. An in-situ study with 103 undergraduate students in a CS class compared AutoStyle to a control tutor which(More)