Erik Harpstead

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RumbleBlocks was developed at the Entertainment Technology Center (ETC) to teach engineering principles of tower stability to children ages 4-7. The game features tower construction, tower piece removal, and tower comparison levels which were designed with feedback from early childhood educators and learning researchers, and iteratively improved with(More)
The field of Educational Games has seen many calls for added rigor. One avenue for improving the rigor of the field is developing more generalizable methods for measuring student learning within games. Throughout the process of development, what is relevant to measure and assess may change as a game evolves into a finished product. The field needs an(More)
The rich interaction space of many educational games presents a challenge for designers and researchers who strive to help players achieve specific learning outcomes. Giving players a large amount of freedom over how they perform a complex game task makes it difficult to anticipate what they will do. In order to address this issue designers must ask: what(More)
We present TRESTLE, an incremental algorithm for probabilistic concept formation in structured domains that builds on prior concept learning research. TRESTLE works by creating a hierarchical categorization tree that can be used to predict missing attribute values and cluster sets of examples into conceptually meaningful groups. It is able to update its(More)
As educational games have become a larger field of study, there has been a growing need for analytic methods that can be used to assess game design and inform iteration. While much previous work has focused on the measurement of student engagement or learning at a gross level, we argue that new methods are necessary for measuring the alignment of a game to(More)
— Beanstalk is an educational game for children ages 6-10 teaching balance-fulcrum principles while folding in scientific inquiry and socio-emotional learning. This paper explores the incorporation of these additional dimensions using intrinsic motivation and a framing narrative. Four versions of the game are detailed, along with preliminary player data in(More)
Having insights into players' learning has important implications for design in an educational game. Empirical learning curve analysis is an approach from intelligent tutoring systems literature for measuring student learning within a system in terms of the skills involved. The approach can be used to evaluate how well different hypothesized models of(More)
A central interest of game designers and game user researchers is to understand why players enjoy their games. While a number of researchers have explored player enjoyment in general, few have talked about methods for enabling designers to understand the players of their specific game. In this paper we explore the creation of engagement profiles of game(More)
The recent surge in interest in using educational data mining on student written programs has led to discoveries about which compiler errors students encounter while they are learning how to program. However, less attention has been paid to the actual code that students produce. In this paper, we investigate programming data by using learning curve analysis(More)
While Educational Data Mining research has traditionally emphasized the practical aspects of learner modeling, such as predictive modeling, estimating students knowledge, and informing adaptive instruction, in the current study, we argue that Educational Data Mining can also be used to test and improve our fundamental theories of human learning. Using the(More)