Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…

Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free-text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

I will propose a tentative framework of how words in two languages could be organized in the cerebral cortex based on neural assembly theory, according to which neurons that fire synchronously are bound into large-scale distributed functional units (assemblies), which represent a mental event as a whole ("gestalt"). For language this…

Speech recognition is an active process that involves some form of predictive coding. This statement is relatively uncontroversial. What is less clear is the source of the prediction. The dual-stream model of speech processing suggests that there are two possible sources of predictive coding in speech perception: the motor speech system and the…

Early on during word recognition, letter positions are not accurately coded. Evidence for this comes from transposed-letter (TL) priming effects, in which letter strings generated by transposing two adjacent letters (e.g., "jugde") produce large priming effects, more than primes with the letters replaced in the corresponding position (e.g.,…

An orthographically similar masked nonword prime facilitates responding in a lexical decision task (Forster & Davis, 1984). Recently, this masked priming paradigm has been used to evaluate models of orthographic coding--models that attempt to quantify prime-target similarity. One general finding is that priming effects often do not occur when…

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the "sequence encoder" is used to learn…

According to parallel distributed processing (PDP) models of visual word recognition, the speed of semantic coding is modulated by the nature of the orthographic-to-semantic mappings. Consistent with this idea, an ambiguity disadvantage and a relatedness-of-meaning (ROM) advantage have been reported in some word recognition tasks in which semantic…

Consistent with converging experimental evidence, we assume that foveal information is initially split across the two cerebral hemispheres. We have previously presented the SERIOL model of letter-position coding, which specifies how the resulting two halves of a letter string are integrated into an abstract representation of letter order. This…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

Nonwords created by transposing two "adjacent" letters (i.e., transposed-letter (TL) nonwords like "jugde") are very effective at activating the lexical representation of their base words. This fact poses problems for most computational models of word recognition (e.g., the interactive-activation model and its extensions), which assume that exact…

The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…