We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…

Today, there is a vast amount of online material for learners. However, due to the lack of prerequisite information needed to master them, a lot of time is spent in identifying the right learning content for mastering these concepts. A system that captures underlying prerequisites needed for learning different concepts can help improve the quality…

Conceptual representations can be altered to align with the current context given learning and task goals. One cognitive process, known as conceptual combination, allows for a unique perspective for exploring how complex conceptual processing occurs and how this processing influences the underlying representations of concepts. During novel nominal…

This dissertation provides evidence that reading is best explained as rational gathering of visual information to identify words efficiently. Although empirical evidence from human reading research suggests a close link between eye movements and cognitive process, it is not clear how readers decide when and where to move their eyes as a function…

Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…

Second language implicit learning research has shown that a variety of linguistic features can be acquired without awareness. However, this research overwhelmingly uses comprehension tests to measure implicit learning. It remains unclear whether newly acquired implicit knowledge can also be recruited for production. To address this question, we…

Lexical access is highly contextual. For example, vowel (rime) information is prioritized over tone in the lexical access of isolated words in Mandarin Chinese, but these roles are flipped in constraining contexts. The time course of these contextual effects remains unclear, and so here we tracked the real-time eye gaze of native Mandarin speakers…

Research has indicated that school aged (6-16 years) versions of cognitive assessment instruments have varying levels of linguistic demand, which could impact assessment results for placement purposes. However, a significant limitation to this research is the fact that it has not been replicated with cognitive assessment instruments used in…

We present the results of an ongoing collaboration between computer science and psychology researchers that employs Natural Language Processing (NLP) methods to examine the trajectory of semantic space used during group idea generation sessions. Specifically, we track and estimate the region of semantic space being used and the degree to which new…

Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…

Aptitude testing is used to select candidates with the greatest potential for professional interpreter training. Implicit in this practice is the expectation that aptitude test scores predict future performance. As such, the predictive validity of score-based inferences and decisions constitutes an important rationale for aptitude testing.…

Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…

There are multiple levels of processing relevant to reading that vary in their visual, sublexical, and lexical orthographic processing demands. Segregating distinct cortical sources for each of these levels has been challenging in EEG studies of early readers. To address this challenge, we applied recent advances in analyzing high-density EEG…

Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…

The launch of ChatGPT has been revolutionary. This AI chatbot can produce conversations which are indistinguishable from that of humans. This exploratory qualitative study is foregrounded in a constructivist-interpretative perspective. The principal objective of this paper is to explore the views of academics on ChatGPT as an AI-based learning…