Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…

Past research has suggested that there may be benefits in learning from expository science text when students study with the expectation that they will need to teach another student. The present experiments were designed to extend prior work by testing if an effect would be seen on both immediate tests (similar to those used in most prior studies)…

The Gradual Release of Responsibility (GRR) model for instructional delivery is well supported by research evidence and is often identified as a critical element of instruction for students with learning difficulties. However, there are challenges associated with effectively releasing responsibility to students. This may be especially true during…

Do children learn a new word by tracking co-occurrences between words and referents across multiple instances ("cross-situational learning" models), or is word-learning a "one-track" process, where learners maintain a single hypothesis about the possible referent, which may be verified or falsified in future occurrences…

Many recent studies have shown that memory for correct answers is enhanced when an error is committed and then corrected, as compared to when the correct answer is provided without intervening error commission. The fact that the kind of errors that produced such a benefit, in past research, were those that were semantically related to the correct…

Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…

Adaptive learning technology solutions often use a learner model to trace learning and make pedagogical decisions. The present research introduces a formalized methodology for specifying learner models, logistic knowledge tracing (LKT), that consolidates many extant learner modeling methods. The strength of LKT is the specification of a symbolic…

Semantic knowledge accumulates through explicit means and productive processes (e.g., analogy). These means work in concert when information explicitly acquired in separate episodes is integrated, and the integrated representation is used to self-derive new knowledge. We tested whether (a) self-derivation through memory integration extends beyond…

Converging evidence suggests that traditional domain-general working memory (WM) training does not have reliable far-transfer effects, but produces reliable, modest near-transfer effects on structurally similar untrained tasks. Given the critical role of WM in academic development, WM training that incorporates task-specific features may maximize…

Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…

To build knowledge, separate yet related learning episodes can be integrated with one another and then used to derive new knowledge. Separate episodes are often experienced through different formats, such as text passages and graphic representations. Accordingly, in the present research, we tested integration of learning episodes provided through…

This article presents the application of the interactive dynamic literacy (IDL) model (Kim, 2020a) toward understanding difficulties in learning to read and write. According to the IDL model, reading and writing are part of communicative acts that draw on largely shared processes and skills as well as unique processes and skills. As such, reading…

Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students. Experimental investigations indicate that errorful learning followed by corrective feedback is beneficial to learning. Interestingly, the…

To account for natural variability in cognitive processing, it is standard practice to optimize a model's parameters by fitting it to behavioral data. Although most language-related theories acknowledge a large role for experience in language processing, variability reflecting that knowledge is usually ignored when evaluating a model's fit to…

Abstraction is a core principle of Distributional Semantic Models (DSMs) that learn semantic representations for words by applying dimensional reduction to statistical redundancies in language. Although the posited learning mechanisms vary widely, virtually all DSMs are prototype models in that they create a single abstract representation of a…