False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…

Purpose: The speech motor system uses feedforward and feedback control mechanisms that are both reliant on prediction errors. Here, we developed a state-space model to estimate the error sensitivity of the control systems. We examined (a) whether the model accounts for the error sensitivity of the control systems and (b) whether the two systems…

Troubleshooting activities require students to diagnose teacher-crafted erroneous examples by detecting and explaining the conceptual errors driving them. In a previous study, the author tested whether diagnosing erroneous examples and then scoring them using a rubric that contained the related worked examples, a step-by-step strategy to solve a…

To confirm the role of social factors in mediating cognitive processes, this systematic replication study seeks to extend the generalizability of an exploratory study (McDonough, Crowther, Kielstra & Trofimovich 2015) that reported a positive association between eye gaze and second language (L2) speakers' responses to recasts. For this…

In a recent paper, Simpson and Dervin (2019a) offer a radical critique of the Council of Europe's "Reference Framework of Competences for Democratic Culture" (RFCDC). However, Simpson and Dervin's paper contains numerous factual errors, interpretative errors and category errors in its description of the RFCDC. We identify 12 such errors…

Research indicates that learning from erroneous examples (EE) is superior to correct examples because errors may provide students with a stimulus to spontaneously produce more self-explanations, leading to better learning outcomes. However, because most studies were conducted in individual settings, it remains an open question whether the…

Recently, Attali and Powers investigated the usefulness of providing immediate feedback on the correctness of answers to constructed response questions and the opportunity to revise incorrect answers. This article introduces an item response theory (IRT) model for scoring revised responses to questions when several attempts are allowed. The model…

A nine-step model is presented for diagnosing and correcting computation errors in arithmetic. The model, which lends itself to curriculum-based assessment and instruction, involves such steps as identifying error patterns, interviewing the student, and selecting the appropriate corrective strategy. (JDD)

A theory of how people detect and correct their own performance errors during skill practice is proposed. Blame assignment, error attribution, and knowledge revision are identified as three cognitive functions in explaining error correction. The theory is embodied in a computer model that learns cognitive skills in ecologically valid domains. (SLD)

Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)

Argues that, to deal effectively with sentence errors of basic writers, it is crucial to distinguish between what should be left alone and what can be productively marked and how it should be marked. Proposes a taxonomy of four sources of errors (knowledge, dialect, process, and developmental errors) and seven ways to address them. (SR)

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…