Electricity and magnetism are fundamental areas of physics and are integral to science curricula at various educational levels. However, this area has been reported to contain several concepts that students find challenging, leading to perspectives that diverge from scientifically accepted views. This study examines the errors made by physics…

Sequence stratigraphic and Wheeler diagram interpretations require a strong combination of conceptual understanding and diagram reasoning skills. Students are generally exposed to the foundational concepts within sequence stratigraphy (relative sea level, eustasy, base level, and accommodation) in a variety of courses along their degree path,…

Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…

Temporality-driven covariate classification had limited impact on: the specification of directed acyclic graphs (DAGs) by 85 novice analysts (medical undergraduates); or the risk of bias in DAG-informed multivariable models designed to generate causal inference from observational data. Only 71 students (83.5%) managed to complete the…

Recent context-control learning studies have shown that switch costs are reduced in a particular context predicting a high probability of switching as compared to another context predicting a low probability of switching. These context-specific switch probability effects suggest that control of task sets, through experience, can become associated…

R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

This paper examines the English grammatical errors and their patterns in the written assignments of a General Education course at City University of Hong Kong. Subjects are 60 local and non-local (exchange) undergraduate students who are all L2 learners with diversified education and disciplinary background (i. e. their major of study) which are…

Translation teachers have long experimented with various methods to help students improve their translation competence. This study approaches the issue by developing an assessment framework based on error analysis and a translation grading system, with the aim of identifying the most common and frequent errors committed by students in their…

The English language plays a significant role in Saudi Arabia at the local and international levels. Spelling errors, as one of the challenging elements in writing confronted by Saudi learners of English, have a negative effect on the quality of their written translation products (Ababneh, 2019). Therefore, more analytical studies are needed to…

This study investigated the erroneous use of the high-frequency verb TAKE by the Chinese college learners of English as a foreign language (EFL), aiming to identify the similarities and differences between Chinese EFL learners, aimed at finding out more effective ways for the teaching and researching of the high-frequency verbs. Corpus-based…

This paper describes a framework for identifying, classifying, and coding student proofs, modified from existing proof-grading rubrics. The framework includes 20 common errors, as well as categories for interpreting the severity of the error. The coding scheme is intended for use in a classroom context, for providing effective student feedback. In…

Although Error Analysis (EA) has been broadly used in Foreign Language and Mother Tongue learning contexts, it has not been applied in the field of engineering and by STEM (Science, Technology, Engineering, and Mathematics) students in a systematic way. In this interdisciplinary pilot study, we applied the EA methodology to a wide corpus of…

This study extracts the comments from a large scale of Chinese EFL learners' translation corpus to study the taxonomy of translation errors. Two unsupervised machine learning approaches are used to obtain the computational evidences of translation error taxonomy. After manually revision, ten types of English to Chinese (E2C) and eight types…

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. The Category Adjustment (CA) model suggests that this bias is due to a Bayesian combination of categorical and metric information, which offers an optimal solution under conditions of uncertainty (Huttenlocher, Hedges, & Duncan,…

In 4 word-translation experiments, we examined the different representational frameworks theory (Crutch & Warrington, 2005; 2010) that concrete words are represented primarily by category, whereas abstract words are represented by association. In our experiments, Chinese-English bilingual speakers were presented with an auditory Chinese word…