Prior knowledge is often strongly related to students' learning. In the present research, we explored the relationship between prior knowledge and the accuracy of students' predictive monitoring judgments (judgments of learning; JOLs) and postdictive monitoring judgments (confidence judgments). In four experiments, students completed prior…

"Attribute-framing bias" reflects people's tendency to evaluate objects framed positively more favorably than the same objects framed negatively. Although biased by the framing valence, evaluations are nevertheless calibrated to the magnitude of the target attribute. In three experiments that manipulated magnitudes in different ways, we…

Recent approaches to the detection of cheaters in tests employ detectors from the field of machine learning. Detectors based on supervised learning algorithms achieve high accuracy but require labeled data sets with identified cheaters for training. Labeled data sets are usually not available at an early stage of the assessment period. In this…

Metacognition refers to cognitions about our own cognitions. In recent years, there has been a concerted effort to examine metacognition among autistic people. The results from these studies have produced a mixed picture, with some concluding that autistic people are just as accurate as typically developing people in judging their own cognitions…

We examined knowledge-based inference in 6-, 8- and 10-year-olds. Participants listened to texts where the number of clues for an inference was manipulated and then judged whether single-word probes (target inference, competing inference, literal word from the text and an unrelated concept) were related to the story. Accuracy and response times…

This study aims to describe the relationships between child-internal and child-external factors and the consonant accuracy of bilingual children. More specifically, the study looks at internal factors: expressive and receptive vocabulary, and external factors: language exposure and language status, of a group of 4-year-old bilingual Arabic-French…

Prior studies suggest autism-specific and general developmental screens are complementary for identifying both autism and developmental delay (DD). Parents completed autism and developmental screens before 18-month visits. Children with failed screens for autism (n = 167) and age, gender, and practice-matched children passing screens (n = 241)…

This paper summarises exploratory analysis undertaken to evaluate the effectiveness of using machine learning approaches to calculate projected completion rates for vocational education and training (VET) programs, and compares this with the current approach used at the National Centre for Vocational Education Research (NCVER) -- Markov chains…

Purpose: To date, there are no automated tools for the identification and fine-grained classification of paraphasias within discourse, the production of which is the hallmark characteristic of most people with aphasia (PWA). In this work, we fine-tune a large language model (LLM) to automatically predict paraphasia targets in Cinderella story…

Though a substantial amount of research exists on imputing missing scores in educational assessments, there is little research on cases where responses or scores to an item are missing for all test takers. In this paper, we tackled the problem of imputing missing scores for tests for which the responses to an item are missing for all test takers.…

Recent work reveals a left digit effect in number line estimation such that adults' and children's estimates for three-digit numbers with different hundreds-place digits but nearly identical magnitudes are systematically different (e.g., 398 is placed too far to the left of 401 on a 0-1000 line, despite their almost indistinguishable magnitudes;…

The research problem addressed in this study is that racial bias programmed into predictive algorithm recommendations negatively impacts students in historically underrepresented groups. The purpose of this qualitative descriptive study was to explore the perception of algorithm accuracy among data professionals in higher education and explore the…

Purpose: This study aims to explore the perception of algorithm accuracy among data professionals in higher education. Design/methodology/approach: Social justice theory guided the qualitative descriptive study and emphasized four principles: access, participation, equity and human rights. Data collection included eight online open-ended…

Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching for solutions to detect such content. The paper examines the general functionality of detection tools for…

In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…