Recent developments in computerized scoring via semantic distance have provided automated assessments of verbal creativity. Here, we extend past work, applying computational linguistic approaches to characterize salient features of creative text. We hypothesize that, in addition to semantic diversity, the degree to which a story includes…

Machine learning (ML) has been increasingly employed in science assessment to facilitate automatic scoring efforts, although with varying degrees of success (i.e., magnitudes of machine-human score agreements [MHAs]). Little work has empirically examined the factors that impact MHA disparities in this growing field, thus constraining the…

Machine learning (ML) is an emergent computerised technology that relies on algorithms built by 'learning' from training data rather than 'instruction', which holds great potential to revolutionise science assessment. This study systematically reviewed 49 articles regarding ML-based science assessment through a triangle framework with technical,…

Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies…

We systematically compared two coding approaches to generate training datasets for machine learning (ML): (1) a holistic approach based on learning progression levels; and (2) a dichotomous, analytic approach of multiple concepts in student reasoning, deconstructed from holistic rubrics. We evaluated four constructed response assessment items for…

Identifying students at risk of failing a course has potential benefits, such as recommending the At-Risk students to various interventions that could improve pass rates. The challenges however, are firstly in measuring how effective these interventions are, i.e. measuring treatment effects, and secondly, to not only predict overall (average)…

Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…

Research in era of data representation to contribute and improve key data policy involving the assessment of learning, training and English language competency. Students are required to communicate in English with high level impact using language and influence. The electronic technology works to assess students' questions positively enabling…

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…