Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

Programming-based activities are becoming more widespread in curricula. Our theoretical and empirical investigation seeks to identify appropriate ways to connect computer programming and algorithmics to mathematical learning. We take the intermediate value theorem as our starting point, as it is covered by the French school curriculum, and because…

This study aimed to predict the culturally responsive teacher roles based on cultural intelligence and self-efficacy using machine learning classification algorithms. The research group consists of 415 teachers from different branches. The Bayes classifier (NaiveBayes), logistic-regression (SMO), lazy-classifier (KStar), meta-classifier…

Recommender systems have been actively used in many areas like e-commerce, movie and video suggestions, and have proven to be highly useful for its users. But the use of recommender systems in online learning platforms is often underrated and less likely used. But many of the times it lacks personalisation especially in collaborative approach…

Sustainable Development Goals (SDG) are at the forefront of government initiatives across the world. The SDGs are primarily concerned with promoting sustainable growth via ensuring wellbeing, economic growth, environmental legislation, and academic advancement. One of the most prominent goals of the SDG is to provide learners with high-quality…

This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…

The training of non-specialists, particularly engineers, in mathematics requires designing specific didactic proposals that make the importance of mathematics evident. One approach to creating such proposals consists in analyzing the mathematics used in authentic contexts of engineering research and then effectuating a didactic transposition to…

This study investigated the influence of CThink4CS2 Module on computational thinking (CT) skills of form four chemistry students. The CThink4CS[superscript]2 Module integrated CT with the Engineering Design Process (EDP) in chemistry class. This study utilized quantitative research methods and quasi-experimental design. Quantitative data were…

This dissertation explores the relationship between quantitative phonetic measurements and listener identification of accents of English, focusing on phonetic distance and its perceptual correlates across various English accent varieties. The Levenshtein distance (LD) measure, which quantifies string similarity by calculating the minimum cost of…

Background: Recent field experiments confirm that learning to teach under a more instructionally effective mentor causes teacher candidates to feel more prepared (Ronfeldt et al., 2020; Ronfeldt, Goldhaber, et al., 2018) and demonstrate more effective teaching (Goldhaber et al., 2022). One of these experiments--designed under a research-practice…

Background: Multilevel randomized controlled trials (MRCTs) have been widely used to evaluate the causal effects of educational interventions. Traditionally, educational researchers and policymakers focused on the average treatment effects (ATE) of the intervention. Recently there has been an increasing interest in evaluating the heterogeneity of…

Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…

I situate computer programming as a cultural practice. I develop this perspective in two ways: exploring how programming practices can support intercultural learning, and examining how programming tools themselves embed cultural assumptions and values. For the former, I study how relationships across difference are formed over computing activities…

Applications of machine learning in chemistry are many and varied, from prediction of structure-property relationships, to modeling of potential energy surfaces for large scale atomistic simulations. We describe a generalized approach for the application of machine learning to the classification of spectra which can be used as the basis for a wide…