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…

Aside from being culturally relevant, artificial intelligence is also supporting companies in making business decisions. Consequently, "workforce needs have shifted rapidly," resulting in a demand for applicants who are skilled in "data, analytics, machine learning, and artificial intelligence" (Miller and Hughes 2017). This…

Human raters and machine scoring systems potentially have complementary strengths in evaluating language ability; specifically, it has been suggested that automated systems might be used to make consistent measurements of specific linguistic phenomena, whilst humans evaluate more global aspects of performance. We report on an empirical study that…

Intelligence is at the heart of what makes us human, but the methods we use for identifying, talking about and valuing human intelligence are impoverished. We invest artificial intelligence (AI) with qualities it does not have and, in so doing, risk losing the capacity for education to pass on the emotional, collaborative, sensory and…

The aim of this research is to investigate the educational potential of AI-powered chatbots in Social Studies learning-teaching processes. The study was conducted using embedded design, evaluated within the framework of mixed methods research. The study group consists of 78 6th-grade students studying in three different classes, along with one…

Artificial intelligence (AI) tools have become a popular topic in the education field. Most of the schools in Hong Kong focus on how to properly use AI software to help students' learning experience. As this is still a relatively new technology, the stance for most of the schools in Hong Kong is skeptical. This study aims to find out whether…

This article originated from a working group on "Learning beyond formal schooling through human--computer--human interaction (HCHI)" convened at the UNESCO EDUSummIT 2023 in Kyoto (Japan). A polylogue approach was adopted by engaging eight co-authors whose diverse perspectives culminated in propositions that addressed the pivotal…

This study provides an empirical approach to utilizing an Artificial Intelligence (AI)-based system for identifying students' university choice factors that impact their matriculation decision. We created an AI-based chatbot that gathered both qualitative and quantitative data from nearly 1200 participants worldwide. The entire human-AI…

In this dissertation I explore the fugitive technology practices of Black high-schoolers in a tech-rich after-school makerspace. To do so, I invoke ontologies from two cyborgs to make sense of these Black teens' practices. First, James and Costa Vargas (2012) offer the Black Cyborg-- the rebel intellectual rejecting victimization through…

For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…

We present the design of a citizen science system that uses machine learning to guide the presentation of image classification tasks to newcomers to help them more quickly learn how to do the task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning for training with tasks with uncertain outcomes is…

For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…

Peer-grading is commonly adopted by instructors as an effective assessment method for MOOCs (Massive Open Online Courses) and SPOCs (Small Private online course). For solving the problems brought by varied skill levels and attitudes of online students, statistical models have been proposed to improve the fairness and accuracy of peer-grading.…

In data collected from virtual learning environments (VLEs), item response theory (IRT) models can be used to guide the ongoing measurement of student ability. However, such applications of IRT rely on unbiased item parameter estimates associated with test items in the VLE. Without formal piloting of the items, one can expect a large amount of…

In this paper, a multi-mode digital teaching approach is proposed based on the use of the VARK (Visual, Aural, Read/Write, Kinaesthetic) model where students have different styles (one or more) that improve their learning (face-to-face and online). Our research question is on the effectiveness of this approach in terms of learning efficacy and…