The advances of machine learning (ML) in scientific discovery (SD) reveal exciting opportunities to utilize it as a cross-cutting tool for inquiry-based learning in K-12 STEM classrooms. There are, however, limited efforts on providing teachers with sufficient knowledge and skills to integrate ML into teaching. Our study addresses this gap by…

Artificial Intelligence (AI) is revolutionizing many industries and becoming increasingly ubiquitous in everyday life. To empower children growing up with AI to navigate society's evolving sociotechnical context, we developed three middle school AI literacy curricula: "Creative AI,| "Dancing with AI," and "How to Train Your…

This paper presents a proposal of specific curriculum in Artificial Intelligence (AI) for high school students, which has been organized as a two-year subject. The curriculum was designed based on two premises. The first one is that, although the proposal is targeted to scientific programmes, the involved students and teachers do not have any…

The rapid expansion of artificial intelligence (AI) necessitates promoting AI education at the K-12 level. However, educating young learners to become AI literate citizens poses several challenges. The components of AI literacy are ill-defined and it is unclear to what extent middle school students can engage in learning about AI as a…

This study evaluated the construct validity of six scoring traits of an automated writing evaluation (AWE) system called "MI Write." Persuasive essays (N = 100) written by students in grades 7 and 8 were randomized at the sentence-level using a script written with Python's NLTK module. Each persuasive essay was randomized 30 times (n =…

This article provides an in-depth look at how K-12 students should be introduced to Machine Learning and the knowledge and skills they will develop as a result. We begin with an overview of the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and briefly discuss each of the "Five Big Ideas in AI" that…

Artificial Intelligence (AI) permeates every aspect of our daily lives and is no longer a subject reserved for a select few in higher education but is essential knowledge that our youth need for the future. Much is unknown about the level of AI knowledge that is age and developmentally appropriate for high school, let alone about how to teach AI…

Many previous studies have highlighted the influence of learners' affective states on learning with tutoring systems. However, the associations between learning and learners' meta-affective capability are still unclear. The goal of this paper is to analyse meta-affective capability and its influence on learning outcomes as well as the dynamics of…

This paper discusses educating stakeholders of algorithmic systems (systems that apply Artificial Intelligence/Machine learning algorithms) in the areas of algorithmic fairness, accountability, transparency and ethics (FATE). We begin by establishing the need for such education and identifying the intended consumers of educational materials on the…

Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…

Educators need actionable information about student progress during the school year. This paper explores an approach to this problem in the writing domain that combines three measurement approaches intended for use in interim-assessment fashion: scenario-based assessments (SBAs), to simulate authentic classroom tasks, automated writing evaluation…

Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However,…

The effect of metacognitive scaffolding for learning by teaching was investigated and compared against learning by being tutored. Three versions of an online learning environment for learning algebra equations were created: (1) APLUS that allows students to interactively teach a synthetic peer with a goal to have the synthetic peer pass the quiz…

The 2017 ASSISTments Data Mining competition aims to use data from a longitudinal study for predicting a brand-new outcome of students which had never been studied before by the educational data mining research community. Specifically, it facilitates research in developing predictive models that predict whether the first job of a student out of…

A successful instructional method is to engage learners with exploratory problem-solving before providing explanations of the canonical solutions and foundational concepts. A key question is whether and what type of guidance will lead learners to explore more productively and how this guidance will affect subsequent learning and transfer. We…