When learning about scientific phenomena, students are expected to "mechanistically" explain how underlying interactions produce the observable phenomenon and "conceptually" connect the observed phenomenon to canonical scientific knowledge. This paper investigates how the integration of the complementary processes of designing…

This book problematizes and explores appropriate ways of using AI technology that can augment educational practice, especially in K-12 teaching and learning. Since the launch of OpenAI ChatGPT in November 2022, people have been debating "to chat or to cheat" while more and more educators have started to explore "to add or to…

Argumentation, a key scientific practice presented in the "Framework for K-12 Science Education," requires students to construct and critique arguments, but timely evaluation of arguments in large-scale classrooms is challenging. Recent work has shown the potential of automated scoring systems for open response assessments, leveraging…

Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…

Second language (L2) writing research has demonstrated that young learners discuss linguistic issues, make use of feedback, and show a generally positive disposition toward writing tasks. However, many issues deserve further investigation. Regarding task implementation, few studies have been conducted with young learners writing individually, and…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

We present two types of validity evidence to support inferences and decisions about use of easyCBMs in relation to state testing programs. The first type involves the use of Benchmarks in reading to use in making predictions of performance on the Smarter Balanced (SB) test. These predictions can be made both well in advance (several months) or…

One-to-one online tutoring provided by human tutors can improve students' learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach to monitoring online one-to-one tutoring quality. The approach analyzes teacher behaviours and classifies tutoring sessions…

Automated written corrective feedback (AWCF) tools play a crucial role in supporting English writing instruction. However, issues such as insufficient accuracy and hallucination have undermined users' trust in these systems. To address these challenges, this study investigates the potential of Generative Artificial Intelligence (GAI) enhanced by…

Automated Essay Scoring (AES) can reliably grade essays at scale and reduce human effort in both classroom and commercial settings. There are currently three dominant supervised learning paradigms for building AES models: feature-based, neural, and hybrid. While feature-based models are more explainable, neural network models often outperform…

Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

Social-emotional development in early childhood (EC) is an important factor to their later development and adjustment. While all young children display unwanted behaviors at some time during development, challenging behaviors that occur across settings and over a period of time should be identified and intervened; thus, data collection efforts…

The acquisition of a new morphological rule can be influenced by numerous factors, including the type of feedback provided during learning. The present study aimed to test the effect of different feedback types on children's ability to learn and generalize an artificial morphological rule (AMR). Two groups of eight-year-olds learned to judge and…

In the present study, two sets of scripts from primary school students were collected, one written in English and the other in their native Chinese on the same topic. The Chinese scripts were translated into English by Google Translate (GT) and compared with the scripts written in English. Sentences in the two sets of passages that were clearly…