In South Korea, curriculum is revised, made public and implemented under a system known as a nation led curriculum. The South Korean national curriculum was completely revised 10 times between 1946 and 2015. At present, a complete revision is underway to replace the current 2015 national curriculum which is called the 2022 revised national…

Solving mathematics story problems requires text comprehension skills. However, previous studies have found few connections between traditional measures of text readability and performance on story problems. We hypothesized that recently developed measures of readability and topic incidence measured by text-mining tools may illuminate associations…

The Common Core assessments emphasize short essay constructed response items over multiple choice items because they are more precise measures of understanding. However, such items are too costly and time consuming to be used in national assessments unless a way is found to score them automatically. Current automatic essay scoring techniques are…

Exploring language provides us with one approach to better understanding the practices and beliefs of a community. With advances in technology--specifically, computational text processing and machine learning tools--we can now examine written language on a large scale. In this study, we investigate the language of mathematics teaching and learning…

The current study uncovers secondary school students' actual use of text-learning strategies during an individual learning task by means of a concurrent self-reported thinking aloud procedure. Think-aloud data of 51 participants with different learning strategy profiles, distinguished based on a retrospective self-report questionnaire (i.e., 15…

Research involving digital games and language learning is rapidly growing. One advantage of using digital games to support language learning is the ability to collect data on students learning in real time. In this study, we use educational data mining methods to explore the relationship between in-game data and elementary students' Chinese…

Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…

We present a method for assessing science inquiry performance, specifically for the inquiry skill of designing and conducting experiments, using educational data mining on students' log data from online microworlds in the Inq-ITS system (Inquiry Intelligent Tutoring System; www.inq-its.org). In our approach, we use a 2-step process: First we use…

We explore multi-modal machine learning-based approaches (facial expression recognition, auditory emotion recognition, and text sentiment analysis) to identify "negative moments" of teacher-student interaction during classroom teaching. Our analyses on a large (957 videos, each 20min) dataset of classroom observations suggest that: (1)…

We present "Science Assistments," an interactive environment, which assesses students' inquiry skills as they engage in inquiry using science microworlds. We frame our variables, tasks, assessments, and methods of analyzing data in terms of "evidence-centered design." Specifically, we focus on the "student model," the…

This study investigates the effects of a scenario-based assessment design on students' writing processes. An experimental data set consisting of four design conditions was used in which the number of scenarios (one or two) and the placement of the essay task with respect to the lead-in tasks (first vs. last) were varied. Students' writing…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…

Reading to learn is a quintessentially self-regulated activity. In order to provide effective support for this activity it is necessary for us to understand how students adapt their self-regulation behaviors within disciplinary reading environments. In this paper, we utilize student response data from a digital literacy platform to examine the…

Curricula often lack metadata to characterize the relatedness of concepts. To investigate automatic methods for generating relatedness metadata for a mathematics curriculum, we first address the task of identifying which terms in the vocabulary from mathematics word problems are associated with the curriculum. High chance-adjusted interannotator…

Automatic assessment of the quality of classroom discourse can have a transformative effect on research and practice on improving teaching effectiveness. We improve on a previous automated method to measure teacher authentic questions -- open-ended questions without pre-scripted responses that predict student achievement growth -- using classroom…