In learning diagnostic assessments, the attribute hierarchy specifies a sequential network of interrelated attribute mastery processes, which makes a test blueprint consistent with the cognitive theory. One of the most important functions of attribute hierarchy is to guide or limit the developmental direction of students and then form a…

We investigated whether the temporal contiguity effect, which holds that information sources, such as visual information and narration need to be temporally coordinated for learning to be effective, can also be found in narrated slideshows. A concurrent presentation-key point format (CPK), in which visual information sequentially appeared as key…

Background: The worked example effect in cognitive load theory suggests that providing worked examples first followed by solving similar problems would facilitate students' learning. Using problem solving-worked example sequence is another way of implementing example-based instruction. Although research has demonstrated the superiority of worked…

K-12 students are expected to acquire competence in data display as part of developing statistical literacy. To support research, assessment design, and instruction, we developed a hypothesized learning progression (LP) using existing empirical literature in the fields of mathematics and statistics education. The data display LP posits a…

We present the results of a qualitative research study designed to explore differences in the types of reasoning triggered by information presented to chemistry students in two different formats. One group of students was asked to analyze a sequence of images designed to represent critical elements in the explanation of a target phenomenon.…

The concept of variability is central to statistics. In this research report, we review mathematics education research on variability and, based on that review and on feedback from an expert panel, propose a learning progression (LP) for variability. The structure of the proposed LP consists of 5 levels of sophistication in understanding…

Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…

THE TRANSFER EFFECTS OF DISCOVERY AND EXPOSITORY INSTRUCTIONAL TECHNIQUES FOR SEQUENCING OF INSTRUCTION WERE THE PURPOSE OF THIS TWO-PART STUDY. THE FIRST STUDY COMPARED THE TWO PROCEDURES IN A PROGRAMED UNIT ON SUMMING NUMBER SERIES. SAMPLES FOR THIS PART OF THE STUDY CONSISTED OF 96 NINTH-GRADE ALGEBRA STUDENTS, WHO WERE ASSIGNED TO EITHER OF…

TWO STRATEGIES FOR TEACHING MULTIPLE-DISCRIMINATION TASKS WERE REPORTED. THE "MULTIPLE CONCEPT" PRESENTS SIMPLE DESCRIPTIONS OF SEVERAL RELATED CONCEPTS AT THE BEGINNING OF INSTRUCTION. INCREASINGLY COMPLEX MATERIAL PERTAINING TO THESE CONCEPTS IS THEN GRADUALLY INTRODUCED. THE "SINGLE CONCEPT" PRESENTS ONE CONCEPT AT A TIME,…

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…