Student's academic performance prediction empowers educational technologies including academic trajectory and degree planning, course recommender systems, early warning and advising systems. Given a student's past data (such as grades in prior courses), the task of student's performance prediction is to predict a student's grades in future…

Many national science frameworks (e.g., Next Generation Science Standards) argue that developing mathematical modeling competencies is critical for students' deep understanding of science. However, science teachers may be unprepared to assess these competencies. We are addressing this need by developing virtual lab performance assessments that…

This paper addresses the question of identifying a concept dependency graph for a MOOC through unsupervised analysis of lecture transcripts. The problem is important: extracting a concept graph is the first step in helping students with varying preparation to understand course material. The problem is challenging: instructors are unaware of the…

With a goal of better understanding the online discourse within the Massive Open Online Course (MOOC) context, this paper presents an open source visualisation dashboard developed to identify and classify emergent discussion topics (or themes). As an extension to the authors' previous work in identifying key topics from MOOC discussion contents,…

We propose a graph mining methodology to analyze the relationships among academic programs from the point of view of cooperative education. The input consists of student - job interview pairs, with each student labelled with his or her academic program. From this input, we build a weighted directed graph, which we refer to as a program graph, in…

The normal curve has long been important in statistics. Most interval variables yield normal or quasi-normal distributions when data are collected from large samples, and the normal "Z" distribution is also used as a test statistic (e.g., to test differences between two means when sample size is large, since "t" approaches…

In this paper we consider an experiment in which 15 years old students explore a phenomenon of covariance, by using Cabri for drawing geometric figures, measuring, and sketching graphs. In this way they collect different types of information. A first research question is how students deal with them in situations of exploration, in particular,…

Methods that have been employed in McGill University's (Montreal, Quebec) program of research into the nature of learning are described. The methods illustrate four phases of inquiry: conceptualization or model-building; data gathering techniques; data representation; and data analysis. For the university's learning task project, the development…

While educational researchers frequently collect data from a sample of individuals on a sample of variables, they sometimes collect data involving samples of: (1) subjects; (2) variables; and (3) occasions of measurement. A multistage procedure for analyzing such three-mode data is presented, focusing on effect sizes and graphic confidence…

In statistical terms, transfer rates require two components: a numerator that represents community college students who transfer and a denominator that approximates the pool of potential transfer students. The California Task Force adopted a set of criteria to judge the appropriateness of prospective pairs of numerators and denominators. Its form…

A pentagonal model, based on the star model of function understanding of C. Janvier (1987), is presented as a framework for the design and interpretation of research in the area of learning the concept of mathematical function. The five vertices of the pentagon correspond to five common representations of mathematical function: (1) graph; (2)…