A growing body of research suggests that accounting for student specific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

In this article, the authors applied profile analysis to Maths exam data to demonstrate how different exam forms, differing in difficulty and length, can be reported and easily interpreted. The results were presented for different groups of participants and for different institutions in different Maths domains by evaluating the balance. Some…

This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…

This study examines the power of cognitive and noncognitive variables to predict students' performance in algebra. We investigated students' prior year's assessment scores and demographic characteristics to predict eighth-grade algebra scores. Using California statewide assessment data, we explored predictive factors in three regression models.…

Taking advanced high school courses (for example, honors, Advanced Placement, and dual-credit courses that offer college credits in high school) can help prepare students for postsecondary education and careers. English learner students, however, face unique obstacles to taking advanced courses because they must divide their time between acquiring…

Pretesting and early intervention measures to identify and remediate at-risk students were implemented in algebra-based introductory physics to help improve student success rates. Pretesting via a math and problem-solving diagnostic exam administered at the beginning of the course was employed to identify at-risk students based on their scores.…

Learning analysts often consider whether learning processes across time are related (1) to one another or (2) to learning outcomes at higher levels. For example, are a group's temporal sequences of talk (e.g., correct evaluation [right arrow] correct, new idea) during its problem solving related to its group solution? I show how to address these…

Objective: Remedial mathematics courses are widely considered a barrier to student success in community college, and there has been a significant amount of work recently to reform them. Yet, there is little research that explicitly examines whether increasing learning in remedial classes improves grades or completion rates. This study examines the…

Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…

Although thousands of students enroll in Massive Open Online Courses (MOOCs) for learning and self-improvement, many get confused, harming learning and increasing dropout rates. In this paper, we quantify these effects in two large MOOCs. We first describe how we automatically estimate students' confusion by looking at their clicking behavior on…

Formative assessments have been deemed the key to effectively measuring if students have mastered the understanding of curriculum standards. Thus, allowing teachers to use the results to tailor remediation and use other efforts to support mastery of student learning before the end of the school year has positive effects on student achievement.…

Improving the outcomes of students in developmental or remedial math remains a puzzle in higher education. Concerns with low persistence and completion rates have motivated proponents of reform to reconsider the delivery of developmental math. Lengthening the amount of time in math is thought to be an intervention that improves academic…

Students at a large urban community college enrolled in fourteen sections of a developmental algebra class. While cognitive variables are often used to place students, affective characteristics may also influence their success. To explore the impact of affective variables, students took ACT's Engage survey measuring motivation, academic-related…

Using a novel design approach, a randomized experiment (RE) was embedded within a regression discontinuity (RD) design (R-RE-D) to evaluate the impact of developmental mathematics at a large midwestern college ("n" = 2,122). Within a region of uncertainty near the cut-score, estimates of benefit from a prospective RE were closely…