To develop competency in science practices, such as data analysis and interpretation, chemistry learners must develop an understanding of what makes an analysis and interpretation "good" (i.e., the criteria for success). One way that individuals extract the criteria for success in a novel situation is through making social comparisons,…

Altmetrics are non-traditional metrics that can capture downloads, social media shares, and other modern measures of research impact and reach. Despite most of the altmetrics literature focusing on evaluating the relationship between research outputs and academic impact/influence, the perceived and actual value of altmetrics among academicians…

An important objective of any analytical chemistry course is for students to generate and interpret data from the analysis of complex, real-world samples in order to assess the effectiveness of the analysis method, including the calibration. In this laboratory exercise, students directly compare calibration methods (external standards and standard…

Collaboration is a complex, multidimensional process; however, details of how multimodal features intersect and mediate group interactions have not been fully unpacked. Characterizing and analyzing the temporal patterns based on multimodal features is a challenging yet important work to advance our understanding of computer-supported collaborative…

This study aims to examine the effectiveness of metacognitive scaffolding in different inquiry tasks related to optics. Two high school classes participated in this study. One class, the treatment group (n = 33), which integrated metacognitive prompts into the simulation-based inquiry, was compared to the other class, the control group (n = 34),…

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…

Research data management is a prominent and evolving consideration for the academic community, especially in scientific disciplines. This research study surveyed 131 graduate students and 79 faculty members in the sciences at two public doctoral universities to determine the importance, knowledge, and interest levels around research data…

Learning analytics are often formatted as visualisations developed from traced data collected as students study in online learning environments. Optimal analytics inform and motivate students' decisions about adaptations that improve their learning. We observe that designs for learning often neglect theories and empirical findings in learning…

Analyzing, interpreting, and clearly presenting real data are skills we hope to develop in all students, majors and nonmajors alike. These process skills require lots of practice coupled with targeted feedback from instructors or mentors. Here we present a pedagogy implemented within a course-based research experience that is designed to help…

The transition to college is challenging for most students, especially those who aspire to major in the science, technology, engineering, or mathematics disciplines, in which introductory courses can be large and instruction less than optimal. This paper describes a novel, disciplinary first-year seminar (FYS) course, Exploring Biology, designed…

Using an educational data mining approach, first-year academic achievement of undergraduate nursing students, which included two compulsory courses in introductory human anatomy and physiology, was compared with achievement in a final semester course that transitioned students into the workplace. We hypothesized that students could be grouped…

This article focuses on concerns related to a lack of students' perception of relevance in school science seen as differing from educators' perception of relevance. In order to determine how relevance is portrayed in teaching and learning materials (TLMs), the titles and introductory texts (scenarios) from 77 TLMs, aiming to induce students'…

Latent variable models, such as the popular Knowledge Tracing method, are often used to enable adaptive tutoring systems to personalize education. However, finding optimal model parameters is usually a difficult non-convex optimization problem when considering latent variable models. Prior work has reported that latent variable models obtained…

Nuclear magnetic resonance spectroscopy (NMR) plays a key role in introductory organic chemistry, spanning theory, concepts, and experimentation. Therefore, it is imperative that the instruction methods for NMR are both efficient and effective. By utilizing eye tracking equipment, the researchers were able to monitor how second-semester organic…

This study explored 6th grade students reading of science text on the iPad to better understand how students with varying strengths of comprehending text and current academic abilities interpret text on their iPads. Our study sample compared three students with strong reading scores based on informal reading inventories, standardized tests, and…