Developmental scientists are often interested in subgroups of people who share commonalities in aspects of development; these subgroups often cannot be captured directly but instead must be inferred from other information. Mixture models can be used in these situations. Two specific types of mixture models, latent profile transition analyses and…

Data modeling practices are often invisible to students in introductory biology courses. However, developing a well-rounded understanding of these practices is critical for scientific literacy. Furthermore, introductory undergraduate science laboratory courses are often taught by graduate students or novice instructors with little autonomy,…

Qualitative coding procedures emanating from grounded theory were limited by technologies of the 1960s: colored pens, scissors, and index cards. Today, electronic documents can be flexibly stored, retrieved, and cross-referenced using qualitative data analysis (QDA) software. We argue the oft-cited grounded theory framework poorly fits many…

The focus of this paper is learning the language of data science and statistics through the use of simple classroom activities. Many terms in statistics are known to be lexically ambiguous, having one meaning in general English conversation and another, more technical, meaning in statistical English. The main aim is to investigate whether the…

Analysis of data from single-case intervention studies commonly involves visual analysis. Previous research indicates that visual analysis may suffer from low reliability and unpromising error rates. We investigated the reliability and validity of visual analysis and explored to what extent data trends affect judgments. We administered a…

Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…

The proliferation of massive open online courses (MOOCs) highlights the necessity of developing accurate and diagnostic evaluation methods to assess the courses' quality and effectiveness. Hence, this study proposes a diagnostic MOOC evaluation (DME) method that combines the Analytic Hierarchy Process algorithm and learner review mining to…

Many national education systems incorporate a central inspectorate tasked with visiting, evaluating and reporting on the performance of schools. The judgements produced by inspectors often play a part in the way that schools are held to account and constitute an important source of data in their own right. Inspection reports are therefore of great…

Understanding the processes in education, such as the student learning behavior within a specific course, is a key to continuous course improvement. In online learning systems, students' learning can be tracked and examined based on data collected by the systems themselves. However, it is non-trivial to decide how to extract the desired students'…

This study employed propensity score matching and regression analysis to determine whether or not a retention scholarship pilot program at a mid-size public research university was effective at increasing first-year retention. The scholarship pilot did not require any application process for students but rather used a predictive logistic…

When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…

There are a number of ways that student investment can be measured, including full cost of attendance (COA, also known as sticker price), net price (COA minus grant aid), and opportunity costs in the form of forgone earnings. This paper explores those options and makes recommendations for how student investment should be measured with ideal data…

In standard statistical data analysis, the effects of intervention or prevention efforts are evaluated in terms of variable relations. Results from application of regression-type methods suggest whether, overall, intervention is successful. In this article, we propose using configural frequency analysis (CFA) either in tandem with regression-type…

The purpose of this dissertation was to develop and use a platform that facilitates Massive Open Online Course (MOOC) replication research. Replication and the verification of previously published findings is an essential step in the scientific process. Unfortunately, a replication crisis has long plagued scientific research, affecting even the…

This case discusses how scenario-based interviews can be used to develop research into policy and practice. Based on data collected from U.K. further education management settings, it shows how and why scenario-based interviews were used. It also explains how the data collected were then used to illustrate and analyze the implementation of a…