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…

Computer-Assisted Qualitative Data Analysis (CAQDAS) is becoming increasingly prevalent in the social and health sciences and an expected skill for many researchers. CAQDAS is much less structured than the use of quantitative analysis software. However, actual CAQDAS practices and challenges have been insufficiently studied, especially among…

Modern technology is necessary and important for improving the quality of education. While machine learning algorithms to support students remain limited. Thus, it is necessary to inspire educational scholars and educational technologists. This research therefore has three main targets: to educate the holistic context of rural education…

Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students' retention services. Big Data mining and machine learning methods are applied to manipulate, analyze and predict students' failure,…

Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…

It is timely to take stock of the wellbeing of educational research in Aotearoa New Zealand. The major Education Work Programme 2021 includes a Research, Evaluation and Development Strategy. Te Ara Paerangi--Future Pathways Green Paper has launched a major review of the design of public funding for research institutions and for research taking…

Purpose: The general goal of this paper is to help educators understand the importance of MOOC training to school teachers and their hypothetical value for predicting the use of teaching strategies in the face-to face-classroom teaching. With this purpose, the study is guided by two research questions: (1) Are there different patterns of…