Participatory modeling (PM) is an engaged research methodology for creating analog or computer-based models of complex systems, such as socio-environmental systems. Used across a range of fields, PM centers stakeholder knowledge and participation to create more internally valid models that can inform policy and increase engagement and trust…

Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning…

Analysing the interaction between classroom dialogue and digital technology is challenging. Studies in this area typically draw on methods developed for the analysis of spoken interactions. This article reports on a new approach for analysing the enacted affordances of digital technology in classroom dialogue. Using examples from cross-country…

Large data sets invite students to engage in scientific practices such as question asking, identifying correlations, using visualizations, and practicing data literacy in an authentic context. However, authentic data sets are rarely introduced in the biology classroom. We prepared an online inquiry activity based on authentic gross characteristics…

Social scientists increasingly use video data, but large-scale analysis of its content is often constrained by scarce manual coding resources. Upscaling may be possible with the application of automated coding procedures, which are being developed in the field of computer vision. Here, we introduce computer vision to social scientists, review the…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

Although various academic disciplines use data papers to support effective research practices, data papers are still uncommon in the educational sciences. Main goals of data papers are enhancing transparency regarding research processes and supporting data sharing among researchers and thus, open science. As many educational research projects…

In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…

The current study used a randomized control trial to evaluate a decision-making model on special education preservice candidates' instructional decision-making and self-reported confidence ratings when analyzing graphed student data. Thirty-two special education preservice candidates viewed authentic curriculum-based measurement (CBM) graphs and…

Today, the use of software in qualitative research analysis is rapidly becoming widespread among researchers. Researchers manage large data sets using features such as editing data, transcribing, creating codes, and searching within data. However, while the data analysis uses software in a format, the analysis of the essence of the data is done by…

Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…

This study applies Indigenous Oral Research Methods to amplify the voice and story of math educators working within Indigenous communities. Publicly posted podcast interviews with five participants of the Fire Circles Professional Development were used to disseminate their experiences and views of professional development programs that they had…

Facebook is widely used and researched. However, though the data generated by educational technology tools and social media platforms other than Facebook have been used for research purposes, very little research has used Facebook posts as a data source--with most studies relying on self-report studies. While it has historically been impractical…

This article introduces an open-source software package--R for Qualitative Data Analysis (RQDA). RQDA is an R package for analysis of text-formatted data, which is compatible across operating platforms. It is user-friendly and seamlessly integrates with R, which makes it possible to conduct statistical analyses on qualitative coding. Alternative…

In response to the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, this paper proposes an English teaching ability estimation algorithm based on big data fuzzy K-means clustering. Firstly, the article establishes a constraint parameter index analysis model. Secondly,…