Businesses assess public sentiment toward relevant topics and gain valuable insights through social media analytics (SMA). Students of business information analytics can therefore reap multiple benefits from SMA as a learning tool. We designed and implemented an SMA capstone project that integrated undergraduate research and community engagement.…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

There has been extensive work within chemistry education research to characterize organic chemistry students' engagement in key science practices like "constructing explanations" and "engaging in argument from evidence". Less has been done to consider how organic chemistry students interact with empirical data, outside of…

Secondary data analyses occur when new analyses are proposed for existing data. Although they are prevalent in special education research, there is little guidance on how to prepare secondary data analyses studies. Preregistration of secondary data analyses studies provides a nice opportunity and structure for fellow researchers to share…

The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose…

Generalizability theory is a modern, powerful, and broad framework used to assess the reliability, or dependability, of measurements. While there exist classic works that explain the basic concepts and mathematical foundations of the method, there is currently a lack of resources addressing computational resources for those researchers wishing to…

A data party is an engaging way to involve stakeholders in program evaluation. We explain the use of a data party for engaging 4-H program stakeholders (e.g., staff and volunteers) in data interpretation and helping them understand, embrace, and use program evaluation information to make data-driven decisions about their programs. We present two…

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…

Biochemistry is a study which consists of many difficult concepts. Research that examines biochemistry learning needs to be continuously carried out so that the quality of learning can be evaluated and improved. Hence, this content analysis addressed to analyze the research methodologies of the articles published in various Indonesian biology…

Students often need to obtain, organize, clean, and analyze data in order to draw conclusions about a particular phenomenon (e.g., why tidal heights change). When conducting a science investigation in biology, chemistry, physics, or Earth science, data can be collected by the student or can be provided to them via secondary data sets. This article…

Physics education research (PER) has long used concept inventories to investigate student learning over time and to compare performance across various student subpopulations. PER has traditionally used normalized gain to explore these questions but has begun to use established methods from other fields, including Cohen's "d," multiple…

As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…

Corpora, large electronic collections of texts, have been used in language teaching for several decades. Also known as Data-Driven Learning (DDL), this method has been gaining popularity because empirical research has consistently shown its effectiveness for learning. However, corpora are still underutilized, especially with learners of languages…

Higher education institutions are increasingly required to provide a measured response to perceptions that challenge institutions' value proposition as assets to their communities. This article focuses on best practices in the campus' efforts to create a pathway to demonstrate community impact. The ability of systematic tracking of partnership and…