A critical issue in using fine-grained gameplay data to measure learning processes is the development of indicators and the algorithms used to derive such indicators. Successful development--that is, developing traceable, interpretable, and sensitive-to-learning indicators--requires understanding the underlying theory, how the theory is…

The use of technology as a facilitator in learning environments has become increasingly prevalent with the global pandemic caused by COVID-19. As such, computer-supported collaborative learning (CSCL) gains a wider adoption in contrast to traditional learning methods. At the same time, the need for automated tools capable of assessing and…

It is particularly important to identify and address issues of fairness and equity in educational contexts as academic performance can have large impacts on the types of opportunities that are made available to students. While it is always the hope that educators approach student assessment with these issues in mind, there are a number of factors…

AutoTutor-ARC (adult reading comprehension) is an intelligent tutoring system that uses conversational agents to help adult learners improve their comprehension skills. However, in such a system, not all lessons and items optimally serve the same purposes. In this paper, we describe a method for classifying items that are "instructive,…

Historically, learning for young students has occurred in formal, in-person classroom environments, but the distance learning context has opened a myriad of learning modalities. To this end, we aim to better understand how deploying learning experience design (LXD) approach supports or hinders children's engagement while participating in an…

This preliminary study examined whether distinct student profiles (N = 760) emerged based on their behavioral patterns in an online algebraic learning game. We applied k-means clustering analysis to clickstream data collected in the game and then examined how students' behavioral patterns varied across the clusters using data visualization. The…

Response Process Validity (RPV) reflects the degree to which items are interpreted as intended by item developers. In this study, teacher responses to constructed response (CR) items to assess pedagogical content knowledge (PCK) of middle school mathematics teachers were evaluated to determine what types of teacher responses signaled weak RPV. We…

Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…

The ability to express yourself concisely and coherently is a crucial skill, both for academic purposes and professional careers. An important aspect to consider in writing is an adequate segmentation of ideas, which in turn requires a proper understanding of where to place paragraph breaks. However, these decisions are often performed…

Past research has yielded ample knowledge regarding the design of analytics-based tools for teachers and has found beneficial effects of several tools on teaching and learning. Yet there is relatively little knowledge regarding the design of tools that support teachers when a class of students uses AI-based tutoring software for self-paced…

Teacher quality, along with the school context, classroom practice, and student mathematics achievement, are the key components in Clarke and Hollingsworth's (2002) model that depicts teachers' professional growth as an ongoing, dynamic, and interactive enterprise. Comfort and preparedness are dispositions that, along with teacher knowledge, are…

Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…

Understanding how young learners come to construct viable mathematical arguments about general claims is a critical objective in early algebra research. The study reported here characterizes empirically developed progressions in Grades K-1 students' thinking about arguments concerning sums of evens and odds. Data are drawn from classroom lessons…

In this paper, we describe the design for PurpleState, an internship simulation that applies the epistemic game model for informed civic learning. PurpleState places students in the role of interns at a political media firm and asks them to design a media campaign on a state level policy issue. Unlike the use of these models in STEM education,…