In an era of rapid technological growth in education, both teachers and students alike must adapt to up-to-date learning and teaching paradigms. Liveworksheets is advantageous in offering students a compilation of interactive sheets that provide instant online feedback. Nevertheless, whether utilizing Liveworksheets in self-study is efficient has…

The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, especially in mathematics, is a well-established and proven approach in learning analytics. In this work, we report on our analysis examining the generalizability of BKT models across academic years attributed to "detector rot." We compare the…

Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against some students and possible harmful long-term…

The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…

Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…

This exploratory case study investigated interactions among internal and external factors and an elementary mathematics teacher's classroom practices and learning outcomes during a longitudinal professional development program. Data from the critical case of a teacher engaged in professional change supported an examination of the interaction of…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

Due to the complexity of latent transition analysis (LTA) model structure and qualitative decision making in LTA, power analysis has less been reported and studied. Baldwin (2015) and Gudicha, et al., (2016) recently reported results about power analysis in LTA, which included useful information. On the other hand, both studies are limited in the…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

This paper explores school development processes in four schools in challenging circumstances. These schools were selected from a sample of schools in a longitudinal mixed-method study over a five-year period of around 100 schools using a typology of different models of change over time. The paper presents first selected findings from the overall…

The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Student procrastination, as the voluntary delay of intended work despite expecting to be worse off for the delay, is an important factor with potentially negative consequences in student well-being and learning. In online educational settings such as Massive Open Online Courses (MOOCs), the effect of procrastination is considered to be even more…

Despite the benefits of multimodal technology in the language classroom and common practice to introduce digital tools in language teaching, research has shown that many language teachers do not feel confident to engage with and create online multimodal learning resources and environments. This exploratory study examines data from five experienced…