This research focuses on better understanding the nature of pre-service teachers' four-frame leadership orientations. As it is known, the phenomenon of leadership still continues to be a research topic in the field of educational administration. But, these studies carried out on teachers and school administrators. As future teachers and school…

The need to identify student cognitive engagement in online-learning settings has increased with our use of online learning approaches because engagement plays an important role in ensuring student success in these environments. Engaged students are more likely to complete online courses successfully, but this setting makes it more difficult for…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

Over the past decade, low graduation and retention rates have plagued higher education institutions. To help students graduate on time and achieve optimal learning outcomes, many institutions provide advising services supported by educational technologies. Accurate grade prediction is an integral part of these services such as degree planning…

This paper will demonstrate how we used state-level longitudinal data to model reading growth trajectories. Using data from large scale assessments that were vertically linked across grades in Hawaii, we utilized a multilevel regression framework to develop growth models to study students' reading performance trajectories during their elementary…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is…

With the increasing adoption of Learning Management Systems (LMS) in colleges and universities, research in exploring the interaction data captured by these systems is promising in developing a better learning environment and improving teaching practice. Most of these research efforts focused on course-level variables to predict student…

Liberal Arts programs are often characterized by their open curriculum. Yet, the abundance of courses available and the highly personalized curriculum are often overwhelming for students who must select courses relevant to their academic interests and suitable to their academic background. This paper presents the course recommender system that we…

In adaptive learning systems, various models are employed to obtain the optimal learning schedule and review for a specific learner. Models of learning are used to estimate the learner's current recall probability by incorporating features or predictors proposed by psychological theory or empirically relevant to learners' performance. Logistic…

Identifying struggling students in real-time provides a virtual learning environment with an opportunity to intervene meaningfully with supports aimed at improving student learning and engagement. In this paper, we present a detailed analysis of quit prediction modeling in students playing a learning game called Physics Playground. From the…

The main purpose of the present study is to predict the relationship between motivation , anxiety, perceived satisfaction and Second Life within asynchronous learning environment specifically in EFL course. Data of the present study were collected from undergraduate students - Sudan University of Technology and Science (SUST) in Sudan. The…

Researchers have highlighted how tracking learners' eye-gaze can reveal their reading behaviors and strategies, and this provides a framework for developing personalized feedback to improve learning and problem solving skills. In this paper, we describe analyses of eye-gaze data collected from 16 middle school students who worked with Betty's…

Determining which students are at risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of research and practice in both K-12 and higher education. The detectors produced from this type of predictive modeling research are increasingly used in early warning…

The greening of the United States teacher workforce puts a premium on districts and schools hiring effective and persistent beginning teachers. Given the limitations of characteristics currently available at the time of hiring (e.g., academic ability measures, preparation type), we built off previous research in economics and psychology to…