One of the main current challenges in Educational Data Mining and Learning Analytics is the portability or transferability of predictive models obtained for a particular course so that they can be applied to other different courses. To handle this challenge, one of the foremost problems is the models' excessive dependence on the low-level…

This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…

Both educational data mining and learning analytics aim to understand learners and optimise learning processes of educational settings like Moodle, a learning management system (LMS). Analytics in an LMS covers many different aspects: finding students at risk of abandoning a course or identifying students with difficulties before the assessments.…

Awareness of students' learning status, and maintaining students' focus and attention during class are important issues in classroom management. Several observation instruments have been designed for human observers to document students' engagement in class, but the processes are time-consuming and laborious. Recently, with the development of…

Early warning systems (EWSs) have been successfully used in online classes, especially in massive open online courses, where it is nearly impossible for students to interact face-to-face with their teachers. Although teachers in higher education institutions typically have smaller class sizes, they also face the challenge of being unable to have…

In higher education, predictive analytics can provide actionable insights to diverse stakeholders such as administrators, instructors, and students. Separate feature sets are typically used for different prediction tasks, e.g., student activity logs for predicting in-course performance and registrar data for predicting long-term college success.…

The present study hypothesized that requiring use of an integrated learning system (ILS) would yield a learning benefit in a classroom situation. Two sections of an introductory psychology course taught by the same instructor and using the same text and exams differed with respect to whether online quizzing and concept mastery exercises in an ILS…

Students in the online learning who have other responsibilities of life such as work and family face attrition. Constructing a model of engagement with smallest granule of time has not been implemented widely, but implementing it is important as it allows to uncover more subtle patterns. We built a student engagement prediction model using 9…

Use of learning management systems is prevalent across the continuum of education formats (online, blended, face-to-face). Specific asynchronous tools such as the discussion board are effective for student-instructor and student-student communication [Calderon, Ginsberg, and Ciabocchi (2012); Jorczak, R. L., & Dupuis, D. N. (2014). Differences…

Pronunciation learners can benefit from peer feedback in a Computermediated Communication (CMC) environment that allows them to notice segmentals and suprasegmentals. This paper explores the intelligibility judgments of same-L1 peers using P-Check (Version2, https://ver2.jp), a Learning Management System (LMS) plug-in that aggregates peer feedback…

In this paper, we present a system for visualizing learning logs of a course in progress together with predictions of learning activities of the following week and the final grades of students by state transition graphs. Data are collected from 236 students attending the course in progress and from 209 students attending the past course for…

Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction…

Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…

As an assessment method based on a constructivist approach, peer assessment has become popular in recent years. However, in peer assessment, a problem remains that reliability depends on the rater characteristics. For this reason, some item response models that incorporate rater parameters have been proposed. Those models are expected to improve…

In recent years, statistics have displayed a consistent increase in the enrollment in college programs of students with autism spectrum disorder (ASD). The research has explained that ASD college students currently face academic and social barriers as they transition to the college setting. There is reason to believe that the use of online…