Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…

Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…

As instruction shifts away from traditional approaches, online learning has grown in popularity in K-12 and higher education. Artificial intelligence (AI) and learning analytics methods such as machine learning have been used by educational scholars to support online learners on a large scale. However, the fairness of AI prediction in educational…

High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…

A text recommendation system helps language learners find suitable reading materials. Similar to graded readers, most systems assign difficulty levels or school grades to the documents in their database, and then identify the documents that best match the language proficiency of the learner. This graded approach has two main limitations. First,…

Being efficient learners is important in the modern workforce, but improved performance and cognitive load do not imply that students are efficient learners. This study investigated the effectiveness of a personalized role-playing game in students' learning efficiency (LE) and mental efficiency. Results showed that students in the personalized…

Monitoring one's learning activities is a key component of self-regulated learning (SRL) leading to successful learning and performance outcomes across settings. Achievement emotions also play an important part in SRL and consequently student learning outcomes. However, there is little research on how specific types of monitoring (i.e.…

Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…

The proliferation of massive open online courses (MOOCs) highlights the necessity of developing accurate and diagnostic evaluation methods to assess the courses' quality and effectiveness. Hence, this study proposes a diagnostic MOOC evaluation (DME) method that combines the Analytic Hierarchy Process algorithm and learner review mining to…

Peer assessment has become a primary solution to the challenge of evaluating a large number of students in Massive Open Online Courses (MOOCs). In peer assessment, all students need to evaluate a subset of other students' assignments, and then these peer grades are aggregated to predict a final score for each student. Unfortunately, due to the…

Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…

Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…

Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational…

Presented study seeks to examine the potential applications of the OpenAI language model, GPT-3, within the realm of education. Specifically, the inquiry focuses on the feasibility of utilizing GPT-3 to generate essays based on customized prompts. To this end, the experimentation involved providing GPT-3 with tailored prompts derived from diverse…

Information literacy is an essential twenty-first-century skill for students. Most students face difficulty in discerning online information while searching, evaluating, and utilizing it effectively. Appropriate information evaluating framework, such as RADAR (relevance, authority, date, appearance, and reason for writing), has been recommended to…