Methods based on machine learning have become increasingly popular in many areas as they allow models to be fitted in a highly-data driven fashion and often show comparable or even increased performance in comparison to classical methods. However, in the area of educational sciences, the application of machine learning is still quite uncommon.…

School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…

Examinations are one way of evaluating students. To ensure the production of valid exams, frameworks such as Bloom's taxonomy are utilised when preparing questions. Bloom's taxonomy is a well-known framework that categorises educational objectives into six hierarchical levels of cognitive complexity. However, manually categorising exam questions…

This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following…

Background/purpose: This study aims to reveal in detail the extent to which the variables in The Primary and Secondary Education Institutions Scholarship Examination (PSEISE) predict the success of students on the scholarship exam with the help of artificial neural networks (ANN). In addition, in light of the findings obtained as a result of the…

How can novel AI techniques be made and put to use in the library? Combining methods from data and library science, this article focuses on Natural Language Processing technologies, especially in national libraries. It explains how the National Library of Sweden's collections enabled the development of a new BERT language model for Swedish. It…

The default risk, one of the main risk factors for bonds, should be measured and reflected in the bond yield. Particularly, in the case of financial companies that treat bonds as a major product, failure to properly identify and filter customers' workout status adversely affects returns. This study proposes a two-stage classification algorithm for…

We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…

The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In this paper, we explore the magnitude of the country and language divide in the leading open-source and…

In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…

In this study, classifications were made from the data obtained from the Health-Related Physical Fitness Report cards and BMIs of students through data mining methods, artificial neural networks, and decision trees models. Then the classification performances of both models were compared. The body weight and height measurements of the students in…

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students' performance and ascertain successful teaching objectives. In…

Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…

The majority of Sub-Saharan African countries are facing a very negative teacher-learner ratio: one teacher for over 120 learners. In order to support the learner training, we propose optimizing search engines for learning contexts, to enable learners to take optimal advantage of the vast reservoir of Open Educational Resources (OER) available on…

This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a mathematics learning platform used by middle and high school students in several African countries. Using this dataset, we conducted two experiments to evaluate the use of large language models (LLM) for grading particularly challenging…