In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

Contribution: The proposed work carries out the training and testing of the available data through an artificial neural network and develops a model to allocate the subject for maximum outcome. The system also provides percentagewise correlation among all the possible subjects of best fit to allocate among the faculty members. Background: Data…

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…

The study of robotics has become a popular course among many educational programs, especially as a technical elective. A significant part of this course involves having the students learn how to program the movement of a robotic arm by controlling the velocity of its individual joint motors, a topic referred to as joint programming. They must…

The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data…

Many U.S. cities with school choice programs have adopted unified enrollment systems to manage their application and placement processes centrally. Typically, these systems use placement algorithms to assign students to schools. These algorithms make placements based on families' rank-ordered requests, seat availability in schools, and various…

Many cities with school choice programs employ algorithms to make school placements. These algorithms use student priorities to determine which applicants get seats in oversubscribed schools. This study explores whether the New Orleans placement algorithm tends to favor students of certain races or socioeconomic classes. Specifically, we examine…

This commentary was written by ChatGPT, an artificial intelligence language model developed by OpenAI. It was conceived by the first author as a test for how the advent of predictive language modeling will create opportunities and challenges for researchers and teachers in mathematics education. The paper consists of a commentary that was written…

Objective/Research Question: Community college graduation rates are typically quite low, and developmental mathematics enrollment and coursetaking patterns may constrain academic outcomes. To identify ways in which community college graduation rates may be improved, decision trees were utilized to examine the STEM coursetaking patterns of N =…

This study explored the effects of practice schedule on the processing of new second language (L2) vocabulary and resulting knowledge. Participants were 107 low-achieving adolescents attending a vocational high school in Korea. They were randomly assigned to one of three practice groups and completed a L2 English-L1 Korean paired-associates…

The emergence of generative artificial intelligence (GenAI) has reignited long-standing debates about technology's role in education. While GenAI potentially offers personalized learning, adaptive tutoring, and automated support, it also raises concerns about algorithmic bias, de-skilling educators, and diminishing human connection. This…

Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…

Purpose: This paper investigates the digital information practices of Afro-Latino youth, focusing on their engagement with mental health content on TikTok. It aims to understand how racial and ethnic identity dimensions shape their information behaviors in digital spaces. Design/methodology/approach: Employing qualitative methods, the study…

Purpose: This study aims to explore children's cognitions about data flows online and their understandings of algorithms, often referred to as algorithmic literacy or algorithmic folk theories, in their everyday uses of social media and YouTube. The authors focused on children ages 8 to 11, as these are the ages when most youth acquire their own…

Purpose: The purpose of this conceptual paper is to describe how the affinity space concept has been used to frame learning via social media, and call for and discuss a refresh of the affinity space concept to accommodate changes in social media platforms and algorithms. Design/methodology/approach: Guided by a sociocultural perspective, this…