The growing significance of artificial intelligence and numerous AI supported educational applications have attracted the attention of educators worldwide. Consequently, AI and software developers have begun creating numerous AI supported applications for teaching and learning. The paper explains the importance of the impacts of the Microsoft…

Pragmatically, machine learning techniques can improve educators' capacity to monitor students' learning progress when applied to quality data. For developing countries, the major obstacle has been the unavailability of quality data that fits the purpose. This is partly because the in-use information systems are either not properly managed or not…

Although student advising is known to improve student success, its application is often inadequate in institutions that are resource constrained. Given recent advances in large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT), automated approaches such as the AutoScholar Advisor system affords viable alternatives to…

A major problem an instructor experiences is the systematic monitoring of students' academic progress in a course. The moment the students, with unsatisfactory academic progress, are identified the instructor can take measures to offer additional support to the struggling students. The fact is that the modern-day educational institutes tend to…

In this study, the authors have developed a web-based programming exercise system currently implemented in classrooms. This system not only provides students with a web-based programming environment but also tracks the time spent on exercises, logging operations such as program editing, building, execution, and testing. Additionally, it records…

Predicting students' performance to identify which students are at risk of receiving a D/Fail/Withdraw (DFW) grade and ensuring their timely graduation is not just desirable but also necessary in most educational entities. In the US, not only is the Science, Technology, Engineering, and Mathematics (STEM) major becoming less popular among…

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 both research and practice in K-12 education. The models produced from this type of predictive modeling research are increasingly used by high schools in Early Warning…

As distance learning becomes increasingly important and artificial intelligence tools continue to advance, automated systems for individual learning have attracted significant attention. However, the scarcity of open-source online tools that are capable of providing personalized feedback has restricted the widespread implementation of…

Progress monitoring is used to assess a student's performance during the early stages of literacy development. Computerized progress monitoring systems are capable of scoring some progress monitoring measures automatically. However, other measures, such as those involving writing or sign language, are typically scored manually, which is…

Oral reading fluency probes are essential for reading assessment, intervention, and progress monitoring. Due to the limited options for choosing oral reading fluency probes, it is important to utilize all available resources such as generative artificial intelligence (AI) like ChatGPT to create oral reading fluency probes. The purpose of this…

Classroom management has many challenges, but when the class is held in a computer lab, even more challenges surface. The obstruction of the line-of-sight between the instructor and the students makes it difficult to monitor student behavior, attention, facial expressions or other non-verbal cues. Also, while the computer is a powerful machine,…

In response to the high school dropout crisis, which comes with great economic and social costs, early warning systems (EWSs) have been developed to systematically predict and improve student outcomes. The purpose of this study is to evaluate different statistical and machine learning methods to predict high school student performance and improve…

Artificial intelligence (AI) technology is becoming the basis for business. Most businesses use it to improve the customer experience. The education community is just beginning to find ways to successfully implement AI for staff and students. Artificial Intelligence should be leveraged to create a better student experience. For example, Elon…

For the forty-second time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Las Vegas, Nevada. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains papers dealing…

The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…