Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…

With the digital revolution of artificial intelligence (AI) in language education, the way how people write and create stories has been transformed in recent years. Although recent studies have started to examine the roles of AI in literacy, there is a lack of systematic review to inform how it has been applied and what has been achieved in…

Because implementing and orchestrating collaborative problem-based learning (PBL) in K-12 classrooms requires teachers to manage multiple activities and access various teaching resources at the same time, this is an exceptionally complex task for designers to develop tools for orchestration support as well as for teachers to coordinate. The aim of…

Purpose: The purpose of this study is to identify global trends in disruptive technological change and map the social and policy implications, particularly as they relate to the educational ecosystem and main stakeholders across all levels of education. Design/methodology/approach: The authors conducted a two-stage meta-analysis of 1,155…

This research presents a proposed approach that could be applied in modeling students' study strategies and performance in higher education. The research used key learning attributes, including intrinsic motivation, extrinsic motivation, autonomy, relatedness, competence, and self-esteem in the modeling. Five machine learning models were…

Effective teachers continue to be in demand in the workforce. Schools and universities need professional teachers who show passion for their jobs and high work performance. This research will investigate the association among teachers' age, gender, tenure, emotional intelligence (EI) scores, perception of emotional intelligence application in…

As artificial intelligence (AI) plays a more prominent role in our everyday lives, it becomes increasingly important to introduce basic AI concepts to K-12 students. Currently, most K-12 AI research focuses on introducing fundamental AI concepts using pure virtual platforms like webpages or software. However, robots, as helpful and popular tools…

Identifying preferred stimuli is an initial step in many evidence-based educational programs for young children. Preference assessments, such as the Multiple Stimulus Without Replacement (MSWO), provide an empirically validated way of identifying and ranking these stimuli. Traditional methods of training professionals to implement MSWO often…

Computational thinking (CT) is a fundamental ability for learners in today's society. Although CT assessments and interventions have been studied widely, little is known about CT predictions. This study predicted students' CT achievement in the ICILS 2018 using five machine learning models. These models were trained on the data from five European…

College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…

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…

Histories of creativity have often included discussions of its origins and examined pivotal moments in their societal contexts (Nelson 2010; Simonton 2001; Still & d'Inverno 2016; Wasserman 2012). Some have considered creativity's compromised status among academics and in schools that resulted from divergent notions of what it means to create…

As education, technology, and society become ever more intertwined with emerging forms of artificial intelligence (AI), the need to comprehend the potential consequences of its integration has reached a critical juncture. This study seeks to address this need by exploring emerging, formative tensions in the integration of AI in educational…

This study examines the impact of AI chatbots as a communication medium on student engagement and support in higher education. The qualitative method and Interpretative Phenomenological Analysis (IPA) were employed as the research approach, utilizing in-depth semi-structured interviews. Purposive sampling was used to select 11 participants from…

Purpose: As evidenced by perceptual learning studies involving adult listeners and speakers with dysarthria, adaptation to dysarthric speech is driven by signal predictability (speaker property) and a flexible speech perception system (listener property). Here, we extend adaptation investigations to adolescent populations and examine whether adult…