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Peer reviewed
Direct linkAndrea Zanellati; Daniele Di Mitri; Maurizio Gabbrielli; Olivia Levrini – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…
Descriptors: Artificial Intelligence, Prior Learning, Knowledge Management, Models
Linyan Li; Xiao Bai; Hongshan Xia – Education and Information Technologies, 2024
The higher the level of development of higher education, the larger its contribution to socioeconomic development. In order to predict the trend of higher education development in a country more accurately, a new methodology is employed in this study. A weakening buffer operator-based GM (1, 1) model is constructed using Kazakhstan's gross…
Descriptors: Prediction, Educational Trends, Higher Education, Models
John O'Connor – Irish Educational Studies, 2024
In Ireland as elsewhere, the value of putting evidence and scientific advice at the centre of public policy-making, has rarely been more evident. The prominence of the science-policy interface has renewed interest in the prospects for evidence based policy (EBP) in education. Notwithstanding the political rhetoric around EBP in education, little…
Descriptors: Evidence Based Practice, Educational Policy, Foreign Countries, Correlation
Wes Bonifay; Sonja D. Winter; Hanamori F. Skoblow; Ashley L. Watts – Grantee Submission, 2024
Replication provides a confrontation of psychological theory, not only in experimental research, but also in model-based research. Goodness-of-fit (GOF) of the original model to the replication data is routinely provided as meaningful evidence of replication. We demonstrate, however, that GOF obscures important differences between the original and…
Descriptors: Goodness of Fit, Evidence, Replication (Evaluation), Bayesian Statistics
Ayesha Farheen; Nia Martin; Scott E. Lewis – Chemistry Education Research and Practice, 2024
Education in organic chemistry is highly reliant on molecular representations. Students abstract information from representations to make sense of submicroscopic interactions. This study investigates relationships between differing representations: bond-line structures, ball-and-stick, or electrostatic potential maps (EPMs), and predicting partial…
Descriptors: Science Instruction, Organic Chemistry, Scientific Concepts, Concept Formation
Hanqiang Liu; Xiao Chen; Feng Zhao – Education and Information Technologies, 2024
Massive open online courses (MOOCs) have become one of the most popular ways of learning in recent years due to their flexibility and convenience. However, high dropout rate has become a prominent problem that hinders the further development of MOOCs. Therefore, the prediction of student dropouts is the key to further enhance the MOOCs platform.…
Descriptors: MOOCs, Video Technology, Behavior Patterns, Prediction
Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
Or Dagan; Carlo Schuengel; Marije L. Verhage; Sheri Madigan; Glenn I. Roisman; Kristin Bernard; Robbie Duschinsky; Marian Bakermans-Kranenburg; Jean-François Bureau; Abraham Sagi-Schwartz; Rina D. Eiden; Maria S. Wong; Geoffrey L. Brown; Isabel Soares; Mirjam Oosterman; R. M. Pasco Fearon; Howard Steele; Carla Martins; Ora Aviezer – Child Development, 2024
An individual participant data meta-analysis was conducted to test pre-registered hypotheses about how the configuration of attachment relationships to mothers and fathers predicts children's language competence. Data from seven studies (published between 1985 and 2014) including 719 children (M[subscript age]: 19.84 months; 51% female; 87% White)…
Descriptors: Parent Child Relationship, Attachment Behavior, Fathers, Mothers
Ikumi Futamura; Yoshihiro Shima – European Journal of Developmental Psychology, 2024
This study examined young children's behaviour predictions in direct reciprocal prosocial situations. Participants aged 4-6 years (N = 60) listened to four stories that addressed the actor's previous behaviour (prosocial/non-prosocial) combined with the partner's behaviour (prosocial/non-prosocial). Then, they made predictions regarding the…
Descriptors: Young Children, Behavior, Prediction, Prosocial Behavior
Download full textYikai Lu; Lingbo Tong; Ying Cheng – Journal of Educational Data Mining, 2024
Knowledge tracing aims to model and predict students' knowledge states during learning activities. Traditional methods like Bayesian Knowledge Tracing (BKT) and logistic regression have limitations in granularity and performance, while deep knowledge tracing (DKT) models often suffer from lacking transparency. This paper proposes a…
Descriptors: Models, Intelligent Tutoring Systems, Prediction, Knowledge Level
Valentina Gliozzi – Cognitive Science, 2024
We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying…
Descriptors: Infants, Computation, Models, Cognitive Development
Babu Noushad; Pascal W. M. Van Gerven; Anique B. H. de Bruin – Advances in Health Sciences Education, 2024
Studying texts constitutes a significant part of student learning in health professions education. Key to learning from text is the ability to effectively monitor one's own cognitive performance and take appropriate regulatory steps for improvement. Inferential cues generated during a learning experience typically guide this monitoring process. It…
Descriptors: Metacognition, Prediction, Cues, Visual Aids
Mark Reddy – ProQuest LLC, 2024
This study addressed a critical gap in the literature by investigating the relationship between organizational culture and mission drift within Christian higher education. While mission drift has been widely discussed in popular press, limited academic research has explored the factors influencing it, particularly organizational culture. Utilizing…
Descriptors: Organizational Culture, Religious Colleges, Christianity, Institutional Mission
Saeed Kabiri; Christopher M. Donner; Seyyedeh Masoomeh Shadmanfaat; Mohammad Mahdi Rahmati – International Journal of Bullying Prevention, 2024
Bullying, particularly among teenagers and young adults, is one of the most important issues facing school communities. At its very heart, this issue speaks to a troubling form of deviant behavior. When students engage in bullying behaviors, the effects are felt far beyond that of the direct victim. As such, it is important to investigate the…
Descriptors: High School Students, Student Attitudes, Bullying, Foreign Countries
Perez, Omar D.; Vogel, Edgar H.; Naraslwodeyar, Sanjay; Soto, Fabian A. – Learning & Memory, 2022
Theories of learning distinguish between elemental and configural stimulus processing depending on whether stimuli are processed independently or as whole configurations. Evidence for elemental processing comes from findings of summation in animals where a compound of two dissimilar stimuli is deemed to be more predictive than each stimulus alone,…
Descriptors: Cues, Associative Learning, Stimuli, Prediction
