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Rachel Horst; Derek Gladwin – Journal of Curriculum and Pedagogy, 2024
It is no surprise that concern for the future is on the rise. Several catastrophes obscure our future(s) imaginary, such as climate change, a global pandemic, racial inequality, and political polarization. Students are feeling a disconnect between what they learn in classrooms and the futures that populate their media platforms. Futures literacies…
Descriptors: Futures (of Society), Multiple Literacies, Interdisciplinary Approach, Inquiry
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Erik Eliassen; Ragnhild Eek Brandlistuen; Mari Vaage Wang – European Early Childhood Education Research Journal, 2024
Many studies have linked quality in early childhood education and care [ECEC] to school performance, but the mechanisms of how ECEC process quality affects children in ways that lead to improved school performance is unclear. In this study on 7431 children in Norway, we test the hypothesis that the relation between process quality in ECEC and…
Descriptors: Early Childhood Education, Academic Achievement, Foreign Countries, Interpersonal Competence
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Christine Michel; Daniel Matthes; Stefanie Hoehl – Child Development, 2024
This study investigates infants' neural and behavioral responses to maternal ostensive signals during naturalistic mother-infant interactions and their effects on object encoding. Mothers familiarized their 9- to 10-month-olds (N = 35, 17 females, mainly White, data collection: 2018-2019) with objects with or without mutual gaze, infant-directed…
Descriptors: Infants, Mothers, Parent Child Relationship, Infant Behavior
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Jia Zhu; Xiaodong Ma; Changqin Huang – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT) for evaluating students' knowledge is an essential task in personalized education. More and more researchers have devoted themselves to solving KT tasks, e.g., deep knowledge tracing (DKT), which can capture more sophisticated representations of student knowledge. Nonetheless, these techniques ignore the reconstruction of…
Descriptors: Teaching Methods, Knowledge Level, Algorithms, Attribution Theory
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Ping Hu; Zhaofeng Li; Pei Zhang; Jimei Gao; Liwei Zhang – International Journal of Web-Based Learning and Teaching Technologies, 2024
Given the extensive use of online learning in educational settings, Knowledge Tracing (KT) is becoming increasingly essential. KT primarily aims to predict a student's future knowledge acquisition based on their past learning activities, thus enhancing the efficiency of student learning. However, the effective acquisition of dynamic and evolving…
Descriptors: Knowledge Level, Graphs, Trend Analysis, Time Factors (Learning)
Alexander Joseph Tylka – ProQuest LLC, 2024
Higher education practitioners and researchers in the STEM field continue seeking ways to effectively identify and understand student challenges as part of an effort to support student success, retention, and persistence. These efforts have led researchers to explore non-cognitive personality factors such as perfectionism as a way of understanding…
Descriptors: Personality Traits, Academic Achievement, College Students, STEM Education
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Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
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Jutta Kray; Linda Sommerfeld; Arielle Borovsky; Katja Häuser – Child Development Perspectives, 2024
Prediction error plays a pivotal role in theories of learning, including theories of language acquisition and use. Researchers have investigated whether and under which conditions children, like adults, use prediction to facilitate language comprehension at different levels of linguistic representation. However, many aspects of the reciprocal…
Descriptors: Prediction, Child Development, Language Acquisition, Error Analysis (Language)
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Sanaz Nazari; Walter L. Leite; A. Corinne Huggins-Manley – Educational and Psychological Measurement, 2024
Social desirability bias (SDB) is a common threat to the validity of conclusions from responses to a scale or survey. There is a wide range of person-fit statistics in the literature that can be employed to detect SDB. In addition, machine learning classifiers, such as logistic regression and random forest, have the potential to distinguish…
Descriptors: Social Desirability, Bias, Artificial Intelligence, Identification
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Senay Kocakoyun Aydogan; Turgut Pura; Fatih Bingül – Malaysian Online Journal of Educational Technology, 2024
In every culture and era, education is considered the most fundamental reality and rule that societies prioritize and deem essential. Throughout the process spanning thousands of years, from the emergence of writing to the present day, education has undergone various forms and formats of change. Education has been a continuous guide for shaping,…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
Abdullah Mana Alfarwan – ProQuest LLC, 2024
This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…
Descriptors: Regression (Statistics), Decision Making, Prediction, Sample Size
Linda Melton Huntley – ProQuest LLC, 2024
The authenticity of a leader impacts the organizational environment and contributes to the success and stability of the individual, the team, and the organization. Although emotional intelligence has been used as a predictor of authentic leadership, the assessment of the leader has been largely self-reported. The purpose of this quantitative…
Descriptors: Emotional Intelligence, Leadership Styles, Prediction, Correlation
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Lisa J. Schlueter; Andrew B. McGee; Tasha Link; Lisa S. Badanes; Julia Dmitrieva; Sarah E. Watamura – Psychology in the Schools, 2024
Extant literature has demonstrated that children's diurnal stress physiology often looks different on childcare versus home days. Specifically, children experience a rise in cortisol, rather than a decline, over the day while in full-time care. Additionally, temperamental fit within classroom environment may influence both child and teacher…
Descriptors: Physiology, Child Care, Classroom Environment, Anxiety
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Seunghee Ha – Journal of Speech, Language, and Hearing Research, 2024
Objectives: The study aimed to investigate the predictive potential of language environment and vocal development status measures obtained through integrated analysis of Language ENvironment Analysis (LENA) recordings during the prelinguistic stage for subsequent speech and language development in Korean-acquiring children. Specifically, this…
Descriptors: Language Acquisition, Korean, Vocabulary Development, Phonological Awareness
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Julia M. Rodriguez Buritica; Ben Eppinger; Hauke R. Heekeren; Eveline A. Crone; Anna C. K. van Duijvenvoorde – npj Science of Learning, 2024
Observational learning is essential for the acquisition of new behavior in educational practices and daily life and serves as an important mechanism for human cognitive and social-emotional development. However, we know little about its underlying neurocomputational mechanisms from a developmental perspective. In this study we used model-based…
Descriptors: Observational Learning, Individual Differences, Children, Young Adults
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