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Pablo Maceira-Elvira; Traian Popa; Anne-Christine Schmid; Andéol Cadic-Melchior; Henning Müller; Roger Schaer; Leonardo G. Cohen; Friedhelm C. Hummel – npj Science of Learning, 2024
Healthy aging often entails a decline in cognitive and motor functions, affecting independence and quality of life in older adults. Brain stimulation shows potential to enhance these functions, but studies show variable effects. Previous studies have tried to identify responders and non-responders through correlations between behavioral change and…
Descriptors: Age Differences, Neurosciences, Prediction, Brain
Harsimran Singh; Banipreet Kaur; Arun Sharma; Ajeet Singh – Education and Information Technologies, 2024
Today, the main aim of educational institutes is to provide a high level of education to students, as career selection is one of the most important and quite difficult decisions for learners, so it is essential to examine students' capabilities and interests. Higher education institutions frequently face higher dropout rates, low academic…
Descriptors: College Students, At Risk Students, Academic Achievement, Artificial Intelligence
Yangyang Luo; Xibin Han; Chaoyang Zhang – Asia Pacific Education Review, 2024
Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…
Descriptors: Prediction, Learning Management Systems, Blended Learning, Classification
Jiaqi Jackie Shi – ProQuest LLC, 2024
One of the many impacts of the COVID-19 pandemic has been the increasing prevalence and accessibility of online education. This trend has also introduced challenges for students, instructors, and institutions. This study examines factors affecting online course satisfaction, focusing on individual, instructor, and institutional level…
Descriptors: Prediction, Online Courses, Higher Education, Student Attitudes
Masato Nakamura; Shota Momma; Hiromu Sakai; Colin Phillips – Cognitive Science, 2024
Comprehenders generate expectations about upcoming lexical items in language processing using various types of contextual information. However, a number of studies have shown that argument roles do not impact neural and behavioral prediction measures. Despite these robust findings, some prior studies have suggested that lexical prediction might be…
Descriptors: Diagnostic Tests, Nouns, Language Processing, Verbs
Dong Zhang; Zhenyu Shi; Yafei Cheng – SAGE Open, 2024
The goal of this study was to predict the preservice physical education teachers' (PPETs) occupational socialization (OS) by their pedagogical content knowledge (PCK) and to investigate the relationship between them. The participants were 56 PPETs from a physical education teacher education (PETE) undergraduate program in the northeastern United…
Descriptors: Pedagogical Content Knowledge, Physical Education, Physical Education Teachers, Socialization
Mustafa Kocaarslan; Ahmet Yamaç – Journal of Computing in Higher Education, 2024
This research explores preservice classroom teachers' perceived importance, self-efficacy beliefs, participation frequencies and conceptions related to new literacies. The research is framed using a dual-level theory of new literacies. The participants of the study consisted of 364 preservice teachers studying in the department of primary…
Descriptors: Student Attitudes, Preservice Teachers, Teacher Education Programs, Multiple Literacies
Blake H. Heller – Annenberg Institute for School Reform at Brown University, 2024
In 2016, the GED® introduced college readiness benchmarks designed to identify testers who are academically prepared for credit-bearing college coursework. The benchmarks are promoted as awarding college credits or exempting "college-ready" GED® graduates from remedial coursework. I show descriptive evidence that those identified as…
Descriptors: High School Equivalency Programs, College Readiness, Eligibility, Benchmarking
Sashi Ranjan; V. P. Joshith; K. Kavitha; Shana Chittakath – Knowledge Management & E-Learning, 2024
Integrating artificial intelligence (AI) with knowledge management (KM) practices presents a promising avenue for advancing sustainable learning in higher education. However, empirical research exploring this synergy remains limited, particularly in developing countries. This study aimed to investigate the impact of AI-enhanced KM practices on…
Descriptors: Artificial Intelligence, Technology Uses in Education, Knowledge Management, Sustainability
Or Goren; Liron Cohen; Amir Rubinstein – International Educational Data Mining Society, 2024
The problem of student dropout in higher education has gained significant attention within the Educational Data Mining research community over the years. Since student dropout is a major concern for the education community and policymakers, many research studies aim to evaluate and uncover profiles of students at-risk of dropping out, allowing…
Descriptors: Dropout Characteristics, Prediction, Potential Dropouts, Student Characteristics
Liu, Ziyi – Journal of Education and Learning, 2019
When memorizing mechanical materials such as words or numbers, people have shown the tendency to overestimate their future memory due to their insensitivity to memory loss. The experiments in this paper investigate whether the same bias applies to conceptual learning and, if so, how the magnitude of this bias compares to that of mechanical…
Descriptors: Memorization, Metacognition, Memory, Prediction
Khan, Ijaz; Ahmad, Abdul Rahim; Jabeur, Nafaa; Mahdi, Mohammed Najah – Smart Learning Environments, 2021
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…
Descriptors: Artificial Intelligence, Academic Achievement, Progress Monitoring, Data Collection
Walck-Shannon, Elise M.; Rowell, Shaina F.; Frey, Regina F. – CBE - Life Sciences Education, 2021
Students' study sessions outside class are important learning opportunities in college courses. However, we often depend on students to study effectively without explicit instruction. In this study, we described students' self-reported study habits and related those habits to their performance on exams. Notably, in these analyses, we controlled…
Descriptors: Study Habits, Academic Achievement, College Students, Learning Strategies
Hawkins, Robert D.; Gweon, Hyowon; Goodman, Noah D. – Cognitive Science, 2021
Recent debates over adults' theory of mind use have been fueled by surprising failures of perspective-taking in communication, suggesting that perspective-taking may be relatively effortful. Yet adults routinely engage in effortful processes when needed. How, then, should speakers and listeners allocate their resources to achieve successful…
Descriptors: Adults, Theory of Mind, Perspective Taking, Pragmatics
Yamashita, Takashi; Smith, Thomas J.; Cummins, Phyllis A. – Journal of Educational and Behavioral Statistics, 2021
In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Maples. Concise overview and key unique aspects of large-scale assessment data…
Descriptors: Learning Analytics, Computer Software, Syntax, Adults

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