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Stephanie Seiler – Canadian Journal for the Scholarship of Teaching and Learning, 2024
Calls to increase active learning, an approach that positions students in the center of their learning experience, have increased considerably in recent decades. In response, there has been substantial work to expand our understanding and implementation of active learning approaches in many educational spaces. However, much of this instructional…
Descriptors: Higher Education, Active Learning, Curriculum Design, Curriculum Based Assessment
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Dannie Wammes; Liesbeth Kester; Bert Slof – International Journal of Technology and Design Education, 2025
Hands-on activities promote interest in engineering, but their use in primary education is under pressure due to doubts about their effect on learning. Based on the Challenge Point Framework, we hypothesized that an adaptive approach in which a pupil starts with tasks at its level of prior knowledge would raise the learning results of hands-on…
Descriptors: Difficulty Level, Prior Learning, Elementary School Students, Individualized Instruction
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Mao, Shun; Zhan, Jieyu; Wang, Yizhao; Jiang, Yuncheng – IEEE Transactions on Learning Technologies, 2023
For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Prediction, Prior Learning
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Frederike Kossack; Eike Uttich; Beate Bender – International Association for Development of the Information Society, 2023
In Engineering Design education, huge numbers of students are a challenge in university teaching, especially since the students have an initially heterogeneous level of technical knowledge, which influences their acquisition of competences. In frontal classroom lectures, individual deficits can hardly be addressed and in self-study phases,…
Descriptors: Engineering Education, Heterogeneous Grouping, College Students, Individualized Instruction
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Duy M. Pham; Kirk P. Vanacore; Adam C. Sales; Johann A. Gagnon-Bartsch – International Educational Data Mining Society, 2024
Effective personalization of education requires knowing how each student will perform under certain conditions, given their specific characteristics. Thus, the demand for interpretable and precise estimation of heterogeneous treatment effects is ever-present. This paper outlines a new approach to this problem based on the Leave-One-Out Potential…
Descriptors: Middle School Students, Middle School Teachers, Middle School Mathematics, Algebra
Daniel Katz; Anne Corinne Huggins-Manley; Walter Leite – Grantee Submission, 2022
According to the Standards for Educational and Psychological Testing (2014), one aspect of test fairness concerns examinees having comparable opportunities to learn prior to taking tests. Meanwhile, many researchers are developing platforms enhanced by artificial intelligence (AI) that can personalize curriculum to individual student needs. This…
Descriptors: High Stakes Tests, Test Bias, Testing Problems, Prior Learning
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Daniel Katz; Anne Corinne Huggins-Manley; Walter Leite – Applied Measurement in Education, 2022
According to the "Standards for Educational and Psychological Testing" (2014), one aspect of test fairness concerns examinees having comparable opportunities to learn prior to taking tests. Meanwhile, many researchers are developing platforms enhanced by artificial intelligence (AI) that can personalize curriculum to individual student…
Descriptors: High Stakes Tests, Test Bias, Testing Problems, Prior Learning
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Sherry Y. Chen; Chia-Yi Tseng; Chao-Yang Cheng – Interactive Learning Environments, 2023
This study proposed a three-tier test to help students learn English grammar. To reduce students' anxiety, game-based learning was incorporated into the three-tier test, where personalization was also implemented to accommodate students' different needs. More specifically, we developed a Personalized Entertaining Three-Tier Test (PET3), which…
Descriptors: English (Second Language), Language Tests, Grammar, Game Based Learning
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Duy M. Pham; Kirk P. Vanacore; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Effective personalization of education requires knowing how each student will perform under certain conditions, given their specific characteristics. Thus, the demand for interpretable and precise estimation of heterogeneous treatment effects is ever-present. This paper outlines a new approach to this problem based on the Leave-One-Out Potential…
Descriptors: Middle School Students, Middle School Teachers, Middle School Mathematics, Algebra
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Akos, Patrick; Wasik, Suzan Z.; McDonald, Angela; Soler, Michelle; Lys, Diana – Counselor Education and Supervision, 2019
There is increased responsibility for programs to demonstrate evidence of student learning and skill. Application of competency-based education is delineated, including prior learning assessment and personalized learning. Implications such as awarding credit for experience in admissions or variable clinical training timelines and requirements are…
Descriptors: Competency Based Education, Counselor Training, Prior Learning, Individualized Instruction
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Zhang, Lishan; Pan, Mengqi; Yu, Shengquan; Chen, Ling; Zhang, Jing – Interactive Learning Environments, 2023
This paper introduces a system that supports student-centered online one-to-one tutoring and evaluates the practical value of the system by running an experiment with 64 experienced mathematics teachers and 810 students in Grade 7. The experiment lasted for 50 days. A comprehensive evaluation was performed using students' academic performance…
Descriptors: Mathematics Teachers, Grade 7, Middle School Students, Middle School Teachers
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Melesse, Tadesse; Belay, Sinatayehu – Cogent Education, 2022
This study sought to determine the significant relationship between student attributes (background knowledge, readiness, interests, and learning profiles) and the teachers' use of DI elements (content, process, product, and learning environment differentiation) in primary and middle schools of Enjibara and Chagni town administrations of Awi zone,…
Descriptors: Individualized Instruction, Elementary School Students, Middle School Students, Student Characteristics
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Renata Kochut; Thomas Brady – International Society for Technology, Education, and Science, 2024
This paper examines the Individualized Credit for Prior Learning (CPL) process in business education. It highlights its role in accrediting students' experiential learning and bridging practical experience with academic credit. This research then recommends solutions that include AI tools, advisor training, and centralized resource hubs. Most…
Descriptors: Business Education, Artificial Intelligence, Technology Uses in Education, Credits
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W. Russ Algar; Noureddine Elouazizi; Jaclyn J. Stewart; E. Jane Maxwell; Tanya Tan; Zuxing Zhang; Robin Stoodley; José R. Rodríguez Núñez; Andrea S. Terpstra; Jason G. Wickenden – Journal of Chemical Education, 2022
To develop expertise, novice chemistry students require deliberate practice with immediate and thoughtful feedback. Whereas opportunities for practice are often abundant, opportunities for feedback tend to be much scarcer. To address this challenge, we collaborated with students to develop a flexible and scalable online platform called…
Descriptors: Active Learning, Individualized Instruction, Chemistry, Educational Technology
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Xie, Haoran; Zou, Di; Zhang, Ruofei; Wang, Minhong; Kwan, Reggie – Journal of Computing in Higher Education, 2019
It is widely acknowledged that the acquisition of vocabulary is the foundation of learning English. With the rapid development of information technologies in recent years, e-learning systems have been widely adopted for English as a Second Language (ESL) Learning. However, a limitation of conventional word learning systems is that the prior…
Descriptors: Electronic Learning, Teaching Methods, Individualized Instruction, Vocabulary Development
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