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Shengyu Jiang; Jiaying Xiao; Chun Wang – Grantee Submission, 2022
An online learning system has the capacity to offer customized content that caters to individual learner's need and has seen growing interest from industry and academia alike in recent years. Different from traditional computerized adaptive testing setting which has a well-calibrated item bank with new items periodically added, online learning…
Descriptors: Item Response Theory, Item Banks, Bayesian Statistics, Learning Management Systems
Erik-Jan van Kesteren; Daniel L. Oberski – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Structural equation modeling (SEM) is being applied to ever more complex data types and questions, often requiring extensions such as regularization or novel fitting functions. To extend SEM, researchers currently need to completely reformulate SEM and its optimization algorithm -- a challenging and time-consuming task. In this paper, we introduce…
Descriptors: Structural Equation Models, Computation, Graphs, Algorithms
Vassoyan, Jean; Vie, Jill-Jênn – International Educational Data Mining Society, 2023
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…
Descriptors: Reinforcement, Networks, Simulation, Educational Technology
Tupouniua, John Griffith – Journal of Pedagogical Research, 2023
A critical part of supporting the development of students' algorithmic thinking is understanding the challenges that emerge when students engage with algorithmatizing tasks--tasks that require the creation of an algorithm. Knowledge of these challenges can serve as a basis upon which educators can build effective strategies for enhancing students'…
Descriptors: Algorithms, Thinking Skills, Mathematics Skills, Task Analysis
Cheung, Sum Kwing; Zhang, Juan; Wu, Chenggang – Educational Psychology, 2023
This study explored whether executive functioning skills and maths test anxiety were associated with children's untimed and timed algorithmic computational performance and their discrepancy. It also investigated whether such relations were moderated by children's basic maths fact fluency. One hundred and thirty third-graders were rated by teachers…
Descriptors: Performance, Algorithms, Computation, Timed Tests
Mayer, Christian W. F.; Ludwig, Sabrina; Brandt, Steffen – Journal of Research on Technology in Education, 2023
This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…
Descriptors: Prompting, Classification, Artificial Intelligence, Natural Language Processing
Sahlgren, Otto – Learning, Media and Technology, 2023
As awareness of bias in educational machine learning applications increases, accountability for technologies and their impact on educational equality is becoming an increasingly important constituent of ethical conduct and accountability in education. This article critically examines the relationship between so-called algorithmic fairness and…
Descriptors: Algorithms, Accountability, Data Collection, Educational Policy
Murad, Dina Fitria; Murad, Silvia Ayunda; Irsan, Muhamad – Journal of Educators Online, 2023
This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…
Descriptors: Online Courses, Grades (Scholastic), Prediction, Context Effect
Soukaina Gouraguine; Mohammed Qbadou; Mohamed Rafik; Mustapha Riad; Khalifa Mansouri – Journal of Information Technology Education: Research, 2023
Aim/Purpose: Our study is focused on prototyping, development, testing, and deployment of a new knowledge primitive for the humanoid robot assistant NAO, in order to enhance student visual learning by establishing a human-robot interaction. Background: This new primitive, utilizing a convolutional neural network (CNN), enables real-time…
Descriptors: Robotics, Technology Uses in Education, Algorithms, Children
Dan Delmonaco – ProQuest LLC, 2023
In the United States, the internet is a vital resource for LGBTQ+ youth to meet their sexual and reproductive health information needs, especially those who cannot receive necessary information from family, healthcare providers, and classrooms. In this dissertation, I present three papers that connect content moderation policies and their impacts…
Descriptors: Sex Education, LGBTQ People, Information Seeking, Online Searching
Kaiyi Long – International Journal of Web-Based Learning and Teaching Technologies, 2023
The test results show that the fast Fourier process with multiple time superposition and a dimension length of 40 is most beneficial to the accuracy of the model. The loss curve value of the convolutional recurrent network model (CRN) is much lower than the other three models. The music tone recognition model learns better. The accuracy rate value…
Descriptors: Music Education, Music Activities, Singing, Audio Equipment
D. Steger; S. Weiss; O. Wilhelm – Creativity Research Journal, 2023
Creativity can be measured with a variety of methods including self-reports, others reports, and ability tests. While typical self-reports are best understood as weak proxies of creativity, biographical reports that assess previous creative activities seem more promising. Drawbacks of such measures -- including skewed item distributions, a lack of…
Descriptors: Creativity, Creativity Tests, Test Construction, Algorithms
Andrew M. Olney – Grantee Submission, 2023
Multiple choice questions are traditionally expensive to produce. Recent advances in large language models (LLMs) have led to fine-tuned LLMs that generate questions competitive with human-authored questions. However, the relative capabilities of ChatGPT-family models have not yet been established for this task. We present a carefully-controlled…
Descriptors: Test Construction, Multiple Choice Tests, Test Items, Algorithms
Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines