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'…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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.,…

Online assessment is one of the important factors in online learning today. An online summary assessment is an example of an open-ended question, offering the advantage of probing students' understanding of the learning materials. However, grading students' summary writings is challenging due to the time-consuming process of evaluating students'…

This article aims to study and implement a deep learning algorithm-based information literacy assistance system for college students to solve the problems of insufficient personalization and untimely feedback in the existing information literacy education methods, so as to improve the information literacy level of college students. This article…

Our preliminary experiment examined a potential pain point with ASSIST, California's database of articulation agreements. That pain point is cross-referencing multiple articulation agreements to manually develop an "optimal" academic plan. Optimal is defined as the minimal set of community college courses that satisfy all transfer…

In this article, I introduce a collaborative annotation activity that supports students in critically examining AI-generated writing in relation to criteria including specificity and complexity. I engage students in collaboratively annotating the AI-generated essays, guiding students to identify instances in which the essays could be more…