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Adrianne L. Jenner; Pamela M. Burrage – International Journal of Mathematical Education in Science and Technology, 2024
Mathematics provides us with tools to capture and explain phenomena in everyday biology, even at the nanoscale. The most regularly applied technique to biology is differential equations. In this article, we seek to present how differential equation models of biological phenomena, particularly the flow through ion channels, can be used to motivate…
Descriptors: Cytology, Mathematical Models, Prediction, Equations (Mathematics)
Mouna Ben Said; Yessine Hadj Kacem; Abdulmohsen Algarni; Atef Masmoudi – Education and Information Technologies, 2024
In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
C. Beaver – PRIMUS, 2024
In this paper, several research topics are presented that provide productive avenues of exploration for students in an undergraduate cryptography course. The topics are intended for a variety of skill levels and interests. In some cases, a student might be inspired to try to solve the proposed problem or write computer code. Other topics might…
Descriptors: Technology, Coding, Undergraduate Students, Student Projects
Thin-Yin Leong; Nang-Laik Ma – INFORMS Transactions on Education, 2024
This paper develops a spreadsheet simulation methodology for teaching simulation and performance analysis of priority queues with multiple servers, without resorting to macros, add-ins, or array formula. The approach is made possible by a "single overtaking" simplifying assumption under which any lower-priority customer may be passed in…
Descriptors: Spreadsheets, Simulation, Teaching Methods, Computer Science Education
Shindler, Michael; Pinpin, Natalia; Markovic, Mia; Reiber, Frederick; Kim, Jee Hoon; Carlos, Giles Pierre Nunez; Dogucu, Mine; Hong, Mark; Luu, Michael; Anderson, Brian; Cote, Aaron; Ferland, Matthew; Jain, Palak; LaBonte, Tyler; Mathur, Leena; Moreno, Ryan; Sakuma, Ryan – Computer Science Education, 2022
Background and Context: We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and…
Descriptors: Misconceptions, Programming, Computer Science Education, Replication (Evaluation)
Ramírez-Sánchez, Camilo Andrés; Romo-Vázquez, Avenilde; Romo-Vázquez, Rebeca; Velásquez-Rojas, Diana – Educational Studies in Mathematics, 2023
The training of non-specialists, particularly engineers, in mathematics requires designing specific didactic proposals that make the importance of mathematics evident. One approach to creating such proposals consists in analyzing the mathematics used in authentic contexts of engineering research and then effectuating a didactic transposition to…
Descriptors: Undergraduate Students, Mathematics Instruction, Engineering, Teaching Methods
Alanah Grant St. James; Luke Hand; Thomas Mills; Liwen Song; Annabel S. J. Brunt; Patrick E. Bergstrom Mann; Andrew F. Worrall; Malcolm I. Stewart; Claire Vallance – Journal of Chemical Education, 2023
Applications of machine learning in chemistry are many and varied, from prediction of structure-property relationships, to modeling of potential energy surfaces for large scale atomistic simulations. We describe a generalized approach for the application of machine learning to the classification of spectra which can be used as the basis for a wide…
Descriptors: Artificial Intelligence, Chemistry, Science Instruction, Classification
Arshia K. Lodhi; Patricia J. Brooks; C. Donnan Gravelle; Jessica E. Brodsky; Maryam Syed; Donna Scimeca – Journal of Media Literacy Education, 2025
Internet users are bombarded with information and need strategies to evaluate its trustworthiness. Expert fact-checkers rely on lateral reading, which involves investigating sources, finding better coverage, and tracing information back to original contexts. This study contrasted college students' preference for and use of lateral reading to…
Descriptors: Encyclopedias, Electronic Publishing, Algorithms, Reading Comprehension
Patricia Domínguez-Gómez; Flavio Celis d’Amico – Informatics in Education, 2024
The creative programming language Processing can be used as a generative architectural design tool, which allows the designer to write design instructions (algorithms) and compute them, obtaining graphical outputs of great interest. This contribution addresses the inclusion of this language in the architecture curriculum, within the context of…
Descriptors: Undergraduate Students, Architectural Education, Architecture, Courseware
Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval
Kasra Lekan; Zachary A. Pardos – Journal of Learning Analytics, 2025
Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…
Descriptors: Technology Uses in Education, Artificial Intelligence, Academic Advising, Majors (Students)
Chang, Hui-Tzu; Lin, Chia-Yu; Jheng, Wei-Bin; Chen, Shih-Hsu; Wu, Hsien-Hua; Tseng, Fang-Ching; Wang, Li-Chun – Educational Technology & Society, 2023
The objective of this research is based on human-centered AI in education to develop a personalized hybrid course recommendation system (PHCRS) to assist students with course selection decisions from different departments. The system integrates three recommendation methods, item-based, user-based and content-based filtering, and then optimizes the…
Descriptors: Artificial Intelligence, Course Selection (Students), Blended Learning, Accuracy
Kotlyar, Igor; Sharifi, Tina; Fiksenbaum, Lisa – International Journal of Artificial Intelligence in Education, 2023
Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…
Descriptors: Algorithms, Undergraduate Students, Computer Simulation, Evaluation
Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
Allan Jeong; Hyoung Seok-Shin – International Association for Development of the Information Society, 2023
The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…
Descriptors: Critical Thinking, Learning Strategies, Concept Mapping, Learning Analytics