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Direct linkBrian P. Woods – Journal of Chemical Education, 2024
In this in-class activity, organic chemistry undergraduates try to place an assortment of molecules in chronological order from oldest to most recently synthesized. In the students' first attempt, they use their knowledge of reactions and synthesis to analyze the organic compounds for their structural complexity. Before a second attempt, the names…
Descriptors: Organic Chemistry, Entrepreneurship, Learning Activities, Undergraduate Students
Kaitlin Gili; Kyle Heuton; Astha Shah; David Hammer; Michael C. Hughes – Physical Review Physics Education Research, 2025
Advances in machine learning (ML) offer new possibilities for science education research. We report on early progress in the design of an ML-based tool to analyze students' mechanistic sensemaking, working from a coding scheme that is aligned with previous work in physics education research (PER) and that is amenable to recently developed ML…
Descriptors: Physics, Science Education, Educational Research, Artificial Intelligence
Simin Cheng; Zhuoning Xie; Qingyuan Hu; Yao Qian; Xiaoxiao Ma – Journal of Chemical Education, 2023
This study highlights the importance of incorporating modern mass spectrometry techniques into undergraduate education. By focusing on the structure-characterizing capability of MS, students are able to gain hands-on experience with cutting-edge techniques and better understand how MS can be used to solve real-world problems. The three-step lipid…
Descriptors: Undergraduate Students, Scientific Concepts, Science Instruction, College Science
Tugba Yuksel; Lynn A. Bryan; Alejandra J. Magana – International Journal of Science Education, 2024
Quantum physics forms the basis for exciting new technologies, including quantum computers, quantum encryption, and quantum entanglement. The advancement of science and technology highlights the importance of mastering quantum physics and its applications, not only at the college level but also as early as high school. In this multiple case study,…
Descriptors: Undergraduate Students, Models, Quantum Mechanics, Science Instruction
Thrall, Elizabeth S.; Lee, Seung Eun; Schrier, Joshua; Zhao, Yijun – Journal of Chemical Education, 2021
Techniques from the branch of artificial intelligence known as machine learning (ML) have been applied to a wide range of problems in chemistry. Nonetheless, there are very few examples of pedagogical activities to introduce ML to chemistry students in the chemistry education literature. Here we report a computational activity that introduces…
Descriptors: Undergraduate Students, Artificial Intelligence, Man Machine Systems, Science Education
Baosen Zhang; Ariana Frkonja-Kuczin; Zhong-Hui Duan; Aliaksei Boika – Journal of Chemical Education, 2023
Computer vision (CV) is a subfield of artificial intelligence (AI) that trains computers to understand our visual world based on digital images. There are many successful applications of CV including face and hand gesture detection, weather recording, smart farming, and self-driving cars. Recent advances in computer vision with machine learning…
Descriptors: Classification, Laboratory Equipment, Visual Aids, Optics
Harrison, Colin D.; Nguyen, Tiffy A.; Seidel, Shannon B.; Escobedo, Alycia M.; Hartman, Courtney; Lam, Katie; Liang, Kristen S.; Martens, Miranda; Acker, Gigi N.; Akana, Susan F.; Balukjian, Brad; Benton, Hilary P.; Blair, J. R.; Boaz, Segal M.; Boyer, Katharyn E.; Bram, Jason B.; Burrus, Laura W.; Byrd, Dana T.; Caporale, Natalia; Carpenter, Edward J.; Chan, Yee-Hung M.; Chen, Lily; Chovnick, Amy; Chu, Diana S.; Clarkson, Bryan K.; Cooper, Sara E.; Creech, Catherine J.; de la Torre, José R.; Denetclaw, Wilfred F.; Duncan, Kathleen; Edwards, Amelia S.; Erickson, Karen; Fuse, Megumi; Gorga, Joseph J.; Govindan, Brinda; Green, L. Jeanette; Hankamp, Paul Z.; Harris, Holly E.; He, Zheng-Hui; Ingalls, Stephen B.; Ingmire, Peter D.; Jacobs, J. Rebecca; Kamakea, Mark; Kimpo, Rhea R.; Knight, Jonathan D.; Krause, Sara K.; Krueger, Lori E.; Light, Terrye L.; Lund, Lance; Márquez-Magaña, Leticia M.; McCarthy, Briana K.; McPheron, Linda; Miller-Sims, Vanessa C.; Moffatt, Cristopher A.; Muick, Pamela C.; Nagami, Paul H.; Nusse, Gloria; Okimura, K. M.; Pasion, Sally G.; Patterson, Robert; Pennings, Pleuni S.; Riggs, Blake; Romeo, Joseph M.; Roy, Scott W.; Russo-Tait, Tatiane; Schultheis, Lisa M.; Sengupta, Lakshmikanta; Spicer, Greg S.; Swei, Andrea; Wade, Jennifer M.; Willsie, Julia K.; Kelley, Loretta A.; Owens, Melinda T.; Trujillo, Gloriana; Domingo, Carmen; Schinske, Jeffrey N.; Tanner, Kimberly D. – CBE - Life Sciences Education, 2019
Instructor Talk--noncontent language used by instructors in classrooms--is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk…
Descriptors: Classroom Communication, Language Usage, Novelty (Stimulus Dimension), Models
Download full textMaskour, Lhoussaine; Alami, Anouar; Moncef Zaki; Boujemaa Agorram – Education Sciences, 2019
This study aims to assess learning outcomes and identify students' misconceptions in plant classification. We conducted a questionnaire survey with undergraduate and master's students. The qualitative analysis of the students' responses made it possible to shed light on the difficulties of assimilation of many notions and also to identify the…
Descriptors: Foreign Countries, Plants (Botany), Classification, Knowledge Management
Gottipati, Swapna; Shankararaman, Venky – Education and Information Technologies, 2018
The applications of learning outcomes and competency frameworks have brought better clarity to engineering programs in many universities. Several frameworks have been proposed to integrate outcomes and competencies into course design, delivery and assessment. However, in many cases, competencies are course-specific and their overall impact on the…
Descriptors: Outcomes of Education, Models, Engineering Education, Curriculum Design
Deep Learning + Student Modeling + Clustering: A Recipe for Effective Automatic Short Answer Grading
Zhang, Yuan; Shah, Rajat; Chi, Min – International Educational Data Mining Society, 2016
In this work we tackled the task of Automatic Short Answer Grading (ASAG). While conventional ASAG research makes prediction mainly based on student answers referred as Answer-based, we leveraged the information about questions and student models into consideration. More specifically, we explore the Answer-based, Question, and Student models…
Descriptors: Automation, Grading, Artificial Intelligence, Test Format
Yang, Jie; DeVore, Seth; Hewagallage, Dona; Miller, Paul; Ryan, Qing X.; Stewart, John – Physical Review Physics Education Research, 2020
Machine learning algorithms have recently been used to predict students' performance in an introductory physics class. The prediction model classified students as those likely to receive an A or B or students likely to receive a grade of C, D, F or withdraw from the class. Early prediction could better allow the direction of educational…
Descriptors: Artificial Intelligence, Man Machine Systems, Identification, At Risk Students
Galloway, Kelli R.; Leung, Min Wah; Flynn, Alison B. – Journal of Chemical Education, 2018
To explore the differences between how organic chemistry students and organic chemistry professors think about organic chemistry reactions, we administered a card sort task to participants with a range of knowledge and experience levels. Beginning students created a variety of categories ranging from structural similarities to process oriented…
Descriptors: Organic Chemistry, Science Instruction, College Science, Graduate Students
Aykutlu, Isil – International Journal of Progressive Education, 2017
The aim of this study is to lay bare pre-service primary school teachers' perception of "physics" through metaphors. The study was realized with the participation of 38 freshmen pre-service teachers taking General Physics at a public university. Data of the study were obtained with participants filling the blanks in the following…
Descriptors: Preservice Teachers, Elementary School Teachers, Comprehension, Physics
Ha¨rtinger, Stefan; Clarke, Nigel – Journal of Chemical Education, 2016
Developing skills for searching the patent literature is an essential element of chemical information literacy programs at the university level. The present article creates awareness of patents as a rich source of chemical information. Patent classification is introduced as a key-component in comprehensive search strategies. The free Espacenet…
Descriptors: Science Instruction, Chemistry, Intellectual Property, Classification
Bollen, Laurens; De Cock, Mieke; Zuza, Kristina; Guisasola, Jenaro; van Kampen, Paul – Physical Review Physics Education Research, 2016
We have investigated whether and how a categorization of responses to questions on linear distance-time graphs, based on a study of Irish students enrolled in an algebra-based course, could be adopted and adapted to responses from students enrolled in calculus-based physics courses at universities in Flanders, Belgium (KU Leuven) and the Basque…
Descriptors: Mechanics (Physics), Motion, Graphs, Classification
