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Soomro, Sohail Ahmed; Casakin, Hernan; Nanjappan, Vijayakumar; Georgiev, Georgi V. – Journal of Science Education and Technology, 2023
Makerspaces are gaining popularity in the educational activities of all age groups, from primary schools to higher education institutions, particularly in science, technology, engineering, and mathematics (STEM) disciplines. Due to makerspaces' hands-on learning approach, it is generally believed that learning in makerspaces influences students'…
Descriptors: Shared Resources and Services, Creativity, STEM Education, Educational Environment
Yang Zhang; Yangping Li; Weiping Hu; Huizhi Bai; Yuanjing Lyu – Journal of Science Education and Technology, 2025
Scientific creativity plays an essential role in science education as an advanced cognitive ability that inspires students to solve scientific problems inventively. The cultivation of scientific creativity relies heavily on effective assessment. Typically, human raters manually score scientific creativity using the Consensual Assessment Technique…
Descriptors: Eye Movements, Artificial Intelligence, Creativity, Scientific Concepts
Maestrales, Sarah; Zhai, Xiaoming; Touitou, Israel; Baker, Quinton; Schneider, Barbara; Krajcik, Joseph – Journal of Science Education and Technology, 2021
In response to the call for promoting three-dimensional science learning (NRC, 2012), researchers argue for developing assessment items that go beyond rote memorization tasks to ones that require deeper understanding and the use of reasoning that can improve science literacy. Such assessment items are usually performance-based constructed…
Descriptors: Artificial Intelligence, Scoring, Evaluation Methods, Chemistry
Wulff, Peter; Buschhüter, David; Westphal, Andrea; Mientus, Lukas; Nowak, Anna; Borowski, Andreas – Journal of Science Education and Technology, 2022
Science education researchers typically face a trade-off between more quantitatively oriented confirmatory testing of hypotheses, or more qualitatively oriented exploration of novel hypotheses. More recently, open-ended, constructed response items were used to combine both approaches and advance assessment of complex science-related skills and…
Descriptors: Evaluation Methods, Science Education, Educational Research, Artificial Intelligence
Bertolini, Roberto; Finch, Stephen J.; Nehm, Ross H. – Journal of Science Education and Technology, 2021
High levels of attrition characterize undergraduate science courses in the USA. Predictive analytics research seeks to build models that identify at-risk students and suggest interventions that enhance student success. This study examines whether incorporating a novel assessment type (concept inventories [CI]) and using machine learning (ML)…
Descriptors: Evaluation Methods, Scores, Artificial Intelligence, Grade Prediction
Dutta, Rubina; Mantri, Archana; Singh, Gurjinder; Singh, Narinder Pal – Journal of Science Education and Technology, 2023
Digital electronics is a fundamental subject for engineering students, and it enables the students to learn design-based approaches and solve complex engineering problems. Students learn about minimization techniques for reducing the hardware components and size of the circuit by solving complex Boolean equations. The Karnaugh map (K-map) is one…
Descriptors: Computer Simulation, Flipped Classroom, Critical Thinking, Learning Motivation
Santhosh, Malavika; Farooqi, Hafsa; Ammar, Mohammad; Siby, Nitha; Bhadra, Jolly; Al-Thani, Noora J.; Sellami, Abdellatif; Fatima, Noshin; Ahmad, Zubair – Journal of Science Education and Technology, 2023
In recent decades, informal project-based learning (PjBL) for science, technology, engineering, and mathematics (STEM) education has gained immense significance. Though some meta-analytical studies have reported the effectiveness of PjBL models, none of them has been explicit for informal PjBL models executed for school students in STEM education.…
Descriptors: Active Learning, Student Projects, STEM Education, Informal Education
Zhai, Xiaoming – Journal of Science Education and Technology, 2021
As cutting-edge technologies, such as machine learning (ML), are increasingly involved in science assessments, it is essential to conceptualize how assessment practices are innovated by technologies. To partially meet this need, this article focuses on ML-based science assessments and elaborates on how ML innovates assessment practices in science…
Descriptors: Artificial Intelligence, Educational Innovation, Science Education, Evaluation Methods
Bortz, Whitney Wall; Gautam, Aakash; Tatar, Deborah; Lipscomb, Kemper – Journal of Science Education and Technology, 2020
Integrating computational thinking (CT) and science education is complex, and assessing the resulting learning gains even more so. Arguments that assessment should match the learning (Biggs, "Assessment & Evaluation in Higher Education," 21(1), 5-16. 1996; Airasian and Miranda, "Theory into Practice," 41(4), 249-254. 2002;…
Descriptors: Computation, Thinking Skills, Science Education, Evaluation Methods
Montgomery, Ryan; Greenwald, Eric; Crane, Samuel; Krakowski, Ari; Barber, Jacqueline – Journal of Science Education and Technology, 2020
New national science standards have elevated attention to student performance with a core set of science and engineering practices, yet guidance about how to assess these practices is only just emerging in the literature. This is particularly true for the set of engineering design-focused concepts and practices articulated in the Next Generation…
Descriptors: Middle School Students, Engineering, Design, Internship Programs
Rosenberg, Joshua M.; Krist, Christina – Journal of Science Education and Technology, 2021
Assessing students' participation in science practices presents several challenges, especially when aiming to differentiate meaningful (vs. rote) forms of participation. In this study, we sought to use machine learning (ML) for a novel purpose in science assessment: developing a construct map for students' "consideration of generality,"…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Models
Lee, Jaeyong; Lee, Gyeong-Geon; Hong, Hun-Gi – Journal of Science Education and Technology, 2023
Here, we describe the development and validation of an automatic assessment system that examines students' hand-drawn visual representations in free-response items. The data were collected from 1,028 students in the second through 11th grades in South Korea using two items from the Test About Particles in a Gas questionnaire (Novick &…
Descriptors: Freehand Drawing, Evaluation Methods, Elementary School Students, Secondary School Students
Williamson, Kenneth C.; Williamson, Vickie M.; Hinze, Scott R. – Journal of Science Education and Technology, 2017
Standardized, well-established paper-and-pencil tests, which measure spatial abilities or which measure reasoning abilities, have long been found to be predictive of success in the STEM (science, technology, engineering, and mathematics) fields. Instructors can use these tests for prediction of success and to inform instruction. A comparative…
Descriptors: Spatial Ability, STEM Education, Prediction, Visual Perception
Shelton, Angi; Smith, Andrew; Wiebe, Eric; Behrle, Courtney; Sirkin, Ruth; Lester, James – Journal of Science Education and Technology, 2016
Formative assessment strategies are used to direct instruction by establishing where learners' understanding is, how it is developing, informing teachers and students alike as to how they might get to their next set of goals of conceptual understanding. For the science classroom, one rich source of formative assessment data about scientific…
Descriptors: Formative Evaluation, Evaluation Methods, Science Instruction, Student Journals
Doerschuk, Peggy; Bahrim, Cristian; Daniel, Jennifer; Kruger, Joseph; Mann, Judith; Martin, Cristopher – Journal of Science Education and Technology, 2016
There is a growing demand for degreed science, technology, engineering and mathematics (STEM) professionals, but the production of degreed STEM students is not keeping pace. Problems exist at every juncture along the pipeline. Too few students choose to major in STEM disciplines. Many of those who do major in STEM drop out or change majors.…
Descriptors: STEM Education, Undergraduate Students, Interdisciplinary Approach, Student Recruitment