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Direct linkTamar Fuhrmann; Leah Rosenbaum; Aditi Wagh; Adelmo Eloy; Jacob Wolf; Paulo Blikstein; Michelle Wilkerson – Science Education, 2025
When learning about scientific phenomena, students are expected to "mechanistically" explain how underlying interactions produce the observable phenomenon and "conceptually" connect the observed phenomenon to canonical scientific knowledge. This paper investigates how the integration of the complementary processes of designing…
Descriptors: Mechanics (Physics), Thinking Skills, Scientific Concepts, Concept Formation
Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Khanal, Shristi Shakya; Prasad, P.W.C.; Alsadoon, Abeer; Maag, Angelika – Education and Information Technologies, 2020
The constantly growing offering of online learning materials to students is making it more difficult to locate specific information from data pools. Personalization systems attempt to reduce this complexity through adaptive e-learning and recommendation systems. The latter are, generally, based on machine learning techniques and algorithms and…
Descriptors: Electronic Learning, Barriers, Online Courses, Accuracy
Litke, Erica; Hill, Heather C. – Elementary School Journal, 2020
Understanding and analyzing data is a crucial aspect of quantitative literacy in the 21st century, leading scholars and policy makers to push for more rigorous instruction in this area rooted in statistical investigation. In this study, we examine 144 upper-elementary mathematics lessons on data and statistics topics to assess the extent to which…
Descriptors: Mathematics Instruction, Elementary School Students, Graphs, Statistics
Litke, Erica; Hill, Heather C. – Elementary School Journal, 2020
Understanding and analyzing data is a crucial aspect of quantitative literacy in the 21st century, leading scholars and policy makers to push for more rigorous instruction in this area rooted in statistical investigation. In this study, we examine 144 upper-elementary mathematics lessons on data and statistics topics to assess the extent to which…
Descriptors: Mathematics Instruction, Elementary School Students, Graphs, Statistics
Download full textLiu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
Danciulescu, Theodora Ioana; Mihaescu, Marian Cristian; Heras, Stella; Palanca, Javier; Julian, Vicente – International Educational Data Mining Society, 2020
Building and especially improving a classification kernel represents a challenging task. The works presented in this paper continue an already developed semi-supervised classification approach that aimed at labelling transcripts from educational videos. We questioned whether the size of the ground-truth data-set (Wikipedia articles) or the quality…
Descriptors: Data Analysis, Classification, Information Retrieval, Video Technology
Alonso-Fernández, Cristina; Martínez-Ortiz, Iván; Caballero, Rafael; Freire, Manuel; Fernández-Manjón, Baltasar – Journal of Computer Assisted Learning, 2020
Serious games have proven to be a powerful tool in education to engage, motivate, and help students learn. However, the change in student knowledge after playing games is usually measured with traditional (paper) prequestionnaires-postquestionnaires. We propose a combination of game learning analytics and data mining techniques to predict…
Descriptors: Case Studies, Teaching Methods, Game Based Learning, Student Motivation
Hirata, Yoko; Thompson, Paul – ELT Journal, 2022
With the development of language corpora, linguists have been able to identify how often specific words, phrases, and expressions are used, and in which contexts. However, applications of corpora in the wider domain of language teaching have remained limited. This article presents an approach to utilizing corpora, combining principles from…
Descriptors: Computational Linguistics, Teaching Methods, Action Research, Communicative Competence (Languages)
Erin C. Yang; Robby Divine; Christine S. Kang; Sidney Chan; Elijah Arenas; Zoe Subol; Peter Tinker; Hayden Manninen; Alicia Feichtenbiner; Talal Mustafa; Julia Hallowell; Isiac Orr; Hugh Haddox; Brian Koepnick; Jacob O'Connor; Ian C. Haydon; Karla-Luise Herpoldt; Kandise Van Wormer; Celine Abell; David Baker; Alena Khmelinskaia; Neil P. King – Journal of Chemical Education, 2022
Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work-study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and…
Descriptors: Undergraduate Students, Teaching Methods, COVID-19, Pandemics
Junokas, M. J.; Lindgren, R.; Kang, J.; Morphew, J. W. – Journal of Computer Assisted Learning, 2018
Gestural recognition systems are important tools for leveraging movement-based interactions in multimodal learning environments but personalizing these interactions has proven difficult. We offer an adaptable model that uses multimodal analytics, enabling students to define their physical interactions with computer-assisted learning environments.…
Descriptors: Nonverbal Communication, Multimedia Instruction, Computer Assisted Instruction, Data Analysis
Manshur, Fadlil Munawwar – Journal of Social Studies Education Research, 2020
This research explores the learning of Islamic Arabic literary works ("Al-Adab Al-'Arabi") typical of "Pesantren" (Islamic boarding schools) and the role of Kyai in the cultural transformation of the teachings of piety in Arabic literature. This study used a phenomenological design and applied qualitative approach for the data…
Descriptors: Islam, Religious Education, Boarding Schools, Role
Mao, Ye; Zhi, Rui; Khoshnevisan, Farzaneh; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2019
Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…
Descriptors: Difficulty Level, Learning Activities, Prediction, Programming
Parkavi, A.; Lakshmi, K.; Srinivasa, K. G. – Educational Research and Reviews, 2017
Data analysis techniques can be used to analyze the pattern of data in different fields. Based on the analysis' results, it is recommended that suggestions be provided to decision making authorities. The data mining techniques can be used in educational domain to improve the outcome of the educational sectors. The authors carried out this research…
Descriptors: Data Analysis, Educational Research, Goodness of Fit, Decision Making
Rollinson, Joseph; Brunskill, Emma – International Educational Data Mining Society, 2015
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Descriptors: Prediction, Models, Educational Policy, Intelligent Tutoring Systems
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