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Direct linkHiggins, Traci; Mokros, Jan; Rubin, Andee; Sagrans, Jacob – Teaching Statistics: An International Journal for Teachers, 2023
In the context of an afterschool program in which students explore relatively large authentic datasets, we investigated how 11- to 14-year old students worked with categorical variables. During the program, students learned to use the Common Online Data Analysis Platform (CODAP), a statistical analysis platform specifically designed for middle and…
Descriptors: Classification, After School Programs, Data Analysis, Middle School Students
Say What? Automatic Modeling of Collaborative Problem Solving Skills from Student Speech in the Wild
Download full textPugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
Mulvey, Bridget – Science Teacher, 2016
Students best learn science through a combination of science inquiry and language learning. This article presents a series of chemistry lessons on the naming of compounds. The weeklong unit focuses on patterns across compound names and chemical formulas and addresses several of the "Next Generation Science Standards" (NGSS Lead States…
Descriptors: Science Instruction, Chemistry, Scientific Concepts, Naming
