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Li, Haiying; Gobert, Janice; Dickler, Rachel; Morad, Natali – Grantee Submission, 2018
In the present study, we first examined the formality and use of academic language in students' scientific explanations in the form of written claim, written evidence, and written reasoning (CER). Middle school students constructed explanations within an intelligent tutoring system after completing a virtual science inquiry investigation. Results…
Descriptors: Academic Language, Language Usage, Intelligent Tutoring Systems, Middle School Students
Li, Haiying; Gobert, Janice; Dickler, Rachel – Grantee Submission, 2018
Examining the interaction between content knowledge, inquiry proficiency, and writing proficiency is central to understanding the relative contribution of each proficiency on students' written communication about their science inquiry. Previous studies, however, have only analyzed one of these primary types of knowledge/proficiencies (i.e. content…
Descriptors: Science Process Skills, Inquiry, Knowledge Level, Writing Skills
Sao Pedro, Michael A.; Gobert, Janice D.; Baker, Ryan S. – Grantee Submission, 2014
We explore in this paper if automated scaffolding delivered via a pedagogical agent within a simulation can help students acquire data collection inquiry skills. Our initial analyses revealed that such scaffolding was effective for helping students who initially did not know two specific skills, designing controlled experiments and testing stated…
Descriptors: Automation, Scaffolding (Teaching Technique), Intelligent Tutoring Systems, Data Collection
Flanagan, Jean C.; Herrmann-Abell, Cari F.; Roseman, Jo Ellen – Online Submission, 2013
AAAS (American Association for the Advancement of Science) is collaborating with BSCS (Biological Sciences Curriculum Study) in the development of a curriculum unit for eighth grade students that connects fundamental chemistry and biology concepts to better prepare them for high school biology. Recognizing that teachers play an influential role in…
Descriptors: Science Teachers, Curriculum Development, Science Instruction, Plants (Botany)
Sao Pedro, Michael; Jiang, Yang; Paquette, Luc; Baker, Ryan S.; Gobert, Janice – Grantee Submission, 2014
Students conducted inquiry using simulations within a rich learning environment for 4 science topics. By applying educational data mining to students' log data, assessment metrics were generated for two key inquiry skills, testing stated hypotheses and designing controlled experiments. Three models were then developed to analyze the transfer of…
Descriptors: Simulation, Transfer of Training, Bayesian Statistics, Inquiry
Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D. – Grantee Submission, 2013
When validating assessment models built with data mining, generalization is typically tested at the student-level, where models are tested on new students. This approach, though, may fail to find cases where model performance suffers if other aspects of those cases relevant to prediction are not well represented. We explore this here by testing if…
Descriptors: Educational Research, Data Collection, Data Analysis, Generalizability Theory
Gobert, Janice Darlene; Sao Pedro, Michael A.; Baker, Ryan S. – Grantee Submission, 2012
In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry skills in another domain (phase change). To do so, we leveraged educational data mining…
Descriptors: Data Collection, Learning Analytics, Inquiry, Science Process Skills
Feng, Mingyu; Beck, Joseph – International Working Group on Educational Data Mining, 2009
Representing domain knowledge is important for constructing educational software, and automated approaches have been proposed to construct and refine such models. In this paper, instead of applying automated and computationally intensive approaches, we simply start with existing hand-constructed transfer models at various levels of granularity and…
Descriptors: Data Analysis, Models, Transfer of Training, Intelligent Tutoring Systems
Feng, Mingyu; Beck, Joseph E.; Heffernan, Neil T. – International Working Group on Educational Data Mining, 2009
A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different instructional strategies by applying an educational data mining technique, learning decomposition. We use logistic regression to determine how much learning is caused by…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Sampling, Statistical Inference
Fortuna, Carolyn – 2001
This paper describes a unit of instruction about media images--how they work, ways they affect people, and means to use them--in which young adolescents learn the consequences of becoming a media-literate consumer. The paper explains that in the unit, divided into 2 "clusters," 110 Boston-area eighth graders share 5 core academic…
Descriptors: Critical Thinking, Critical Viewing, Early Adolescents, Grade 8