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Panaite, Marilena; Ruseti, Stefan; Dascalu, Mihai; Balyan, Renu; McNamara, Danielle S.; Trausan-Matu, Stefan – Grantee Submission, 2019
Intelligence Tutoring Systems (ITSs) focus on promoting knowledge acquisition, while providing relevant feedback during students' practice. Self-explanation practice is an effective method used to help students understand complex texts by leveraging comprehension. Our aim is to introduce a deep learning neural model for automatically scoring…
Descriptors: Computer Assisted Testing, Scoring, Intelligent Tutoring Systems, Natural Language Processing
Olney, Andrew M.; Gilbert, Stephen B.; Rivers, Kelly – Grantee Submission, 2021
Cyberlearning technologies increasingly seek to offer personalized learning experiences via adaptive systems that customize pedagogy, content, feedback, pace, and tone according to the just-in-time needs of a learner. However, it is historically difficult to: (1) create these smart learning environments; (2) continuously improve them based on…
Descriptors: Educational Technology, Computer Assisted Instruction, Learning Analytics, Intelligent Tutoring Systems
Joe Olsen; Amy Adair; Janice Gobert; Michael Sao Pedro; Mariel O'Brien – Grantee Submission, 2022
Many national science frameworks (e.g., Next Generation Science Standards) argue that developing mathematical modeling competencies is critical for students' deep understanding of science. However, science teachers may be unprepared to assess these competencies. We are addressing this need by developing virtual lab performance assessments that…
Descriptors: Mathematical Models, Intelligent Tutoring Systems, Performance Based Assessment, Data Collection
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Albacete, Patricia; Silliman, Scott; Jordan, Pamela – Grantee Submission, 2017
Intelligent tutoring systems (ITS), like human tutors, try to adapt to student's knowledge level so that the instruction is tailored to their needs. One aspect of this adaptation relies on the ability to have an understanding of the student's initial knowledge so as to build on it, avoiding teaching what the student already knows and focusing on…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Multiple Choice Tests, Computer Assisted Testing
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of writing proficiency generally includes analyses of the specific linguistic and rhetorical features contained in the singular essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing might more closely capture writing skill.…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Writing Skills
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Allen, Laura K.; Jacovina, Matthew E.; McNamara, Danielle S. – Grantee Submission, 2016
The development of strong writing skills is a critical (and somewhat obvious) goal within the classroom. Individuals across the world are now expected to reach a high level of writing proficiency to achieve success in both academic settings and the workplace (Geiser & Studley, 2001; Powell, 2009; Sharp, 2007). Unfortunately, strong writing…
Descriptors: Writing Skills, Writing Instruction, Writing Strategies, Teaching Methods
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Gobert, Janice D.; Sao Pedro, Michael A. – Grantee Submission, 2017
In this chapter, we provide an overview of the design, data-collection, and data-analysis efforts for a digital learning and assessment environment for scientific inquiry / science practices called "Inq-ITS" ("I"nquiry "I"ntelligent "T"utoring "S"ystem; www.inqits.org). We first present a brief…
Descriptors: Educational Assessment, Electronic Learning, Science Process Skills, Intelligent Tutoring Systems
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Sao Pedro, Michael A.; Gobert, Janice D.; Betts, Cameron G. – Grantee Submission, 2014
There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled…
Descriptors: Performance Based Assessment, Computer Assisted Testing, Inquiry, Science Process Skills
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Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2014
This study explores correlations between human ratings of essay quality and component scores based on similar natural language processing indices and weighted through a principal component analysis. The results demonstrate that such component scores show small to large effects with human ratings and thus may be suitable to providing both summative…
Descriptors: Essays, Computer Assisted Testing, Writing Evaluation, Scores
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Roscoe, Rod D.; Varner, Laura K.; Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2013
Various computer tools have been developed to support educators' assessment of student writing, including automated essay scoring and automated writing evaluation systems. Research demonstrates that these systems exhibit relatively high scoring accuracy but uncertain instructional efficacy. Students' writing proficiency does not necessarily…
Descriptors: Writing Instruction, Intelligent Tutoring Systems, Computer Assisted Testing, Writing Evaluation
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Roscoe, Rod D.; Jacovina, Matthew E.; Harry, Danielle; Russell, Devin G.; McNamara, Danielle S. – Grantee Submission, 2015
Multimedia instructional materials require learners to select, organize, and integrate information across multiple modalities. To facilitate these comprehension processes, a variety of multimedia design principles have been proposed. This study further explores the redundancy principle by manipulating the degree of partial redundancy between…
Descriptors: Multimedia Instruction, Multimedia Materials, High School Students, Writing Instruction