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Haridas, Mithun; Gutjahr, Georg; Raman, Raghu; Ramaraju, Rudraraju; Nedungadi, Prema – Education and Information Technologies, 2020
In many rural Indian schools, English is a second language for teachers and students. Intelligent tutoring systems have good potential because they enable students to learn at their own pace, in an exploratory manner. This paper describes a 3-year longitudinal study of 2123 Indian students who used the intelligent tutoring system, AmritaITS. The…
Descriptors: Foreign Countries, Predictor Variables, English (Second Language), Second Language Learning
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Wetzel, Jon; VanLehn, Kurt; Butler, Dillan; Chaudhari, Pradeep; Desai, Avaneesh; Feng, Jingxian; Grover, Sachin; Joiner, Reid; Kong-Sivert, Mackenzie; Patade, Vallabh; Samala, Ritesh; Tiwari, Megha; van de Sande, Brett – Interactive Learning Environments, 2017
This paper describes Dragoon, a simple intelligent tutoring system which teaches the construction of models of dynamic systems. Modelling is one of seven practices dictated in two new sets of educational standards in the U.S.A., and Dragoon is one of the first systems for teaching model construction for dynamic systems. Dragoon can be classified…
Descriptors: Intelligent Tutoring Systems, Models, Computer Interfaces, Comparative Analysis
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Zheng, Guoguo; Fancsali, Stephen E.; Ritter, Steven; Berman, Susan R. – Journal of Learning Analytics, 2019
If we wish to embed assessment for accountability within instruction, we need to better understand the relative contribution of different types of learner data to statistical models that predict scores and discrete achievement levels on assessments used for accountability purposes. The present work scales up and extends predictive models of math…
Descriptors: Formative Evaluation, Predictor Variables, Summative Evaluation, Scores
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Conejo, Ricardo; Guzmán, Eduardo; Trella, Monica – International Journal of Artificial Intelligence in Education, 2016
This article describes the evolution and current state of the domain-independent Siette assessment environment. Siette supports different assessment methods--including classical test theory, item response theory, and computer adaptive testing--and integrates them with multidimensional student models used by intelligent educational systems.…
Descriptors: Automation, Student Evaluation, Intelligent Tutoring Systems, Item Banks
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
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of argumentative writing generally includes analyses of the specific linguistic and rhetorical features contained in the individual essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing may more accurately capture their…
Descriptors: Writing (Composition), Persuasive Discourse, Essays, Language Usage
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Verdú, Elena; Regueras, Luisa M.; Gal, Eran; de Castro, Juan P.; Verdú, María J.; Kohen-Vacs, Dan – Educational Technology Research and Development, 2017
INTUITEL is a research project aiming to offer a personalized learning environment. The INTUITEL approach includes an Intelligent Tutoring System that gives students recommendations and feedback about what the best learning path is for them according to their profile, learning progress, context and environmental influences. INTUITEL combines…
Descriptors: Technology Integration, Intelligent Tutoring Systems, Computer Networks, Computer System Design
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Shute, Valerie J.; Zapata-Rivera, Diego – ETS Research Report Series, 2008
Recent advances in educational assessment, cognitive science, and artificial intelligence have made it possible to integrate valid assessment and instruction in the form of modern computer-based intelligent systems. These intelligent systems leverage assessment information that is gathered from various sources (e.g., summative and formative). This…
Descriptors: Educational Assessment, Intelligent Tutoring Systems, Artificial Intelligence, Summative Evaluation
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Inoue, Yukiko – Journal of Educational Technology Systems, 2001
Discussion of intelligent tutoring systems (ITS) focuses on ITS evaluation studies, particularly methodological issues. Topics include summative evaluation for efficiency; quantitative evaluation; formative evaluation; informal evaluation; cognitive mediation perspectives of evaluation; integrating cognitive theories into ITS; effectiveness of…
Descriptors: Epistemology, Evaluation Methods, Evaluation Research, Formative Evaluation
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Bloom, Charles; Linton, Frank; Bell, Brigham – Journal of Interactive Learning Research, 1997
Learn, Explore, and Practice (LEAP) is an intelligent tutoring system for training new customer contact employees in customer interaction skills (problem solving and sales) as well as domain knowledge, such as telecommunications products and services. This article describes the design and evaluation (formative and summative) of the first version…
Descriptors: Computer Assisted Instruction, Computer Software Development, Formative Evaluation, Instructional Design
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Baggott, Glenn K.; Rayne, Richard C. – Bioscience Education e-Journal, 2007
Formative computer-based assessments (CBAs) for self-instruction were introduced into a Year-2 field biology module. These CBAs were provided in "tutorial" mode where each question had context-related diagnostic feedback and tutorial pages, and a self-test mode where the same CBA returned only a score. The summative assessments remained…
Descriptors: Feedback (Response), Student Evaluation, Units of Study, Summative Evaluation