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Stefan Ruseti; Mihai Dascalu; Amy M. Johnson; Renu Balyan; Kristopher J. Kopp; Danielle S. McNamara – Grantee Submission, 2018
This study assesses the extent to which machine learning techniques can be used to predict question quality. An algorithm based on textual complexity indices was previously developed to assess question quality to provide feedback on questions generated by students within iSTART (an intelligent tutoring system that teaches reading strategies). In…
Descriptors: Questioning Techniques, Artificial Intelligence, Networks, Classification
Sahba Akhavan Niaki – ProQuest LLC, 2018
The increasing amount of available subjective text data in internet such as product reviews, movie critiques and social media comments provides golden opportunities for information retrieval researchers to extract useful information out of such datasets. Topic modeling and sentiment analysis are two widely researched fields that separately try to…
Descriptors: Models, Classification, Content Analysis, Documentation
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Dong, Jian-Jie; Hwang, Wu-Yuin; Shadiev, Rustam; Chen, Ginn-Yein – IEEE Transactions on Learning Technologies, 2019
In this study, we developed an on-call-tutor system to facilitate peer-help activities. The system was implemented in a face-to-face heterogeneous classroom with 119 students from different departments who were not familiar with each other. Students learned Geographic Information System (GIS) in a computer classroom in two groups: students, who…
Descriptors: Peer Teaching, Synchronous Communication, Social Networks, Friendship
Glaze, Andrew R. – ProQuest LLC, 2019
The purpose of this mixed-methods study was to investigate the relationship between teachers' conceptions of mathematics and their use of intelligent tutoring systems for mathematics instruction. Intelligent tutoring systems are adaptive computer programs which administer mathematics instruction to students based on their cognitive state. A…
Descriptors: Mathematics Instruction, Teaching Methods, Intelligent Tutoring Systems, Web Sites
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Wiggins, Joseph B.; Grafsgaard, Joseph F.; Boyer, Kristy Elizabeth; Wiebe, Eric N.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2017
In recent years, significant advances have been made in intelligent tutoring systems, and these advances hold great promise for adaptively supporting computer science (CS) learning. In particular, tutorial dialogue systems that engage students in natural language dialogue can create rich, adaptive interactions. A promising approach to increasing…
Descriptors: Intelligent Tutoring Systems, Self Efficacy, Computer Science Education, Dialogs (Language)
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Lavbic, Dejan; Matek, Tadej; Zrnec, Aljaž – Interactive Learning Environments, 2017
Today's software industry requires individuals who are proficient in as many programming languages as possible. Structured query language (SQL), as an adopted standard, is no exception, as it is the most widely used query language to retrieve and manipulate data. However, the process of learning SQL turns out to be challenging. The need for a…
Descriptors: Evaluation Methods, Information Systems, Intelligent Tutoring Systems, Computer Science Education
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Johnson, Amy M.; McCarthy, Kathryn S.; Kopp, Kristopher J.; Perret, Cecile A.; McNamara, Danielle S. – Grantee Submission, 2017
Intelligent tutoring systems for ill-defined domains, such as reading and writing, are critically needed, yet uncommon. Two such systems, the Interactive Strategy Training for Active Reading and Thinking (iSTART) and Writing Pal (W-Pal) use natural language processing (NLP) to assess learners' written (i.e., typed) responses and provide immediate,…
Descriptors: Reading Instruction, Writing Instruction, Intelligent Tutoring Systems, Reading Strategies
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Chounta, Irene-Angelica; Albacete, Patricia; Jordan, Pamela; Katz, Sandra; McLaren, Bruce M. – Grantee Submission, 2017
In this paper, we propose a computational approach to model the Zone of Proximal Development (ZPD) using predicted probabilities of correctness and engaging students in reflective dialogue. To that end, we employ a predictive model that uses a linear function of a variety of parameters, including difficulty and student knowledge and we analyze the…
Descriptors: Learning Theories, Sociocultural Patterns, Intelligent Tutoring Systems, Physics
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Chounta, Irene-Angelica; McLaren, Bruce M.; Albacete, Patricia; Jordan, Pamela; Katz, Sandra – Grantee Submission, 2017
In this paper, we propose a computational approach to modeling the Zone of Proximal Development of students who learn using a natural language tutoring system for physics. We employ a student model that predicts students' performance based on their prior knowledge and their activity when using a dialogue tutor to practice with conceptual,…
Descriptors: Learning Theories, Sociocultural Patterns, Intelligent Tutoring Systems, Physics
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Sottilare, Robert A.; Shawn Burke, C.; Salas, Eduardo; Sinatra, Anne M.; Johnston, Joan H.; Gilbert, Stephen B. – International Journal of Artificial Intelligence in Education, 2018
The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or…
Descriptors: Meta Analysis, Teaching Methods, Teamwork, Outcomes of Education
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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Sharma Mittal, Ruhi; Nagar, Seema; Sharma, Mourvi; Dwivedi, Utkarsh; Dey, Prasenjit; Kokku, Ravi – International Educational Data Mining Society, 2018
As education gets increasingly digitized, and intelligent tutoring systems gain commercial prominence, scalable assessment generation mechanisms become a critical requirement for enabling increased learning outcomes. Assessments provide a way to measure learners' level of understanding and difficulty, and personalize their learning. There have…
Descriptors: Vocabulary Development, Language Tests, Semantics, Associative Learning
Pearson, 2018
Pearson sought to explore whether the use of Mastering Chemistry, an online tutorial system designed to help students with chemistry concepts, problem-solving skills and quantitative reasoning, is related to students' course scores and exam scores. This Research Report presents findings from two research studies: one correlational study conducted…
Descriptors: Mastery Learning, Intelligent Tutoring Systems, Chemistry, College Science
Pearson, 2018
Pearson sought to explore whether the use of MyLab Statistics, a teaching, learning and assessment system used to teach statistics at the higher education level, is related to higher exam scores. This Research Report presents findings from one research study: a correlational study conducted at Maastricht University School of Business and Economics…
Descriptors: Foreign Countries, Correlation, Statistics, Mathematics Instruction
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Janning, Ruth; Schatten, Carlotta; Schmidt-Thieme, Lars – International Journal of Artificial Intelligence in Education, 2016
Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology
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