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Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2014
In the current study, we utilize natural language processing techniques to examine relations between the linguistic properties of students' self-explanations and their reading comprehension skills. Linguistic features of students' aggregated self-explanations were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. Results…
Descriptors: Natural Language Processing, Reading Comprehension, Linguistics, Predictor Variables
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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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Du, Jie; Wimmer, Hayden; Rada, Roy – Journal of Information Technology Education: Innovations in Practice, 2016
The Hour of Code is a one-hour introduction to computer science organized by Code.org, a non-profit dedicated to expanding participation in computer science. This study investigated the impact of the Hour of Code on students' attitudes towards computer programming and their knowledge of programming. A sample of undergraduate students from two…
Descriptors: Undergraduate Students, Computer Science Education, Programming, Introductory Courses
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Muñoz, Karla; Noguez, Julieta; Neri, Luis; Mc Kevitt, Paul; Lunney, Tom – Educational Technology & Society, 2016
Game-based Learning (GBL) environments make instruction flexible and interactive. Positive experiences depend on personalization. Student modelling has focused on affect. Three methods are used: (1) recognizing the physiological effects of emotion, (2) reasoning about emotion from its origin and (3) an approach combining 1 and 2. These have proven…
Descriptors: Educational Games, Psychological Patterns, Models, Academic Achievement
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Erdemir, Mustafa; Ingeç, Sebnem Kandil – Universal Journal of Educational Research, 2016
The purpose of this study is to identify pre-service primary mathematics teachers' views regarding on Web-based Intelligent Tutoring Systems (WBITS) in relation to its usability and influence on teaching. A survey method was used. The study was conducted with 43 students attending the mathematics teaching program under the department of elementary…
Descriptors: Preservice Teachers, Mathematics, Mathematics Teachers, Mathematics Instruction
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Roschelle, Jeremy; Feng, Mingyu; Murphy, Robert F.; Mason, Craig A. – AERA Open, 2016
In a randomized field trial with 2,850 seventh-grade mathematics students, we evaluated whether an educational technology intervention increased mathematics learning. Assigning homework is common yet sometimes controversial. Building on prior research on formative assessment and adaptive teaching, we predicted that combining an online homework…
Descriptors: Middle School Students, Grade 7, Secondary School Mathematics, Mathematics Achievement
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Chen, Lujie; Li, Xin; Xia, Zhuyun; Song, Zhanmei; Morency, Louis-Philippe; Dubrawski, Artur – International Educational Data Mining Society, 2016
Solving challenging math problems often invites a child to ride an "emotional roller-coaster" and experience a complex mixture of emotions including confusion, frustration, joy, and surprise. Early exposure to this type of "hard fun" may stimulate child's interest and curiosity of mathematics and nurture life long skills such…
Descriptors: Young Children, Mathematics Education, Problem Solving, Psychological Patterns
Duval, Erik, Ed.; Sharples, Mike, Ed.; Sutherland, Rosamund, Ed. – Springer, 2017
This book gives an overview of the state-of-the-art in Technology Enhanced Learning (TEL). It is organized as a collection of 14 research themes, each introduced by leading experts and including references to the most relevant literature on the theme of each cluster. Additionally, each chapter discusses four seminal papers on the theme with expert…
Descriptors: Educational Technology, Technology Uses in Education, Educational Research, Learning Theories
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Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
Koedinger, Kenneth R.; McLaughlin, Elizabeth A.; Stamper, John C. – International Educational Data Mining Society, 2012
Student modeling plays a critical role in developing and improving instruction and instructional technologies. We present a technique for automated improvement of student models that leverages the DataShop repository, crowd sourcing, and a version of the Learning Factors Analysis algorithm. We demonstrate this method on eleven educational…
Descriptors: Educational Technology, Intelligent Tutoring Systems, Educational Improvement, Mathematics
Eagle, Michael; Johnson, Matthew; Barnes, Tiffany – International Educational Data Mining Society, 2012
We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…
Descriptors: Data Analysis, Interaction, Network Analysis, Problem Solving
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Wu, Ejean; Yang, Shu Ching – Computer Assisted Language Learning, 2016
This study examines the differential impact of tutor labeling vs. non-labeling approaches on the performance; motivation beliefs; and cognitive, social, and teaching presence of low-achieving students. Two interactive tutoring strategy patterns are investigated based on the taxonomical e-moderating model of Salmon. In addition, the tutees' online…
Descriptors: Low Achievement, Student Behavior, Student Attitudes, Intervention
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – Grantee Submission, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Sequential Learning, Data Collection, Information Retrieval, Evaluation Methods
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
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Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Psychology, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
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