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Allen, Laura K.; Perret, Cecile; Likens, Aaron; McNamara, Danielle S. – Grantee Submission, 2017
In this study, we investigated the degree to which the cognitive processes in which students engage during reading comprehension could be examined through dynamical analyses of their natural language responses to texts. High school students (n = 142) generated typed self-explanations while reading a science text. They then completed a…
Descriptors: Discourse Analysis, Cognitive Processes, Reading Comprehension, High School Students
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Kurby, Christopher A.; Magliano, Joseph P.; Dandotkar, Srikanth; Woehrle, James; Gilliam, Sara; McNamara, Danielle S. – Journal of Educational Computing Research, 2012
This study assessed whether and how self-explanation reading training, provided by iSTART (Interactive Strategy Training for Active Reading and Thinking), improves the effectiveness of comprehension processes. iSTART teaches students how to self-explain and which strategies will most effectively aid comprehension from moment-to-moment. We used…
Descriptors: Computer Assisted Testing, Federal Aid, Control Groups, Experimental Groups
Snow, Erica L. – International Educational Data Mining Society, 2015
Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…
Descriptors: Intelligent Tutoring Systems, Models, Individualized Instruction, Needs Assessment
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Jackson, G. Tanner; McNamara, Danielle S. – Journal of Educational Psychology, 2013
One strength of educational games stems from their potential to increase students' motivation and engagement during educational tasks. However, game features may also detract from principle learning goals and interfere with students' ability to master the target material. To assess the potential impact of game-based learning environments, in this…
Descriptors: Intelligent Tutoring Systems, Educational Games, Student Motivation, Learning
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Jackson, G. Tanner; Snow, Erica L.; Varner, Laura K.; McNamara, Danielle S. – Grantee Submission, 2013
Intelligent Tutoring Systems (ITSs) have begun to develop hybrid systems that balance the learning benefits of ITSs with the motivational benefits of games. iSTART-ME (Motivationally Enhanced) is a new game-based learning environment developed on top of an existing ITS for reading comprehension (iSTART). In an 11 session lab-based study, 40 high…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Educational Games
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Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2016
Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…
Descriptors: Student Behavior, Pretests Posttests, High School Students, Teaching Methods
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Jackson, G. Tanner; McNamara, Danielle S. – Grantee Submission, 2017
By combining the benefits from Intelligent Tutoring Systems (ITSs) and video games, educational games offer the unique potential to capture learners' interest, compel them to persist with targeted tasks, and can result in improved mastery of educational content and skills. These benefits are described within the context of educational game…
Descriptors: Educational Games, Intelligent Tutoring Systems, Educational Benefits, Learning Motivation
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages…
Descriptors: Reading Comprehension, Reading Skills, Natural Language Processing, Intelligent Tutoring Systems
Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2015
Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…
Descriptors: High School Students, Pretests Posttests, Teaching Methods, Technology Uses in Education
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Scott A. Crossley; Danielle S. McNamara – Grantee Submission, 2016
The purpose of this handbook is to provide actionable information to educators, administrators, and researchers about current, available research-based educational technologies that provide adaptive (personalized) instruction to students on literacy, including reading comprehension and writing. This handbook is comprised of chapters by leading…
Descriptors: Educational Technology, Literacy, Reading Comprehension, Writing Skills
Snow, Erica L.; Jackson, G. Tanner; McNamara, Danielle S. – Grantee Submission, 2014
Self-regulative behaviors are dynamic and evolve as a function of time and context. However, dynamical fluctuations in behaviors are often difficult to measure and therefore may not be fully captured by traditional measures alone. Utilizing system log data and two novel statistical methodologies, this study examined emergent patterns of controlled…
Descriptors: Educational Technology, Computer Uses in Education, Educational Games, Intelligent Tutoring Systems
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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
Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; McNamara, Danielle S. – Grantee Submission, 2015
When students exhibit control and employ a strategic plan of action over a situation they are said to be demonstrating agency (Bandura, 2001). The current work is comprised of two studies designed to investigate how agency manifests within students' choice patterns and ultimately influences self-explanation quality within the game-based system…
Descriptors: Performance, Decision Making, Video Games, Educational Games
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Snow, Erica L.; Jacovina, Matthew E.; Jackson, G. Tanner; McNamara, Danielle S. – Grantee Submission, 2016
This chapter provides an overview of the Interactive Strategy Tutor for Active Reading and Thinking-2 (iSTART-2). iSTART-2 is a game-based tutoring system designed to improve students' reading comprehension skills. It does so by providing them with instruction on how to self-explain using comprehension strategies. In this chapter, we first discuss…
Descriptors: Reading Comprehension, Reading Strategies, Reading Instruction, Educational Games
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Jackson, G. Tanner; Varner, Laura K.; Boonthum-Denecke, Chutima; McNamara, Danielle S. – Grantee Submission, 2013
Educational games have the potential to provide motivating, effective training; however, the efficacy of these systems is unclear, and evaluations often fail to identify the relative impact of individual differences on learning outcomes. The current study aims to address these issues by comparing the learning gains from an educational game…
Descriptors: Educational Games, Intelligent Tutoring Systems, Program Effectiveness, High School Students
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