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Allison Liu; Jenny Yun-Chen Chan; Ji-Eun Lee; Lauren E. Decker-Woodrow; Shihfen Tu; Adam Sales; Craig A. Mason – Grantee Submission, 2022
The current study investigated how prior knowledge moderated the effects of three educational technologies ("From Here to There," "DragonBox 12+," and problem sets in "ASSISTments") on seventh-grade students' later algebraic knowledge. Pretest scores only moderated effects of "From Here to There," with…
Descriptors: Prior Learning, Program Effectiveness, Game Based Learning, Intervention
Panayiota Kendeou; Ellen Orcutt; Tracy Arner; Tong Li; Renu Balyan; Reese Butterfuss; Micah Watanabe; Danielle McNamara – Grantee Submission, 2022
In this paper, we present iSTART-Early, an intelligent tutoring system that provides automated instruction and practice on higher-order reading comprehension strategies to 3rd and 4th grade students. iSTART-Early provides personalized, interactive, game-based strategy instruction and practice on comprehension strategies (i.e., Ask It, Reword It,…
Descriptors: Intelligent Tutoring Systems, Reading Instruction, Reading Comprehension, Reading Strategies
Norum, Reilly; Lee, Ji-Eun; Ottmar, Erin – Grantee Submission, 2022
This preliminary study examined whether distinct student profiles (N = 760) emerged based on their behavioral patterns in an online algebraic learning game. We applied k-means clustering analysis to clickstream data collected in the game and then examined how students' behavioral patterns varied across the clusters using data visualization. The…
Descriptors: Computer Games, Game Based Learning, Student Characteristics, Visual Aids
Ji-Eun Lee; Aravind Stalin; Vy Ngo; Katharine Drzewiecki; Cindy Trac; Erin Ottmar – Grantee Submission, 2021
We apply an advanced data visualization technique, "Sankey diagram," to explore how middle-school students (N = 343) solved problems in a game-based algebraic notation tool. The results indicate that there is a large variation in the types of students' strategies to solve the problems, with some approaches being more efficient than…
Descriptors: Mathematics Instruction, Middle School Students, Problem Solving, Game Based Learning
Allison S. Liu; Kirk Vanacore; Erin Ottmar – Grantee Submission, 2022
Feedback in educational technologies can teach and engage students in math, but questions remain on how to present failure feedback that supports positive learning behaviors. We explore how error- and reward-based feedback influenced students' choices to replay completed problems in "From Here to There!," a math game-based educational…
Descriptors: Educational Technology, Technology Uses in Education, Feedback (Response), Failure
Sawrey, Katharine; Chan, Jenny Yun-Chen; Ottmar, Erin – Grantee Submission, 2020
The concept of equivalence can be elusive to students and can be confounded with unproductive understandings of the equals sign. Using the game-based digital algebraic notation system, From Here to There! (FH2T), students explore ideas of equivalence by dynamically transforming expressions or equations among mathematically equivalent states. In…
Descriptors: Mathematical Concepts, Symbols (Mathematics), Game Based Learning, Algebra
Laffey, James; Griffin, Joseph; Sigoloff, Justin; Sadler, Troy; Goggins, Sean; Womack, Andrew; Wulff, Eric – Grantee Submission, 2019
Mission HydroSci (MHS) teaches water systems and scientific argumentation towards meeting Next Generation Science Standards. MHS is a game-based 3D virtual environment for enacting transformational role-playing, wherein students must learn new knowledge and competencies in order to successfully complete the game missions. MHS was developed for…
Descriptors: Educational Games, Educational Technology, Technology Uses in Education, Role Playing
Jeremy Stoddard; Jais Brohinsky; Derek Behnke; David Shaffer; Codu Marquart; M. Shane Tutweiler; Jason Chen – Grantee Submission, 2022
In this paper, we describe the design for PurpleState, an internship simulation that applies the epistemic game model for informed civic learning. PurpleState places students in the role of interns at a political media firm and asks them to design a media campaign on a state level policy issue. Unlike the use of these models in STEM education,…
Descriptors: Citizenship Education, Educational Games, Teaching Methods, Persuasive Discourse
Wulff, Eric P.; Romine, William; Sadler, Troy D.; Womack, A. J.; Laffey, James M.; Goggins, Sean P.; Griffin, Joseph; Sigoloff, Justin – Grantee Submission, 2019
This study explores middle school student learning of Next Generation Science Standards aligned content and practices associated with use of an innovative virtual learning environment. The learning environment, a computer-based game called Mission HydroSci (MHS), was developed with the aim of supporting student learning of water systems science…
Descriptors: Academic Standards, Alignment (Education), Middle School Students, Computer Games
Erica L. Snow; Maria Ofelia Z. San Pedro; Matthew Jacovina; Danielle S. McNamara; Ryan S. Baker – Grantee Submission, 2015
This study investigates how we can effectively predict what type of game a user will choose within the game-based environment iSTART-2. Seventy-seven college students interacted freely with the system for approximately 2 hours. Two models (a baseline and a full model) are compared that include as features the type of games played, previous game…
Descriptors: Game Based Learning, Decision Making, Prediction, Student Attitudes
Roscoe, Rod D.; Allen, Laura K.; Johnson, Adam C.; McNamara, Danielle S. – Grantee Submission, 2018
This study evaluates high school students' perceptions of automated writing feedback, and the influence of these perceptions on revising, as a function of varying modes of computer-based writing instruction. Findings indicate that students' perceptions of automated feedback accuracy, ease of use, relevance, and understandability were favorable.…
Descriptors: High School Students, Student Attitudes, Writing Evaluation, Feedback (Response)
Matthew E. Jacovina; Erica L. Snow; G. Tanner Jackson; Danielle S. McNamara – Grantee Submission, 2015
To optimize the benefits of game-based practice within Intelligent Tutoring Systems (ITSs), researchers examine how game features influence students' motivation and performance. The current study examined the influence of game features and individual differences (reading ability and learning intentions) on motivation and performance. Participants…
Descriptors: Game Based Learning, Intelligent Tutoring Systems, Learning Motivation, Performance
Erica L. Snow; Danielle S. McNamara; Matthew E. Jacovina; Laura K. Allen; Amy M. Johnson; Cecile A. Perret – Grantee Submission, 2014
Metacognitive awareness has been shown to be a critical skill for academic success. However, students often struggle to regulate this ability during learning tasks. The current study investigates how features designed to promote metacognitive awareness can be built into the game-based intelligent tutoring system (ITS) iSTART-2. College students…
Descriptors: Educational Technology, Intelligent Tutoring Systems, Game Based Learning, College Students
Erica L. Snow; Mathew E. Jacovina; Laura K. Allen; Jianmin Dai; Danielle S. McNamara – Grantee Submission, 2014
This study investigates variations in how users exert agency and control over their choice patterns within the game-based ITS, iSTART-2, and how these individual differences relate to performance. Seventy-six college students interacted freely with iSTART-2 for approximately 2 hours. The current work captures and classifies variations in students'…
Descriptors: Personal Autonomy, College Students, Individual Differences, Game Based Learning