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Jon Wai; Joni M. Lakin – Grantee Submission, 2024
Students' talent and potential cannot be served until they are recognized by schools or caregivers. While the field of gifted education has had success in identifying talent among many students with talents in reading and mathematics, those with spatial talents are often overlooked. This article reviews how we might identify spatial talent using…
Descriptors: Spatial Ability, Identification, Talent, Student Evaluation
Matthew M. Grondin; Fangli Xia; Michael Swart; Mitchell J. Nathan – Grantee Submission, 2022
This full paper concerns the use of gesture analysis to guide instructional approaches in engineering education. Engineering is rife with abstract mathematics and processes for quantifying physical phenomena. In engineering instruction, "formalisms first" is a practice that privileges formalisms over grounded and applied ways of knowing…
Descriptors: Engineering Education, Student Evaluation, Nonverbal Communication, Formative Evaluation
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
Shute, Valerie; Lu, Xi; Rahimi, Seyedahmad – Grantee Submission, 2021
Stealth assessment is intended to not only measure important competencies, but also to support their development during gameplay or within other types of immersive learning environments. It uses evidence-centered assessment design to create the models (Mislevy, Steinberg, and Almond 2003), in conjunction with a statistical scoring and accumulation…
Descriptors: Student Evaluation, Game Based Learning, Evidence Based Practice, Evaluation Methods

Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2024
Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…
Descriptors: Student Evaluation, Computer Assisted Testing, Artificial Intelligence, Comprehension
Amy Adair; Michael Sao Pedro; Janice Gobert; Jessica A. Owens – Grantee Submission, 2023
Developing models and using mathematics are two key practices in internationally recognized science education standards such as the Next Generation Science Standards (NGSS, 2013). In this paper, we used a virtual performance-based formative assessment to capture students' competencies at both "developing" and "evaluating"…
Descriptors: Student Evaluation, Mathematical Models, Competence, Scientific Research
Christine M. White; Christopher Schatschneider – Grantee Submission, 2023
Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…
Descriptors: Screening Tests, Reading Tests, Reading Difficulties, Classification
Danielle S. McNamara; Tracy Arner; Reese Butterfuss; Ying Fang; Micah Watanabe; Natalie Newton; Kathryn S. McCarthy; Laura K. Allen; Rod D. Roscoe – Grantee Submission, 2022
The Interactive Strategy Training for Active Reading and Thinking (iSTART) game-based intelligent tutoring system (ITS) was developed with a foundation of comprehension theory and principles of learning science to improve students' comprehension of complex scientific texts. iSTART has been shown to improve reading comprehension for learners from…
Descriptors: Reading Strategies, Reading Instruction, Reading Programs, Reading Comprehension
Blair P. Lloyd; Jessica N. Torelli; Marney S. Pollack; Emily S. Weaver – Grantee Submission, 2022
For students with severe or complex challenging behavior, incorporating hypothesis testing as a component of functional behavior assessment (FBA) is often warranted. Several hypothesis testing strategies (i.e., functional analysis, antecedent analysis, concurrent operant analysis) can confirm whether and how features of a student's environment…
Descriptors: Behavior Disorders, Severe Disabilities, Functional Behavioral Assessment, Environmental Influences
Janice D. Gobert; Michael A. Sao Pedro; Haiying Li; Christine Lott – Grantee Submission, 2023
In this entry, we define Intelligent Tutoring Systems (ITSs) and present a description of their core components. We outline a history of the development of ITSs with a focus on key issues that have driven change and innovation in ITSs from their inception to present day. We also present a brief case study on a specific ITS, Inq-ITS (Inquiry…
Descriptors: Intelligent Tutoring Systems, Student Evaluation, Evaluation Methods, Natural Language Processing
Hollylynne S. Lee; Hamid Sanei; Lisa Famularo; Jessica Masters; Laine Bradshaw; Madeline Schellman – Grantee Submission, 2023
Assessing students' conceptions related to independence of events and determining probabilities from a sample space has been the focus of research in probability education for over 40 years. While we know a lot from past studies about predictable ways students may reason with well-known tasks, developing a diagnostic assessment that can be used by…
Descriptors: Probability, Concept Formation, Validity, Misconceptions
Tae Yeon Kwon; A. Corinne Huggins-Manley; Jonathan Templin; Mingying Zheng – Grantee Submission, 2023
In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…
Descriptors: Classification, Accuracy, Student Evaluation, Sequential Approach
Jamie Gillespie; Kevin Winn; Malinda Faber; Jessica Hunt – Grantee Submission, 2022
ASSISTments is a free online learning tool for improving students' mathematics achievement by providing immediate feedback and hints to students, detailed information on how students performed to teachers, and instructional suggestions for teachers to use. Researchers at the Friday Institute for Educational Innovation conducted an intrinsic,…
Descriptors: Formative Evaluation, Electronic Learning, Grade 7, Mathematics Teachers
Adrea J. Truckenmiller; Eunsoo Cho; Gary A. Troia – Grantee Submission, 2022
Although educators frequently use assessment to identify who needs supplemental instruction and if that instruction is working, there is a lack of research investigating assessment that informs what instruction students need. The purpose of the current study was to determine if a brief (approximately 20 min) task that reflects a common middle…
Descriptors: Middle School Teachers, Middle School Students, Test Validity, Writing (Composition)
Maria Blanton; Angela Murphy Gardiner; Ana Stephens; Rena Stroud; Eric Knuth; Despina Stylianou – Grantee Submission, 2023
We describe here lessons learned in designing an early algebra curriculum to measure early algebra's impact on children's algebra readiness for middle grades. The curriculum was developed to supplement regular mathematics instruction in Grades K-5. Lessons learned centered around the importance of several key factors, including using conceptual…
Descriptors: Mathematics Curriculum, Curriculum Design, Mathematics Instruction, Kindergarten