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Beal, Jennifer S.; Scott, Jessica A.; Spell, Kelly – Journal of Deaf Studies and Deaf Education, 2021
The present study used an observational learning framework to investigate changes in non-native signing deaf children's narrative renditions before (Time 1) and after (Time 2) a single viewing of a signing adult's rendition of the same story. The deaf adult model rendered the picture book "Goodnight Gorilla" in American Sign Language…
Descriptors: Deafness, Children, American Sign Language, Picture Books
Zachary Conrad – ProQuest LLC, 2021
In the past twenty-five years, assessment developers and educators have been seeking ways to make assessments more informative and to advance understandings of students' cognitive processes (Ercikan, 2006; Leighton & Gierl, 2007). Demands for personalized formative assessment feedback have stimulated interest in the application of diagnostic…
Descriptors: Evaluation, Test Validity, Feedback (Response), Individualized Instruction
Ayaz, A. Salman; Venkat, Jaya A.; Gulzar, Zameer – International Journal of Information and Communication Technology Education, 2020
The information available online is mostly present in an unstructured form and search engines are indispensable tools especially in higher education organizations for obtaining information from the Internet. Various search engines were developed to help learners to retrieve the information but unfortunately, most of the information retrieved is…
Descriptors: Search Engines, Information Retrieval, Internet, Classification
Rohlfing, Ingo – Field Methods, 2020
Empirical researchers using qualitative comparative analysis (QCA) can work with crisp, multivalue, and fuzzy sets. The relative advantages of crisp and multivalue sets have been discussed in the QCA literature. There has been little reflection on the more frequent decision between crisp and fuzzy sets for which there often is no theoretical…
Descriptors: Qualitative Research, Comparative Analysis, Reliability, Classification
Diego G. Campos; Tim Fütterer; Thomas Gfrörer; Rosa Lavelle-Hill; Kou Murayama; Lars König; Martin Hecht; Steffen Zitzmann; Ronny Scherer – Educational Psychology Review, 2024
Systematic reviews and meta-analyses are crucial for advancing research, yet they are time-consuming and resource-demanding. Although machine learning and natural language processing algorithms may reduce this time and these resources, their performance has not been tested in education and educational psychology, and there is a lack of clear…
Descriptors: Artificial Intelligence, Algorithms, Computer System Design, Natural Language Processing
Gerardo Ibarra-Vazquez; María Soledad Ramírez-Montoya; Hugo Terashima – Education and Information Technologies, 2024
This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following…
Descriptors: Foreign Countries, College Students, Private Colleges, Gender Bias
Eisuke Saito; Jennifer Mansfield; Richard O'Donovan – Interactive Learning Environments, 2024
By assessing student engagement with learning tasks along with students' understanding of subject matter before and during teaching, teachers are able to shift their teaching approaches through improvisational pedagogical reasoning in real time. However, if a teacher does not know how to respond to students' cues, their capacity to effectively…
Descriptors: Educational Practices, Teaching Methods, Reflective Teaching, Decision Making
Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Sarah C. Adcock – ProQuest LLC, 2024
Over the past twenty-five years, many academic libraries have shifted from print to digital collections. One consequence of this change has been the increased use of a library's website to access books, journals, and databases in a digital format. Thus, library space, once used to house print material, is now available for other purposes, creating…
Descriptors: Academic Libraries, Medical Libraries, Space Utilization, Library Automation
Nicole Schroeder – ProQuest LLC, 2024
Background and Purpose: Physical therapy (PT) student academic and clinical success is dependent on their ability to develop clinical reasoning in the first year, especially prior to the first clinical education experience. However, literature has revealed a very low ability of learners to spontaneously transfer basic science knowledge into…
Descriptors: Physical Therapy, Allied Health Personnel, Allied Health Occupations Education, Thinking Skills
Mary Elizabeth Lockhart; Karen Rambo-Hernandez – European Journal of Engineering Education, 2024
Engineering identity is a rapidly evolving construct within engineering, primarily due to its link to engineering persistence. Yet, most engineering identity research has been qualitative in nature or has described individuals within the analytical technique as coming from a single population. This study is the first to allow for the detection of…
Descriptors: Engineering Education, Self Concept, College Freshmen, Gender Differences
Cross-Classified Item Response Theory Modeling with an Application to Student Evaluation of Teaching
Sijia Huang; Li Cai – Journal of Educational and Behavioral Statistics, 2024
The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…
Descriptors: Classification, Data Collection, Data Analysis, Item Response Theory
Alison C. Witte – Learning Assistance Review, 2024
This article reports on data collected from a study of 101 students taking a first-year experience course. Using a mapping methodology in an effort to understand what resources students could identify and what relationships they saw between resources, the study showed that resources associated with a specific location or connected with people were…
Descriptors: Undergraduate Students, First Year Seminars, School Orientation, Academic Support Services
Giannis Karagiannakis; Marie-Pascale Noël; Anna Baccaglini-Frank; Cristiano Termine – Discover Education, 2024
By the end of primary school, children are expected to acquire a range of mathematical skills that progressively develop. This study aimed to gain insight into how a large number of numerical and geometrical measures are grouped and whether the structures shift or remain invariant along child's development based on the data obtained from a sample…
Descriptors: Mathematics Skills, Classification, Elementary School Students, Geometry