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Yangmeng Xu; Stefanie A. Wind – Educational Measurement: Issues and Practice, 2025
Double-scoring constructed-response items is a common but costly practice in mixed-format assessments. This study explored the impacts of Targeted Double-Scoring (TDS) and random double-scoring procedures on the quality of psychometric outcomes, including student achievement estimates, person fit, and student classifications under various…
Descriptors: Academic Achievement, Psychometrics, Scoring, Evaluation Methods
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Alexandra Jackson; Cheryl Bodnar; Elise Barrella; Juan Cruz; Krista Kecskemety – Journal of STEM Education: Innovations and Research, 2025
Recent curricular interventions in engineering education have focused on encouraging students to develop an entrepreneurial mindset (EM) to equip them with the skills needed to generate innovative ideas and address complex global problems upon entering the workforce. Methods to evaluate these interventions have been inconsistent due to the lack of…
Descriptors: Engineering Education, Entrepreneurship, Concept Mapping, Student Evaluation
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Koen Suzelis; Gabriel Mott; John Curiel – Journal of Academic Ethics, 2025
Student evaluations of teaching (SET) act as the primary means to gauge instructor effectiveness. Likewise, SETs provide the primary qualitative feedback to instructors via student comments. However, mostly students with strong feelings tend to write comments. Among the most recallable are toxic comments: comments that are unhelpful/hurtful in…
Descriptors: Student Evaluation of Teacher Performance, Automation, Identification, Student Attitudes
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Jonathan K. Foster; Peter Youngs; Rachel van Aswegen; Samarth Singh; Ginger S. Watson; Scott T. Acton – Journal of Learning Analytics, 2024
Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…
Descriptors: Learning Analytics, Automation, Classification, Artificial Intelligence
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Di Rezze, Briano; Gentles, Stephen James; Hidecker, Mary Jo Cooley; Zwaigenbaum, Lonnie; Rosenbaum, Peter; Duku, Eric; Georgiades, Stelios; Roncadin, Caroline; Fang, Hanna; Tajik-Parvinchi, Diana; Viveiros, Helena – Journal of Autism and Developmental Disorders, 2022
The Autism Classification System of Functioning: Social Communication (ACSF) describes social communication functioning levels. First developed for preschoolers with ASD, this study tests an expanded age range (2-to-18 years). The ACFS rates the child's typical and best (i.e., capacity) performance. Qualitative methods tested parent and clinician…
Descriptors: Content Validity, Reliability, Autism Spectrum Disorders, Classification
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Gresse Von Wangenheim, Christiane; Da Cruz Alves, Nathalia; Rauber, Marcelo F.; Hauck, Jean C. R.; Yeter, Ibrahim H. – Informatics in Education, 2022
Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for…
Descriptors: Performance Based Assessment, Artificial Intelligence, Learning Processes, Scoring Rubrics
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Albudoor, Nahar; Peña, Elizabeth D. – Journal of Speech, Language, and Hearing Research, 2022
Purpose: The differential diagnosis of developmental language disorder (DLD) in bilingual children represents a unique challenge due to their distributed language exposure and knowledge. The current evidence indicates that dual-language testing yields the most accurate classification of DLD among bilinguals, but there are limited personnel and…
Descriptors: Language Impairments, Bilingualism, Clinical Diagnosis, Language Tests