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Showing 1 to 15 of 140 results Save | Export
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Kevin Ng – Education Economics, 2025
This study evaluates techniques to identify high-quality teachers. Since tenure restricts dismissals of experienced teachers, schools must predict productivity and dismiss those expected to perform ineffectively prior to tenure receipt. Many states rely on evaluation scores to guide these personnel decisions without considering other dimensions of…
Descriptors: Identification, Teacher Effectiveness, Teacher Selection, Teacher Evaluation
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Kelsey Medeiros; David H. Cropley; Rebecca L. Marrone; Roni Reiter-Palmon – Journal of Creative Behavior, 2025
Much has been made of the apparent capacity for creativity of generative AI. However, as research expands the knowledge base regarding the capabilities and performance of this technology, the prevailing view is shifting away from "AI is creative" and towards a more balanced model of Human-AI co-creativity. Nevertheless, even this…
Descriptors: Man Machine Systems, Creativity, Artificial Intelligence, Models
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Majid Ghasemy; James Eric Gaskin; James A. Elwood – Journal of Applied Research in Higher Education, 2024
Purpose: The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job…
Descriptors: Industrial Psychology, Models, Higher Education, Job Satisfaction
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Anthony, Bokolo, Jr.; Kamaludin, Adzhar; Romli, Awanis – Technology, Knowledge and Learning, 2023
Blended Learning (BL) has been implemented by lecturers in higher educations for promoting effective pedagogical practices. However, intention to use and actual usage of BL by lecturers in higher education seems to be a major setback for successful BL implementation. Therefore, this study developed a model to examine the factors that influences…
Descriptors: Higher Education, Intention, Predictor Variables, Blended Learning
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Al Zeer, Imad; Ajouz, Mousa; Salahat, Mahmoud – International Journal of Educational Management, 2023
Purpose: Considering the importance of employee performance in the changes in state higher education institutions, this study aims to conceptualize the mediating role of employee engagement and empowerment in predicting employee performance. Design/methodology/approach: The study uses a quantitative survey method to collect data from staff members…
Descriptors: Employees, Work Attitudes, Empowerment, Predictor Variables
Keith David Reeves – ProQuest LLC, 2021
Traditional letter and number grades are inaccurate and harmful to children, while research indicates that standards-based grading is both more accurate and better for all stakeholders. However, despite standards-based report cards (SBRCs) coming in many forms, the best number and arrangement of performance level descriptors (PLDs) remains…
Descriptors: Academic Standards, Report Cards, Models, Standardized Tests
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Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
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Vaziri, Stacey; Vaziri, Baback; Novoa, Luis J.; Torabi, Elham – INFORMS Transactions on Education, 2022
The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically,…
Descriptors: Student Motivation, Introductory Courses, Business Administration Education, Data Analysis
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Siebra, Clauirton Albuquerque; Santos, Ramon N.; Lino, Natasha C. Q. – International Journal of Distance Education Technologies, 2020
This work proposes a dropout prediction approach that is able to self-adjust their outcomes at any moment of a degree program timeline. To that end, a rule-based classification technique was used to identify courses, grade thresholds and other attributes that have a high influence on the dropout behavior. This approach, which is generic so that it…
Descriptors: Dropouts, Predictor Variables, At Risk Students, Distance Education
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Walsh, Bridget; Christ, Sharon; Weber, Christine – Journal of Speech, Language, and Hearing Research, 2021
Purpose: The purpose of this study is to investigate how epidemiological and clinical factors collectively predict whether a preschooler who is stuttering will persist or recover and to provide guidance on how clinicians can use these factors to evaluate a child's risk for stuttering persistence. Method: We collected epidemiological and clinical…
Descriptors: Stuttering, At Risk Persons, Preschool Children, Persistence
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Mandalapu, Varun; Chen, Lujie Karen; Chen, Zhiyuan; Gong, Jiaqi – International Educational Data Mining Society, 2021
With the increasing adoption of Learning Management Systems (LMS) in colleges and universities, research in exploring the interaction data captured by these systems is promising in developing a better learning environment and improving teaching practice. Most of these research efforts focused on course-level variables to predict student…
Descriptors: Integrated Learning Systems, Interaction, Undergraduate Students, Minority Group Students
Rubin, Marc – New England Journal of Higher Education, 2017
The "2018 Guide to New England Colleges & Universities" data published by "Boston" magazine in association with the New England Board of Higher Education provided the author the opportunity to examine the schools' "prices," defined as "tuition plus fees," as a function of several independent factors. By…
Descriptors: Fees, Institutional Characteristics, Paying for College, Student Costs
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Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
Ong, Adrian; Circelli, Michelle – National Centre for Vocational Education Research (NCVER), 2018
People participate in vocational education and training (VET) for a variety of reasons and at different stages of their life. Some undertake VET to gain the vocational skills necessary to enter the labour market for the first time, while others enter in order to upgrade existing skills, learn new ones, or simply for personal interest. Successful…
Descriptors: Qualifications, Vocational Education, Graduation Rate, Performance Factors
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Natale, Vickie C.; Jones, Stephanie J. – Community College Journal of Research and Practice, 2018
The study examined how institutional and student characteristics may influence the earning of student success points by state-supported community colleges under the Texas performance funding system that was fully implemented in the 2016-2017 biennium. Texas has historically funded community colleges based on an enrollment formula; however, the…
Descriptors: Institutional Characteristics, Student Characteristics, Community Colleges, Two Year College Students
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