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Gulnur Tyulepberdinova; Madina Mansurova; Talshyn Sarsembayeva; Sulu Issabayeva; Darazha Issabayeva – Journal of Computer Assisted Learning, 2024
Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…
Descriptors: Artificial Intelligence, Algorithms, Predictor Variables, Physical Health
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Hubert Izienicki – Teaching Sociology, 2024
Many instructors use a syllabus quiz to ensure that students learn and understand the content of the syllabus. In this project, I move beyond this exercise's primary function and examine students' syllabus quiz scores to see if they can predict how well students perform in the course overall. Using data from 495 students enrolled in 18 sections of…
Descriptors: Tests, Course Descriptions, Performance, Predictor Variables
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Harun Cigdem; Umut Birkan Ozkan – Journal of Interactive Learning Research, 2024
Online formative quizzes have been shown to be an effective tool for improving students' academic achievement. This quasi-experimental study investigated the effects of students' engagement in online formative quizzes on academic achievement in an undergraduate engineering course, employing a one-group post-test research design. Participants (n =…
Descriptors: Engineering Education, Formative Evaluation, Computer Assisted Testing, Learner Engagement
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Bag, Sudin; Aich, Payel; Islam, Md. Aminul – Journal of Applied Research in Higher Education, 2022
Purpose: The aim of the study is to examine the intention of students toward the online education system with emphasis on online examination in higher education. The study investigated different constructs that have an influence on the use of the online platform for learning to the specific domain that mitigates the personal needs of the learners…
Descriptors: Intention, Student Attitudes, College Students, Online Courses
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Laura L. Beaton – Journal of Educational Technology Systems, 2025
Online quizzes and learning platforms provided by textbook publishers have become common components of undergraduate education. Here, I examine how participation in these formative assessments related to student course performance. Over multiple semesters, students completed either free online unlimited attempt quizzes or assignments from a…
Descriptors: Formative Evaluation, Computer Assisted Testing, Tests, Student Evaluation
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Alamri, Hamdan – Education and Information Technologies, 2023
Drawing on social cognitive theory, this study investigated instructors' online teaching self-efficacy during the sudden, COVID-19-induced transition to online teaching. The pandemic has forced instructors to shift to online teaching, arming them with valuable hands-on experience in this alternative teaching mode. This study examined instructors'…
Descriptors: Teacher Effectiveness, Self Efficacy, Online Courses, COVID-19
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Schrempft, S.; Piumatti, G.; Gerbase, M. W.; Baroffio, A. – Advances in Health Sciences Education, 2021
This study examined conscientiousness and the perceived educational environment as independent and interactive predictors of medical students' performance within Biggs' theoretical model of learning. Conscientiousness, the perceived educational environment, and learning approaches were assessed at the beginning of the third year in 268 medical…
Descriptors: Undergraduate Students, Medical Students, Educational Environment, Predictor Variables
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Isaacs, Talia; Hu, Ruolin; Trenkic, Danijela; Varga, Julia – Language Testing, 2023
The COVID-19 pandemic has changed the university admissions and proficiency testing landscape. One change has been the meteoric rise in use of the fully automated Duolingo English Test (DET) for university entrance purposes, offering test-takers a cheaper, shorter, accessible alternative. This rapid response study is the first to investigate the…
Descriptors: Predictive Validity, Educational Technology, Handheld Devices, Language Tests
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Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics
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Sense, Florian; van der Velde, Maarten; van Rijn, Hedderik – Journal of Learning Analytics, 2021
Modern educational technology has the potential to support students to use their study time more effectively. Learning analytics can indicate relevant individual differences between learners, which adaptive learning systems can use to tailor the learning experience to individual learners. For fact learning, cognitive models of human memory are…
Descriptors: Predictor Variables, Undergraduate Students, Learning Analytics, Cognitive Psychology
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Dalman, Mohammadreza; Kang, Okim – International Journal of Listening, 2023
This study investigated U.S. undergraduates' perceptions of non-native speakers' (NNS) speech which had received 100% proficiency scores on the TOEFL iBT test. Fifty-five U.S. undergraduates rated 20 speech samples for comprehensibility, accentedness, and acceptability. The speech samples were also analyzed for acoustic fluency. Descriptively,…
Descriptors: Undergraduate Students, Student Attitudes, Scores, Speech Communication
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Vandeweerd, Nathan; Housen, Alex; Paquot, Magali – Language Testing, 2023
This study investigates whether re-thinking the separation of lexis and grammar in language testing could lead to more valid inferences about proficiency across modes. As argued by Römer, typical scoring rubrics ignore important information about proficiency encoded at the lexis-grammar interface, in particular how the co-selection of lexical and…
Descriptors: French, Language Tests, Grammar, Second Language Learning
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Morales-Martinez, Guadalupe Elizabeth; Lopez-Ramirez, Ernesto Octavio; Mezquita-Hoyos, Yanko Norberto; Lopez-Perez, Rafael; Resendiz, Ana Yolanda Lara – European Journal of Educational Research, 2019
A sample of 327 engineering bachelor students from a public university in Mexico took part in an information integration study to explore systematic thinking underlying propensity for cheating during a course exam. All study participants were provided with written descriptions of 12 scenarios pertaining to the academic evaluation criteria and were…
Descriptors: Undergraduate Students, Engineering Education, Cheating, Computer Assisted Testing
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Park, Enoch; Martin, Florence; Lambert, Richard – Quarterly Review of Distance Education, 2019
The purpose of this study was to identify the potential factors that could predict college students' success in a large-size undergraduate hybrid learning course. Predictive values of students' demographic and academic background variables were examined to establish standardized models of contribution toward final grades. Next, patterns of student…
Descriptors: Predictor Variables, Academic Achievement, Undergraduate Students, Student Participation
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Dore, Kelly L.; Reiter, Harold I.; Kreuger, Sharyn; Norman, Geoffrey R. – Advances in Health Sciences Education, 2017
Typically, only a minority of applicants to health professional training are invited to interview. However, pre-interview measures of cognitive skills predict for national licensure scores (Gauer et al. in "Med Educ Online" 21 2016) and subsequently licensure scores predict for performance in practice (Tamblyn et al. in "JAMA"…
Descriptors: Allied Health Occupations Education, Interviews, Cognitive Ability, Predictor Variables
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