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Fu Chen; Chang Lu; Ying Cui – Education and Information Technologies, 2024
Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…
Descriptors: Computer Assisted Testing, Problem Solving, Learning Analytics, Learning Processes
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
Abdessamad Chanaa; Nour-eddine El Faddouli – Journal of Education and Learning (EduLearn), 2024
Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning…
Descriptors: Electronic Learning, Evaluation Methods, Artificial Intelligence, Taxonomy
Emily R. Forcht; Ethan R. Van Norman – Psychology in the Schools, 2024
The present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end-of-year proficiency in reading and math. Participants included 13,009 students in Grades 3-8 who had at least one fall screening score and end-of-year…
Descriptors: Computer Assisted Testing, Adaptive Testing, Diagnostic Tests, Screening Tests
Umar Bin Qushem; Solomon Sunday Oyelere; Gökhan Akçapinar; Rogers Kaliisa; Mikko-Jussi Laakso – Technology, Knowledge and Learning, 2024
Predicting academic performance for students majoring in computer science has long been a significant field of research in computing education. Previous studies described that accurate prediction of students' early-stage performance could identify low-performing students and take corrective action to improve performance. Besides, adopting machine…
Descriptors: Predictor Variables, Learning Analytics, At Risk Students, Computer Science
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
Witmer, Sara E.; Bouck, Emily C. – Assessment for Effective Intervention, 2023
One perceived advantage of computer-based testing is that accessibility tools can be embedded within the testing format, allowing students with disabilities to use them when necessary to remove unique barriers within testing. However, an important assumption is that students activate and use the tools when needed. Initial data from large-scale…
Descriptors: Predictor Variables, Accessibility (for Disabled), Computer Assisted Testing, Access to Computers
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
Dixon, Chris; Oxley, Emily; Nash, Hannah; Gellert, Anna Steenberg – Journal of Learning Disabilities, 2023
Traditional static tests of reading and reading-related skills offer some ability to predict future reading performance, though such screeners may misclassify children with or at risk of reading disorder (RD). Dynamic assessment (DA) is an alternative approach that measures learning potential and may be less dependent on learning background. A…
Descriptors: Evaluation Methods, Identification, Reading Difficulties, Literature Reviews
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
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
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
Daniels, Lia M.; Bulut, Okan – Journal of Computer Assisted Learning, 2020
In computer-based testing (CBT) environments instructors can provide students with feedback immediately. Commonly, instructors give students their percentage correct without additional descriptive feedback. Our objectives were (a) to compare students' perceived usefulness of a percentage-only score report vs. a descriptive feedback report in a CBT…
Descriptors: Computer Assisted Testing, Feedback (Response), Value Judgment, Student Attitudes
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
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables