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Mussa Saidi Abubakari; Gamal Abdul Nasir Zakaria; Juraidah Musa – Discover Education, 2025
In the contemporary world of digitalisation, comprehensive digital competence (DC) is and should be an integral part of students' repertoire to guarantee not only academic but also professional success. However, the level and requirements for DC may vary within specific educational contexts, especially in culturally oriented institutions. This…
Descriptors: College Students, Digital Literacy, Student Evaluation, Foreign Countries
Liqing Qiu; Lulu Wang – IEEE Transactions on Education, 2025
In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Questioning Techniques, Student Evaluation
Student Approaches to Generating Mathematical Examples: Comparing E-Assessment and Paper-Based Tasks
George Kinnear; Paola Iannone; Ben Davies – Educational Studies in Mathematics, 2025
Example-generation tasks have been suggested as an effective way to both promote students' learning of mathematics and assess students' understanding of concepts. E-assessment offers the potential to use example-generation tasks with large groups of students, but there has been little research on this approach so far. Across two studies, we…
Descriptors: Mathematics Skills, Learning Strategies, Skill Development, Student Evaluation
Juuso Henrik Nieminen – Studies in Higher Education, 2025
Assessment of student learning is commonly understood as a seemingly objective measurement of learning outcomes. It is seen as fair that assessment targets students' abilities -- not their identities or personalities. This idea fails to acknowledge how assessment transforms its object, the students, often in unintended ways. While higher education…
Descriptors: Foreign Countries, College Students, Student Evaluation, Self Concept
Michelle Cheong – Journal of Computer Assisted Learning, 2025
Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…
Descriptors: Artificial Intelligence, Performance Based Assessment, Spreadsheets, Models
Achmad Bisri; Supardi; Yayu Heryatun; Hunainah; Annisa Navira – Journal of Education and Learning (EduLearn), 2025
In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…
Descriptors: Data Analysis, Models, Academic Achievement, Evaluation Methods
Ana Jesús López-Menéndez; Rigoberto Pérez-Suárez – Review of Education, 2025
Econometrics has become increasingly important in Economics and Business degrees, since it appears to be narrowly related to several main skills and competencies as information management, creativity, problem-solving or decision-making. Furthermore, the development of information technologies, including econometric software, makes it possible to…
Descriptors: Teamwork, Economics, Models, Information Management
Katherine E. Castellano; Daniel F. McCaffrey; Joseph A. Martineau – Educational Measurement: Issues and Practice, 2025
Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of…
Descriptors: Student Evaluation, Growth Models, Student Educational Objectives, Educational Indicators
Khalid Alalawi; Rukshan Athauda; Raymond Chiong; Ian Renner – Education and Information Technologies, 2025
Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…
Descriptors: Intervention, Learning Analytics, Guidelines, Prediction
Soomin Jwa – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2025
With increasing attention to student engagement with feedback, the need for a paradigm shift problematizing the transmissive view of feedback has been voiced. Recent perspectives hold that feedback is a dialogic process and opportunities for dialogue promote students' knowledge-making processes in their engagement with feedback. Theoretically…
Descriptors: Written Language, Feedback (Response), Learner Engagement, Models
Katia Ciampa; Zora Wolfe; Meagan Hensley – Technology, Pedagogy and Education, 2025
This study explores the role of artificial intelligence (AI) in K-12 student assessment practices, focusing on educators' use of AI tools. Through content analysis of active Facebook groups dedicated to AI in education, the authors examined how educators integrate AI into assessment across various grade levels and subjects. Using the Technology…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Kindergarten