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Direct linkCheng, Chao-Yang; Chen, Jim-Ming; Chen, Sherry Y. – Interactive Learning Environments, 2023
Online tests offer many advantages but they still belong to assessment, which may make learners have anxiety. Thus, students may experience certain emotion. Academic emotion is a branch of emotion and has great effects on student learning. Such effects can be associated with individual differences, especially prior knowledge. To this end, this…
Descriptors: College Students, Prior Learning, Academic Achievement, Emotional Response
Moon, Jung Aa; Lindner, Marlit Annalena; Arslan, Burcu; Keehner, Madeleine – Educational Measurement: Issues and Practice, 2022
Many test items use both an image and text, but present them in a spatially separate manner. This format could potentially cause a split-attention effect in which the test taker's cognitive load is increased by having to split attention between the image and text, while mentally integrating the two sources of information. We investigated the…
Descriptors: Computer Assisted Testing, Cognitive Processes, Difficulty Level, Attention
Download full textKaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
Zur, Amir; Applebaum, Isaac; Nardo, Jocelyn Elizabeth; DeWeese, Dory; Sundrani, Sameer; Salehi, Shima – International Educational Data Mining Society, 2023
Detailed learning objectives foster an effective and equitable learning environment by clarifying what instructors expect students to learn, rather than requiring students to use prior knowledge to infer these expectations. When questions are labeled with relevant learning goals, students understand which skills are tested by those questions.…
Descriptors: Equal Education, Prior Learning, Educational Objectives, Chemistry
Jonathan Serfaty; Raquel Serrano – Language Learning & Technology, 2024
Digital flashcard apps allow students to learn and practice foreign language vocabulary independently and efficiently, leaving more classroom time for communicative activities. However, words learned this way may be forgotten. Previous lab studies have shown that vocabulary retrieval practice can be optimized for long-term memory by employing…
Descriptors: Computer Assisted Testing, Computer Software, Vocabulary Development, Secondary School Students
Abdulhadi Shoufan – ACM Transactions on Computing Education, 2023
With the immense interest in ChatGPT worldwide, education has seen a mix of both excitement and skepticism. To properly evaluate its impact on education, it is crucial to understand how far it can help students without prior knowledge answer assessment questions. This study aims to address this question as well as the impact of the question type.…
Descriptors: Prior Learning, Artificial Intelligence, Technology Uses in Education, Computer Assisted Testing
Kempegowda, Swetha Nagarahalli; Ramachandra, Shobha Chikkavaddaragudi; Arun, Brunda; Devaraju, Abhijith; Shivashankar, Kusuma Kasapura; Raghunathachar, Sahana Kabbathy; Bettadapura, Anjalidevi Shankarrao; Puttalingaiah, Sujatha; Devegowda, Devananda; Vishwanath, Prashant; Nataraj, Suma Maduvanahalli; Prashant, Akila – Biochemistry and Molecular Biology Education, 2023
Online assessments are needed during the prevailing pandemic situation to continue educational activities while ensuring safety. After conducting the online practical assessment (OPrA) in Biochemistry, we analyzed the students' responses. The blueprint of the OPrA was prepared by the faculty, referring to the various levels and domains of Bloom's…
Descriptors: Biochemistry, Science Instruction, Science Tests, Feedback (Response)
Saerys-Foy, Jeffrey E.; LoCasto, Paul C.; Burn, David; Ferranti, Daniella – Discourse Processes: A Multidisciplinary Journal, 2022
According to theories of validation, people routinely check incoming information against prior knowledge during comprehension. On these theories, information is validated if it fits with prior knowledge. Some researchers argue that information needs to be successfully validated before being incorporated into the situation model. We report five…
Descriptors: Fantasy, Reading Rate, Prior Learning, Reading Comprehension
Sherry Y. Chen; Chia-Yi Tseng; Chao-Yang Cheng – Interactive Learning Environments, 2023
This study proposed a three-tier test to help students learn English grammar. To reduce students' anxiety, game-based learning was incorporated into the three-tier test, where personalization was also implemented to accommodate students' different needs. More specifically, we developed a Personalized Entertaining Three-Tier Test (PET3), which…
Descriptors: English (Second Language), Language Tests, Grammar, Game Based Learning
Duy M. Pham; Kirk P. Vanacore; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Effective personalization of education requires knowing how each student will perform under certain conditions, given their specific characteristics. Thus, the demand for interpretable and precise estimation of heterogeneous treatment effects is ever-present. This paper outlines a new approach to this problem based on the Leave-One-Out Potential…
Descriptors: Middle School Students, Middle School Teachers, Middle School Mathematics, Algebra
Mertens, Ute; Finn, Bridgid; Lindner, Marlit Annalena – Journal of Educational Psychology, 2022
Feedback is one of the most important factors for successful learning. Contemporary computer-based learning and testing environments allow the implementation of automated feedback in a simple and efficient manner. Previous meta-analyses suggest that different types of feedback are not equally effective. This heterogeneity might depend on learner…
Descriptors: Computer Assisted Testing, Feedback (Response), Electronic Learning, Network Analysis
