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Peer reviewed
Direct linkHernandez-Gonzalez, Jeronimo; Herrera, Pedro Javier – IEEE Transactions on Learning Technologies, 2023
In peer assessment, students assess a task done by their peers, provide feedback and usually a grade. The extent to which these peer grades can be used to formally grade the task is unclear, with doubts often arising regarding their validity. The instructor could supervise the peer assessments, but would not then benefit from workload reduction,…
Descriptors: Peer Evaluation, Supervision, Models, Computation
Pallavi Singh; Phat K. Huynh; Dang Nguyen; Trung Q. Le; Wilfrido Moreno – IEEE Transactions on Learning Technologies, 2025
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria integer programming (MCIP), which simultaneously accommodates multiple criteria, thereby innovatively addressing the complex task of…
Descriptors: Teamwork, Group Dynamics, Research Design, Models
Davi Bernardo Silva; Deborah Ribeiro Carvalho; Carlos N. Silla – IEEE Transactions on Learning Technologies, 2024
Throughout a programming course, students develop various source code tasks. Using these tasks to track students' progress can provide clues to the strengths and weaknesses found in each learning topic. This practice allows the teacher to intervene in learning in the first few weeks of class and maximize student gains. However, the biggest…
Descriptors: Computation, Models, Ability Grouping, Programming
Oliveira Moraes, Laura; Pedreira, Carlos Eduardo – IEEE Transactions on Learning Technologies, 2021
Manually determining concepts present in a group of questions is a challenging and time-consuming process. However, the process is an essential step while modeling a virtual learning environment since a mapping between concepts and questions using mastery level assessment and recommendation engines is required. In this article, we investigated…
Descriptors: Computer Science Education, Semantics, Coding, Matrices
Min, Wookhee; Frankosky, Megan H.; Mott, Bradford W.; Rowe, Jonathan P.; Smith, Andy; Wiebe, Eric; Boyer, Kristy Elizabeth; Lester, James C. – IEEE Transactions on Learning Technologies, 2020
A distinctive feature of game-based learning environments is their capacity for enabling stealth assessment. Stealth assessment analyzes a stream of fine-grained student interaction data from a game-based learning environment to dynamically draw inferences about students' competencies through evidence-centered design. In evidence-centered design,…
Descriptors: Game Based Learning, Student Evaluation, Artificial Intelligence, Models
Capuano, Nicola; Loia, Vincenzo; Orciuoli, Francesco – IEEE Transactions on Learning Technologies, 2017
Massive Open Online Courses (MOOCs) are becoming an increasingly popular choice for education but, to reach their full extent, they require the resolution of new issues like assessing students at scale. A feasible approach to tackle this problem is peer assessment, in which students also play the role of assessor for assignments submitted by…
Descriptors: Participative Decision Making, Models, Peer Evaluation, Online Courses
