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Pavlik, Philip I., Jr.; Zhang, Liang – Grantee Submission, 2022
A longstanding goal of learner modeling and educational data mining is to improve the domain model of knowledge that is used to make inferences about learning and performance. In this report we present a tool for finding domain models that is built into an existing modeling framework, logistic knowledge tracing (LKT). LKT allows the flexible…
Descriptors: Models, Regression (Statistics), Intelligent Tutoring Systems, Learning Processes
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Tom Reshef-Israeli; Shulamit Kapon – Online Submission, 2024
As problems become increasingly complex, science educators need to better understand how new knowledge is constructed and applied in heterogeneous team collaborations, and how to teach students to productively engage in these processes. We discuss the emergence of insights in collaborative sensemaking and suggest a model that articulates the…
Descriptors: Comprehension, Constructivism (Learning), Teaching Methods, Learner Engagement
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…
Descriptors: Automation, Scoring, Documentation, Likert Scales
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Upmeier zu Belzen, Annette; Alonzo, Alicia C.; Krell, Moritz; Krüger, Dirk – Contributions from Science Education Research, 2019
This chapter contributes to ongoing debates about approaches to modeling student learning. By providing a basis for individual diagnoses, such models can foster teaching that is responsive to students' learning needs. In addition, these models can inform the development of standards and curricula and advance theory and research about student…
Descriptors: Learning Processes, Models, Science Education, Foreign Countries
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Onoue, Akira; Shimada, Atsushi; Minematsu, Tsubasa; Taniguchi, Rin-Ichiro – International Association for Development of the Information Society, 2019
This study aimed to cluster learners based on the structures of the knowledge maps they created. Learners drew their own knowledge maps to reflect their learning activities. Our system collected individual knowledge maps from many learners and clustered them to generate an integrated version of the knowledge maps of each cluster. We applied the…
Descriptors: Concept Mapping, Learning Processes, Cluster Grouping, Graphs
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James A. Middleton – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
An extended (and probably unnecessary) parallel is drawn between engagement in mathematics and engagement in musical performance. Key facets of engagement are described and a model of how mathematics engagement plays out in task-level activities is discussed in light of new findings related to its social and emotional facets. Implications for…
Descriptors: Mathematics Instruction, Learning Processes, Music, Learner Engagement
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Doewes, Afrizal; Saxena, Akrati; Pei, Yulong; Pechenizkiy, Mykola – International Educational Data Mining Society, 2022
In Automated Essay Scoring (AES) systems, many previous works have studied group fairness using the demographic features of essay writers. However, individual fairness also plays an important role in fair evaluation and has not been yet explored. Initialized by Dwork et al., the fundamental concept of individual fairness is "similar people…
Descriptors: Scoring, Essays, Writing Evaluation, Comparative Analysis
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Sonderegger, Stefan – International Association for Development of the Information Society, 2022
The use of social robots in education is a growing area of research and the potential future applications are various. However, the conversational models behind current social robots and chatbot systems often rely on rule-based and retrieval-based methods. This limits the social robot to predefined responses and topics, thus hindering it from…
Descriptors: Robotics, Teaching Methods, Learning Processes, Models
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Tran, Tuan M.; Hasegawa, Shinobu – International Association for Development of the Information Society, 2022
A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…
Descriptors: Markov Processes, Learning Processes, Models, Scores
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Maurra S. Wijaya; Ahmad Marzuq; Ihwan Rahman Bahtiar – International Society for Technology, Education, and Science, 2023
Innovative learning media are very important in supporting the learning process, including learning Arabic. Therefore, this study aims to develop video media for learning speaking skills as a medium for learning speaking skills for seventh grade students at MTS Negeri 39 Jakarta. The research was conducted using the Research and Development…
Descriptors: Arabic, Second Language Learning, Second Language Instruction, Foreign Countries
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Pandey, Shalini; Karypis, George – International Educational Data Mining Society, 2019
Knowledge tracing is the task of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities. Each student's knowledge is modeled by estimating the performance of the student on the learning activities. It is an important research area for providing a personalized learning platform to…
Descriptors: Learning Processes, Databases, Intelligent Tutoring Systems, Knowledge Level
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Rho, Jihyun; Rau, Martina A.; Van Veen, Barry D. – International Educational Data Mining Society, 2022
Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…
Descriptors: Learning Processes, Models, Introductory Courses, Engineering Education
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Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
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Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
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Doyer, Ilse; Bean, Wilna L.; du Plessis, André – Bulgarian Comparative Education Society, 2023
This paper presents the use of the time-on-task analysis (TOTA) diagnostic model as an instrument to improve the efficient management of allocated academic time in schools and focuses on the descriptive analytics produced by the TOTA model. The model aims to analyse how time is spent during the school day to enable school leaders, managers, and…
Descriptors: Time on Task, Teaching Methods, Learning Processes, Time Management
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