The study proposes a frontline deliberate learning (FDL) process involving knowledge generation, knowledge articulation, and knowledge codification, which enable organizations to capture knowledge embedded in the frontlines. It examines the antecedent effects of three orientations (i.e., performance, learning, and customer orientation) at both the…

Drawing upon the social network theory and social cognitive theory, this research proposes a model that assesses team performance from the mediating aspect of knowledge application, which represents a team's learning process whereby an effective retrieval mechanism enables the team to access knowledge. In the model, team performance relates to…

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…

Considering the importance of mathematics in modern society, it is crucial to understand the cognitive processes involved in the acquisition of complex mathematical competency. As a new generation of evaluation theory, cognitive diagnosis has its unique advantages in personalized evaluation. Based on the mathematical cognitive framework of Trends…

Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…

The focus of the present study is the learning processes of concepts related to hydrogen bonds, which were developed using a didactic sequence (DS). Based on the perspective of Imre Lakatos, it was observed whether the explanatory models created by upper-secondary students form progressive transition sequences, which are similar to what Lakatos,…

This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…

When organizations create new knowledge and work practices as a reaction to challenges they face, they often have difficulty to adopt these new practices "on the ground". One of the reasons is that in these cases, individual informal learning and collective knowledge creation are often insufficiently connected. In this paper, we…

In the research reported in this paper, using a modified version of the interconnected model of teacher professional growth (IMTPG) proposed by Clarke and Hollingsworth (Teaching Teacher Educ 18:947-967, 2002), we aimed to understand the learning dynamics in a lesson study of a group of five teachers of grades 5-6, during their work around…

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…

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…

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…

Although small teacher education preparation programs (STEPP) may struggle to implement robust program design frameworks compared to their larger preparation program peers, a collaborative design can help smaller programs with resource limitations. This collaboration can facilitate the design of effective and efficient teacher preparation programs…

One of the essential problems, in educational data mining, is to predict students' performance on future learning materials, such as problems, assignments, and quizzes. Pioneer algorithms for predicting student performance mostly rely on two sources of information: students' past performance, and learning materials' domain knowledge model. The…

The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…