Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…

Purpose: The purpose of this paper is the presentation of a learning model for a manager and employee working collaboratively to make advances in knowledge, skills, work performance and in the quality of their relationship. The model is called reciprocal action learning. Design/methodology/approach: The approach was to examine concepts and…

Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…

Knowledge tracing (KT) is a method to evaluate a student's knowledge state (KS) based on their historical problem-solving records by predicting the next answer's binary correctness. Although widely applied to closed-ended questions, it lacks a detailed option tracing (OT) method for assessing multiple-choice questions (MCQs). This paper introduces…

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…

This paper introduces a model built upon the Method of Varying Inquiry, offering a didactical approach to problem posing and solving activities that stimulates inquiry-based learning in mathematics classrooms. The model combines the inquiry-based framework with the variation theory and with specific didactical and theoretical elements (the…

Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available; however, being…

In the human-to-human Collaborative Problem Solving (CPS) test, students' problem-solving process reflects the interdependency among partners. The high interdependency in CPS makes it very sensitive to group composition. For example, the group outcome might be driven by a highly competent group member, so it does not reflect all the individual…

Background/purpose: The increasing integration of digital technology in education underscores the need for instructional models that support personalized, skill-based, and problem-solving focused learning. While traditional pedagogies often fail to address these needs comprehensively, this study proposes that the Mastery Adaptive Problem-Solving…

Contribution: Model-based learning improves systems thinking (ST) based on students' prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and…

According to previous studies, traditional laboratory safety courses are delivered in a classroom setting where the instructor teaches and the students listen and read the course materials passively. The course content is also uninspiring and dull. Additionally, the teaching period is spread out, which adds to the instructor's workload. As a…

The benefits of incorporating process information in a large-scale assessment with the complex micro-level evidence from the examinees (i.e., process log data) are well documented in the research across large-scale assessments and learning analytics. This study introduces a deep-learning-based approach to predictive modeling of the examinee's…

Multimodal learning refers to teaching strategies that involve multiple sensory systems simultaneously. Teachers can create materials for students with different learning styles (auditory, visual, kinesthetic reading, and writing). Multimodal learning keeps students engaged, encourages them to apply what they learn in real-life situations,…

An imagineering learning model using advance organizers with the internet of things was developed to promote creative innovation for learners in the 21st century. It is an innovation initiated by integrating classroom learning and technology that connects with the internet of things. The objectives of this research were (1) to study and synthesize…

Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can…