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Palmer, Russ; Choi, Ikseon – Educational Technology Research and Development, 2023
The goal of this article is to propose a framework for understanding the nature of "how people construct problems" by interacting with situations and subsequently to offer implications for instructional design and future research. We propose that people must interactively frame the components of a situation in order to establish the…
Descriptors: Problem Solving, Epistemology, Models, Cognitive Processes
Zhang, Maoxin; Andersson, Björn – Educational Assessment, 2023
Process data from educational assessments enhance the understanding of how students answer cognitive items. However, effectively making use of these data is challenging. We propose an approach to identify solution patterns from operation sequences and response times by generating networks from process data and defining network features that…
Descriptors: Problem Solving, Network Analysis, Cognitive Processes, Mathematics
Toukiloglou, Pavlos; Xinogalos, Stelios – Journal of Educational Computing Research, 2023
Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback.…
Descriptors: Educational Games, Programming, Sequential Learning, Cognitive Processes
Rott, Benjamin; Specht, Birte; Knipping, Christine – ZDM: Mathematics Education, 2021
Complementary to existing "normative" models, in this paper we suggest a descriptive phase model of problem solving. Real, not ideal, problem-solving processes contain errors, detours, and cycles, and they do not follow a predetermined sequence, as is presumed in normative models. To represent and emphasize the non-linearity of empirical…
Descriptors: Mathematics Skills, Problem Solving, Models, Cognitive Processes
Julius Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Instructional Science: An International Journal of the Learning Sciences, 2024
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…
Descriptors: Problem Based Learning, Problem Solving, Prompting, Models
Kahn, Joshua D.; Bullis, Michael D. – Leadership and Policy in Schools, 2023
In this integrative literature review, we synthesize the scant literature from the last 40 years of educational research on how school principals make difficult decisions. Reviewing 15 peer-reviewed articles, articles were coded for the methods used and their substantive findings. We review sampling techniques, the types of problems and methods…
Descriptors: Cognitive Processes, Decision Making, Principals, Models
Xiaohong Liu; Jianjun Gu; Jinlei Xu – International Journal of Technology and Design Education, 2024
Creativity and problem-solving are 21st-century skills that students must have to respond to the complex world dominated by technology. Teaching activities integrating Design Thinking (DT) have the potential to cultivate individual skills. As future in-service teachers, pre-service teachers need to understand DT so as to be able to use it in their…
Descriptors: Preservice Teachers, Design, Cognitive Processes, Models
Schulz, Sandra; McLaren, Bruce M.; Pinkwart, Niels – International Journal of Artificial Intelligence in Education, 2023
This paper develops a method for the construction and evaluation of cognitive models to support students in their problem-solving skills during robotics in school, aiming to build a basis for an implementation of a tutoring system in the future. Two Wizard-of-Oz studies were conducted, one in the classroom and one in the lab. Based on the…
Descriptors: Cognitive Processes, Models, Intelligent Tutoring Systems, Robotics
Haavold, Per Øystein; Sriraman, Bharath – ZDM: Mathematics Education, 2022
Even after many decades of productive research, problem solving instruction is still considered ineffective. In this study we address some limitations of extant problem solving models related to the phenomenon of insight during problem solving. Currently, there are two main views on the source of insight during problem solving. Proponents of the…
Descriptors: Creativity, Creative Thinking, Problem Solving, Novices
Lange, Christopher; Gorbunova, Anna; Shcheglova, Irina; Costley, Jamie – Innovations in Education and Teaching International, 2023
Research often examines cognitive load as it relates to direct instruction, worked examples and problem-solving combined as an integrated whole. The present study examines these strategies in isolation to see their effect on cognitive load. Using learning materials covering the basics of critical thinking to undergraduate law students (n = 160) at…
Descriptors: Direct Instruction, Problem Solving, Educational Strategies, Cognitive Processes
Erickson, Sarah A.; Lockwood, Elise – International Journal of Research in Undergraduate Mathematics Education, 2021
Combinatorial proof is an important topic both for combinatorics education and proof education researchers, but relatively little has been studied about the teaching and learning of combinatorial proof. In this paper, we focus on one specific phenomenon that emerged during interviews with mathematicians and students who were experienced provers as…
Descriptors: Mathematics Skills, Mathematical Logic, Mathematics Instruction, Multiplication
Sternberg, Robert J.; Glaveanu, Vlad; Karami, Sareh; Kaufman, James C.; Phillipson, Shane N.; Preiss, David D. – Journal of Intelligence, 2021
A deeper understanding of the processes leading to problem framing and behind finding solutions to problems should help explain variability in the quality of the solutions to those problems. Using Sternberg's WICS model as the conceptual basis of problem solving, this article discusses the relations between creative, analytical, practical, and…
Descriptors: Intelligence, Creative Thinking, Logical Thinking, Cognitive Processes
Julius Moritz Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Journal of Computer Assisted Learning, 2024
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…
Descriptors: Video Technology, Models, Cues, Problem Solving
Vegard Gjerde; Sivert Hagane – Physical Review Physics Education Research, 2024
Peer Instruction gives practice in the abstract language of physics, addresses common misconceptions among students, and is more effective than traditional lecturing. However, it is not clear what makes Peer Instruction effective nor how we might improve the method. An emerging perspective is that what makes Peer Instruction effective is how it…
Descriptors: Science Instruction, Peer Teaching, Scientific Concepts, Models
Hoogerheide, Vincent; Roelle, Julian – Applied Cognitive Psychology, 2020
Decades of research has shown that example-based learning is an effective instructional strategy for learning new skills. The field of learning from examples is seeing a shift in focus towards more innovative and use-inspired research, in part because the use of examples for informal and formal learning purposes has mushroomed. This special issue…
Descriptors: Observational Learning, Problem Solving, Cognitive Processes, Difficulty Level