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Download full textRadmehr, Farzad – Journal on Mathematics Education, 2023
Task design is an important element of effective mathematics teaching and learning. Past research in mathematics education has investigated task design in mathematics education from different perspectives (e.g., cognitive and cultural) and offered a number of (theoretical) frameworks and sets of principles. In this study, through a narrative…
Descriptors: Guidelines, Instructional Design, Ethnography, Teaching Methods
Direct linkJohnson, Staci N.; Gallagher, Eliza D. – Advances in Physiology Education, 2021
This qualitative study investigated processes used by undergraduate students over a course sequence in anatomy and physiology (A&P). Longitudinal data for each participant include weekly written reflections and interviews at the beginning, middle, and end of the two-semester sequence. The themes that emerged describe three variations of…
Descriptors: Anatomy, Physiology, Undergraduate Students, Learning Processes
Dorambari, Diedon – International Journal of Education and Practice, 2022
This study examined whether instructional humor (IH) was not just another type of seductive detail when covariates such as humor pre-disposition, prior-knowledge, and working memory capacity were controlled. Participants were students (N = 228) from universities who were randomly assigned two stimuli conditions in the classic experimental design.…
Descriptors: Humor, Multimedia Instruction, Prior Learning, Short Term Memory
Novak, Magdalena; Phelan, Siëlle; Lewalter, Doris; Schwan, Stephan – International Journal of Science Education, 2020
Previous research from in and outside museums suggests that the haptic exploration of surfaces and objects have various educational benefits and can positively influence the museum visit experience. However, there is still a need for more research on the potential effects of object handling on museum learning, especially in science museums. The…
Descriptors: Science Education, Museums, Learning Processes, Photography
Münchow, Hannes; Bannert, Maria – Educational Psychology, 2019
Emotional designing describes the elicitation of positive affect during learning through specific design elements of the learning environment to enhance learning. This experimental study examined the effectivity of an emotional design procedure on learning performance. Moreover, the learner's affective states before learning were taken into…
Descriptors: Educational Environment, Instructional Design, Affective Behavior, Student Motivation
Knörzer, L.; Brünken, R.; Park, B. – Journal of Computer Assisted Learning, 2016
The Cognitive-Affective Theory of Learning with Media postulates that affective factors as well as individual learner characteristics impact multimedia learning. The present study investigated how experimentally induced positive and negative emotions influence multimedia learning and how learner characteristics moderated this impact. Results…
Descriptors: Psychological Patterns, Multimedia Instruction, Student Characteristics, Learning Theories
Peer reviewedIlleris, Knud – International Journal of Lifelong Education, 2003
An overarching learning theory is presented, based on assumptions that all learning includes (1) external learner-environment interaction and internal acquisition and elaboration and (2) cognitive, emotional, and social dimensions. The framework depicts four types of learning: cumulative, assimilative, accommodative, and transformative. (Contains…
Descriptors: Affective Behavior, Cognitive Processes, Cognitive Structures, Competence
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
