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ZENODO
Dataset . 2026
Data sources: ZENODO
ZENODO
Dataset . 2026
Data sources: Datacite
ZENODO
Dataset . 2026
Data sources: Datacite
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APPLICATION OF HEURISTIC LEARNING IN TEACHING PHYSICAL PROCESSES

Authors: Toshev Salimjon Nurboboyevich;

APPLICATION OF HEURISTIC LEARNING IN TEACHING PHYSICAL PROCESSES

Abstract

In recent years, learner-centered educational approaches have gained increasing attention in science education. Among them, heuristic learning plays a crucial role in developing students’ independent thinking and problem-solving skills. Physics, as an experimental and conceptually complex discipline, requires instructional methods that actively engage learners in the process of knowledge construction. This article explores the application of heuristic learning in teaching physical processes and evaluates its pedagogical effectiveness. The study is based on a quasi-experimental research design involving secondary school students. Heuristic learning strategies such as problem-based tasks, guided inquiry, experimental observation, and reflective questioning were implemented in the experimental group, while traditional lecture-based instruction was used in the control group. Data were collected through pre-tests, post-tests, classroom observations, and practical assignments. The results indicate that heuristic learning significantly improves students’ conceptual understanding of physical processes, analytical reasoning, and ability to apply theoretical knowledge in practical situations. The findings suggest that integrating heuristic learning into physics education enhances learning outcomes and promotes deeper scientific understanding.

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average