Augmented Reality Supported by Deep-Learning-Oriented Pedagogy for Solar System Learning: Development and Preliminary Evaluation of Junior High School Students’ Creative Thinking
DOI:
https://doi.org/10.59698/kognisi.v4i1.625Keywords:
Augmented Reality, Creative Thinking, Deep Learning Pedagogy, Science Education, Solar System, ADDIEAbstract
Creative thinking is increasingly recognized as a core learning outcome in science education, yet abstract astronomical concepts can be difficult for junior high school students to explore through conventional two-dimensional media. This study developed and preliminarily evaluated an augmented reality (AR) learning medium integrated with a deep-learning-oriented pedagogy for the Solar System topic. In this article, deep learning refers to an educational approach that emphasizes active knowledge construction, meaningful connections, reflection, and sustained cognitive engagement rather than artificial-intelligence deep learning. The study employed a Research and Development design using the ADDIE model. Two expert validators reviewed the product, and the implementation involved 32 Grade VII students selected through cluster random sampling from a population of 296 students at SMP Negeri 3 Karanganyar, Indonesia; a small-scale trial involved 10 students, and two science teachers provided practicality responses. Data were collected through observation, interviews, expert-validation questionnaires, student and teacher response questionnaires, and a 10-item pretest-posttest instrument adapted from the Torrance Test of Creative Thinking dimensions of fluency, flexibility, originality, and elaboration. Expert-validation coefficients were .89 for AR media, .82 for content and language, .87 for the deep-learning lesson plan, and .80 for test content. Practicality ratings reached 83% in the small-scale trial, 88% among students in the limited-scale implementation, and 91% among teachers. A paired-samples comparison indicated a significant pre-post difference (p = .001), while the mean normalized gain was .4460, representing a moderate improvement. Fluency showed the largest gain (.4683) and elaboration the smallest (.3495). The findings support the feasibility and educational promise of combining interactive AR visualization with cognitively engaging pedagogy. Because the implementation used a one-group pretest-posttest design without a control group, the results should be interpreted as preliminary evidence rather than a causal estimate of effectiveness.
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