Students’ Concept Retention on the Use of Gamification in Biology

  1. Vladimir D. Tanilong
  2. Rolly James F. Cheng

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Abstract

Conventional teaching methods in biology often result in student disinterest and difficulty in understanding complex concepts, leading to limited long-term retention. This study addresses this issue by comparing the effectiveness of gamification with traditional teaching methods among Grade 10 Biology students using a quasi-experimental design. The intervention group experienced gamified learning, while the conventional group received standard lecture-based instruction. Results showed that the gamification group achieved significantly higher retention scores (mean = 57.29) compared to the conventional group (mean = 37.62), with statistical significance (p = 0.00). The mean scores of intervention group increased notably from pre-test to post-test by 22.58 points and further improved by 12.33 points from post-test to retention test, both with moderate effect sizes (Cohen’s d = 0.69). Students reported that gamification made learning more enjoyable and engaging, which enhanced their focus, motivation, and confidence. Additionally, gamified lessons promoted better social interaction and collaboration among students. These findings provide evidence that gamification not only improves direct learning outcomes but also supports retention and a more motivating learning environment. The study recommends integrating gamified elements thoughtfully into biology instruction to enhance student engagement, motivation, and academic performance while ensuring alignment with curriculum goals and equitable access to technology.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/18272741.

    Does the introduction explain the objective of the research presented in the preprint? Yes
    Are the methods well-suited for this research? Highly appropriate
    Are the conclusions supported by the data? Highly supported
    Are the data presentations, including visualizations, well-suited to represent the data? Somewhat appropriate and clear
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly
    Is the preprint likely to advance academic knowledge? Highly likely
    Would it benefit from language editing? No
    Would you recommend this preprint to others? Yes, but it needs to be improved
    Is it ready for attention from an editor, publisher or broader audience? Yes, after minor changes

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  2. Version published to 10.20944/preprints202601.1058.v1