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Measuring changes in hydrolysis concept of students taught by inquiry model: stacking and racking analysis techniques

Lukman Abdul Rauf Laliyo1, Bambang Sumintono2, Citra Panigoro3

  • 1Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Gorontalo, 96128, Indonesia.

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The process-oriented guided inquiry learning (POGIL) model improved student conceptual change in hydrolysis when integrated with socio-scientific issues (SSI). Stacking and racking analyses effectively detailed student progress and item difficulty.

Keywords:
Hydrolysis conceptual changesInquiry modelRackingRasch modelStacking

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Area of Science:

  • Chemistry Education
  • Science Education Research
  • Learning Analytics

Background:

  • Conceptual change in science education is crucial for deep understanding.
  • Integrating socio-scientific issues (SSI) can enhance engagement and relevance in science learning.
  • The Rasch model offers robust psychometric analysis for educational assessments.

Purpose of the Study:

  • To measure conceptual changes in hydrolysis using the Rasch model with stacking and racking analyses.
  • To evaluate the effectiveness of the process-oriented guided inquiry learning (POGIL) model in the context of SSI.
  • To identify factors influencing conceptual change, including lucky guesses and misconceptions.

Main Methods:

  • Pretest-posttest control group design involving 11th-grade students.
  • Utilized 15 three-tier multiple-choice items assessed with a diagnostic rubric and certainty of response index.
  • Rasch Partial Credit Model analysis using WINSTEPS 4.5.5 software, incorporating stacking and racking techniques.

Main Results:

  • The POGIL approach in SSI context led to significantly better positive conceptual changes compared to conventional teaching.
  • Analysis revealed instances of lucky guesses, cheating, carelessness, boredom, and misconceptions impacting conceptual change.
  • Stacking and racking analyses provided detailed insights into student ability changes, item difficulty, and learning progression.

Conclusions:

  • The POGIL model effectively promotes conceptual change in hydrolysis within an SSI framework.
  • Psychometric analyses like stacking and racking are vital for understanding nuanced student learning trajectories.
  • Individual student responses and learning patterns necessitate tailored instructional considerations.