Subtopic Deep Dive
Measurement Scales in Quantitative Math Education Studies
Research Guide
What is Measurement Scales in Quantitative Math Education Studies?
Measurement scales in quantitative math education studies refer to psychometric instruments assessing attitudes, math anxiety, and achievement for use in statistical modeling of learning outcomes.
Researchers apply Likert scales, Rasch models, and item response theory (IRT) to validate instruments measuring constructs like math anxiety and reasoning ability. Studies often analyze scale reliability and validity in contexts such as gender differences and online learning. Over 10 papers from 2011-2022, with top-cited works exceeding 15 citations, focus on Indonesian math education contexts (Astalini et al., 2021; Susanti & Rohmah, 2011).
Why It Matters
Valid measurement scales enable rigorous regression models linking math anxiety to reasoning performance, informing interventions like classical music therapy (Susanti & Rohmah, 2011, 13 citations). They support evaluation of e-modules and online tools by quantifying gender-based perceptions and barriers (Astalini et al., 2021, 15 citations; Luthfiyah & Hadi, 2021). Accurate scaling improves policy decisions on pedagogy, such as PISA-aligned assessments (Muhsana & Diana, 2022).
Key Research Challenges
Scale Validity in Diverse Contexts
Ensuring scales measure intended constructs across genders and school levels remains challenging amid cultural variations. Studies show inconsistencies in math anxiety scales during online learning (Luthfiyah & Hadi, 2021). Rasch analysis reveals item biases in achievement tests (Rizbudiani et al., 2021).
Reliability Under E-Learning Constraints
Maintaining scale reliability shifts with pandemic-induced online formats complicates data collection. E-learning barriers inflate anxiety measures, skewing results (Syamila & Alyani, 2021). Repeated testing needed for stability (Atikah et al., 2022).
Item Difficulty Calibration
Balancing item difficulty for varied abilities using IRT proves difficult in final exams. Poor calibration misrepresents student reasoning on PISA-like problems (Muhsana & Diana, 2022). Stake models highlight program-wide inconsistencies (Nusantara & Jailani, 2019).
Essential Papers
Male or Female, who is better? Students' Perceptions of Mathematics Physics E-Module Based on Gender
Astalini Astalini, Darmaji Darmaji, Dwi Agus Kurniawan et al. · 2021 · Indonesian Journal on Learning and Advanced Education (IJOLAE) · 15 citations
This study aims to determine student perceptions of the physics-mathematical e-module based on gender differences. This type of research is quantitative research. This research targets the students...
EFEKTIVITAS MUSIK KLASIK DALAM MENURUNKAN KECEMASAN MATEMATIKA (MATH ANXIETY) PADA SISWA KELAS XI
Devi Winja Susanti, Faridah Ainur Rohmah · 2011 · Humanitas Indonesian Psychological Journal · 13 citations
This study aims to determine the effectiveness of classical music in<br />reducing math anxiety. The participants in this study were 14 public high<br />school students from class XI at Department ...
An evaluation of mathematics learning program at primary education using Countenance Stake Evaluation model
Bayuk Nusantara, Jailani Jailani · 2019 · Jurnal Penelitian dan Evaluasi Pendidikan · 6 citations
The quality of mathematics learning in Bantaeng Regency, South Sulawesi were in a low category based on the research findings from the Institute of Educational Quality Assurance of South Sulawesi i...
Rasch model item response theory (IRT) to analyze the quality of mathematics final semester exam test on system of linear equations in two variables (SLETV)
Adilla Desy Rizbudiani, Amat Jaedun, Abdul Rahim et al. · 2021 · Al-Jabar Jurnal Pendidikan Matematika · 6 citations
A high-quality test has a balanced level of difficulty and can be completed by the respondent with their level of abilities. This study analyzed the test instrument used to measure students' mathem...
PENGARUH KECEMASAN MATEMATIKA TERHADAP KEMAMPUAN PENALARAN MATEMATIS BERBASIS SOAL PISA
Novila Muhsana, Hafsah Adha Diana · 2022 · Jurnal Pendidikan Matematika Universitas Lampung · 5 citations
This study aims to determine the relationship and influence of mathematics anxiety levels on students' mathematical reasoning abilities in solving PISA-based math problems. This research is quantit...
Hambatan E-learning Terhadap Pembelajaran Matematika di Sekolah Menengah Pertama
Faza Syamila, Fitri Alyani · 2021 · Jurnal Cendekia Jurnal Pendidikan Matematika · 5 citations
Saat ini indonesia terdampak penyebaran covid-19 salah satu nya dalam lembaga pendidikan. Pembelajaran saat ini menggunakan pembelajaran berbasis online atau disebut dengan e-learning. E-learning m...
Assessing the item of final assessment mathematics test of junior high school using Rasch model
Atikah Atikah, Sudiyatno Sudiyatno, Abdul Rahim et al. · 2022 · Jurnal Elemen · 4 citations
The test is a tool to collect information about the achievement of learning objectives so that the test must have good quality in order to be able to measure students' abilities accurately. To dete...
Reading Guide
Foundational Papers
Start with Susanti & Rohmah (2011, 13 citations) for math anxiety scale validation via intervention; it establishes baseline psychometrics before Rasch advancements.
Recent Advances
Study Rizbudiani et al. (2021) and Atikah et al. (2022) for IRT applications in exams; Muhsana & Diana (2022) links anxiety to PISA reasoning.
Core Methods
Core techniques: Rasch model for item response, Likert for attitudes, Cronbach's alpha for reliability, applied in quantitative designs (Nusantara & Jailani, 2019).
How PapersFlow Helps You Research Measurement Scales in Quantitative Math Education Studies
Discover & Search
Research Agent uses searchPapers('Rasch model math anxiety scales Indonesia') to find Rizbudiani et al. (2021), then citationGraph reveals connections to Atikah et al. (2022), and findSimilarPapers uncovers Susanti & Rohmah (2011) for foundational anxiety measures.
Analyze & Verify
Analysis Agent applies readPaperContent on Astalini et al. (2021) to extract Likert scale items, verifyResponse with CoVe checks psychometric claims against Rasch standards, and runPythonAnalysis computes Cronbach's alpha via pandas on provided datasets; GRADE grading scores evidence as high for intervention studies like Susanti & Rohmah (2011).
Synthesize & Write
Synthesis Agent detects gaps in gender-specific scaling from Luthfiyah & Hadi (2021), flags contradictions in e-learning reliability (Syamila & Alyani, 2021), while Writing Agent uses latexEditText for scale tables, latexSyncCitations for 10+ papers, and latexCompile for publication-ready reports with exportMermaid for validation flowcharts.
Use Cases
"Run Rasch analysis on math exam items from Indonesian studies"
Analysis Agent → runPythonAnalysis (load exam data from Rizbudiani et al. 2021 via readPaperContent, compute item fit with NumPy/pandas) → researcher gets calibrated difficulty plot and CSV export.
"Draft LaTeX appendix with validated math anxiety scales"
Synthesis Agent → gap detection on Susanti & Rohmah (2011) scales → Writing Agent latexEditText + latexSyncCitations + latexCompile → researcher gets compiled PDF with 5 cited instruments.
"Find GitHub repos analyzing math education scale data"
Research Agent → paperExtractUrls on Atikah et al. (2022) → paperFindGithubRepo → githubRepoInspect → researcher discovers R scripts for IRT validation.
Automated Workflows
Deep Research workflow scans 50+ papers via searchPapers on 'math anxiety Rasch Indonesia', producing structured GRADE-graded review with citationGraph. DeepScan applies 7-step CoVe to verify scale reliabilities in Muhsana & Diana (2022), outputting checkpoint-validated report. Theorizer generates hypotheses on anxiety-scale interactions from Susanti & Rohmah (2011) and recent works.
Frequently Asked Questions
What defines measurement scales in this subtopic?
Psychometric tools like Likert and Rasch models quantify attitudes, anxiety, and achievement for statistical analysis in math education (Astalini et al., 2021).
What methods validate these scales?
Rasch IRT assesses item quality and fit; Cronbach's alpha tests reliability in studies like Rizbudiani et al. (2021) and Atikah et al. (2022).
What are key papers?
Astalini et al. (2021, 15 citations) on gender perceptions; Susanti & Rohmah (2011, 13 citations) on anxiety reduction; Rizbudiani et al. (2021, 6 citations) on IRT.
What open problems exist?
Adapting scales for e-learning contexts and cross-cultural validity amid biases (Syamila & Alyani, 2021; Luthfiyah & Hadi, 2021).
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