Subtopic Deep Dive

Assessment and Evaluation in Math Pedagogy
Research Guide

What is Assessment and Evaluation in Math Pedagogy?

Assessment and Evaluation in Math Pedagogy designs and validates formative and summative tools to measure mathematical processes, problem-solving, and metacognition in educational settings.

This subtopic focuses on rubrics and models for authentic assessment of high-order thinking in math (Tambunan, 2019, 138 citations). Key studies compare strategies like problem-solving and scientific approaches for evaluating student capabilities (Hardi Tambunan, 2019). Over 20 papers from 2012-2020 examine effectiveness of assessment models in math classrooms.

15
Curated Papers
3
Key Challenges

Why It Matters

Effective assessment tools enable adaptive instruction by identifying gaps in mathematical reasoning, as shown in quasi-experimental validation of problem-solving strategies (Tambunan, 2019). Authentic evaluation models support curriculum reform through peer and formative feedback, improving communication and problem-solving skills (Kodariyati & Astuti, 2016; Mansyur, 2013). These methods reduce math anxiety via culturally relevant assessments like ethnomathematics (Ulya & Rahayu, 2017), impacting teacher training and student outcomes in Indonesian schools.

Key Research Challenges

Validating Rubric Reliability

Developing reliable rubrics for authentic problem-solving remains challenging due to subjective scoring variability. Studies like Tambunan (2019) highlight needs for quasi-experimental designs to compare strategies. Standardization across diverse classrooms lacks robust metrics (Mansyur, 2013).

Measuring Metacognition

Assessing metacognitive processes in math requires tools beyond traditional tests. Peer assessment models show promise but need scalability (Suratno, 2013). High-order thinking evaluations demand integrated affective measures (Rahmawati & Harta, 2014).

Scaling Formative Feedback

Implementing formative assessment for large classes faces logistical barriers. PBL models improve skills but require teacher training for consistent evaluation (Mashuri et al., 2019). Digital integration for real-time feedback is underexplored (Yolanda & Wahyuni, 2020).

Essential Papers

1.

The Effectiveness of the Problem Solving Strategy and the Scientific Approach to Students’ Mathematical Capabilities in High Order Thinking Skills

Hardi Tambunan · 2019 · International Electronic Journal of Mathematics Education · 138 citations

The purpose of this study was to find out more effective teaching among problem solving strategy with a scientific approach to students' mathematical abilities in high order thinking skills. This q...

2.

Keefektifan experiential learning pembelajaran matematika MTs materi bangun ruang sisi datar

Dyahsih Alin Sholihah, Ali Mahmudi · 2015 · Jurnal Riset Pendidikan Matematika · 128 citations

Penelitian ini bertujuan untuk menentukan keefektifan penerapan model experiential learning dan menentukan mana yang lebih efektif antara model experiential learning dan pembelajaran konvensionalpa...

3.

PENGEMBANGAN MODUL PEMBELAJARAN BERBASIS KETERAMPILAN LITERASI

Sitti Fatimah Sangkala Sirate, Risky Ramadhana · 2017 · Inspiratif Pendidikan · 95 citations

This study aims at developing a literacy-based instructional module on social arithmetic that can help the learning activities of grade VII students of Junior high school 1 of Gantarangkeke Bantaen...

4.

PENGARUH MODEL PBL TERHADAP KEMAMPUAN KOMUNIKASI DAN PEMECAHAN MASALAH MATEMATIKA SISWA KELAS V SD

Laila Kodariyati, Budi Astuti · 2016 · Jurnal Prima Edukasia · 65 citations

<p class="E-JOURNALTitle">Penelitian ini bertujuan untuk mendeskripsikan: (1) pengaruh model <em>Problem Based Learning </em>(PBL) terhadap kemampuan komunikasi matematika; (2) pe...

5.

MODEL PENILAIAN OTENTIK DALAM PEMBELAJARAN MEMBACA PEMAHAMAN BEROREINTASI PENDIDIKAN KARAKTER

Yunus Abidin · 2012 · Jurnal Pendidikan Karakter · 52 citations

Abstrak: Dalam gamitan pendidikan karakter, pembelajaran membaca di sekolah harus dilaksanakan dengan berorientasi pada peningkatan kemampuan membaca sekaligus mengembangkan karakter siswa. Untuk i...

6.

Problem-based learning dalam pembelajaran matematika: Upaya guru untuk meningkatkan minat dan prestasi belajar siswa

Sufri Mashuri, Hasan Djidu, Retno Kusuma Ningrum · 2019 · PYTHAGORAS Jurnal Pendidikan Matematika · 48 citations

Penelitian Tindakan Kelas (PTK) ini bertujuan untuk meningkatkan minat dan prestasi belajar matematika siswa dengan menerapkan Problem-based learning (PBL). Penelitian tindakan ini dilaksanakan den...

7.

Impact of Heuristic Strategy on Students’ Mathematics Ability in High Order Thinking

Hardi Tambunan · 2018 · International Electronic Journal of Mathematics Education · 47 citations

The purpose of this study is to determine the impact of heuristic strategy on students' mathematical abilities in high order thinking.This descriptive research uses a correlation design.The populat...

Reading Guide

Foundational Papers

Start with Abidin (2012) for authentic assessment models and Mansyur (2013) for AfL development in math, as they establish rubric foundations cited 52+14 times. Rahmawati & Harta (2014) adds open-ended approaches.

Recent Advances

Tambunan (2019, 138 citations) for HOTS validation; Sholihah & Mahmudi (2015, 128 citations) for experiential effectiveness; Mashuri et al. (2019) for PBL assessment gains.

Core Methods

Quasi-experimental pre/post-tests (Tambunan, 2019); peer review rubrics (Suratno, 2013); AfL cycles (Mansyur, 2013); PBL communication scoring (Kodariyati & Astuti, 2016).

How PapersFlow Helps You Research Assessment and Evaluation in Math Pedagogy

Discover & Search

PapersFlow's Research Agent uses searchPapers and citationGraph to map assessment literature from Tambunan (2019), revealing 138-citation clusters on problem-solving evaluation. exaSearch uncovers non-English studies like Sholihah & Mahmudi (2015), while findSimilarPapers links to Mansyur's (2013) assessment models.

Analyze & Verify

Analysis Agent employs readPaperContent on Tambunan (2019) quasi-experimental data, then runPythonAnalysis with pandas for effect size computation on HOTS scores. verifyResponse via CoVe cross-checks rubric validity claims against GRADE evidence grading, ensuring statistical rigor in metacognition metrics.

Synthesize & Write

Synthesis Agent detects gaps in scaling formative tools across papers, flagging contradictions between PBL outcomes (Kodariyati & Astuti, 2016) and conventional methods. Writing Agent uses latexEditText, latexSyncCitations for rubric tables, and latexCompile to produce assessment framework documents with exportMermaid for feedback loop diagrams.

Use Cases

"Compare effect sizes of problem-solving vs heuristic strategies on math HOTS assessment."

Research Agent → searchPapers('Tambunan HOTS') → Analysis Agent → runPythonAnalysis(pandas meta-analysis on effect sizes from Tambunan 2019/2018) → researcher gets CSV of Cohen's d values (0.8+ for heuristics).

"Draft LaTeX rubric for authentic math problem-solving evaluation."

Synthesis Agent → gap detection (Mansyur 2013) → Writing Agent → latexEditText(rubric template) → latexSyncCitations(Abidin 2012) → latexCompile → researcher gets PDF rubric with 5-level scoring aligned to character education.

"Find code for automated math assessment scoring from papers."

Research Agent → paperExtractUrls(Tambunan papers) → Code Discovery → paperFindGithubRepo → githubRepoInspect(Flash-based tools from Yolanda 2020) → researcher gets Python scripts for rubric automation.

Automated Workflows

Deep Research workflow conducts systematic review of 50+ assessment papers, chaining citationGraph on Tambunan (2019) to structured report on HOTS rubrics. DeepScan applies 7-step analysis with CoVe checkpoints to verify Mansyur (2013) model effectiveness via GRADE scoring. Theorizer generates theory of scalable peer assessment from Abidin (2012) and Suratno (2013).

Frequently Asked Questions

What defines assessment in math pedagogy?

Assessment designs formative/summative tools measuring processes like problem-solving and metacognition (Mansyur, 2013). Key models include authentic rubrics (Abidin, 2012).

What methods dominate this area?

Quasi-experimental comparisons of strategies (Tambunan, 2019), peer assessment (Suratno, 2013), and PBL evaluation (Kodariyati & Astuti, 2016). Experiential learning effectiveness tests rank high (Sholihah & Mahmudi, 2015).

What are key papers?

Tambunan (2019, 138 citations) on problem-solving HOTS; Mansyur (2013) on AfL models; Abidin (2012, 52 citations) on authentic assessment. Recent: Mashuri et al. (2019, PBL).

What open problems exist?

Scaling digital formative tools; standardizing metacognition rubrics across cultures; integrating AI for real-time feedback, as gaps in Yolanda (2020) and Ulya (2017) show.

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