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 115 學年度 第 1 學期 教育學系教育數位評量與數據分析碩士班 林素微教師 數學評量專題研究 課程大綱
課程簡介   Course Introduction
開課年度學期
Year / Term
115 學年度 第 1 學期
開課班級
Department
教育學系教育數位評量與數據分析碩士班 教育數位評量測統碩博合選
Master Program of Online Educational Assessment and Data Analysis, Department of Education
授課方式
Instructional Method
課堂教學 、 中文
課程電腦代號
Course Reference Number
112034
課程名稱(中文)
Course Title(Chinese)
數學評量專題研究
課程名稱(英文)
Course Title(English)
Seminar on Mathematics Assessment
學分數/時數
Credit Hours
3 / 3
必(選)修
Required / Elective Course
選修 Elective
授課老師
Instructor
林素微
助教
Teaching Assistant
上課時間
Meeting Time
星期三,節次C
Wed, Period C、D、E
上課教室
Classroom
A304
Office Hours

獲獎及補助情形   Awards and Grants

聯合國永續發展目標 (SDGs跨域類別)   Sustainable Development Goals, SDGs

屬於大學社會責任(USR)性質   Courses related to University Social Responsibility(USR)

是否運用AI輔助教學   Using Artificial Intelligence (AI) to assist teaching

課程目標   Learning Objectives
1. 學生能覺察、省思當前國際與學校教學中數學評量的相關議題,針對該議題,進行文獻(含評量工具)閱覽。
2. 學生能依據上述文獻探討結果,針對數學領域進行革新的評量設計,並進行小樣本試用、結果分析和課堂的分享討論。
3.針對國際數學評比資料庫,依據測驗理論與技術進行分析,並討論其可能的意涵。
 

先修 ( 前置 ) 課程   Prerequisite
 

彈性教學規劃   Flexible Teaching/Planning Schedules
*本課程實施16+2週彈性教學方案,其中第17、18週之彈性規劃如下:
線上教學/討論
校外參訪

課程大綱   Course Syllabus
週次
Week
課程單元大綱
Unit
教學方式
Instructional Method/Style/Teaching Style
參考資料或相關作業
References or Related Materials
評量方式
Grading
1 課程簡介與數學評量趨勢 講述與討論  介紹課程大綱與評量要求;討論 PISA 等國際數學評量發展趨勢  口頭討論 
2 數學評量的理論基礎 講述與討論  探討心理測驗理論與古典測驗理論在數學評量中的應用  口頭討論 
3 數學評量議題與文獻探討(一) 講述與討論  討論素養導向評量與形成性評量的設計與實務挑戰  口頭討論 
4 數學評量議題與文獻探討(二) 講述與討論  分析生成式 AI 在教育評量命題與數學教學回饋中的應用與倫理  口頭討論 
5 數學評量工具發展與設計(一) 講述與討論  評量框架設計、雙向細目表編製與選擇題編製原則  口頭討論&實作 
6 數學評量工具發展與設計(二) 講述與討論  素養題、建構反應題 (非選擇題) 與實作表現任務的設計與評分規準  口頭討論&實作 
7 國際數學評比資料庫分析(一) 講述與討論  深入解析 PISA/TIMSS 數學評比資料庫結構介紹與資料清理處理  口頭討論&實作 
8 國際數學評比資料庫分析(二) 講述與討論  運用進階量化技術 (如 SEM、CFA、HLM) 進行次級資料分析與詮釋  口頭討論&實作 
9 期中進度報告 口頭報告  學生報告文獻探討成果或初步的數學評量工具設計構想   
10 非認知因素與數學學習評量 講述與討論  探討學生恆毅力 (Grit)、韌性、自我效能等情意特質的測量工具設計  口頭討論&實作 
11 現代測驗理論與量化議題(一) 講述與討論  試題反應理論 (IRT) 的模型與其在數學評量題目分析中的應用  口頭討論&實作 
12 現代測驗理論與量化議題(二) 講述與討論  潛在類別分析 (LCA) 或認知診斷模型 (CDM) 等進階量化技術之應用  口頭討論&實作 
13 數學評量工具之實作與試用(一) 講述與討論  學生針對其設計的創新評量工具,進行小樣本試測設計與實施  口頭討論&實作 
14 數學評量工具之實作與試用(二) 講述與討論  試測資料收集完成,進行初步數據檢核與資料整併  口頭討論&實作 
15 測驗結果分析與解釋(一) 講述與討論  運用統計軟體 (如 Mplus) 分析試測結果,進行信度與效度檢驗  口頭討論&實作 
16 測驗結果分析與解釋(二) 講述與討論  運用統計軟體 (如 Mplus) 分析試測結果,進行信度與效度檢驗  口頭討論&實作 
17 書面論文初稿問題討論 線上學習  書面論文初稿問題討論  口頭討論&實作(10%) 
18 綜合討論與反思 線上學習  分享改良後的評量工具,針對數學評量實務與量化分析進行深度反思  重點摘要及心得(10%) 


單一課程對應校能力指標程度   The Degree to Which Single Course Corresponds to School Competence
編號
No.
校核心能力
School Core Competencies
符合程度
Degree of conformity
1 公民力 (Citizen) 5
2 自學力 (Self-learning) 5
3 資訊力 (Information) 5
4 創造力 (Creativity) 5
5 溝通力 (Communication) 5
6 就業力(Employability) 5

單一課程對應系能力指標程度   The Degree to Which Single Course Corresponds to Department Competence
編號
No.
類別
Category
系核心能力
Department Core Competencies
符合程度
Degree of conformity
01 系所 能分析與解釋量化與類別資料 5
02 系所 能批判量化研究設計 5
03 系所 能創新評量工具(碩) 5
04 系所 能整合科技進行測驗創新議題探討 5
05 系所 能發表測驗統計議題的論文 5
06 系所 能提供基礎水準測驗與統計問題的諮詢服務(碩) 5

單一課程對應院能力指標程度   The Degree to Which Single Course Corresponds to College Competence
編號
No.
院核心能力
College Core Competencies
符合程度
Degree of conformity
1 探究能力 5
2 語文與溝通能力 5
3 創新與實踐能力 5
4 專業知能 5


教科書或參考用書   Textbooks or Reference Books
館藏書名   Library Books
備註   Remarks
Key Journals:

1.Journal of Educational Measurement (JEM): Flagship applied-theoretical measurement journal: test theory, scaling, equating, standard setting, validity
2.Psychometrika: The premier quantitative-theory journal: IRT, factor analysis, SEM, classification, latent-variable theory
3.Applied Psychological Measurement (APM): Applied/methodological studies on IRT, CTT, equating, CAT
Educational and Psychological Measurement (EPM): Scale development, validity, reliability, quantitative methods
4.Journal of Educational and Behavioral Statistics (JEBS): Statistical methodology for educational/behavioral data — multilevel models, psychometric statistics
Large-scale Assessments in Education (LSAE): Open-access journal dedicated to PISA/TIMSS/PIAAC/NAEP-type methodology and findings
International Journal of Testing (IJT) Taylor & Francis / ITC Cross-cultural test development, adaptation, fairness, testing policy
Journal for Research in Mathematics Education (JRME) NCTM Leading U.S. journal for empirical/theoretical research on math teaching and learning
Educational Studies in Mathematics (ESM) Springer International theoretical/empirical mathematics education research
ZDM – Mathematics Education Springer International math education research; strong overlap with assessment and comparative studies

Classic Textbooks (The Core Dissertation Toolkit)
Textbook Author(s), Year Covers
Statistical Theories of Mental Test Scores Lord & Novick, 1968 CTT foundations + early IRT (Birnbaum chapters)
Standards for Educational and Psychological Testing AERA/APA/NCME, 2014 Authoritative U.S. professional testing standards
Fundamentals of Item Response Theory Hambleton, Swaminathan & Rogers, 1991 Standard first IRT read: 1PL/2PL/3PL, invariance, DIF, CAT
The Theory and Practice of Item Response Theory (2nd ed.) de Ayala, 2022 Comprehensive current IRT text: polytomous models, MIRT, DIF, software
Item Response Theory: Foundations for Psychologists and Social Scientists Embretson & Reise, 2000/2013 Applied IRT with strong polytomous-model coverage
Multidimensional Item Response Theory Reckase, 2009 Definitive MIRT text: model forms, dimensionality, estimation, adaptive testing
Diagnostic Measurement: Theory, Methods, and Applications Rupp, Templin & Henson, 2010 Standard CDM/DCM reference; 2012 AERA Division D award winner
Test Equating, Scaling, and Linking: Methods and Practices (3rd ed.) Kolen & Brennan, 2014 Equating/scaling essential for PISA/TIMSS/NAEP work

Seminal Papers Every Student Should Master
Paper Author(s), Year Why It's Essential
"Some Latent Trait Models and Their Use in Inferring an Examinee's Ability" Birnbaum, 1968 Introduced 2PL/3PL models — the operational basis of nearly all large-scale math testing
"Cognitive Assessment Models With Few Assumptions..." Junker & Sijtsma, 2001 Canonical formalization of the DINA model
"DINA Model and Parameter Estimation: A Didactic" de la Torre, 2009 The go-to worked example for CDM estimation using math data
"Rule Space: An Approach for Dealing With Misconceptions..." Tatsuoka, 1983 First operational cognitive-diagnostic model; origin of the field's benchmark math dataset
"The Generalized DINA Model Framework" de la Torre, 2011 Unifying CDM framework (G-DINA) used across most current applications
Explanatory Item Response Models De Boeck & Wilson, 2004 Recasts IRT as GLMM/NLMM — essential for covariate-driven item/person modeling
"The Use of Test Scores From Large-Scale Assessment Surveys" Braun & von Davier, 2017 Demystifies plausible-value methodology underlying PISA/TIMSS/NAEP scores
PISA 2022 Technical Report OECD, 2024 Primary source for PISA's actual sampling/scaling/QA procedures
"Automatic Item Generation: Theory and Practice" Gierl & Haladyna (Eds.), 2013 Establishes AIG as a field — required before engaging any AI-item-generation literature
"The Rise of Artificial Intelligence in Educational Measurement" Bulut et al., 2024 Current field-defining synthesis of AI's role in assessment, scoring, and item generation

Key Professional Organizations
• NCME (National Council on Measurement in Education) — ncme.org
• Psychometric Society (publishes Psychometrika; hosts IMPS annual meeting) — psychometricsociety.org
• AERA Division D (Measurement and Research Methodology) — aera.net/Division-D
• OECD PISA Programme — oecd.org/PISA
• IEA / TIMSS & PIRLS International Study Center — iea.nl/studies/iea/timss
• NCES NAEP ("The Nation's Report Card") — nces.ed.gov/nationsreportcard/tdw

Recommended Reading Sequence
1. Foundations first: Lord & Novick (1968) → Hambleton, Swaminathan & Rogers (1991) → de Ayala (2022)
2. Advance to multidimensionality and diagnosis: Reckase (2009) → Junker & Sijtsma (2001) → de la Torre (2009, 2011) → Rupp, Templin & Henson (2010)
3. Ground in mathematics-specific applications: Tatsuoka (1983, 1990) → Bradshaw et al. (2014) → Templin & Bradshaw (2014)
4. Move to large-scale operational context: OECD PISA Technical Report → TIMSS Technical Report → Braun & von Davier (2017) → Chmielewski et al. (2018)
5. Finish at the research frontier: Gierl & Haladyna (2013) → Bulut et al. (2024) → Leng, Bezirhan & von Davier (2026)


※請尊重智慧財產權,不得非法影印教科書※
※   Please respect intellectual property rights and do not illegally photocopy textbooks.  ※

教學方法   Teaching Method
教學方法
Teaching Method
百分比
Percentage
講述 35 %
問題導向學習 35 %
專題實作 30 %
總和  Total 100 %

成績評量方式   Grading
評量方式
Grading
百分比
Percentage
課堂參與 40 %
個人書面報告 40 %
第17週自主學習 10 %
第18週自主學習 10 %
總和  Total 100 %

成績評量方式補充說明   
 

課程大綱補充資料   Supplementary Material of Course Syllabus