Add DIF_Dataset_Column_Inventory.csv

DIF_Dataset_Column_Inventory.csv

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+Dataset,Table/File,Column Name,Data Type,Description,Verified Source
+EEDI,questions.csv,QuestionId,int,Unique item identifier,NeurIPS 2020 challenge docs
+EEDI,questions.csv,SubjectId,int,Topic/subject tag,NeurIPS 2020 challenge docs
+EEDI,questions.csv,CorrectAnswer,int (1-4),Correct answer choice index,NeurIPS 2020 challenge docs
+EEDI,questions.csv,QuestionText,str,Item stem text,NeurIPS 2020 challenge docs
+EEDI,questions.csv,AnswerAText–AnswerDText,str,Text of each answer option,NeurIPS 2020 challenge docs
+EEDI,answer_metadata.csv,UserId,int,Anonymized student ID,NeurIPS 2020 challenge docs
+EEDI,answer_metadata.csv,QuestionId,int,Item answered,NeurIPS 2020 challenge docs
+EEDI,answer_metadata.csv,AnswerValue,int,Student's selected answer,NeurIPS 2020 challenge docs
+EEDI,answer_metadata.csv,IsCorrect,bool,Binary correctness flag,NeurIPS 2020 challenge docs
+EEDI,answer_metadata.csv,DateAnswered,datetime,Timestamp,NeurIPS 2020 challenge docs
+EEDI,student_metadata.csv,UserId,int,Student ID,NeurIPS 2020 challenge docs
+EEDI,student_metadata.csv,Gender,int,Demographic grouping variable,NeurIPS 2020 challenge docs
+EEDI,student_metadata.csv,PremiumPupil,bool,SES proxy,NeurIPS 2020 challenge docs
+PISA 2022,CY08MSP_STU_COG.sav,CNTSTUID,int,Unique student ID (merge key),OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_COG.sav,CNT,str,Country ISO code,OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_COG.sav,BOOKID,int,Test booklet assigned (determines items seen),OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_COG.sav,CM033Q01S (example),int,"Item score: 0=incorrect, 1=partial, 2=correct, 7=not administered, 8=not reached, 9=missing",OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_COG.sav,~900 item columns total,int,One column per cognitive item across math/reading/science,OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_QQQ.sav,CNTSTUID,int,Student ID (merge key with COG file),OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_QQQ.sav,ST004D01T,int,"Gender (1=Female, 2=Male)",OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_QQQ.sav,ESCS,float,"Economic, Social, Cultural Status index (continuous SES)",OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_QQQ.sav,IMMIG,int,"Immigration status (1=native, 2=first gen, 3=second gen)",OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_QQQ.sav,LANGN,int,"Language at home (1=test language, 2=other)",OECD PISA 2022 codebook
+PISA 2022,CY08MSP_STU_QQQ.sav,PV1MATH–PV10MATH,float,10 plausible values for math proficiency,OECD PISA 2022 codebook
+PISA 2022,Released Items PDFs (separate),Item text + options,PDF,"Full question stem + answer options for ~30-50% of items. Linked by item ID (e.g., M033Q01).",OECD released items publications
+TIMSS 2019,BSA*.sav (Student Achievement),IDCNTRY,int,Country code (merge key),IEA TIMSS 2019 User Guide
+TIMSS 2019,BSA*.sav (Student Achievement),IDSTUD,int,Student ID (merge key),IEA TIMSS 2019 User Guide
+TIMSS 2019,BSA*.sav (Student Achievement),IDBOOK,int,Booklet assignment,IEA TIMSS 2019 User Guide
+TIMSS 2019,BSA*.sav (Student Achievement),M071001 (example),int,Item score: correct/incorrect/partial/not administered. One column per item.,IEA TIMSS 2019 User Guide
+TIMSS 2019,BSG*.sav (Student Background),ITSEX,int,"Gender (1=Girl, 2=Boy)",IEA TIMSS 2019 User Guide
+TIMSS 2019,BSG*.sav (Student Background),BSBG04,int,Books in the home (SES proxy),IEA TIMSS 2019 User Guide
+TIMSS 2019,BSG*.sav (Student Background),BSDGLCNT,int,Language of test at home,IEA TIMSS 2019 User Guide
+TIMSS 2019,Item Information Excel (in IDB),"ItemID, ContentDomain, CognitiveDomain, ItemType, MaxScore",mixed,Metadata for ALL items (even unreleased). No question text.,IEA TIMSS 2019 IDB
+TIMSS 2019,Released Items PDFs (separate),Item text + options,PDF,Full text for ~30-50% of items. Item ID in PDF matches variable name.,IEA released items publications
+NAEP,NAEP Data Explorer (public),Group-level statistics only,aggregates,"Mean scores, percentiles, p-values by subgroup. NO individual student records.",NCES NAEP documentation
+NAEP,Restricted-Use Files (license required),Student × item responses (sparse BIB),int,Scored responses for ~25 items per student (out of ~300 total). 3-6 month application.,NCES Restricted Use Data Procedures
+NAEP,Restricted-Use Files,"Race/Ethnicity, Gender, NSLP, ELL, IEP, State",categorical,Rich US demographics — but ONLY in restricted data,NCES NAEP documentation
+ASSISTments 2012-2013,main CSV,student_id,int,Anonymous student identifier,ASSISTments data site + KDD 2014 challenge docs
+ASSISTments 2012-2013,main CSV,problem_id,int,Problem identifier (no text),ASSISTments data site
+ASSISTments 2012-2013,main CSV,skill_id,float,Skill/KC identifier,ASSISTments data site
+ASSISTments 2012-2013,main CSV,skill_name,str,"Text name of skill (e.g., 'Box and Whisker')",ASSISTments data site
+ASSISTments 2012-2013,main CSV,correct,int,Binary 0/1 correctness,ASSISTments data site
+ASSISTments 2012-2013,main CSV,attempt_count,int,Number of attempts,ASSISTments data site
+ASSISTments 2012-2013,main CSV,hint_count,int,Number of hints requested,ASSISTments data site
+ASSISTments 2012-2013,main CSV,ms_first_response,int,Milliseconds for first response,ASSISTments data site
+ASSISTments 2012-2013,main CSV,school_id,int,Anonymous school ID,ASSISTments data site
+ASSISTments 2012-2013,main CSV,gender,str,M/F (may have missing values),ASSISTments data site + KDD challenge docs
+ASSISTments 2012-2013,main CSV,economically_disadvantaged,bool,School-level FRPL proxy for SES,KDD challenge docs
+ASSISTments 2012-2013,main CSV,ELL,bool,English Language Learner status,KDD challenge docs
+ASSISTments 2012-2013,main CSV,IEP,bool,Individualized Education Program (disability),KDD challenge docs
+FoundationalASSIST,Interactions.csv,user_xid,str,Anonymous student ID (NO demographics),HF README + arXiv:2602.00070
+FoundationalASSIST,Interactions.csv,problem_id,int,Links to Problems.csv,HF README
+FoundationalASSIST,Interactions.csv,discrete_score,int,0/1 (1 = correct on first try without hints),HF README
+FoundationalASSIST,Interactions.csv,answer_text,str,Exact text of student's first answer,HF README
+FoundationalASSIST,Interactions.csv,hint_count,int,Number of hints requested,HF README
+FoundationalASSIST,Interactions.csv,saw_answer,bool,Whether student requested to see correct answer,HF README
+FoundationalASSIST,Interactions.csv,end_time,datetime,When student submitted correct answer,HF README
+FoundationalASSIST,Problems.csv,problem_id,int,Unique problem identifier,HF README
+FoundationalASSIST,Problems.csv,Problem Body,str (HTML),Full problem text with HTML markup,HF README
+FoundationalASSIST,Problems.csv,Problem Type,str,Type of problem,HF README
+FoundationalASSIST,Problems.csv,Answer Type,str,Numeric/MC/DropDown/Algebraic/etc.,HF README
+FoundationalASSIST,Problems.csv,Multiple Choice Options,str,MC answer options separated by ||,HF README
+FoundationalASSIST,Problems.csv,Multiple Choice Answers,str,Correct MC option(s),HF README
+FoundationalASSIST,Problems.csv,Fill-in Options / Answers,str,Fill-in correct answer(s),HF README
+FoundationalASSIST,Skills.csv,"problem_id, skill_id, node_code, node_name",mixed,224 unique skills mapped to problems,HF README
+EdNet,kt1 (HF: mgor/EDNet),timestamp,int64,Unix timestamp in ms,HF dataset viewer (verified)
+EdNet,kt1,solving_id,int64,Sequential attempt number per student,HF dataset viewer (verified)
+EdNet,kt1,question_id,str,"Question identifier (e.g., q3854)",HF dataset viewer (verified)
+EdNet,kt1,user_answer,str,Selected option (a/b/c/d),HF dataset viewer (verified)
+EdNet,kt1,elapsed_time,int64,Time spent in ms,HF dataset viewer (verified)
+EdNet,kt1,subject_id,str,Subject/user identifier,HF dataset viewer (verified)
+EdNet,kt1,correct_answer,str,Correct option (a/b/c/d),HF dataset viewer (verified)
+EdNet,kt1,is_correct,bool,Binary correctness,HF dataset viewer (verified)
+EdNet,questions (HF: mgor/EDNet),question_id,str,Question identifier,HF dataset viewer (verified)
+EdNet,questions,bundle_id,str,Bundle/group identifier,HF dataset viewer (verified)
+EdNet,questions,correct_answer,str,Correct option letter,HF dataset viewer (verified)
+EdNet,questions,part,int64,TOEIC part (1-7),HF dataset viewer (verified)
+EdNet,questions,tags,str,Skill tag IDs (semicolon-separated),HF dataset viewer (verified)
+EdNet,questions,deployed_at,int64,Deployment timestamp,HF dataset viewer (verified)
+EdNet,questions,❌ NO question_text column,—,TOEIC items are copyrighted; text not released,HF dataset viewer (verified) + arXiv:1912.03072
+Junyi Academy,student_log (DataShop),Anon Student Id,str,Anonymous student ID,arXiv:1912.03072 + arXiv:2403.13179
+Junyi Academy,student_log,Problem Name,str,Exercise ID (not text),PSLC DataShop format docs
+Junyi Academy,student_log,KC (Default),str,Skill/topic tag,PSLC DataShop format docs
+Junyi Academy,student_log,Outcome,str,CORRECT/INCORRECT/HINT,PSLC DataShop format docs
+Junyi Academy,student_log,Time,datetime,Timestamp,PSLC DataShop format docs
+Junyi Academy,exercise_info,"topic, area",str,"Skill tags (40 topics, 7 areas) in Traditional Chinese",arXiv:1912.03072
+Junyi Academy,—,❌ NO gender/age/demographics columns,—,Confirmed absent in all papers,"arXiv:1912.03072, arXiv:2602.00070 Table 3, arXiv:2403.13179"
+Junyi Academy,—,❌ NO question text,—,Only exercise IDs and skill tags,arXiv:2602.00070 Table 3
+OULAD,studentAssessment,id_student,int,Student ID,Kuzilek et al. 2017 (Scientific Data)
+OULAD,studentAssessment,id_assessment,int,Assessment ID,Kuzilek et al. 2017
+OULAD,studentAssessment,score,float,Single score (0-100) per ENTIRE assessment — NOT per question,Kuzilek et al. 2017
+OULAD,studentAssessment,date_submitted,int,Days from module start,Kuzilek et al. 2017
+OULAD,studentInfo,gender,str,M/F,Kuzilek et al. 2017
+OULAD,studentInfo,age_band,str,0-35 / 35-55 / 55<=,Kuzilek et al. 2017
+OULAD,studentInfo,imd_band,str,Index of Multiple Deprivation (SES proxy),Kuzilek et al. 2017
+OULAD,studentInfo,highest_education,str,Education level,Kuzilek et al. 2017
+OULAD,studentInfo,disability,str,Y/N,Kuzilek et al. 2017
+OULAD,studentInfo,region,str,UK region,Kuzilek et al. 2017
+OULAD,—,❌ NO item-level responses,—,Only assessment-level aggregate scores. Cannot do item-level DIF.,Kuzilek et al. 2017
+Duolingo SLAM,exercise data,user_id,str,Learner ID,Settles et al. 2018 (BEA Workshop)
+Duolingo SLAM,exercise data,token,str,Word/token in exercise,Settles et al. 2018
+Duolingo SLAM,exercise data,label,int,"0=correct, 1=error (per token)",Settles et al. 2018
+Duolingo SLAM,exercise data,days,float,Days since learner started course,Settles et al. 2018
+Duolingo SLAM,exercise data,client,str,Platform (web/ios/android),Settles et al. 2018
+Duolingo SLAM,exercise data,session,str,Session type (lesson/practice/test),Settles et al. 2018
+Duolingo SLAM,exercise data,format,str,"Exercise format (reverse_translate, etc.)",Settles et al. 2018
+Duolingo SLAM,—,❌ NO gender/age/race/SES,—,"Only course metadata, not personal demographics",Settles et al. 2018