[{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-5291a20b802b9bbbe22b24cb","output_id":"a0035d9db2a3b259be06cc07b1f64ffaf640514ac142cf2b55594a8c9452fb26","section":"requirements","status":"invalid","value_json":null,"candidate_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\",\"n3\"],\"condition\":null,\"course\":null,\"evidence\":\"I SY E/PSYCH 349and (I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340), graduate/professional standing, or member of Engineering Guest Students\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":349,\"minimum_grade\":null,\"subjects\":[\"ISYE\",\"PSYCH\"],\"timing\":\"prior\"},\"evidence\":\"I SY E/PSYCH 349\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[\"n4\",\"n5\",\"n6\",\"n7\",\"n8\",\"n9\"],\"condition\":null,\"course\":null,\"evidence\":\"(I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340)\",\"id\":\"n2\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":210,\"minimum_grade\":null,\"subjects\":[\"ISYE\"],\"timing\":\"prior\"},\"evidence\":\"I SY E 210\",\"id\":\"n4\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":331,\"minimum_grade\":null,\"subjects\":[\"ECE\"],\"timing\":\"prior\"},\"evidence\":\"E C E 331\",\"id\":\"n5\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":310,\"minimum_grade\":null,\"subjects\":[\"MATH\",\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"MATH/STAT 310\",\"id\":\"n6\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":312,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"STAT 312\",\"id\":\"n7\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":324,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"324\",\"id\":\"n8\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":340,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"340\",\"id\":\"n9\",\"kind\":\"course\"}],\"notes\":[\"STAT 340 is mentioned in requirements_text but not in linked_courses; treated as verbatim condition leaf with assumed canonical reference.\"],\"root\":\"n0\",\"status\":\"needs_review\"}","error":"Node n0 references missing nodes: n3.","model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-5291a20b802b9bbbe22b24cb","output_id":"a0035d9db2a3b259be06cc07b1f64ffaf640514ac142cf2b55594a8c9452fb26","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Introduction to basic probability and statistical tools and methods from an industrial application perspective. Random variables and probability distributions; descriptive statistics; point estimates. Perform hypothesis testing, construct confidence intervals, and understand design of experiments in the context of motivating case studies. Regression and correlation analysis.\"},{\"course_id\":\"ECE 331\",\"field\":\"description\",\"quote\":\"Introduction to probability, random variables, and random processes. Confidence intervals, introduction to experimental design and hypothesis testing. Statistical averages, correlation, and spectral analysis for wide sense stationary processes. Random signals and noise in linear systems.\"},{\"course_id\":\"STAT 324\",\"field\":\"description\",\"quote\":\"Descriptive statistics, probability concepts and distributions, random variables. Hypothesis tests and confidence intervals for one- and two-sample problems. Linear regression, model checking, and inference. Analysis of variance and basic ideas in experimental design. Utilizes the R programming language.\"}],\"text\":\"Probability, statistics, and R programming fundamentals.\"},{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Focus on applying statistical methods and tools to solve engineering problems.\"}],\"text\":\"Application of statistical methods to engineering problems.\"}],\"search_phrases\":[\"human-computer interaction data visualization\",\"cognitive engineering visualization\",\"R programming interactive graphs\",\"visual analytics design intent\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"Creating static and interactive visualizations using R.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Applying cognitive engineering principles to visualization design.\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"title\",\"quote\":\"INTERACTIVE DATA ANALYTICS\"},{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities. The philosophical perspective, scientific basis, and practical tools for effective data visualization and visual analytics. Data processing and how to create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"ISYE 649 teaches cognitive engineering approaches to data visualization and interactive analytics using R.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"human-computer interaction and data visualization\"}],\"text\":\"Human-computer interaction.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Visualization design principles and human capabilities.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"visual analytics\"}],\"text\":\"Visual analytics.\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-5291a20b802b9bbbe22b24cb","output_id":"a0035d9db2a3b259be06cc07b1f64ffaf640514ac142cf2b55594a8c9452fb26","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-5590a4969e0a630fe46a86e8","output_id":"935d149d55bbc849eb761a137cbcd451c90c2d869d0393f857122cdbc2d3df36","section":"requirements","status":"valid","value_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\",\"n3\",\"n4\"],\"condition\":null,\"course\":null,\"evidence\":\"I SY E/PSYCH 349and (I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340), graduate/professional standing, or member of Engineering Guest Students\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":349,\"minimum_grade\":null,\"subjects\":[\"ISYE\",\"PSYCH\"],\"timing\":\"prior\"},\"evidence\":\"I SY E/PSYCH 349\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[\"n5\",\"n6\",\"n7\",\"n8\",\"n9\",\"n10\"],\"condition\":null,\"course\":null,\"evidence\":\"(I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340)\",\"id\":\"n2\",\"kind\":\"any\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n3\",\"kind\":\"condition\"},{\"children\":[],\"condition\":\"member of Engineering Guest Students\",\"course\":null,\"evidence\":\"member of Engineering Guest Students\",\"id\":\"n4\",\"kind\":\"condition\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":210,\"minimum_grade\":null,\"subjects\":[\"ISYE\"],\"timing\":\"prior\"},\"evidence\":\"I SY E 210\",\"id\":\"n5\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":331,\"minimum_grade\":null,\"subjects\":[\"ECE\"],\"timing\":\"prior\"},\"evidence\":\"E C E 331\",\"id\":\"n6\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":310,\"minimum_grade\":null,\"subjects\":[\"MATH\",\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"MATH/STAT 310\",\"id\":\"n7\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":312,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"STAT 312\",\"id\":\"n8\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":324,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"324\",\"id\":\"n9\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":340,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"340\",\"id\":\"n10\",\"kind\":\"course\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-5590a4969e0a630fe46a86e8","output_id":"935d149d55bbc849eb761a137cbcd451c90c2d869d0393f857122cdbc2d3df36","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Introduction to basic probability and statistical tools and methods from an industrial application perspective. Random variables and probability distributions; descriptive statistics; point estimates. Perform hypothesis testing, construct confidence intervals, and understand design of experiments in the context of motivating case studies. Regression and correlation analysis.\"},{\"course_id\":\"ECE 331\",\"field\":\"description\",\"quote\":\"Introduction to probability, random variables, and random processes. Confidence intervals, introduction to experimental design and hypothesis testing. Statistical averages, correlation, and spectral analysis for wide sense stationary processes. Random signals and noise in linear systems.\"},{\"course_id\":\"STAT 324\",\"field\":\"description\",\"quote\":\"Descriptive statistics, probability concepts and distributions, random variables. Hypothesis tests and confidence intervals for one- and two-sample problems. Linear regression, model checking, and inference. Analysis of variance and basic ideas in experimental design. Utilizes the R programming language.\"}],\"text\":\"Probability, statistics, and R programming fundamentals.\"},{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Focus on applying statistical methods and tools to solve engineering problems.\"}],\"text\":\"Application of statistical methods to engineering problems.\"}],\"search_phrases\":[\"human-computer interaction data visualization\",\"cognitive engineering visualization\",\"R programming interactive graphs\",\"visual analytics design intent\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"Creating static and interactive visualizations using R.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Applying cognitive engineering principles to visualization design.\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"title\",\"quote\":\"INTERACTIVE DATA ANALYTICS\"},{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities. The philosophical perspective, scientific basis, and practical tools for effective data visualization and visual analytics. Data processing and how to create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"ISYE 649 teaches cognitive engineering approaches to data visualization and interactive analytics using R.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"human-computer interaction and data visualization\"}],\"text\":\"Human-computer interaction.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Visualization design principles and human capabilities.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"visual analytics\"}],\"text\":\"Visual analytics.\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-5590a4969e0a630fe46a86e8","output_id":"935d149d55bbc849eb761a137cbcd451c90c2d869d0393f857122cdbc2d3df36","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-789789da373eecc1ff75f626","output_id":"9dded396f4db239e4320808ed3e6ca79753575462a19323ae1b0d03d8eca0179","section":"requirements","status":"needs_review","value_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\",\"n3\",\"n4\"],\"condition\":null,\"course\":null,\"evidence\":\"I SY E/PSYCH 349and (I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340), graduate/professional standing, or member of Engineering Guest Students\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":349,\"minimum_grade\":null,\"subjects\":[\"ISYE\",\"PSYCH\"],\"timing\":\"prior\"},\"evidence\":\"I SY E/PSYCH 349\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[\"n5\",\"n6\",\"n7\",\"n8\",\"n9\",\"n10\"],\"condition\":null,\"course\":null,\"evidence\":\"(I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340)\",\"id\":\"n2\",\"kind\":\"any\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n3\",\"kind\":\"condition\"},{\"children\":[],\"condition\":\"member of Engineering Guest Students\",\"course\":null,\"evidence\":\"member of Engineering Guest Students\",\"id\":\"n4\",\"kind\":\"condition\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":210,\"minimum_grade\":null,\"subjects\":[\"ISYE\"],\"timing\":\"prior\"},\"evidence\":\"I SY E 210\",\"id\":\"n5\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":331,\"minimum_grade\":null,\"subjects\":[\"ECE\"],\"timing\":\"prior\"},\"evidence\":\"E C E 331\",\"id\":\"n6\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":310,\"minimum_grade\":null,\"subjects\":[\"MATH\",\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"MATH/STAT 310\",\"id\":\"n7\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":312,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"STAT 312\",\"id\":\"n8\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":324,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"324\",\"id\":\"n9\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":340,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"340\",\"id\":\"n10\",\"kind\":\"course\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-789789da373eecc1ff75f626","output_id":"9dded396f4db239e4320808ed3e6ca79753575462a19323ae1b0d03d8eca0179","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Introduction to basic probability and statistical tools and methods from an industrial application perspective. Random variables and probability distributions; descriptive statistics; point estimates. Perform hypothesis testing, construct confidence intervals, and understand design of experiments in the context of motivating case studies. Regression and correlation analysis.\"},{\"course_id\":\"ECE 331\",\"field\":\"description\",\"quote\":\"Introduction to probability, random variables, and random processes. Confidence intervals, introduction to experimental design and hypothesis testing. Statistical averages, correlation, and spectral analysis for wide sense stationary processes. Random signals and noise in linear systems.\"},{\"course_id\":\"STAT 324\",\"field\":\"description\",\"quote\":\"Descriptive statistics, probability concepts and distributions, random variables. Hypothesis tests and confidence intervals for one- and two-sample problems. Linear regression, model checking, and inference. Analysis of variance and basic ideas in experimental design. Utilizes the R programming language.\"}],\"text\":\"Probability, statistics, and R programming fundamentals.\"},{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Focus on applying statistical methods and tools to solve engineering problems.\"}],\"text\":\"Application of statistical methods to engineering problems.\"}],\"search_phrases\":[\"human-computer interaction data visualization\",\"cognitive engineering visualization\",\"R programming interactive graphs\",\"visual analytics design intent\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"Creating static and interactive visualizations using R.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Applying cognitive engineering principles to visualization design.\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"title\",\"quote\":\"INTERACTIVE DATA ANALYTICS\"},{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities. The philosophical perspective, scientific basis, and practical tools for effective data visualization and visual analytics. Data processing and how to create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"ISYE 649 teaches cognitive engineering approaches to data visualization and interactive analytics using R.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"human-computer interaction and data visualization\"}],\"text\":\"Human-computer interaction.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Visualization design principles and human capabilities.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"visual analytics\"}],\"text\":\"Visual analytics.\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-789789da373eecc1ff75f626","output_id":"9dded396f4db239e4320808ed3e6ca79753575462a19323ae1b0d03d8eca0179","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"ae0d8f6f8e6cf5fb9f36cf48d9f77a319535b51245d747e53262cf68df86049d","section":"requirements","status":"valid","value_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\",\"n3\",\"n4\"],\"condition\":null,\"course\":null,\"evidence\":\"I SY E/PSYCH 349and (I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340), graduate/professional standing, or member of Engineering Guest Students\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":349,\"minimum_grade\":null,\"subjects\":[\"ISYE\",\"PSYCH\"],\"timing\":\"prior\"},\"evidence\":\"I SY E/PSYCH 349\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[\"n5\",\"n6\",\"n7\",\"n8\",\"n9\",\"n10\"],\"condition\":null,\"course\":null,\"evidence\":\"(I SY E 210,E C E 331,MATH/STAT 310,STAT 312,324, or340)\",\"id\":\"n2\",\"kind\":\"any\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n3\",\"kind\":\"condition\"},{\"children\":[],\"condition\":\"member of Engineering Guest Students\",\"course\":null,\"evidence\":\"member of Engineering Guest Students\",\"id\":\"n4\",\"kind\":\"condition\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":210,\"minimum_grade\":null,\"subjects\":[\"ISYE\"],\"timing\":\"prior\"},\"evidence\":\"I SY E 210\",\"id\":\"n5\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":331,\"minimum_grade\":null,\"subjects\":[\"ECE\"],\"timing\":\"prior\"},\"evidence\":\"E C E 331\",\"id\":\"n6\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":310,\"minimum_grade\":null,\"subjects\":[\"MATH\",\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"MATH/STAT 310\",\"id\":\"n7\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":312,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"STAT 312\",\"id\":\"n8\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":324,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"324\",\"id\":\"n9\",\"kind\":\"course\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":340,\"minimum_grade\":null,\"subjects\":[\"STAT\"],\"timing\":\"prior\"},\"evidence\":\"340\",\"id\":\"n10\",\"kind\":\"course\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"ae0d8f6f8e6cf5fb9f36cf48d9f77a319535b51245d747e53262cf68df86049d","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Introduction to basic probability and statistical tools and methods from an industrial application perspective. Random variables and probability distributions; descriptive statistics; point estimates. Perform hypothesis testing, construct confidence intervals, and understand design of experiments in the context of motivating case studies. Regression and correlation analysis.\"},{\"course_id\":\"ECE 331\",\"field\":\"description\",\"quote\":\"Introduction to probability, random variables, and random processes. Confidence intervals, introduction to experimental design and hypothesis testing. Statistical averages, correlation, and spectral analysis for wide sense stationary processes. Random signals and noise in linear systems.\"},{\"course_id\":\"STAT 324\",\"field\":\"description\",\"quote\":\"Descriptive statistics, probability concepts and distributions, random variables. Hypothesis tests and confidence intervals for one- and two-sample problems. Linear regression, model checking, and inference. Analysis of variance and basic ideas in experimental design. Utilizes the R programming language.\"}],\"text\":\"Probability, statistics, and R programming fundamentals.\"},{\"evidence\":[{\"course_id\":\"ISYE 210\",\"field\":\"description\",\"quote\":\"Focus on applying statistical methods and tools to solve engineering problems.\"}],\"text\":\"Application of statistical methods to engineering problems.\"}],\"search_phrases\":[\"human-computer interaction data visualization\",\"cognitive engineering visualization\",\"R programming interactive graphs\",\"visual analytics design intent\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"Creating static and interactive visualizations using R.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Applying cognitive engineering principles to visualization design.\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"title\",\"quote\":\"INTERACTIVE DATA ANALYTICS\"},{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"A cognitive engineering approach to human-computer interaction and data visualization in particular. Includes a four-part description of effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities. The philosophical perspective, scientific basis, and practical tools for effective data visualization and visual analytics. Data processing and how to create static graphs as well as web-based interactive visualizations using the statistical language R.\"}],\"text\":\"ISYE 649 teaches cognitive engineering approaches to data visualization and interactive analytics using R.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"human-computer interaction and data visualization\"}],\"text\":\"Human-computer interaction.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"effective visualization: design intent, data and application domain, representation and interface features, and human limits and capabilities.\"}],\"text\":\"Visualization design principles and human capabilities.\"},{\"evidence\":[{\"course_id\":\"ISYE 649\",\"field\":\"description\",\"quote\":\"visual analytics\"}],\"text\":\"Visual analytics.\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"ae0d8f6f8e6cf5fb9f36cf48d9f77a319535b51245d747e53262cf68df86049d","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_d91e0232f347175d68aa3e95","course_id":"ISYE 649","catalog_version_id":"a8e32e7c54df594601e037d660c21e594719e423f2df261fc082ee47be9901d3","record_version_id":"725e2c90ee72f0f5fbc2224db539d9065bf36f16da4e965b8a37ae88df3e5065","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"ae0d8f6f8e6cf5fb9f36cf48d9f77a319535b51245d747e53262cf68df86049d","section":"student_summary","status":"valid","value_json":"{\"context_hash\":\"942d57c59d4fa20ab7a12f0182602d35e986aa746a6c3672e5421d1cf1ad1ed4\",\"course_id\":\"ISYE 649\",\"current_instructors\":[],\"difficulty_workload\":[],\"errors\":[],\"historical_context\":[],\"message\":\"No course-specific reviews available\",\"offered\":false,\"profile_hash\":\"5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02\",\"quick_take\":[{\"citations\":[{\"course_id\":\"ISYE 649\",\"run_id\":\"20260907T155543-ce3781c4\",\"source_record\":{\"entity_id\":\"8de981ea-0696-3b19-a9ce-30f05d28e07b\",\"file\":\"tables/observations.parquet\",\"kind\":\"grades\",\"source\":\"madgrades\"},\"table\":\"grades_latest\",\"term_id\":\"1242\",\"type\":\"grade\"},{\"course_id\":\"ISYE 649\",\"run_id\":\"20260907T155543-ce3781c4\",\"source_record\":{\"entity_id\":\"8de981ea-0696-3b19-a9ce-30f05d28e07b\",\"file\":\"tables/observations.parquet\",\"kind\":\"grades\",\"source\":\"madgrades\"},\"table\":\"grades_latest\",\"term_id\":\"1252\",\"type\":\"grade\"},{\"course_id\":\"ISYE 649\",\"run_id\":\"20260907T155543-ce3781c4\",\"source_record\":{\"entity_id\":\"8de981ea-0696-3b19-a9ce-30f05d28e07b\",\"file\":\"tables/observations.parquet\",\"kind\":\"grades\",\"source\":\"madgrades\"},\"table\":\"grades_latest\",\"term_id\":\"1262\",\"type\":\"grade\"}],\"text\":\"Recent recorded grades — Fall 2023: 3.66 GPA, 88.7% A/AB (n=53 letter grades); Fall 2024: 3.83 GPA, 96.4% A/AB (n=55 letter grades); Fall 2025: 3.79 GPA, 96.6% A/AB (n=29 letter grades).\"}],\"student_experience\":[],\"task_hash\":\"74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68\",\"teaching_history\":[],\"term_id\":\"1272\",\"term_name\":\"2026 Fall\",\"version\":2}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true}]