# COMARTS 110: Artificial Intelligence in Story and Screen | UW–Madison [View on UW Courses](https://uwcourses.com/courses/COMARTS_110) ## Dataset ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ### repository twangodev/uwcourses ### schema version 6 ### importer version 7 ### projection id 52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07 ### observed at 2026-09-07T15:55:43.033547+00:00 ### built at 2026-09-10T19:50:42.743001+00:00 ### courses 8951 ### current instructors 5754 ### limited false ### terms * 1272 * 1264 * 1262 * 1254 * 1252 * 1244 * 1242 * 1234 * 1232 * 1224 * 1222 * 1212 * 1204 * 1202 * 1194 * 1192 * 1184 * 1182 * 1174 * 1172 * 1164 * 1162 * 1154 * 1152 * 1144 * 1142 * 1134 * 1132 * 1124 * 1122 * 1114 * 1112 * 1104 * 1102 * 1094 * 1092 * 1084 * 1082 * 1074 * 1072 ### term 1272 ### departments | subject | count | | --------- | ----- | | AAE | 90 | | ABT | 20 | | ACCTIS | 36 | | ACTSCI | 14 | | AFAERO | 10 | | AFRICAN | 87 | | AFROAMER | 71 | | AGROECOL | 21 | | AMERIND | 53 | | ANAT\&PHY | 7 | | ANATOMY | 2 | | ANESTHES | 8 | | ANSCI | 57 | | ANTHRO | 95 | | ART | 125 | | ARTED | 10 | | ARTHIST | 121 | | ASIALANG | 129 | | ASIAN | 109 | | ASIANAM | 28 | | ASTRON | 38 | | ATMOCN | 69 | | BIOCHEM | 51 | | BIOCORE | 10 | | BIOLOGY | 14 | | BIOMDSCI | 18 | | BME | 66 | | BMI | 41 | | BMOLCHEM | 10 | | BOTANY | 69 | | BSE | 44 | | C\&ESOC | 73 | | CBE | 48 | | CHEM | 101 | | CHICLA | 52 | | CIVENGR | 133 | | CLASSICS | 47 | | CNP | 10 | | CNSRSCI | 50 | | COMARTS | 137 | | COMPBIO | 15 | | COMPLIT | 11 | | COMPSCI | 138 | | COUNPSY | 78 | | CRB | 19 | | CS\&D | 71 | | CSCS | 40 | | CURRIC | 193 | | DANCE | 93 | | DERM | 8 | | DS | 88 | | DYSCI | 35 | | ECE | 155 | | ECON | 145 | | EDPOL | 114 | | EDPSYCH | 97 | | ELPA | 70 | | EMA | 53 | | EMERMED | 17 | | ENGL | 206 | | ENTOM | 40 | | ENVIRST | 148 | | EP | 15 | | EPD | 67 | | ESL | 16 | | F\&WECOL | 60 | | FAMMED | 22 | | FINANCE | 50 | | FOLKLORE | 40 | | FOODSCI | 43 | | FRENCH | 63 | | GEN\&WS | 145 | | GENBUS | 72 | | GENECSLR | 17 | | GENETICS | 60 | | GEOG | 113 | | GEOSCI | 83 | | GERMAN | 82 | | GLE | 48 | | GNS | 38 | | GREEK | 27 | | HDFS | 41 | | HEBR-BIB | 13 | | HEBR-MOD | 10 | | HISTORY | 233 | | HISTSCI | 56 | | HONCOL | 13 | | ILS | 43 | | INFOSYS | 9 | | INTEGART | 7 | | INTEGSCI | 22 | | INTER-AG | 18 | | INTER-HE | 11 | | INTER-LS | 22 | | INTEREGR | 16 | | INTLBUS | 21 | | INTLST | 50 | | ISYE | 83 | | ITALIAN | 53 | | JEWISH | 56 | | JOURN | 88 | | KINES | 128 | | LACIS | 26 | | LANDARC | 61 | | LATIN | 24 | | LAW | 120 | | LEGALST | 48 | | LINGUIS | 35 | | LIS | 89 | | LITTRANS | 78 | | LSC | 52 | | M\&ENVTOX | 7 | | MARKETNG | 62 | | MATH | 153 | | MDGENET | 8 | | ME | 130 | | MEDHIST | 43 | | MEDICINE | 60 | | MEDIEVAL | 32 | | MEDPHYS | 39 | | MEDSC-M | 29 | | MEDSC-V | 41 | | MHR | 68 | | MICROBIO | 45 | | MILSCI | 16 | | MM\&I | 22 | | MOLBIOL | 6 | | MS\&E | 59 | | MUSIC | 165 | | MUSPERF | 126 | | NAVSCI | 20 | | NE | 44 | | NEURODPT | 11 | | NEUROL | 7 | | NEURSURG | 4 | | NTP | 11 | | NURSING | 111 | | NUTRSCI | 65 | | OBS\&GYN | 18 | | OCCTHER | 39 | | ONCOLOGY | 14 | | OPHTHALM | 5 | | OTM | 43 | | PATH | 34 | | PATH-BIO | 29 | | PEDIAT | 26 | | PHARMACY | 31 | | PHILOS | 77 | | PHMCOL-M | 11 | | PHMPRAC | 45 | | PHMSCI | 60 | | PHYASST | 37 | | PHYSICS | 88 | | PHYSIOL | 3 | | PHYTHER | 37 | | PLANTSCI | 52 | | PLPATH | 35 | | POLISCI | 192 | | POPHLTH | 58 | | PORTUG | 33 | | PSYCH | 101 | | PSYCHIAT | 22 | | PUBAFFR | 54 | | PUBLHLTH | 23 | | RADIOL | 11 | | REALEST | 41 | | RELIGST | 90 | | RHABMED | 9 | | RMI | 24 | | RP\&SE | 102 | | S\&APHM | 17 | | SCANDST | 73 | | SLAVIC | 89 | | SOC | 149 | | SOCWORK | 87 | | SOILSCI | 46 | | SPANISH | 83 | | SRMED | 21 | | STAT | 94 | | STDYABRD | 52 | | STS | 8 | | SURGERY | 25 | | SURGSCI | 33 | | THEATRE | 91 | | URBRPL | 60 | | UROLOGY | 5 | | ZOOLOGY | 89 | ## course ### run id 20260907T155543-ce3781c4 ### semester 1272 ### observed at 2026-09-07 15:55:43.033547+00:00 ### record version id 56cf6cd348a5d00489cd6a69518ce5ad55cb6247c00b3c4143193eb5789b609d ### course id COMARTS 110 ### course uid course\_1a95d09dffbc5341c5d903d4 ### catalog version id 24beb555f5b3e8d51909f566fbcafaf724c2db29d9d173a63a8197b401f13b59 ### course number 110 ### subjects * COMARTS ### title ARTIFICIAL INTELLIGENCE IN STORY AND SCREEN ### description Explore how artificial intelligence (AI) gains meaning through the stories we tell about it. Through close readings of both nonfiction texts and science fiction narratives, examine how our AI-driven culture is shaped by the media texts that structure, theme, and provide perspective on new technologies. Learn how film, television, and other popular forms of media narrative are powerful forms of literature that influence the development and understanding of AI technologies - and how those visions in turn shape our perceptions of humanity. ### requirements text None ### credits min 3 ### credits max 3 ### credit offering ids * 1272:250:027333 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 2388d1627d4538933212bdf69b8462c5e2fb96cc3ab8d15ccf0091c1e35d6496 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary COMARTS 110 explores how AI gains meaning through stories, examining media narratives that shape technology and human perception. ### llm topics * Science fiction narratives * Film and television media * AI-driven culture * Perceptions of humanity ### llm skills * Close reading of nonfiction and science fiction texts * Examining the influence of media on cultural perceptions * Analyzing popular media as literature ### llm assumed background None recorded. ### llm search phrases * AI in media narratives * science fiction and technology * cultural impact of AI * film and TV analysis * human perception of technology ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash 43f02c6943f0566fca41ec3df472fea5f21511232521f71f3cad9b370c826f25 #### course id COMARTS 110 #### current instructors ```json [ { "instructor_uid": "instructor_e2f5f7ff189d687329a8b7d1", "message": "No course-specific reviews available", "name": "Derek Johnson", "review_status": "no_course_reviews", "rmp_instructor_id": "rmp:1079424", "summary": [] } ] ``` #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered true #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take None recorded. #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history None recorded. #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [], "condition": "None", "course": null, "evidence": "None", "id": "source_requirements", "kind": "condition" } ] ``` #### notes * Display fallback using original requirements text; not an LLM-parsed rule. #### root source\_requirements #### status needs\_review ### instructors ```json [ { "instructor_uid": "instructor_e2f5f7ff189d687329a8b7d1", "source": "enrollment", "source_instructor_id": "drjohnson3", "identity_basis": "netid", "identity_status": "source_identified", "name": "Derek Johnson", "email": "DRJOHNSON3@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 43, "quality": 3.63, "difficulty": 3.47, "quality_count": 43, "difficulty_count": 43, "profile_id": "rmp:1079424", "source_url": "https://www.ratemyprofessors.com/professor/1079424", "match_basis": "exact_name", "observed_at": "2026-09-07 16:43:50.599968+00:00", "courses": { "course_391fcb703c547d7e79b0643f": { "review_count": 1, "quality": 4, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.6394240582687605, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/DEREK_JOHNSON" } ] ``` ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:250:027333", "course_id": "COMARTS 110", "course_uid": "course_1a95d09dffbc5341c5d903d4", "term_id": "1272", "source_course_id": "027333", "source_subject_id": "250", "title": "Artificial Intelligence in Story and Screen", "credits_min": 3, "credits_max": 3, "typically_offered": "Not Applicable" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:36757", "term_id": "1272", "source_section_id": "36757", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 100, "enrolled": 99, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" } ] ``` ### grade instructors ```json [ { "instructor_uid": "instructor_e2f5f7ff189d687329a8b7d1", "source": "enrollment", "source_instructor_id": "drjohnson3", "identity_basis": "netid", "identity_status": "source_identified", "name": "Derek Johnson", "email": "DRJOHNSON3@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 43, "quality": 3.63, "difficulty": 3.47, "quality_count": 43, "difficulty_count": 43, "profile_id": "rmp:1079424", "source_url": "https://www.ratemyprofessors.com/professor/1079424", "match_basis": "exact_name", "observed_at": "2026-09-07 16:43:50.599968+00:00", "courses": { "course_391fcb703c547d7e79b0643f": { "review_count": 1, "quality": 4, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.6394240582687605, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/DEREK_JOHNSON" } ] ``` ### grades None recorded. ### statistics #### graded 0 #### counts * 0 * 0 * 0 * 0 * 0 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_1a95d09dffbc5341c5d903d4-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_1a95d09dffbc5341c5d903d4-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_1a95d09dffbc5341c5d903d4-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_1a95d09dffbc5341c5d903d4-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_1a95d09dffbc5341c5d903d4-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_1a95d09dffbc5341c5d903d4-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_1a95d09dffbc5341c5d903d4-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_1a95d09dffbc5341c5d903d4-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## instructor Trends None recorded. ## following None recorded.