{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:GV6V4SN322UTMVH2TO2IDG2EYO","short_pith_number":"pith:GV6V4SN3","schema_version":"1.0","canonical_sha256":"357d5e49bbd6a93654fa9bb4819b44c3b6547a8bb4448a06140d90467baaf133","source":{"kind":"arxiv","id":"2307.00150","version":1},"attestation_state":"computed","paper":{"title":"Large Language Models (GPT) for automating feedback on programming assignments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Maciej Pankiewicz, Ryan S. Baker","submitted_at":"2023-06-30T21:57:40Z","abstract_excerpt":"Addressing the challenge of generating personalized feedback for programming assignments is demanding due to several factors, like the complexity of code syntax or different ways to correctly solve a task. In this experimental study, we automated the process of feedback generation by employing OpenAI's GPT-3.5 model to generate personalized hints for students solving programming assignments on an automated assessment platform. Students rated the usefulness of GPT-generated hints positively. The experimental group (with GPT hints enabled) relied less on the platform's regular feedback but perfo"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.00150","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2023-06-30T21:57:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"09f689f4dd79c1ef99d7a9b3fb0b04bee38cdd199a0e119a31860dd0658f808b","abstract_canon_sha256":"8f18f83996cd729b7fc8e615301b6a2e791b271bee93ceb61284383465db1d1e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:26:52.254031Z","signature_b64":"Od1CtLx5pym3B2S2P7h39aysP0wrcZUKiclwMcAcNPL6NEFT4G+xT2TBrVk2ovTB6KoBapYl+s5DQWAHbqK6DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"357d5e49bbd6a93654fa9bb4819b44c3b6547a8bb4448a06140d90467baaf133","last_reissued_at":"2026-07-05T06:26:52.253553Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:26:52.253553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Large Language Models (GPT) for automating feedback on programming assignments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Maciej Pankiewicz, Ryan S. Baker","submitted_at":"2023-06-30T21:57:40Z","abstract_excerpt":"Addressing the challenge of generating personalized feedback for programming assignments is demanding due to several factors, like the complexity of code syntax or different ways to correctly solve a task. In this experimental study, we automated the process of feedback generation by employing OpenAI's GPT-3.5 model to generate personalized hints for students solving programming assignments on an automated assessment platform. Students rated the usefulness of GPT-generated hints positively. The experimental group (with GPT hints enabled) relied less on the platform's regular feedback but perfo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.00150","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2307.00150/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.00150","created_at":"2026-07-05T06:26:52.253609+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.00150v1","created_at":"2026-07-05T06:26:52.253609+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.00150","created_at":"2026-07-05T06:26:52.253609+00:00"},{"alias_kind":"pith_short_12","alias_value":"GV6V4SN322UT","created_at":"2026-07-05T06:26:52.253609+00:00"},{"alias_kind":"pith_short_16","alias_value":"GV6V4SN322UTMVH2","created_at":"2026-07-05T06:26:52.253609+00:00"},{"alias_kind":"pith_short_8","alias_value":"GV6V4SN3","created_at":"2026-07-05T06:26:52.253609+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":5,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.22809","citing_title":"AI-Assisted Help-Seeking Trajectories in Programming Education from an SRL-Informed Perspective","ref_index":29,"is_internal_anchor":false},{"citing_arxiv_id":"2606.08807","citing_title":"A Classroom Study of LLM-Generated Feedback Intervention in Introductory Programming","ref_index":40,"is_internal_anchor":false},{"citing_arxiv_id":"2606.03814","citing_title":"Leveraging BART to Assess CS1 C++ Programming Assignments using Rubric-based Criteria","ref_index":2,"is_internal_anchor":false},{"citing_arxiv_id":"2605.16933","citing_title":"The Effects of Structured LLM-Generated Feedback on Programming Assignment Performance","ref_index":23,"is_internal_anchor":false},{"citing_arxiv_id":"2604.19931","citing_title":"Hint-Writing with Deferred AI Assistance: Fostering Critical Engagement in Data Science Education","ref_index":45,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO","json":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO.json","graph_json":"https://pith.science/api/pith-number/GV6V4SN322UTMVH2TO2IDG2EYO/graph.json","events_json":"https://pith.science/api/pith-number/GV6V4SN322UTMVH2TO2IDG2EYO/events.json","paper":"https://pith.science/paper/GV6V4SN3"},"agent_actions":{"view_html":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO","download_json":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO.json","view_paper":"https://pith.science/paper/GV6V4SN3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.00150&json=true","fetch_graph":"https://pith.science/api/pith-number/GV6V4SN322UTMVH2TO2IDG2EYO/graph.json","fetch_events":"https://pith.science/api/pith-number/GV6V4SN322UTMVH2TO2IDG2EYO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO/action/storage_attestation","attest_author":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO/action/author_attestation","sign_citation":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO/action/citation_signature","submit_replication":"https://pith.science/pith/GV6V4SN322UTMVH2TO2IDG2EYO/action/replication_record"}},"created_at":"2026-07-05T06:26:52.253609+00:00","updated_at":"2026-07-05T06:26:52.253609+00:00"}