Suchergebnisse - "programming process data"

On the Opportunities of Large Language Models for Programming Process Data

Autoren: John Edwards Arto Hellas Juho Leinonen et al.

Weitere Verfasser: John Edwards Arto Hellas Juho Leinonen et al.

Quelle: Proceedings of the 27th Australasian Computing Education Conference. :105-113

Schlagwörter: FOS: Computer and information sciences, programming process data, K.3, Computer Science - Artificial Intelligence, E.m, programming process summarization, programming process feedback, keystroke data, Computer Science - Computers and Society, Artificial Intelligence (cs.AI), generative AI, Computers and Society (cs.CY), large language models

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2411.00414
https://aaltodoc.aalto.fi/handle/123456789/137005

Credential-Based Pseudonym Generation for Programming Process Data Collection

Autoren: Björn Fischer Marc Stöttinger Berit Barthelmes et al.

Quelle: Proceedings of the 30th ACM Conference on Innovation and Technology in Computer Science Education V. 1. :228-234

Seeking Consent for Programming Process Data Collection with Trustee-Based Encryption

Autoren: Björn Fischer Berit Barthelmes Sven Eric Panitz et al.

Quelle: Proceedings of the 2024 ACM Conference on International Computing Education Research - Volume 1. :131-142

On the Opportunities of Large Language Models for Programming Process Data

Autoren: Edwards, John Hellas, Arto Leinonen, Juho

Index Begriffe: Computer Science - Computers and Society, Computer Science - Artificial Intelligence, K.3, E.m, text

URL: http://arxiv.org/abs/2411.00414

Early Performance Prediction using Interpretable Patterns in Programming Process Data

Autoren: Ge Gao Thomas W. Price Samiha Marwan

Quelle: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education. :342-348

Schlagwörter: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Software Engineering, 4. Education, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0503 education, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/pdf/2102.05765
http://arxiv.org/abs/2102.05765
https://dblp.uni-trier.de/db/journals/corr/corr2102.html#abs-2102-05765
https://doi.org/10.1145/3408877.3432439
https://arxiv.org/pdf/2102.05765
https://arxiv.org/abs/2102.05765
http://export.arxiv.org/pdf/2102.05765
http://ui.adsabs.harvard.edu/abs/2021arXiv210205765G/abstract

ProgSnap2: A Flexible Format for Programming Process Data

Autoren: Luke Gusukuma Andrew Petersen Stephen H. Edwards et al.

Quelle: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. :356-362

Schlagwörter: 4. Education, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0503 education

Zugangs-URL: https://researchrepository.ucd.ie/bitstream/10197/10158/2/ProgSnap2.pdf
https://dblp.uni-trier.de/db/conf/iticse/iticse2020.html#PriceHRGBKBPGEB20

Early Performance Prediction using Interpretable Patterns in Programming Process Data

Autoren: Gao, Ge Marwan, Samiha Price, Thomas W.

Index Begriffe: Computer Science - Machine Learning, Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2102.05765

Using Programming Process Data to Detect Differences in Students' Patterns of Programming

Autoren: Christopher D. Hundhausen Adam S. Carter

Quelle: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education. :105-110

Schlagwörter: 4. Education, 05 social sciences, 10. No inequality, 0503 education

Zugangs-URL: https://dl.acm.org/doi/pdf/10.1145/3017680.3017785
https://dblp.uni-trier.de/db/conf/sigcse/sigcse2017.html#CarterH17

ProgSnap2: A Flexible Format for Programming Process Data

Autoren: Price, Thomas W. Hovemeyer, David Rivers, Kelly et al.

Schlagwörter: Programming process data, Data standards, Data sharing, Learning analytics

Relation: http://hdl.handle.net/10197/10158

Verfügbarkeit: http://hdl.handle.net/10197/10158

Analyzing Student Behaviors in CS1 Through Programming Process Data

Autoren: Hart, Kaden F.

Quelle: All Graduate Theses and Dissertations, Fall 2023 to Present

Schlagwörter: Keystrokes, Engagement, Vigilance, Do Not Disturb, Metacognition, Computer Sciences

Dateibeschreibung: application/pdf

Relation: https://digitalcommons.usu.edu/etd2023/177; https://digitalcommons.usu.edu/context/etd2023/article/1188/viewcontent/COMSetd2024Spring_Hart_Kaden_EMBARGO.pdf

Verfügbarkeit: https://digitalcommons.usu.edu/etd2023/177
https://doi.org/10.26076/83f4-0bfe
https://digitalcommons.usu.edu/context/etd2023/article/1188/viewcontent/COMSetd2024Spring_Hart_Kaden_EMBARGO.pdf

G is for Generalisation: Predicting Student Success from Keystrokes

Autoren: Pullar-Strecker, Zac Pereira, Filipe Dwan Denny, Paul et al.

Weitere Verfasser: Pullar-Strecker, Zac Pereira, Filipe Dwan Denny, Paul et al.

Quelle: Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1. :1028-1034

Schlagwörter: ta113, learning analytics, programming process data, computing education, educational data mining, predicting performance

Dateibeschreibung: application/pdf

Zugangs-URL: http://juuli.fi/Record/0675408723
https://doi.org/10.1145/3545945.3569824
https://aaltodoc.aalto.fi/handle/123456789/125473

Factors Affecting Compilable State at Each Keystroke in CS1

Autoren: Scott, Steven Hellas, A Leinonen, J et al.

Weitere Verfasser: Scott, Steven Hellas, A Leinonen, J et al.

Quelle: 2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET). :314-323

Schlagwörter: Educational data mining, Keystroke analysis, Programming process data, 4. Education, Keystroke data, 05 social sciences, 0101 mathematics, Predicting performance, 0503 education, 01 natural sciences

Dateibeschreibung: application/pdf

Zugangs-URL: https://aaltodoc.aalto.fi/handle/123456789/125520

A Study of Keystroke Data in Two Contexts: Written Language and Programming Language Influence Predictability of Learning Outcomes

Autoren: Edwards, John Leinonen, Juho Hellas et al.

Weitere Verfasser: Edwards, John Leinonen, Juho Hellas et al.

Quelle: Proceedings of the 51st ACM Technical Symposium on Computer Science Education. :413-419

Schlagwörter: Educational sciences, ta113, Computer and information sciences, Keystroke analysis, 4. Education, Keystroke data, 05 social sciences, 02 engineering and technology, Educational data mining, Programming process data, Digraphs, 0202 electrical engineering, electronic engineering, information engineering, Predicting performance, 0503 education

Dateibeschreibung: application/pdf

Zugangs-URL: https://helda.helsinki.fi/bitstream/10138/318519/1/SIGCSE2020_digraphs.pdf
http://juuli.fi/Record/0371072820
https://doi.org/10.1145/3328778.3366863
https://researchportal.helsinki.fi/en/publications/a-study-of-keystroke-data-in-two-contexts-written-language-and-pr
https://helda.helsinki.fi/handle/10138/318519
https://dblp.uni-trier.de/db/conf/sigcse/sigcse2020.html#EdwardsLH20
https://helda.helsinki.fi/bitstream/10138/318519/1/SIGCSE2020_digraphs.pdf
http://hdl.handle.net/10138/318519
https://aaltodoc.aalto.fi/handle/123456789/101429

Pausing while programming: insights from keystroke analysis

Autoren: Shrestha, Raj Leinonen, Juho Zavgorodniaia, Albina et al.

Weitere Verfasser: Shrestha, Raj Leinonen, Juho Zavgorodniaia, Albina et al.

Quelle: Computer Science Student Research

Schlagwörter: programming process data, pausing, Computer Sciences, pauses, breaks, 4. Education, 05 social sciences, 0503 education, keystroke data, digraphs

Dateibeschreibung: application/pdf

Zugangs-URL: https://digitalcommons.usu.edu/computer_science_stures/23
https://digitalcommons.usu.edu/context/computer_science_stures/article/1022/viewcontent/Pausing_while_programming_insights_from_keystroke_analysis.pdf
https://aaltodoc.aalto.fi/handle/123456789/115327

IDE Action Log Dataset from a CS1 MOOC

Autoren: Leinonen, Juho orcid:0000-0001-6829- Hellas, Arto

Schlagwörter: IDE logs, log data, programming process data, Integrated Development Environment, IDE, programming, CS1, keystroke data, learning analytics, educational data mining

Relation: https://zenodo.org/records/6903968; oai:zenodo.org:6903968; https://doi.org/10.5281/zenodo.6903968

Verfügbarkeit: https://doi.org/10.5281/zenodo.6903968
https://zenodo.org/records/6903968

Using a Timeline of Programming Events as a Method for Understanding the Introductory Students' Programming Process.

Autoren: Beck, Phyllis Jean Mohammadi-Aragh, Mahnas Jean

Quelle: Proceedings of the ASEE Annual Conference & Exposition; 2024, p1-7, 7p

Exploring students' cognitive and affective states during problem solving through multimodal data: Lessons learned from a programming activity.

Autoren: Mangaroska, Katerina Sharma, Kshitij Gašević, Dragan et al.

Quelle: Journal of Computer Assisted Learning; Feb2022, Vol. 38 Issue 1, p40-59, 20p

Schlagwörter: BRAIN physiology, THOUGHT & thinking, PSYCHOLOGY of college students, PROBLEM solving, AFFECT (Psychology), ELECTROENCEPHALOGRAPHY, COGNITION, LEARNING strategies, T-test (Statistics), UNIVERSITIES & colleges, COMMUNICATION, COMPUTER systems, TIME series analysis, DESCRIPTIVE statistics, STATISTICAL correlation, WRITTEN communication, READING

Geografische Kategorien: NORWAY

Measure Student Aptitude in Learning Programming in Higher Education—A Data Analysis.

Autoren: Pires, João Borges, Ana Rosa Bernardino, Jorge et al.

Quelle: Computers (2073-431X); Oct2025, Vol. 14 Issue 10, p428, 21p

Schlagwörter: COMPUTER programming education, COGNITIVE testing, HIGHER education, PREDICTION models, EDUCATIONAL evaluation, ANALYTICAL skills, ACADEMIC achievement, DATA analysis

CodeDive: A Web-Based IDE with Real-Time Code Activity Monitoring for Programming Education.

Autoren: Park, Hyunchan Kim, Youngpil Lee, Kyungwoon et al.

Quelle: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 19, p10403, 28p

Schlagwörter: COMPUTER programming education, EDUCATION ethics, WEB-based user interfaces, AUTOMATIC tracking, CLOUD computing, ACHIEVEMENT gains (Education), ACADEMIC achievement

Method development and validation of orlistat by using RP-HPLC.

Autoren: Nagarajan, Kandasamy Bhardwaj, Snigdha Kamboj, Surbhi et al.

Quelle: Current Pharmaceutical Analysis; Jun2025, Vol. 21 Issue 6, p313-322, 10p