Tools Used for Automated Formative Assessment in Computer-Assisted Programming Courses ; Herramientas usadas para la evaluación formativa automatizada en cursos de programación asistidos por computadora
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| Název: | Tools Used for Automated Formative Assessment in Computer-Assisted Programming Courses ; Herramientas usadas para la evaluación formativa automatizada en cursos de programación asistidos por computadora |
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| Autoři: | Leytón-Yela, Ginna-Viviana, Bucheli-Guerrero, Victor-Andrés, Ordoñez-Erazo, Hugo-Armando |
| Zdroj: | Revista Científica; Vol. 45 No. 3 (2022): September-December 2022; 358-368 ; Revista Científica; Vol. 45 Núm. 3 (2022): Septiembre-Diciembre 2022; 358-368 ; 2344-8350 ; 0124-2253 |
| Informace o vydavateli: | Universidad Distrital Francisco José de Caldas |
| Rok vydání: | 2022 |
| Sbírka: | Universidad Distrital de la ciudad de Bogotá: Open Journal Systems |
| Témata: | automated feedback, formative assessment, learning programming, programming course, programming tools, aprendizaje de programación, curso de programación, evaluación formativa, herramientas de programación, realimentación automatizada |
| Popis: | This study presents the use of tools for verifying the operation of automated feedback as implemented in programming courses. Educational environments offer the experience of summative and formative evaluation of computer programs, which is aimed at students. In this type of tool, students solve a programming task, which is automatically validated in order to generate grades and feedback. Regarding summative evaluation, a numerical or percentage grade is generated on whether the solution of a task is correct. In the case of formative evaluation, information is generated on errors or suggestions to be incorporated to the programs in order to improve learning. The employed tools are UNCode, Ask-Elle, and Nbgrader. In addition, some important remarks are made about some of the tools used for comparing programs and validating differences. ; Este estudio presenta el despliegue de herramientas para verificación del funcionamiento de la realimentación automatizada implementada en cursos de programación. Los entornos educativos ofrecen la experiencia de evaluación sumativa y formativa de programas informáticos dirigida a estudiantes. En este tipo de herramientas, los estudiantes resuelven una tarea de programación, la cual es validada de manera automática para generar calificaciones y realimentación. Con respecto a la evaluación sumativa, se genera una calificación numérica o porcentual sobre si es correcta o no la solución de una tarea. Para el caso de la evaluación formativa, se genera información sobre los errores o sugerencias a incorporar en los programas con el fin de mejorar el aprendizaje. Las herramientas utilizadas son UNCode, Ask-Elle y Nbgrader. Adicionalmente, se hacen menciones importantes sobre algunas de las herramientas usadas para la comparación de programas y validación de diferencias. |
| Druh dokumentu: | article in journal/newspaper |
| Popis souboru: | application/pdf; text/xml |
| Jazyk: | Spanish; Castilian |
| Relation: | https://revistas.udistrital.edu.co/index.php/revcie/article/view/19662/18553; https://revistas.udistrital.edu.co/index.php/revcie/article/view/19662/18610; Akram, B., Azizolsoltani, H., Min, W., Wiebe, E., Navied, A., Mott, B. W., Boyer, K., Lester, J. C. (2020). A Data-Driven Approach to Automatically Assessing Concept-Level CS Competencies Based on Student Programs. En CSEDM@EDM; Angelone, A. M., Vittorini, P. (2020). The Automated Grading of R Code Snippets: Preliminary Results in a Course of Health Informatics. En 9th International Conference (pp. 19-27). Springer. https://doi.org/10.1007/978-3-030-23990-9_3; Annamaa, A., Suviste, R., Vene, V. (2017). Comparing different styles of automated feedback for programming exercises. En Proceedings of the 17th Koli Calling International Conference on Computing Education Research (pp. 183-184). https://doi.org/10.1145/3141880.3141909; Ardimento, P., Bernardi, M. L., Cimitile, M. (2020). Software Analytics to Support Students in Object-Oriented Programming Tasks: An Empirical Study. IEEE Access, 8, 132171-132187. https://doi.org/10.1109/ACCESS.2020.3010172; Beck, P., Mohammadi-Aragh, M. J., Archibald, C. (2019). An Initial Exploration of Machine Learning Techniques to Classify Source Code Comments in Real-time. En ASEE Annual Conference & Exposition; Dominguez, A. K., Yacef, K., Curran, J. (2010). Data mining to generate individualised feedback. En Proceedings of the 10th international conference on Intelligent Tutoring Systems (pp. 303-305). https://doi.org/10.1007/978-3-642-13437-1_52; Edwards, S. H. (2014). Work-in-progress: Program grading and feedback generation with Web-CAT. En Proceedings of the first ACM conference on Learning @ scale conference (pp. 215-216). https://doi.org/10.1145/2556325.2567888; English, J., English, T. (2019). Combining Summative and Formative Evaluation Using Automated Assessment. Issues in Informing Science and Information Technology, 16, 143-151. https://doi.org/10.28945/4293; Funabiki, N., Mohri, T., Yamaguchi, S. (2016). Toward personalized learning in JPLAS: Generating and scoring functions for debugging questions. En IEEE 5th Global Conference on Consumer Electronics (pp. 1-4). https://doi.org/10.1109/GCCE.2016.7800392; Gerdes, A., Heeren, B., Jeuring, J., van Binsbergen, L. T. (2017). Ask-Elle: An Adaptable Programming Tutor for Haskell Giving Automated Feedback. International Journal of Artificial Intelligence in Education, 27(1), 65-100. https://doi.org/10.1007/s40593-015-0080-x; Hidalgo, C., G, V. A. B., Calle, F. R., Osorio, F. A. G. (2021). Estrategia de enseñanza basada en la colaboración y la evaluación automática de código fuente en un curso de programación CS1. Investigación e Innovación en Ingenierías, 9(1), 50-60; Jeuring, J., Gerdes, A., Heeren, B. (2012). Ask-Elle: A Haskell Tutor. En 21st Century Learning for 21st Century Skills (pp. 453-458). Springer. https://doi.org/10.1007/978-3-642-33263-0_42 Jupyter Development Team. (s. f.). nbgrader—Nbgrader 0.7.1 documentation. https://nbgrader.readthedocs.io/en/stable/; Jupyter, P., Blank, D., Bourgin, D., Brown, A., Bussonnier, M., Frederic, J., Granger, B., Griffiths, T., Hamrick, J., Kelley, K., Pacer, M., Page, L., Perez, F., Ragan-Kelley, B., Suchow, J., Willing, C. (2019). nbgrader: A Tool for Creating and Grading Assignments in the Jupyter Notebook. Journal of Open Source Education, 2, e32. https://doi.org/10.21105/jose.00032; Keuning, H., Jeuring, J., Heeren, B. (2016). Towards a Systematic Review of Automated Feedback Generation for Programming Exercises. En Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (pp. 41-46). https://doi.org/10.1145/2899415.2899422; Keuning, H., Jeuring, J., Heeren, B. (2018). A Systematic Literature Review of Automated Feedback Generation for Programming Exercises. ACM Transactions on Computing Education, 19(1), 1-43. https://doi.org/10.1145/3231711; Kim, D., Kwon, Y., Liu, P., Kim, I. L., Perry, D. M., Zhang, X., Rodriguez-Rivera, G. (2016). Apex: Automatic programming assignment error explanation. En Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (pp. 311-327). https://doi.org/10.1145/2983990.2984031; Manzoor, H., Naik, A., Shaffer, C. A., North, C., Edwards, S. H. (2020). Auto-Grading Jupyter Notebooks. En Proceedings of the 51st ACM Technical Symposium on Computer Science Education (pp. 1139-1144). https://doi.org/10.1145/3328778.3366947; Marin, V. J., Pereira, T., Sridharan, S., Rivero, C. R. (2017). Automated Personalized Feedback in Introductory Java Programming MOOCs. En IEEE 33rd International Conference on Data Engineering (pp. 1259-1270). https://doi.org/10.1109/ICDE.2017.169; McBroom, J., Yacef, K., Koprinska, I. (2020). Scalability in Online Computer Programming Education: Automated Techniques for Feedback, Evaluation and Equity. En Proceedings of the 13th International Conference on Educational Data Mining. https://educationaldatamining.org/files/conferences/EDM2020/papers/paper\_252.pdf; Narciss, S. (2008). Feedback Strategies for Interactive Learning Tasks (pp. 125-144) Ramirez-Echeverry, J. J., Restrepo-Calle, F., González, F. (2018). Uncode: Interactive System for Learning and Automatic Evaluation of Computer Programming Skills. https://doi.org/10.21125/edulearn.2018.1632; Razeeth, M., Kariapper, R. K. A. R., Pirapuraj, P., Nafrees, A., Rishan, U. M., Ali, S. (2019). E-learning at home vs traditional learning among higher education students: A survey based analysis. https://www.semanticscholar.org/paper/E-learning-at-home-vs-traditional-learning-among-a-Razeeth-Kariapper/546b671af8f0542edb932a7819b62e80a0c3010b; Shermis, M. D. (2014). State-of-the-art automated essay scoring: Competition, results, and future directions from a United States demonstration. Assessing Writing, 20, 53-76. https://doi.org/10.1016/j.asw.2013.04.001; Srikant, S., Aggarwal, V. (2014). A system to grade computer programming skills using machine learning. En Proceedings of the 20th International Conference on Knowledge Discovery and Data Mining (pp. 1887-1896). https://doi.org/10.1145/2623330.2623377; Universidad del Valle. (s. f.). Course list - INGInious M-iDEA. http://ingin.ddns.net/courselist Universidad Nacional de Colombia. (2022). UNCode [Python]. UNCode. https://github.com/JuezUN/INGInious; Université catholique de Louvain. (s. f.). What is INGInious? —INGInious 0.7 documentation. https://docs.inginious.org/en/v0.7/what_is_inginious.html; Universiteit Utrecht, Open Universiteit. (s. f.-a). Ask-Elle. https://ideas.science.uu.nl/AskElle/ Universiteit Utrecht, Open Universiteit. (s. f.-b). Ideas tutorial. https://ideas.science.uu.nl/tutorial/; Vittorini, P., Menini, S., Tonelli, S. (2021). An AI-Based System for Formative and Summative Assessment in Data Science Courses. International Journal of Artificial Intelligence in Education, 31(2), 159-185. https://doi.org/10.1007/s40593-020-00230-2; Yong Castillo, E., Bedoya Ortiz, D. H. (2022). De la educación tradicional a la educación mediada por TIC. https://pdf4pro.com/amp/view/de-la-educaci-243-n-tradicional-a-la-educaci-243-n-mediada-por-tic-733bf7.html; https://revistas.udistrital.edu.co/index.php/revcie/article/view/19662 |
| Dostupnost: | https://revistas.udistrital.edu.co/index.php/revcie/article/view/19662 |
| Rights: | Derechos de autor 2022 Ginna-Viviana Leytón-Yela, Victor-Andrés Bucheli-Guerrero, Hugo-Armando Ordoñez-Erazo ; https://creativecommons.org/licenses/by-nc-sa/4.0 |
| Přístupové číslo: | edsbas.2F42894 |
| Databáze: | BASE |
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